Estefani Gaytan Nunez

upload

Showing 97 changed files with 13098 additions and 4 deletions
......@@ -86,6 +86,9 @@ if __name__ == '__main__':
scores[report[7:11]]['f1-score']=summaryScores[2]
print(DF(scores).T)
print('------------------------------- SAVING TABLE --------------------------------\n')
with open(os.path.join(options.inputPath, str(options.figureName) ), 'w') as File:
scoresTable = DF(scores).T
imageName=os.path.join(options.outputPath, options.figureName)
......
from optparse import OptionParser
import re
from collections import defaultdict as df
import os
import random
from pandas import DataFrame as DF
import matplotlib.pyplot as plt
# Objective
# Drawn figures of grid reports
#
# Input parameters
# --inputPath=PATH Path of inputfiles
# --outputPath=PATH Path to place output figures
# --figureName single run specific name figure, multifigure first part of name
# --inputFile Use it for a single report
# --version CRF-script version of reports
#
# Output
# training and test data set
#
# Examples
# python figures-reports.py
# --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/reports/
# --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/figures/
# --figureName FiguresGrid
# --inputFile report_Run1_v11.txt
# --version v11
# python figures-tag-report.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/reports/ --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/figures/ --figureName FiguresGrid_v11 --version v11
__author__ = 'egaytan'
####################################################################################
# FUNCTIONS #
####################################################################################
def Filter(rfile, options,v):
if options[0]=='all':
if rfile[0:6]=='report' and rfile[-7:-4]==v: return(True)
elif rfile in options:
return(True)
return(False)
####################################################################################
# MAIN PROGRAM #
####################################################################################
if __name__ == '__main__':
# Defining parameters
parser = OptionParser()
parser.add_option('--inputPath', dest='inputPath', help='Path of output from CoreNLP', metavar='PATH')
parser.add_option('--outputPath', dest='outputPath', help='Path to place output figures', metavar='PATH')
parser.add_option('--figureName', dest='figureName', help='Specific or first part of figurename', metavar='FILE')
parser.add_option('--version', dest='version', help='script version', metavar='FILE')
parser.add_option('--inputFile', dest='inputFile', help='Use it for a specific report files', metavar='FILE', default='all,')
(options, args) = parser.parse_args()
if len(args) > 0:
parser.error('Any parameter given.\nFor multi input files be sure to seprate the filenames by coma')
sys.exit(1)
print('-------------------------------- PARAMETERS --------------------------------')
print('Path of output from CoreNLP: ' + str(options.inputPath))
print('Path to place output figures: ' + str(options.outputPath))
print('Specific or first part of figurename: ' + str(options.figureName))
print('CRF-script version: ' + str(options.version))
print('-------------------------------- PROCESSING --------------------------------')
rawInputRepotsList = str(options.inputFile).split(',')
reportFileList = [ rfile for rfile in os.listdir(options.inputPath) if Filter(rfile, rawInputRepotsList, str(options.version)) ]
scores = df(dict)
#CV={}
print('Report files: ' + str(options.inputFile ))
print('\n'.join(reportFileList))
print('----------------------------------- NOTE -----------------------------------')
print('\n-------- All chosen report files should be in inputPath given---------------\n')
print('------------------------------- SAVING DATA --------------------------------\n')
OD, pH, Technique, Med, Temp, Vess, Agit, Phase, Air, Anti, Strain, Gtype, Substrain, Supp, Gversion = [], [], [], [], [], [], [], [], [], [], [], [], [], [], []
precision = df(list)
recall = df(list)
fscore = df(list)
support = df(list)
for report in reportFileList:
tags = {}
with open(os.path.join(options.inputPath, report), 'r') as File:
string = File.read()
tags['OD']= re.findall('OD\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['pH']= re.findall('pH\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Technique']= re.findall('Technique\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Med']= re.findall('Med\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Temp']= re.findall('Temp\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Vess']= re.findall('Vess\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Agit']= re.findall('Agit\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Phase']= re.findall('Phase\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Air']= re.findall('Air\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Anti']= re.findall('Anti\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Strain']= re.findall('Strain\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Gtype']= re.findall('Gtype\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Substrain']= re.findall('Substrain\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Supp']= re.findall('Supp\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
tags['Gversion']= re.findall('Gversion\s+(\d+.\d+)\s+(\d+\.\d+)\s+(\d+\.\d+)', string)[0]
for k in tags.keys():
precision[k].append(float(tags[k][0]))
recall[k].append(float(tags[k][1]))
fscore[k].append(float(tags[k][2]))
#support[k].append(tags[k][3])
print(DF(precision))
print(precision)
#lines = ['-', '--', '-.', ':', '.', ',', 'o', 'v', '^', '<', '>', '1', '2', '3', '4', 's', 'p', '*', 'h', 'H', '+', 'x', 'D', 'd', '|', '_']
lines = ['-','--','-.',':','o','v','^','<','>','s','p','*','H','+','x','D','|']
imageName = str(options.figureName) + '_' + str(options.version)
fig = plt.figure()
plt.rcParams.update({'font.size': 15})
#fig.set_figheight(13)
#fig.set_figwidth(20)
plt.xlabel("Runs")
plt.ylabel("score")
plt.ylim(-0.2, 1.2)
lines=['-', '--', '-.', ':', ',', 'o', 'v', '^', '<', '>', '1', '2', '3', '4', 's', 'p', '*', 'h', 'H', '+', 'x', 'D', 'd', '|', '_']
for i,k in enumerate(tags.keys()):
plt.grid(False)
plt.plot(precision[k], lines[i], label=k, linewidth=8)
plt.legend(loc='lower right')
plt.tight_layout()
plt.xticks(range(8),['run1', 'run2', 'run3', 'run4', 'run5', 'run6', 'run7', 'run8'])
fig.savefig(imageName, bbox_inches='tight', pad_inches = 0.5)
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_1 --version _v12 > ../outputs/Run_1.txt
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_2 --version _v12 --S1 > ../outputs/Run_2.txt
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_3 --version _v12 --S2 > ../outputs/Run_3.txt
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_4 --version _v12 --S1 --S2 > ../outputs/Run_4.txt
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_5 --version _v12 --S3 > ../outputs/Run_5.txt
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_6 --version _v12 --S1 --S3 > ../outputs/Run_6.txt
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_7 --version _v12 --S2 --S3 > ../outputs/Run_7.txt
python3 training_validation_v12.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_8 --version _v12 --S1 --S2 --S3 > ../outputs/Run_8.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_1 --version _v13 > ../outputs/Run_1.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_2 --version _v13 --S1 > ../outputs/Run_2.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_3 --version _v13 --S2 > ../outputs/Run_3.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_4 --version _v13 --S1 --S2 > ../outputs/Run_4.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_5 --version _v13 --S3 > ../outputs/Run_5.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_6 --version _v13 --S1 --S3 > ../outputs/Run_6.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_7 --version _v13 --S2 --S3 > ../outputs/Run_7.txt
python3 training_validation_v13.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --Gridname Run_8 --version _v13 --S1 --S2 --S3 > ../outputs/Run_8.txt
......@@ -423,7 +423,8 @@ if __name__ == "__main__":
# Saving model
print(" Saving training model...")
t1 = time()
nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + str(options.version) + '.mod'
#nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + str(options.version) + '_S3_' + str(options.S3) + '.mod'
nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + '_S3_' + str(options.S3) + '_' + str(options.Gridname) + str(options.version) + '.mod'
joblib.dump(crf, os.path.join(options.outputPath, "models", nameModel))
print(" Saving training model done in: %fs" % (time() - t1))
......
......@@ -177,9 +177,9 @@ def word2features(sent, i, S1, S2, S3):
features['postag[:1]']= postag[:1]
#lemma and postag secondChar
if len(lemma)>1:
features['lemma[:2]']= lemma[:2]
features['lemma[:2]']= lemma[:2]
if len(postag)>1:
features['postag[:2]']= postag[:2]
features['postag[:2]']= postag[:2]
#=========================== S2 =============================#
## NAME LEVEL S2
## FEATURE TYPE Complete word features
......@@ -423,7 +423,9 @@ if __name__ == "__main__":
# Saving model
print(" Saving training model...")
t1 = time()
nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + str(options.version) + '_S3_' + str(options.S3) + '.mod'
#nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + str(options.version) + '_S3_' + str(options.S3) + '.mod'
nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + '_S3_' + str(options.S3) + '_' + str(options.Gridname) + str(options.version) + '.mod'
joblib.dump(crf, os.path.join(options.outputPath, "models", nameModel))
print(" Saving training model done in: %fs" % (time() - t1))
......
# -*- coding: UTF-8 -*-
import os
from itertools import chain
from optparse import OptionParser
from time import time
from collections import Counter
import re
import nltk
import sklearn
import scipy.stats
import sys
from sklearn.externals import joblib
from sklearn.metrics import make_scorer
from sklearn.cross_validation import cross_val_score
from sklearn.grid_search import RandomizedSearchCV
import sklearn_crfsuite
from sklearn_crfsuite import scorers
from sklearn_crfsuite import metrics
from pandas import DataFrame as DF
from nltk.corpus import stopwords
# Objective
# Training and evaluation of CRFs with sklearn-crfsuite.
#
# Input parameters
# --inputPath=PATH Path of training and test data set
# --trainingFile File with training data set
# --testFile File with test data set
# --outputPath=PATH Output path to place output files
# --nameGrid Number of run
# --version Version Report
# Output
# 1) Best model
# 2) Report
# Examples
# python training_validation_v10.py
# --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
# --trainingFile training-data-set-70.txt
# --testFile test-data-set-30.txt
# --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/
# --version _v1
# python3 training_validation_v9.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --nameGrid Run1 --version _v1 --S1 --S2 --S3
##################################################################
# FEATURES #
##################################################################
#================== COMPLETE WORD FEATURES ======================#
def isGreek(word):
## Complete word are greek letters
alphabet = ['Α','Β','Γ','Δ','Ε','Ζ','Η','Θ','Ι','Κ','Λ','Μ','Ν','Ξ','Ο','Π','Ρ','Σ','Τ','Υ','Φ','Χ','Ψ','Ω',
'α','β','γ','δ','ε','ζ','η','θ','ι','κ','λ','μ','ν','ξ','ο','π','ρ','ς','σ','τ','υ','φ','χ','ψ','ω']
if word in alphabet:
return True
else:
return False
#================ INNER OF THE WORD FEATURES ====================#
def hNumber(word):
## Al leats has one greek letter
for l in word:
if l.isdigit():
return True
return False
def symb(word):
n=0
## At least a not alphanumeric character
for l in word:
if l.isdigit(): n = n+1
if l.isalpha(): n = n+1
#Exclude Greek letters
if isGreek(l): n = n+1
if n<len(word): return True
else: return False
def hUpper(word):
## At least an upper letter
for l in word:
if l.isupper(): return True
return False
def hLower(word):
## At least a lower letter
for l in word:
if l.islower(): return True
return False
def hGreek(word):
## At least a greek letter
for l in word:
if isGreek(l): return True
return False
#============================FEATURES===========================#
def word2features(sent, i, S1, S2, S3):
## Getting word features
## Saving CoreNLP annotations
listElem = sent[i].split('|')
word = listElem[0]
lemma = listElem[1]
postag = listElem[2]
#ner = listElem[4]
#=========================== G =============================#
## NAME LEVEL G
## FUTURE TYPE General features
features = {
## basal features
'lemma': lemma,
'postag': postag
}
## more tha one word in sentence
if i > 0:
## Anterior word
listElem = sent[i - 1].split('|')
## Saving CoreNLP annotations
lemma0 = listElem[1]
postag0 = listElem[2]
features.update({
#LemaG anterior
'-1:lemma': lemma0,
#Postag anterior
'-1:postag': postag0,
})
## is not the last word
if i < len(sent) - 1:
## Posterior word
listElem = sent[i + 1].split('|')
## Saving CoreNLP annotations
lemma2 = listElem[1]
postag2 = listElem[2]
features.update({
#LemaG posterior
'+1:lemma': lemma2,
#Postag posterior
'+1:postag': postag2,
})
#=========================== S1 =============================#
## NAME LEVEL S1
## FEATURE TYPE Inner word features
if S1:
#Add features
features['hUpper']= hUpper(word)
features['hLower']= hUpper(word)
features['hGreek']= hGreek(word)
features['symb']= symb(word)
#word firstChar
features['word[:1]']= word[:1]
#word secondChar
if len(word)>1:
features['word[:2]']= word[:2]
#lemma and postag firstChar
#features['lemma[:1]']= lemma[:1]
features['postag[:1]']= postag[:1]
#lemma and postag secondChar
#if len(lemma)>1:
# features['lemma[:2]']= lemma[:2]
if len(postag)>1:
features['postag[:2]']= postag[:2]
#=========================== S2 =============================#
## NAME LEVEL S2
## FEATURE TYPE Complete word features
if S2:
#Add features
features['word']= word
features['isUpper']= word.isupper()
features['isLower']= word.islower()
features['isGreek']= isGreek(word)
features['isNumber']= word.isdigit()
## more tha one word in sentence
if i > 0:
## Anterior word
listElem = sent[i - 1].split('|')
## Saving CoreNLP annotations
word0 = listElem[0]
features['-1:word']= word0
## is not the last word
if i < len(sent)-1:
listElem = sent[i + 1].split('|')
## Saving CoreNLP annotations
word2 = listElem[0]
## Posterior word
features['+1:word']= word2
#=========================== S3 =============================#
## NAME LEVEL S3
## FEATURE TYPE Extended context features
if S3:
## more tha two words in sentence
if i > 1:
## two anterior lemma and postag
listElem = sent[i - 2].split('|')
## Saving CoreNLP annotations
lemma01 = listElem[1]
postag01 = listElem[2]
features['-2:lemma']= lemma01
features['-2:postag']= postag01
## is not the penultimate word
if i < len(sent) - 2:
listElem = sent[i + 2].split('|')
## Saving CoreNLP annotations
lemma02 = listElem[1]
postag02 = listElem[2]
## two posterior lemma and postag
features['+2:lemma']= lemma02
features['+2:postag']= postag02
return features
def sent2features(sent, S1, S2, S3):
## Itering in sentence for each word and saving its features
return [word2features(sent, i, S1, S2, S3) for i in range(len(sent))]
def sent2labels(sent):
## 3rd position by word is the label
return [elem.split('|')[3] for elem in sent]
def sent2tokens(sent):
return [token for token, postag, label in sent]
def print_transitions(trans_features, f):
for (label_from, label_to), weight in trans_features:
f.write("{:6} -> {:7} {:0.6f}\n".format(label_from, label_to, weight))
def print_state_features(state_features, f):
for (attr, label), weight in state_features:
f.write("{:0.6f} {:8} {}\n".format(weight, label, attr.encode("utf-8")))
__author__ = 'egaytan'
##################################################################
# MAIN PROGRAM #
##################################################################
if __name__ == "__main__":
## Defining parameters
parser = OptionParser()
parser.add_option("--inputPath", dest="inputPath", help="Path of training data set", metavar="PATH")
parser.add_option("--outputPath", dest="outputPath", help="Output path to place output files", metavar="PATH")
parser.add_option("--trainingFile", dest="trainingFile", help="File with training data set", metavar="FILE")
parser.add_option("--testFile", dest="testFile", help="File with test data set", metavar="FILE")
parser.add_option("--Gridname", dest="Gridname", help="Report number run", metavar="FILE")
parser.add_option("--version", dest="version", help="Report file", metavar="FILE")
parser.add_option("--S1", dest="S1", help="Future Type", action="store_true", default=False)
parser.add_option("--S2", dest="S2", help="Future Type", action="store_true", default=False)
parser.add_option("--S3", dest="S3", help="Future Type", action="store_true", default=False)
parser.add_option("--excludeStopWords", dest="excludeStopWords",help="Exclude stop words", action="store_true", default=False)
parser.add_option("--excludeSymbols", dest="excludeSymbols", help="Exclude punctuation marks", action="store_true", default=False)
(options, args) = parser.parse_args()
if len(args) > 0:
parser.error("Any parameter given.")
sys.exit(1)
print('-------------------------------- PARAMETERS --------------------------------')
print("Path of training data set: " + options.inputPath)
print("File with training data set: " + str(options.trainingFile))
print("Path of test data set: " + options.inputPath)
print("File with test data set: " + str(options.testFile))
print("Exclude stop words: " + str(options.excludeStopWords))
print("Levels: " + str(options.S1) + " " + str(options.S2))
print("Report file: " + str(options.version))
symbols = ['.', ',', ':', ';', '?', '!', '\'', '"', '<', '>', '(', ')', '-', '_', '/', '\\', '¿', '¡', '+', '{',
'}', '[', ']', '*', '%', '$', '#', '&', '°', '`', '...']
print("Exclude symbols: " + str(options.excludeSymbols))
print('-------------------------------- PROCESSING --------------------------------')
print('Reading corpus...')
t0 = time()
sentencesTrainingData = []
sentencesTestData = []
stopwords = [word for word in stopwords.words('english')]
with open(os.path.join(options.inputPath, options.trainingFile), "r") as iFile:
for line in iFile.readlines():
listLine = []
line = line.strip('\n')
for token in line.split():
if options.excludeStopWords:
listToken = token.split('|')
lemma = listToken[1]
if lemma in stopwords:
continue
if options.excludeSymbols:
listToken = token.split('|')
lemma = listToken[1]
if lemma in symbols:
continue
listLine.append(token)
sentencesTrainingData.append(listLine)
print(" Sentences training data: " + str(len(sentencesTrainingData)))
with open(os.path.join(options.inputPath, options.testFile), "r") as iFile:
for line in iFile.readlines():
listLine = []
line = line.strip('\n')
for token in line.split():
if options.excludeStopWords:
listToken = token.split('|')
lemma = listToken[1]
if lemma in stopwords:
continue
if options.excludeSymbols:
listToken = token.split('|')
lemma = listToken[1]
if lemma in symbols:
continue
listLine.append(token)
sentencesTestData.append(listLine)
print(" Sentences test data: " + str(len(sentencesTestData)))
print("Reading corpus done in: %fs" % (time() - t0))
print('-------------------------------- FEATURES --------------------------------')
Dtraning = sent2features(sentencesTrainingData[0], options.S1, options.S2, options.S3)[2]
Dtest = sent2features(sentencesTestData[0], options.S1, options.S2, options.S3)[2]
print('--------------------------Features Training ---------------------------')
print(DF(list(Dtraning.items())))
print('--------------------------- FeaturesTest -----------------------------')
print(DF(list(Dtest.items())))
t0 = time()
X_train = [sent2features(s, options.S1, options.S2, options.S3) for s in sentencesTrainingData]
y_train = [sent2labels(s) for s in sentencesTrainingData]
X_test = [sent2features(s, options.S1, options.S2, options.S3) for s in sentencesTestData]
# print X_test
y_test = [sent2labels(s) for s in sentencesTestData]
# Fixed parameters
# crf = sklearn_crfsuite.CRF(
# algorithm='lbfgs',
# c1=0.1,
# c2=0.1,
# max_iterations=100,
# all_pgossible_transitions=True
# )
# Hyperparameter Optimization
crf = sklearn_crfsuite.CRF(
algorithm='lbfgs',
max_iterations=100,
all_possible_transitions=True
)
params_space = {
'c1': scipy.stats.expon(scale=0.5),
'c2': scipy.stats.expon(scale=0.05),
}
# Original: labels = list(crf.classes_)
# Original: labels.remove('O')
labels = list(['Gtype', 'Gversion', 'Med', 'Phase', 'Strain', 'Substrain', 'Supp', 'Technique', 'Temp', 'OD', 'Anti', 'Agit', 'Air', 'Vess', 'pH'])
# use the same metric for evaluation
f1_scorer = make_scorer(metrics.flat_f1_score,
average='weighted', labels=labels)
# search
rs = RandomizedSearchCV(crf, params_space,
cv=10,
verbose=3,
n_jobs=-1,
n_iter=20,
# n_iter=50,
scoring=f1_scorer)
rs.fit(X_train, y_train)
# Fixed parameters
# crf.fit(X_train, y_train)
# Best hiperparameters
# crf = rs.best_estimator_
nameReport = str(options.Gridname) + str(options.version) + '.txt'
with open(os.path.join(options.outputPath, "reports", "report_" + nameReport), mode="w") as oFile:
oFile.write("********** TRAINING AND TESTING REPORT **********\n")
oFile.write("Training file: " + options.trainingFile + '\n')
oFile.write('\n')
oFile.write('best params:' + str(rs.best_params_) + '\n')
oFile.write('best CV score:' + str(rs.best_score_) + '\n')
oFile.write('model size: {:0.2f}M\n'.format(rs.best_estimator_.size_ / 1000000))
print("Training done in: %fs" % (time() - t0))
t0 = time()
# Update best crf
crf = rs.best_estimator_
# Saving model
print(" Saving training model...")
t1 = time()
nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + '_S3_' + str(options.S3) + '_' + str(options.Gridname) + str(options.version) + '.mod'
joblib.dump(crf, os.path.join(options.outputPath, "models", nameModel))
print(" Saving training model done in: %fs" % (time() - t1))
# Evaluation against test data
y_pred = crf.predict(X_test)
print("*********************************")
print("Prediction done in: %fs" % (time() - t0))
# labels = list(crf.classes_)
# labels.remove('O')
with open(os.path.join(options.outputPath, "reports", "report_" + nameReport), mode="a") as oFile:
oFile.write('\n')
oFile.write("Flat F1: " + str(metrics.flat_f1_score(y_test, y_pred, average='weighted', labels=labels)))
oFile.write('\n')
# labels = list(crf.classes_)
sorted_labels = sorted(
labels,
key=lambda name: (name[1:], name[0])
)
oFile.write(metrics.flat_classification_report(
y_test, y_pred, labels=sorted_labels, digits=3
))
oFile.write('\n')
oFile.write("\nTop likely transitions:\n")
print_transitions(Counter(crf.transition_features_).most_common(50), oFile)
oFile.write('\n')
oFile.write("\nTop unlikely transitions:\n")
print_transitions(Counter(crf.transition_features_).most_common()[-50:], oFile)
oFile.write('\n')
oFile.write("\nTop positive:\n")
print_state_features(Counter(crf.state_features_).most_common(200), oFile)
oFile.write('\n')
oFile.write("\nTop negative:\n")
print_state_features(Counter(crf.state_features_).most_common()[-200:], oFile)
oFile.write('\n')
# -*- coding: UTF-8 -*-
import os
from itertools import chain
from optparse import OptionParser
from time import time
from collections import Counter
import re
import nltk
import sklearn
import scipy.stats
import sys
from sklearn.externals import joblib
from sklearn.metrics import make_scorer
from sklearn.cross_validation import cross_val_score
from sklearn.grid_search import RandomizedSearchCV
import sklearn_crfsuite
from sklearn_crfsuite import scorers
from sklearn_crfsuite import metrics
from pandas import DataFrame as DF
from nltk.corpus import stopwords
# Objective
# Training and evaluation of CRFs with sklearn-crfsuite.
#
# Input parameters
# --inputPath=PATH Path of training and test data set
# --trainingFile File with training data set
# --testFile File with test data set
# --outputPath=PATH Output path to place output files
# --nameGrid Number of run
# --version Version Report
# Output
# 1) Best model
# 2) Report
# Examples
# python training_validation_v10.py
# --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
# --trainingFile training-data-set-70.txt
# --testFile test-data-set-30.txt
# --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/
# --version _v1
# python3 training_validation_v9.py --inputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets --trainingFile training-data-set-70.txt --testFile test-data-set-30.txt --outputPath /home/egaytan/automatic-extraction-growth-conditions/CRF/ --nameGrid Run1 --version _v1 --S1 --S2 --S3
##################################################################
# FEATURES #
##################################################################
#================== COMPLETE WORD FEATURES ======================#
def isGreek(word):
## Complete word are greek letters
alphabet = ['Α','Β','Γ','Δ','Ε','Ζ','Η','Θ','Ι','Κ','Λ','Μ','Ν','Ξ','Ο','Π','Ρ','Σ','Τ','Υ','Φ','Χ','Ψ','Ω',
'α','β','γ','δ','ε','ζ','η','θ','ι','κ','λ','μ','ν','ξ','ο','π','ρ','ς','σ','τ','υ','φ','χ','ψ','ω']
if word in alphabet:
return True
else:
return False
#================ INNER OF THE WORD FEATURES ====================#
def hNumber(word):
## Al leats has one greek letter
for l in word:
if l.isdigit():
return True
return False
def symb(word):
n=0
## At least a not alphanumeric character
for l in word:
if l.isdigit(): n = n+1
if l.isalpha(): n = n+1
#Exclude Greek letters
if isGreek(l): n = n+1
if n<len(word): return True
else: return False
def hUpper(word):
## At least an upper letter
for l in word:
if l.isupper(): return True
return False
def hLower(word):
## At least a lower letter
for l in word:
if l.islower(): return True
return False
def hGreek(word):
## At least a greek letter
for l in word:
if isGreek(l): return True
return False
#============================FEATURES===========================#
def word2features(sent, i, S1, S2, S3):
## Getting word features
## Saving CoreNLP annotations
listElem = sent[i].split('|')
word = listElem[0]
lemma = listElem[1]
postag = listElem[2]
#ner = listElem[4]
#=========================== G =============================#
## NAME LEVEL G
## FUTURE TYPE General features
features = {
## basal features
'lemma': lemma,
'postag': postag
}
## more tha one word in sentence
if i > 0:
## Anterior word
listElem = sent[i - 1].split('|')
## Saving CoreNLP annotations
lemma0 = listElem[1]
postag0 = listElem[2]
features.update({
#LemaG anterior
'-1:lemma': lemma0,
#Postag anterior
'-1:postag': postag0,
})
## is not the last word
if i < len(sent) - 1:
## Posterior word
listElem = sent[i + 1].split('|')
## Saving CoreNLP annotations
lemma2 = listElem[1]
postag2 = listElem[2]
features.update({
#LemaG posterior
'+1:lemma': lemma2,
#Postag posterior
'+1:postag': postag2,
})
#=========================== S1 =============================#
## NAME LEVEL S1
## FEATURE TYPE Inner word features
if S1:
#Add features
features['hUpper']= hUpper(word)
features['hLower']= hUpper(word)
features['hGreek']= hGreek(word)
features['symb']= symb(word)
'''
#word firstChar
features['word[:1]']= word[:1]
#word secondChar
if len(word)>1:
features['word[:2]']= word[:2]
'''
#lemma and postag firstChar
features['lemma[:1]']= lemma[:1]
#features['postag[:1]']= postag[:1]
#lemma and postag secondChar
if len(lemma)>1:
features['lemma[:2]']= lemma[:2]
'''
if len(postag)>1:
features['postag[:2]']= postag[:2]
'''
#=========================== S2 =============================#
## NAME LEVEL S2
## FEATURE TYPE Complete word features
if S2:
#Add features
features['word']= word
features['isUpper']= word.isupper()
features['isLower']= word.islower()
features['isGreek']= isGreek(word)
features['isNumber']= word.isdigit()
## more tha one word in sentence
if i > 0:
## Anterior word
listElem = sent[i - 1].split('|')
## Saving CoreNLP annotations
word0 = listElem[0]
features['-1:word']= word0
## is not the last word
if i < len(sent)-1:
listElem = sent[i + 1].split('|')
## Saving CoreNLP annotations
word2 = listElem[0]
## Posterior word
features['+1:word']= word2
#=========================== S3 =============================#
## NAME LEVEL S3
## FEATURE TYPE Extended context features
if S3:
## more tha two words in sentence
if i > 1:
## two anterior lemma and postag
listElem = sent[i - 2].split('|')
## Saving CoreNLP annotations
lemma01 = listElem[1]
postag01 = listElem[2]
features['-2:lemma']= lemma01
features['-2:postag']= postag01
## is not the penultimate word
if i < len(sent) - 2:
listElem = sent[i + 2].split('|')
## Saving CoreNLP annotations
lemma02 = listElem[1]
postag02 = listElem[2]
## two posterior lemma and postag
features['+2:lemma']= lemma02
features['+2:postag']= postag02
return features
def sent2features(sent, S1, S2, S3):
## Itering in sentence for each word and saving its features
return [word2features(sent, i, S1, S2, S3) for i in range(len(sent))]
def sent2labels(sent):
## 3rd position by word is the label
return [elem.split('|')[3] for elem in sent]
def sent2tokens(sent):
return [token for token, postag, label in sent]
def print_transitions(trans_features, f):
for (label_from, label_to), weight in trans_features:
f.write("{:6} -> {:7} {:0.6f}\n".format(label_from, label_to, weight))
def print_state_features(state_features, f):
for (attr, label), weight in state_features:
f.write("{:0.6f} {:8} {}\n".format(weight, label, attr.encode("utf-8")))
__author__ = 'egaytan'
##################################################################
# MAIN PROGRAM #
##################################################################
if __name__ == "__main__":
## Defining parameters
parser = OptionParser()
parser.add_option("--inputPath", dest="inputPath", help="Path of training data set", metavar="PATH")
parser.add_option("--outputPath", dest="outputPath", help="Output path to place output files", metavar="PATH")
parser.add_option("--trainingFile", dest="trainingFile", help="File with training data set", metavar="FILE")
parser.add_option("--testFile", dest="testFile", help="File with test data set", metavar="FILE")
parser.add_option("--Gridname", dest="Gridname", help="Report number run", metavar="FILE")
parser.add_option("--version", dest="version", help="Report file", metavar="FILE")
parser.add_option("--S1", dest="S1", help="Future Type", action="store_true", default=False)
parser.add_option("--S2", dest="S2", help="Future Type", action="store_true", default=False)
parser.add_option("--S3", dest="S3", help="Future Type", action="store_true", default=False)
parser.add_option("--excludeStopWords", dest="excludeStopWords",help="Exclude stop words", action="store_true", default=False)
parser.add_option("--excludeSymbols", dest="excludeSymbols", help="Exclude punctuation marks", action="store_true", default=False)
(options, args) = parser.parse_args()
if len(args) > 0:
parser.error("Any parameter given.")
sys.exit(1)
print('-------------------------------- PARAMETERS --------------------------------')
print("Path of training data set: " + options.inputPath)
print("File with training data set: " + str(options.trainingFile))
print("Path of test data set: " + options.inputPath)
print("File with test data set: " + str(options.testFile))
print("Exclude stop words: " + str(options.excludeStopWords))
print("Levels: " + str(options.S1) + " " + str(options.S2))
print("Report file: " + str(options.version))
symbols = ['.', ',', ':', ';', '?', '!', '\'', '"', '<', '>', '(', ')', '-', '_', '/', '\\', '¿', '¡', '+', '{',
'}', '[', ']', '*', '%', '$', '#', '&', '°', '`', '...']
print("Exclude symbols: " + str(options.excludeSymbols))
print('-------------------------------- PROCESSING --------------------------------')
print('Reading corpus...')
t0 = time()
sentencesTrainingData = []
sentencesTestData = []
stopwords = [word for word in stopwords.words('english')]
with open(os.path.join(options.inputPath, options.trainingFile), "r") as iFile:
for line in iFile.readlines():
listLine = []
line = line.strip('\n')
for token in line.split():
if options.excludeStopWords:
listToken = token.split('|')
lemma = listToken[1]
if lemma in stopwords:
continue
if options.excludeSymbols:
listToken = token.split('|')
lemma = listToken[1]
if lemma in symbols:
continue
listLine.append(token)
sentencesTrainingData.append(listLine)
print(" Sentences training data: " + str(len(sentencesTrainingData)))
with open(os.path.join(options.inputPath, options.testFile), "r") as iFile:
for line in iFile.readlines():
listLine = []
line = line.strip('\n')
for token in line.split():
if options.excludeStopWords:
listToken = token.split('|')
lemma = listToken[1]
if lemma in stopwords:
continue
if options.excludeSymbols:
listToken = token.split('|')
lemma = listToken[1]
if lemma in symbols:
continue
listLine.append(token)
sentencesTestData.append(listLine)
print(" Sentences test data: " + str(len(sentencesTestData)))
print("Reading corpus done in: %fs" % (time() - t0))
print('-------------------------------- FEATURES --------------------------------')
Dtraning = sent2features(sentencesTrainingData[0], options.S1, options.S2, options.S3)[2]
Dtest = sent2features(sentencesTestData[0], options.S1, options.S2, options.S3)[2]
print('--------------------------Features Training ---------------------------')
print(DF(list(Dtraning.items())))
print('--------------------------- FeaturesTest -----------------------------')
print(DF(list(Dtest.items())))
t0 = time()
X_train = [sent2features(s, options.S1, options.S2, options.S3) for s in sentencesTrainingData]
y_train = [sent2labels(s) for s in sentencesTrainingData]
X_test = [sent2features(s, options.S1, options.S2, options.S3) for s in sentencesTestData]
# print X_test
y_test = [sent2labels(s) for s in sentencesTestData]
# Fixed parameters
# crf = sklearn_crfsuite.CRF(
# algorithm='lbfgs',
# c1=0.1,
# c2=0.1,
# max_iterations=100,
# all_pgossible_transitions=True
# )
# Hyperparameter Optimization
crf = sklearn_crfsuite.CRF(
algorithm='lbfgs',
max_iterations=100,
all_possible_transitions=True
)
params_space = {
'c1': scipy.stats.expon(scale=0.5),
'c2': scipy.stats.expon(scale=0.05),
}
# Original: labels = list(crf.classes_)
# Original: labels.remove('O')
labels = list(['Gtype', 'Gversion', 'Med', 'Phase', 'Strain', 'Substrain', 'Supp', 'Technique', 'Temp', 'OD', 'Anti', 'Agit', 'Air', 'Vess', 'pH'])
# use the same metric for evaluation
f1_scorer = make_scorer(metrics.flat_f1_score,
average='weighted', labels=labels)
# search
rs = RandomizedSearchCV(crf, params_space,
cv=10,
verbose=3,
n_jobs=-1,
n_iter=20,
# n_iter=50,
scoring=f1_scorer)
rs.fit(X_train, y_train)
# Fixed parameters
# crf.fit(X_train, y_train)
# Best hiperparameters
# crf = rs.best_estimator_
nameReport = str(options.Gridname) + str(options.version) + '.txt'
with open(os.path.join(options.outputPath, "reports", "report_" + nameReport), mode="w") as oFile:
oFile.write("********** TRAINING AND TESTING REPORT **********\n")
oFile.write("Training file: " + options.trainingFile + '\n')
oFile.write('\n')
oFile.write('best params:' + str(rs.best_params_) + '\n')
oFile.write('best CV score:' + str(rs.best_score_) + '\n')
oFile.write('model size: {:0.2f}M\n'.format(rs.best_estimator_.size_ / 1000000))
print("Training done in: %fs" % (time() - t0))
t0 = time()
# Update best crf
crf = rs.best_estimator_
# Saving model
print(" Saving training model...")
t1 = time()
nameModel = 'model_S1_' + str(options.S1) + '_S2_' + str(options.S2) + '_S3_' + str(options.S3) + '_' + str(options.Gridname) + str(options.version) +'.mod'
joblib.dump(crf, os.path.join(options.outputPath, "models", nameModel))
print(" Saving training model done in: %fs" % (time() - t1))
# Evaluation against test data
y_pred = crf.predict(X_test)
print("*********************************")
print("Prediction done in: %fs" % (time() - t0))
# labels = list(crf.classes_)
# labels.remove('O')
with open(os.path.join(options.outputPath, "reports", "report_" + nameReport), mode="a") as oFile:
oFile.write('\n')
oFile.write("Flat F1: " + str(metrics.flat_f1_score(y_test, y_pred, average='weighted', labels=labels)))
oFile.write('\n')
# labels = list(crf.classes_)
sorted_labels = sorted(
labels,
key=lambda name: (name[1:], name[0])
)
oFile.write(metrics.flat_classification_report(
y_test, y_pred, labels=sorted_labels, digits=3
))
oFile.write('\n')
oFile.write("\nTop likely transitions:\n")
print_transitions(Counter(crf.transition_features_).most_common(50), oFile)
oFile.write('\n')
oFile.write("\nTop unlikely transitions:\n")
print_transitions(Counter(crf.transition_features_).most_common()[-50:], oFile)
oFile.write('\n')
oFile.write("\nTop positive:\n")
print_state_features(Counter(crf.state_features_).most_common(200), oFile)
oFile.write('\n')
oFile.write("\nTop negative:\n")
print_state_features(Counter(crf.state_features_).most_common()[-200:], oFile)
oFile.write('\n')
mv model_S1_False_S2_False_v11_S3_False.mod model_S1_False_S2_False_S3_False_Run_1_v11.mod
mv model_S1_True_S2_False_v11_S3_False.mod model_S1_True_S2_False_S3_False_Run_2_v11.mod
mv model_S1_False_S2_True_v11_S3_False.mod model_S1_False_S2_True_S3_False_Run_3_v11.mod
mv model_S1_True_S2_True_v11_S3_False.mod model_S1_True_S2_True_S3_False_Run_4_v11.mod
mv model_S1_False_S2_False_v11_S3_True.mod model_S1_False_S2_False_S3_True_Run_5_v11.mod
mv model_S1_True_S2_False_v11_S3_True.mod model_S1_True_S2_False_S3_True_Run_6_v11.mod
mv model_S1_False_S2_True_v11_S3_True.mod model_S1_False_S2_True_S3_True_Run_7_v11.mod
mv model_S1_True_S2_True_v11_S3_True.mod model_S1_True_S2_True_S3_True_Run_8_v11.mod
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: False False
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003697s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.754459 - 0.9s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.884863 - 1.0s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.921051 - 1.0s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.708368 - 1.1s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.823525 - 1.0s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.686315 - 0.9s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.797169 - 1.0s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.891872 - 1.1s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.827517 - 1.0s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.790114 - 1.1s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.846283 - 1.0s
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[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
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[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
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[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
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[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
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[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
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[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
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[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
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[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
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[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
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[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
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[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
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[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
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[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
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[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
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[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
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[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
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[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
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[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
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[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
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[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
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[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
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[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
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[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
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[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
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[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
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[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
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[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
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[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
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[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
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[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
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[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
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[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
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[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
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[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
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[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
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[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
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[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
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[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
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[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
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[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
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[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
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[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
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[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
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[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
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[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
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[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
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[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
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[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
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[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
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[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
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[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
[CV] c1=0.566877090439985, c2=0.11885476879365008, score=0.807845 - 1.0s
[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
[CV] c1=0.5013481333641194, c2=0.0038888430334755165, score=0.708368 - 1.1s
[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
[CV] c1=0.55474081003644, c2=0.03200599838771336, score=0.794216 - 1.1s
[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
[CV] c1=0.8754300341342343, c2=0.07834116642130053, score=0.761012 - 0.9s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.851982 - 1.0s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.655956 - 0.9s
[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
[CV] c1=0.5013481333641194, c2=0.0038888430334755165, score=0.869930 - 1.0s
[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
[CV] c1=0.55474081003644, c2=0.03200599838771336, score=0.884863 - 1.0s
[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
[CV] c1=0.8754300341342343, c2=0.07834116642130053, score=0.686315 - 1.0s
[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
[CV] c1=0.4716413701252996, c2=0.020707741802851287, score=0.869930 - 1.1s
[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
[CV] c1=0.6408852258158738, c2=0.00974947513922504, score=0.794216 - 1.1s
[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
[CV] c1=0.5013481333641194, c2=0.0038888430334755165, score=0.894739 - 1.1s
[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
[CV] c1=0.55474081003644, c2=0.03200599838771336, score=0.848019 - 1.0s
[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
[CV] c1=0.8754300341342343, c2=0.07834116642130053, score=0.587002 - 1.0s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.921051 - 1.0s
[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
[CV] c1=0.6408852258158738, c2=0.00974947513922504, score=0.924261 - 1.1s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.839679 - 1.1s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.884863 - 1.0s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.879947 - 0.8s
[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
[CV] c1=0.4716413701252996, c2=0.020707741802851287, score=0.920058 - 1.1s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.765776 - 1.1s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.920093 - 1.0s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.797169 - 0.9s
[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
[CV] c1=0.8754300341342343, c2=0.07834116642130053, score=0.735694 - 1.0s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.783479 - 1.1s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.846283 - 1.0s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.853491 - 1.0s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.707416 - 1.1s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.679174 - 0.9s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.752310 - 1.1s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.807845 - 1.1s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.855893 - 1.1s
[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
[CV] c1=1.7051690366028645, c2=0.04119436723956498, score=0.693211 - 1.1s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.920058 - 1.1s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.812884 - 1.0s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.759895 - 1.0s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.708368 - 1.1s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.856415 - 1.0s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.859998 - 0.9s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.868591 - 1.0s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.683196 - 1.1s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.921051 - 1.0s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.619013 - 1.1s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.781269 - 0.8s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.729107 - 1.1s
[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
[CV] c1=0.566877090439985, c2=0.11885476879365008, score=0.797169 - 1.0s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.871681 - 1.3s
[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
[CV] c1=0.55474081003644, c2=0.03200599838771336, score=0.707115 - 1.1s
[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
[CV] c1=0.8754300341342343, c2=0.07834116642130053, score=0.765873 - 1.1s
[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
[CV] c1=0.4716413701252996, c2=0.020707741802851287, score=0.868591 - 1.0s
[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
[CV] c1=0.6408852258158738, c2=0.00974947513922504, score=0.893214 - 1.1s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.857498 - 1.0s
[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
[CV] c1=0.55474081003644, c2=0.03200599838771336, score=0.862342 - 1.1s
[CV] c1=0.8754300341342343, c2=0.07834116642130053 ...................
[CV] c1=0.8754300341342343, c2=0.07834116642130053, score=0.905836 - 1.0s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.913639 - 1.1s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.709347 - 1.1s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.922832 - 1.1s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.919477 - 1.1s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.927169 - 0.8s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.708368 - 1.1s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.548315 - 1.1s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.794216 - 1.1s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.821611 - 1.1s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.836791 - 0.8s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.827517 - 1.0s
[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
[CV] c1=0.6408852258158738, c2=0.00974947513922504, score=0.804678 - 1.1s
[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
[CV] c1=0.5013481333641194, c2=0.0038888430334755165, score=0.812884 - 1.1s
[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
[CV] c1=0.55474081003644, c2=0.03200599838771336, score=0.927188 - 1.1s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.919905 - 0.9s
[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
[CV] c1=0.37003802271170205, c2=0.03235596392564057, score=0.914009 - 1.0s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.883195 - 1.0s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.824977 - 1.0s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.824046 - 1.0s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.889676 - 0.9s
[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
[CV] c1=0.4716413701252996, c2=0.020707741802851287, score=0.812884 - 1.1s
[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
[CV] c1=1.3109075902903429, c2=0.0987913465628396, score=0.746345 - 1.1s
[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
[CV] c1=0.19892136084009834, c2=0.0215890963028946, score=0.906540 - 1.1s
[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
[CV] c1=0.6236675675631103, c2=0.08801024577462967, score=0.772475 - 1.1s
[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
[CV] c1=0.06704945233304155, c2=0.06794151143065376, score=0.876457 - 0.8s
Training done in: 6.765294s
Saving training model...
Saving training model done in: 0.016333s
*********************************
Prediction done in: 0.029945s
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: True False
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003524s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 lemma[:1] 2
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 hUpper True
7 hLower True
8 hGreek False
9 symb True
10 lemma[:1] d
11 lemma[:2] de
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
[CV] c1=0.0505702396295773, c2=0.03724107191018463, score=0.903013 - 1.0s
[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
[CV] c1=0.14504807394901736, c2=0.07115988818379711, score=0.823347 - 1.2s
[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
[CV] c1=0.09696363230645079, c2=0.05497775519339914, score=0.826770 - 1.3s
[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
[CV] c1=0.1708100222872568, c2=0.17867095411785475, score=0.804632 - 1.3s
[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
[CV] c1=0.17887820290814255, c2=0.02972437620845303, score=0.822297 - 1.3s
[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
[CV] c1=0.0505702396295773, c2=0.03724107191018463, score=0.768346 - 1.2s
[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
[CV] c1=0.14504807394901736, c2=0.07115988818379711, score=0.914124 - 1.2s
[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
[CV] c1=0.09696363230645079, c2=0.05497775519339914, score=0.826784 - 1.2s
[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
[CV] c1=0.1708100222872568, c2=0.17867095411785475, score=0.818942 - 1.2s
[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
[CV] c1=0.17887820290814255, c2=0.02972437620845303, score=0.813100 - 1.4s
[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
[CV] c1=0.0505702396295773, c2=0.03724107191018463, score=0.839590 - 1.2s
[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
[CV] c1=0.14504807394901736, c2=0.07115988818379711, score=0.920107 - 1.2s
[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
[CV] c1=0.09696363230645079, c2=0.05497775519339914, score=0.914124 - 1.3s
[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
[CV] c1=0.1708100222872568, c2=0.17867095411785475, score=0.832633 - 1.3s
[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
[CV] c1=0.17887820290814255, c2=0.02972437620845303, score=0.914124 - 1.2s
[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
[CV] c1=0.0505702396295773, c2=0.03724107191018463, score=0.845585 - 1.0s
[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
[CV] c1=0.14504807394901736, c2=0.07115988818379711, score=0.768346 - 1.4s
[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
[CV] c1=0.09696363230645079, c2=0.05497775519339914, score=0.794216 - 1.3s
[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
[CV] c1=0.1708100222872568, c2=0.17867095411785475, score=0.914573 - 1.2s
[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
[CV] c1=0.17887820290814255, c2=0.02972437620845303, score=0.741087 - 1.4s
[CV] c1=0.2953014349078118, c2=0.0012108405088671111 .................
[CV] c1=0.2953014349078118, c2=0.0012108405088671111, score=0.822003 - 1.1s
[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
[CV] c1=0.14504807394901736, c2=0.07115988818379711, score=0.858878 - 1.3s
[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
[CV] c1=0.09696363230645079, c2=0.05497775519339914, score=0.927031 - 1.2s
[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
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[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
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[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
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[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
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[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
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[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
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[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
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[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
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[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
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[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
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[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
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[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
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[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
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[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.2953014349078118, c2=0.0012108405088671111 .................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
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[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
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[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
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[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.2953014349078118, c2=0.0012108405088671111 .................
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[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
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[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
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[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
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[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
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[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
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[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
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[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
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[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
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[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
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[CV] c1=0.2953014349078118, c2=0.0012108405088671111 .................
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[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
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[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
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[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
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[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
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[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
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[CV] c1=0.14504807394901736, c2=0.07115988818379711 ..................
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[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
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[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
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[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
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[CV] c1=1.7637796840994346, c2=0.051521349900768856 ..................
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[CV] c1=0.0505702396295773, c2=0.03724107191018463 ...................
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[CV] c1=0.09696363230645079, c2=0.05497775519339914 ..................
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[CV] c1=0.1708100222872568, c2=0.17867095411785475 ...................
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[CV] c1=0.17887820290814255, c2=0.02972437620845303 ..................
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[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
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[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
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[CV] c1=0.2953014349078118, c2=0.0012108405088671111 .................
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[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
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[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
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[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
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[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
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[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
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[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
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[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
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[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
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[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
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[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
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[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
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[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
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[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
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[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
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[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
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[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
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[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
[CV] c1=0.13330184503096318, c2=0.015952382909212963, score=0.860459 - 1.3s
[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
[CV] c1=0.2359376373743631, c2=0.039179017178379495, score=0.892261 - 1.1s
[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
[CV] c1=0.06034444472286749, c2=0.04518594376646258, score=0.796207 - 1.4s
[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
[CV] c1=0.049883149420407336, c2=0.07084188092752734, score=0.866858 - 1.3s
[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
[CV] c1=0.5134380380315382, c2=0.007750215333905019, score=0.929292 - 1.3s
[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
[CV] c1=0.05001865029147576, c2=0.03772187459395407, score=0.864644 - 1.3s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.823109 - 1.0s
[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
[CV] c1=0.2063113369204353, c2=0.15341573930424565, score=0.837805 - 1.3s
[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
[CV] c1=0.06894682357962188, c2=0.003142860192667755, score=0.894860 - 1.2s
[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
[CV] c1=0.7592894566389128, c2=0.05514117224596054, score=0.783557 - 1.2s
[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
[CV] c1=0.13330184503096318, c2=0.015952382909212963, score=0.897553 - 1.3s
[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
[CV] c1=0.2359376373743631, c2=0.039179017178379495, score=0.908120 - 1.1s
[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
[CV] c1=0.06034444472286749, c2=0.04518594376646258, score=0.919306 - 1.3s
[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
[CV] c1=0.06894682357962188, c2=0.003142860192667755, score=0.823347 - 1.1s
[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
[CV] c1=0.5134380380315382, c2=0.007750215333905019, score=0.860662 - 1.3s
[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
[CV] c1=0.13330184503096318, c2=0.015952382909212963, score=0.924267 - 1.2s
[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
[CV] c1=0.2359376373743631, c2=0.039179017178379495, score=0.794216 - 1.3s
[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
[CV] c1=0.2063113369204353, c2=0.15341573930424565, score=0.806663 - 1.4s
[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
[CV] c1=0.06894682357962188, c2=0.003142860192667755, score=0.858057 - 1.3s
[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
[CV] c1=0.7592894566389128, c2=0.05514117224596054, score=0.804464 - 1.4s
[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
[CV] c1=0.05001865029147576, c2=0.03772187459395407, score=0.940579 - 1.2s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.741087 - 1.1s
[CV] c1=0.2953014349078118, c2=0.0012108405088671111 .................
[CV] c1=0.2953014349078118, c2=0.0012108405088671111, score=0.855571 - 1.4s
[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
[CV] c1=0.098397359682104, c2=0.018958226770139863, score=0.845585 - 1.3s
[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
[CV] c1=0.23305546986968095, c2=0.053519080953157376, score=0.929292 - 1.3s
[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
[CV] c1=0.13330184503096318, c2=0.015952382909212963, score=0.847686 - 1.4s
[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
[CV] c1=0.2359376373743631, c2=0.039179017178379495, score=0.820852 - 1.2s
[CV] c1=0.06034444472286749, c2=0.04518594376646258 ..................
[CV] c1=0.06034444472286749, c2=0.04518594376646258, score=0.927031 - 1.3s
[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
[CV] c1=0.049883149420407336, c2=0.07084188092752734, score=0.839590 - 1.3s
[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
[CV] c1=0.5134380380315382, c2=0.007750215333905019, score=0.904818 - 1.3s
[CV] c1=0.13330184503096318, c2=0.015952382909212963 .................
[CV] c1=0.13330184503096318, c2=0.015952382909212963, score=0.845585 - 1.3s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.807863 - 1.2s
[CV] c1=0.2953014349078118, c2=0.0012108405088671111 .................
[CV] c1=0.2953014349078118, c2=0.0012108405088671111, score=0.741087 - 1.3s
[CV] c1=0.098397359682104, c2=0.018958226770139863 ...................
[CV] c1=0.098397359682104, c2=0.018958226770139863, score=0.768346 - 1.4s
[CV] c1=0.23305546986968095, c2=0.053519080953157376 .................
[CV] c1=0.23305546986968095, c2=0.053519080953157376, score=0.794216 - 1.4s
[CV] c1=2.333584831476656, c2=0.013244261040358064 ...................
[CV] c1=2.333584831476656, c2=0.013244261040358064, score=0.728777 - 1.4s
[CV] c1=0.2359376373743631, c2=0.039179017178379495 ..................
[CV] c1=0.2359376373743631, c2=0.039179017178379495, score=0.860459 - 1.3s
[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
[CV] c1=0.2063113369204353, c2=0.15341573930424565, score=0.818942 - 1.3s
[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
[CV] c1=0.06894682357962188, c2=0.003142860192667755, score=0.840844 - 1.4s
[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
[CV] c1=0.7592894566389128, c2=0.05514117224596054, score=0.798293 - 1.2s
[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
[CV] c1=0.05001865029147576, c2=0.03772187459395407, score=0.796207 - 1.3s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.855571 - 1.1s
[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
[CV] c1=0.2063113369204353, c2=0.15341573930424565, score=0.768346 - 1.4s
[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
[CV] c1=0.06894682357962188, c2=0.003142860192667755, score=0.892817 - 1.3s
[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
[CV] c1=0.7592894566389128, c2=0.05514117224596054, score=0.857689 - 1.3s
[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
[CV] c1=0.05001865029147576, c2=0.03772187459395407, score=0.927031 - 1.3s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.896765 - 1.1s
[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
[CV] c1=0.2063113369204353, c2=0.15341573930424565, score=0.914573 - 1.2s
[CV] c1=0.049883149420407336, c2=0.07084188092752734 .................
[CV] c1=0.049883149420407336, c2=0.07084188092752734, score=0.845585 - 1.2s
[CV] c1=0.5134380380315382, c2=0.007750215333905019 ..................
[CV] c1=0.5134380380315382, c2=0.007750215333905019, score=0.816050 - 1.4s
[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
[CV] c1=0.05001865029147576, c2=0.03772187459395407, score=0.768346 - 1.3s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.857708 - 1.2s
[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
[CV] c1=0.2063113369204353, c2=0.15341573930424565, score=0.948580 - 1.4s
[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
[CV] c1=0.06894682357962188, c2=0.003142860192667755, score=0.935664 - 1.3s
[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
[CV] c1=0.7592894566389128, c2=0.05514117224596054, score=0.934521 - 1.3s
[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
[CV] c1=0.05001865029147576, c2=0.03772187459395407, score=0.926835 - 1.3s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.830456 - 1.1s
[CV] c1=0.2063113369204353, c2=0.15341573930424565 ...................
[CV] c1=0.2063113369204353, c2=0.15341573930424565, score=0.799176 - 1.3s
[CV] c1=0.06894682357962188, c2=0.003142860192667755 .................
[CV] c1=0.06894682357962188, c2=0.003142860192667755, score=0.822181 - 1.3s
[CV] c1=0.7592894566389128, c2=0.05514117224596054 ...................
[CV] c1=0.7592894566389128, c2=0.05514117224596054, score=0.856309 - 1.3s
[CV] c1=0.05001865029147576, c2=0.03772187459395407 ..................
[CV] c1=0.05001865029147576, c2=0.03772187459395407, score=0.864170 - 1.4s
[CV] c1=0.2879622492417609, c2=0.003122804893055269 ..................
[CV] c1=0.2879622492417609, c2=0.003122804893055269, score=0.923528 - 1.1s
Training done in: 8.470806s
Saving training model...
Saving training model done in: 0.013144s
*********************************
Prediction done in: 0.032331s
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: False True
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003601s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 word 2
5 isUpper False
6 isLower False
7 isGreek False
8 isNumber True
9 -1:word fructose
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 word delta-arcA
7 isUpper False
8 isLower False
9 isGreek False
10 isNumber False
11 -1:word _
12 +1:word _
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
[CV] c1=0.935722192523284, c2=0.0005318801626229629, score=0.930900 - 1.3s
[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
[CV] c1=0.6760058051882148, c2=0.00456290903506356, score=0.928690 - 1.3s
[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
[CV] c1=0.025397838188738985, c2=0.010943674737961755, score=0.930828 - 1.4s
[CV] c1=1.4843188945989627, c2=0.06435826732715343 ...................
[CV] c1=1.4843188945989627, c2=0.06435826732715343, score=0.683821 - 1.4s
[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
[CV] c1=0.7824372927862602, c2=0.32105281575317696, score=0.719421 - 1.0s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.867080 - 1.4s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.756173 - 1.3s
[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
[CV] c1=0.7019199343375351, c2=0.014002713155773422, score=0.773435 - 1.2s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.795085 - 1.5s
[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
[CV] c1=0.7824372927862602, c2=0.32105281575317696, score=0.684686 - 1.2s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.684280 - 1.5s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.856192 - 1.4s
[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
[CV] c1=0.7019199343375351, c2=0.014002713155773422, score=0.859281 - 1.3s
[CV] c1=1.4843188945989627, c2=0.06435826732715343 ...................
[CV] c1=1.4843188945989627, c2=0.06435826732715343, score=0.870142 - 1.4s
[CV] c1=0.002053052959069552, c2=0.018920275579881927 ................
[CV] c1=0.002053052959069552, c2=0.018920275579881927, score=0.849145 - 1.1s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.954622 - 1.4s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.780437 - 1.3s
[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
[CV] c1=0.7019199343375351, c2=0.014002713155773422, score=0.876548 - 1.3s
[CV] c1=1.4843188945989627, c2=0.06435826732715343 ...................
[CV] c1=1.4843188945989627, c2=0.06435826732715343, score=0.846283 - 1.4s
[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
[CV] c1=0.7824372927862602, c2=0.32105281575317696, score=0.848732 - 1.1s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.853491 - 1.3s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.788111 - 1.4s
[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
[CV] c1=0.7019199343375351, c2=0.014002713155773422, score=0.926918 - 1.4s
[CV] c1=1.4843188945989627, c2=0.06435826732715343 ...................
[CV] c1=1.4843188945989627, c2=0.06435826732715343, score=0.757382 - 1.4s
[CV] c1=0.002053052959069552, c2=0.018920275579881927 ................
[CV] c1=0.002053052959069552, c2=0.018920275579881927, score=0.927937 - 1.1s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.935212 - 1.3s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.772475 - 1.4s
[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
[CV] c1=0.7251994052584196, c2=0.059043207959615734, score=0.693707 - 1.4s
[CV] c1=0.5640531474503676, c2=0.06464287784131272 ...................
[CV] c1=0.5640531474503676, c2=0.06464287784131272, score=0.785527 - 1.2s
[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
[CV] c1=0.7824372927862602, c2=0.32105281575317696, score=0.760702 - 1.2s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.920093 - 1.3s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.859588 - 1.4s
[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
[CV] c1=0.7019199343375351, c2=0.014002713155773422, score=0.855506 - 1.3s
[CV] c1=1.4843188945989627, c2=0.06435826732715343 ...................
[CV] c1=1.4843188945989627, c2=0.06435826732715343, score=0.828806 - 1.4s
[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
[CV] c1=0.7824372927862602, c2=0.32105281575317696, score=0.890908 - 1.1s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.794216 - 1.3s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.572747 - 1.4s
[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
[CV] c1=0.7019199343375351, c2=0.014002713155773422, score=0.789760 - 1.5s
[CV] c1=1.4843188945989627, c2=0.06435826732715343 ...................
[CV] c1=1.4843188945989627, c2=0.06435826732715343, score=0.740710 - 1.4s
[CV] c1=0.002053052959069552, c2=0.018920275579881927 ................
[CV] c1=0.002053052959069552, c2=0.018920275579881927, score=0.814733 - 1.4s
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[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
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[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
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[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
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[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
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[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
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[CV] c1=0.002053052959069552, c2=0.018920275579881927 ................
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[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
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[CV] c1=0.5640531474503676, c2=0.06464287784131272 ...................
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[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
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[CV] c1=0.41373565924979, c2=0.09238653639376901 .....................
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[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
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[CV] c1=0.5640531474503676, c2=0.06464287784131272 ...................
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[CV] c1=0.41373565924979, c2=0.09238653639376901 .....................
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[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
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[CV] c1=0.5640531474503676, c2=0.06464287784131272 ...................
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[CV] c1=0.002053052959069552, c2=0.018920275579881927 ................
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[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
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[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
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[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
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[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
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[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
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[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.41373565924979, c2=0.09238653639376901 .....................
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[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
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[CV] c1=0.5640531474503676, c2=0.06464287784131272 ...................
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[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
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[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
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[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
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[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
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[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.002053052959069552, c2=0.018920275579881927 ................
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[CV] c1=0.41373565924979, c2=0.09238653639376901 .....................
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[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
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[CV] c1=0.5640531474503676, c2=0.06464287784131272 ...................
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[CV] c1=0.002053052959069552, c2=0.018920275579881927 ................
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[CV] c1=0.41373565924979, c2=0.09238653639376901 .....................
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[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
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[CV] c1=0.7251994052584196, c2=0.059043207959615734 ..................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
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[CV] c1=0.41373565924979, c2=0.09238653639376901 .....................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
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[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
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[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
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[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
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[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
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[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
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[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
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[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
[CV] c1=0.025397838188738985, c2=0.010943674737961755, score=0.867517 - 1.2s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
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[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.684751 - 1.0s
[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
[CV] c1=0.9221917662018542, c2=0.005799172918219737, score=0.919847 - 1.4s
[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
[CV] c1=0.6760058051882148, c2=0.00456290903506356, score=0.714206 - 1.4s
[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
[CV] c1=0.025397838188738985, c2=0.010943674737961755, score=0.709493 - 1.4s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.927937 - 1.3s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.857498 - 1.1s
[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
[CV] c1=0.935722192523284, c2=0.0005318801626229629, score=0.772475 - 1.3s
[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
[CV] c1=0.6760058051882148, c2=0.00456290903506356, score=0.780680 - 1.3s
[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
[CV] c1=0.025397838188738985, c2=0.010943674737961755, score=0.839499 - 1.3s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.915933 - 1.2s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.927937 - 1.0s
[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
[CV] c1=0.9221917662018542, c2=0.005799172918219737, score=0.890908 - 1.3s
[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
[CV] c1=0.019312034848527993, c2=0.0625879432690274, score=0.694239 - 1.4s
[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
[CV] c1=2.6412622667185475, c2=0.03736596703804092, score=0.617476 - 1.4s
[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
[CV] c1=1.652119003219986, c2=0.10376523465777213, score=0.796283 - 1.3s
[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
[CV] c1=0.7292179112540754, c2=0.004120725812307264, score=0.876548 - 1.3s
[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
[CV] c1=0.935722192523284, c2=0.0005318801626229629, score=0.743179 - 1.2s
[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
[CV] c1=0.019312034848527993, c2=0.0625879432690274, score=0.814733 - 1.4s
[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
[CV] c1=2.6412622667185475, c2=0.03736596703804092, score=0.533174 - 1.4s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.834805 - 1.3s
[CV] c1=0.7292179112540754, c2=0.004120725812307264 ..................
[CV] c1=0.7292179112540754, c2=0.004120725812307264, score=0.800642 - 1.2s
[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
[CV] c1=0.9221917662018542, c2=0.005799172918219737, score=0.772475 - 1.4s
[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
[CV] c1=0.019312034848527993, c2=0.0625879432690274, score=0.930828 - 1.3s
[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
[CV] c1=2.6412622667185475, c2=0.03736596703804092, score=0.717659 - 1.4s
[CV] c1=1.652119003219986, c2=0.10376523465777213 ....................
[CV] c1=1.652119003219986, c2=0.10376523465777213, score=0.690777 - 1.4s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.808985 - 1.2s
[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
[CV] c1=0.935722192523284, c2=0.0005318801626229629, score=0.890908 - 1.3s
[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
[CV] c1=0.6760058051882148, c2=0.00456290903506356, score=0.773435 - 1.2s
[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
[CV] c1=2.6412622667185475, c2=0.03736596703804092, score=0.666013 - 1.4s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.853328 - 1.5s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.862849 - 1.1s
[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
[CV] c1=0.935722192523284, c2=0.0005318801626229629, score=0.594163 - 1.4s
[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
[CV] c1=0.6760058051882148, c2=0.00456290903506356, score=0.863495 - 1.3s
[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
[CV] c1=0.025397838188738985, c2=0.010943674737961755, score=0.856072 - 1.4s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.863576 - 1.3s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.941978 - 1.1s
[CV] c1=0.9221917662018542, c2=0.005799172918219737 ..................
[CV] c1=0.9221917662018542, c2=0.005799172918219737, score=0.876548 - 1.4s
[CV] c1=0.019312034848527993, c2=0.0625879432690274 ..................
[CV] c1=0.019312034848527993, c2=0.0625879432690274, score=0.849711 - 1.3s
[CV] c1=2.6412622667185475, c2=0.03736596703804092 ...................
[CV] c1=2.6412622667185475, c2=0.03736596703804092, score=0.853878 - 1.4s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.683171 - 1.4s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.803015 - 1.2s
[CV] c1=0.935722192523284, c2=0.0005318801626229629 ..................
[CV] c1=0.935722192523284, c2=0.0005318801626229629, score=0.678563 - 1.4s
[CV] c1=0.6760058051882148, c2=0.00456290903506356 ...................
[CV] c1=0.6760058051882148, c2=0.00456290903506356, score=0.786229 - 1.4s
[CV] c1=0.025397838188738985, c2=0.010943674737961755 ................
[CV] c1=0.025397838188738985, c2=0.010943674737961755, score=0.946871 - 1.4s
[CV] c1=0.23160144515790687, c2=0.008798280691368095 .................
[CV] c1=0.23160144515790687, c2=0.008798280691368095, score=0.922832 - 1.3s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.892921 - 1.1s
[CV] c1=0.7824372927862602, c2=0.32105281575317696 ...................
[CV] c1=0.7824372927862602, c2=0.32105281575317696, score=0.553702 - 1.1s
[CV] c1=0.17393534309447636, c2=0.03996743049378701 ..................
[CV] c1=0.17393534309447636, c2=0.03996743049378701, score=0.839700 - 1.1s
[CV] c1=1.0739040365330779, c2=0.014049858881180455 ..................
[CV] c1=1.0739040365330779, c2=0.014049858881180455, score=0.690587 - 1.3s
[CV] c1=0.7019199343375351, c2=0.014002713155773422 ..................
[CV] c1=0.7019199343375351, c2=0.014002713155773422, score=0.714206 - 1.4s
[CV] c1=1.4843188945989627, c2=0.06435826732715343 ...................
[CV] c1=1.4843188945989627, c2=0.06435826732715343, score=0.648506 - 1.4s
[CV] c1=0.17593338376582365, c2=0.04437736465223883 ..................
[CV] c1=0.17593338376582365, c2=0.04437736465223883, score=0.813649 - 1.0s
Training done in: 8.711573s
Saving training model...
Saving training model done in: 0.013376s
*********************************
Prediction done in: 0.034608s
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: True True
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003628s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 lemma[:1] 2
9 word 2
10 isUpper False
11 isLower False
12 isGreek False
13 isNumber True
14 -1:word fructose
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 hUpper True
7 hLower True
8 hGreek False
9 symb True
10 lemma[:1] d
11 lemma[:2] de
12 word delta-arcA
13 isUpper False
14 isLower False
15 isGreek False
16 isNumber False
17 -1:word _
18 +1:word _
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.946646 - 1.6s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.864170 - 1.6s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.807845 - 1.7s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.929494 - 1.6s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.803340 - 1.4s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.840339 - 1.6s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.923027 - 1.5s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.798710 - 1.6s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.926918 - 1.5s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.837807 - 1.2s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.714781 - 1.6s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.820752 - 1.5s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.743438 - 1.5s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.830582 - 1.6s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.884496 - 1.4s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.929494 - 1.5s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.908120 - 1.5s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.913219 - 1.5s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.742060 - 1.6s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.904631 - 1.4s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.852640 - 1.5s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.830314 - 1.5s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.643754 - 1.6s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.815575 - 1.6s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.760326 - 1.4s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.913219 - 1.5s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.742060 - 1.7s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.817039 - 1.7s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.837271 - 1.6s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.932576 - 1.6s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.830873 - 1.4s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.820852 - 1.6s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.844732 - 1.6s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.924267 - 1.5s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.839590 - 1.5s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.830314 - 1.5s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.817039 - 1.5s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.798710 - 1.6s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.923027 - 1.3s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.769157 - 1.6s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.645578 - 1.4s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.870314 - 1.5s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.913219 - 1.5s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.820752 - 1.5s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.837807 - 1.3s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.807845 - 1.6s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.914885 - 1.7s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.734123 - 1.5s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.956017 - 1.6s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.826784 - 1.3s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.896825 - 1.5s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.731320 - 1.4s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.857484 - 1.7s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.851303 - 1.6s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.839590 - 1.3s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.794652 - 1.7s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.950725 - 1.7s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.772475 - 1.6s
[CV] c1=0.1252600216535052, c2=0.03782809818801547 ...................
[CV] c1=0.1252600216535052, c2=0.03782809818801547, score=0.923229 - 1.6s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.865652 - 1.4s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.794216 - 1.6s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.913219 - 1.4s
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05 .................
[CV] c1=1.1633545759416617, c2=4.814017520065372e-05, score=0.929494 - 1.6s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.807863 - 1.6s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.912280 - 1.5s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.784595 - 1.5s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.787673 - 1.6s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.799746 - 1.5s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.908120 - 1.4s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.855428 - 1.6s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.820852 - 1.6s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.914210 - 1.6s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.755608 - 1.7s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.814665 - 1.3s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.763659 - 1.5s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.769157 - 1.6s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.798710 - 1.6s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.587894 - 1.6s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.789624 - 1.6s
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.923027 - 1.5s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.823347 - 1.5s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.884120 - 1.5s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.946646 - 1.6s
[CV] c1=0.19452520614152963, c2=0.07921367781554413 ..................
[CV] c1=0.19452520614152963, c2=0.07921367781554413, score=0.832065 - 1.1s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.930758 - 1.6s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.524048 - 1.6s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.848615 - 1.6s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.922774 - 1.5s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.830456 - 1.4s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.839590 - 1.6s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.876468 - 1.5s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.799746 - 1.7s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.843908 - 1.5s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
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[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.818335 - 1.7s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.805797 - 1.6s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.714781 - 1.6s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.929292 - 1.5s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.920107 - 1.3s
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.848615 - 1.7s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.851303 - 1.5s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.867361 - 1.6s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.844732 - 1.3s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.833705 - 1.3s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.923229 - 1.4s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.814642 - 1.7s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.663126 - 1.5s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.712432 - 1.6s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.731210 - 1.6s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.923229 - 1.6s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.857414 - 1.6s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.719025 - 1.4s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.880765 - 1.5s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.904043 - 1.3s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.845585 - 1.3s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.867361 - 1.7s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.723924 - 1.8s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.848984 - 1.8s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.855571 - 1.4s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.926918 - 1.5s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.950725 - 1.6s
[CV] c1=1.0317333456990663, c2=0.008270998659918627 ..................
[CV] c1=1.0317333456990663, c2=0.008270998659918627, score=0.816050 - 1.6s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.772475 - 1.8s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.734741 - 1.5s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.851303 - 1.6s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.761785 - 1.6s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.820852 - 1.7s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.913219 - 1.4s
[CV] c1=0.19452520614152963, c2=0.07921367781554413 ..................
[CV] c1=0.19452520614152963, c2=0.07921367781554413, score=0.829435 - 1.2s
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.820752 - 1.5s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.797878 - 1.5s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.799176 - 1.6s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.735326 - 1.6s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.802530 - 1.5s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.926918 - 1.5s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.706226 - 1.6s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.769157 - 1.6s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.799176 - 1.6s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.789624 - 1.5s
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.794216 - 1.6s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.926918 - 1.5s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.637277 - 1.6s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.656649 - 1.6s
[CV] c1=0.19452520614152963, c2=0.07921367781554413 ..................
[CV] c1=0.19452520614152963, c2=0.07921367781554413, score=0.794216 - 1.3s
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653 ................
[CV] c1=6.554750484992917e-05, c2=0.05088901762281653, score=0.867442 - 1.7s
[CV] c1=0.2482723614159239, c2=0.0959138388411172 ....................
[CV] c1=0.2482723614159239, c2=0.0959138388411172, score=0.921016 - 1.7s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.950725 - 1.7s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.734123 - 1.5s
[CV] c1=0.19452520614152963, c2=0.07921367781554413 ..................
[CV] c1=0.19452520614152963, c2=0.07921367781554413, score=0.742060 - 1.3s
[CV] c1=0.10224977118326696, c2=0.08574073868552615 ..................
[CV] c1=0.10224977118326696, c2=0.08574073868552615, score=0.922774 - 1.3s
[CV] c1=1.1334212532044017, c2=0.007010862010272158 ..................
[CV] c1=1.1334212532044017, c2=0.007010862010272158, score=0.643754 - 1.7s
[CV] c1=0.24448285707107864, c2=0.07828996063095572 ..................
[CV] c1=0.24448285707107864, c2=0.07828996063095572, score=0.806504 - 2.0s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.817039 - 1.6s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.860742 - 1.6s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.820676 - 1.7s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.852396 - 1.5s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.923027 - 1.4s
[CV] c1=1.3271060079387977, c2=0.016327328938926227 ..................
[CV] c1=1.3271060079387977, c2=0.016327328938926227, score=0.924280 - 1.6s
[CV] c1=0.28189060423376666, c2=0.03192405059605604 ..................
[CV] c1=0.28189060423376666, c2=0.03192405059605604, score=0.923528 - 1.4s
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.807863 - 1.6s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.742060 - 1.6s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.798710 - 1.5s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.798710 - 1.6s
[CV] c1=0.19452520614152963, c2=0.07921367781554413 ..................
[CV] c1=0.19452520614152963, c2=0.07921367781554413, score=0.923027 - 1.3s
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.734741 - 1.7s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.924267 - 1.5s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.817039 - 1.6s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.890895 - 1.6s
[CV] c1=0.19452520614152963, c2=0.07921367781554413 ..................
[CV] c1=0.19452520614152963, c2=0.07921367781554413, score=0.842269 - 1.2s
[CV] c1=0.07240461944941606, c2=0.016662416283521466 .................
[CV] c1=0.07240461944941606, c2=0.016662416283521466, score=0.936198 - 1.7s
[CV] c1=1.9180357321696457, c2=0.042428547481606495 ..................
[CV] c1=1.9180357321696457, c2=0.042428547481606495, score=0.886457 - 1.5s
[CV] c1=0.35893080441515235, c2=0.06547892139571729 ..................
[CV] c1=0.35893080441515235, c2=0.06547892139571729, score=0.929292 - 1.6s
[CV] c1=0.5319496072976292, c2=0.07723824010154955 ...................
[CV] c1=0.5319496072976292, c2=0.07723824010154955, score=0.816050 - 1.6s
[CV] c1=0.26433572200108835, c2=0.022956147621051873 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.914885 - 1.4s
[CV] c1=0.31977486593330257, c2=0.02388226330543089 ..................
[CV] c1=0.31977486593330257, c2=0.02388226330543089, score=0.920107 - 1.5s
[CV] c1=0.07274256234028868, c2=0.03280670164668215 ..................
[CV] c1=0.07274256234028868, c2=0.03280670164668215, score=0.815575 - 1.7s
[CV] c1=1.129501798705037, c2=0.020140916704590495 ...................
[CV] c1=1.129501798705037, c2=0.020140916704590495, score=0.866417 - 1.5s
[CV] c1=1.119719790930437, c2=0.054437062769718686 ...................
[CV] c1=1.119719790930437, c2=0.054437062769718686, score=0.817039 - 1.6s
[CV] c1=0.19452520614152963, c2=0.07921367781554413 ..................
[CV] c1=0.19452520614152963, c2=0.07921367781554413, score=0.837271 - 1.2s
Training done in: 10.069118s
Saving training model...
Saving training model done in: 0.014113s
*********************************
Prediction done in: 0.045015s
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: False False
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003560s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 -2:lemma Cra
5 -2:postag NNP
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 -2:lemma affyexp
7 -2:postag JJ
8 +2:lemma glucose
9 +2:postag NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.904317 - 1.1s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.866353 - 1.2s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.782679 - 1.2s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.844592 - 1.2s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.665848 - 1.2s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.935724 - 1.0s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.866353 - 1.1s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.777310 - 1.2s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.722395 - 1.2s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.566809 - 1.2s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.889632 - 1.1s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.893442 - 1.2s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.876191 - 1.2s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.796785 - 1.2s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.808421 - 1.2s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.884047 - 0.9s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.907978 - 1.3s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.697995 - 1.3s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.884047 - 1.1s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.681687 - 1.3s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.702102 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.892074 - 1.1s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.881520 - 1.2s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.874448 - 1.1s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.911799 - 1.1s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.935724 - 1.3s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.878257 - 1.2s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.799307 - 1.2s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.934983 - 1.1s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.823276 - 1.1s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.854811 - 1.0s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.842052 - 1.2s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.791206 - 1.2s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.836305 - 1.1s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.652057 - 1.2s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.934983 - 1.0s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.722395 - 1.3s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.620509 - 1.3s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.934983 - 1.1s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.661453 - 1.3s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.864680 - 1.1s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.797327 - 1.3s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.803280 - 1.2s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.864680 - 1.2s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.676857 - 1.2s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.924118 - 1.1s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.938750 - 1.3s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.925944 - 1.2s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.901233 - 1.2s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.839358 - 1.2s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.722395 - 1.1s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.954937 - 1.3s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.806520 - 1.3s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.854811 - 1.1s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.742882 - 1.3s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.934983 - 1.2s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.859890 - 1.2s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.612120 - 1.2s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.884047 - 1.0s
[CV] c1=2.282844107076996, c2=0.02119864096637369 ....................
[CV] c1=2.282844107076996, c2=0.02119864096637369, score=0.777084 - 1.2s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.922360 - 1.1s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.707667 - 1.2s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.722857 - 1.1s
[CV] c1=0.06582026288344721, c2=0.05682820602315697 ..................
[CV] c1=0.06582026288344721, c2=0.05682820602315697, score=0.935724 - 1.2s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.759131 - 1.3s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.842052 - 1.0s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.797327 - 1.3s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.844358 - 1.2s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.843508 - 1.2s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.839973 - 1.1s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.884047 - 1.1s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.902661 - 1.3s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.876191 - 1.2s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.722395 - 1.2s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.854874 - 1.2s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.796785 - 1.1s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.869105 - 1.3s
[CV] c1=1.1460943161482862, c2=0.026153895974214678 ..................
[CV] c1=1.1460943161482862, c2=0.026153895974214678, score=0.867125 - 1.4s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.901578 - 1.2s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.626801 - 1.3s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.806478 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.934983 - 1.1s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.814901 - 1.1s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.859890 - 1.2s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.787478 - 1.2s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.864680 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.845755 - 1.3s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.911204 - 1.1s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.697995 - 1.2s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.884047 - 1.1s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.737329 - 1.3s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.916469 - 1.3s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.722395 - 1.2s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.954937 - 1.0s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.907124 - 1.0s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.839355 - 1.2s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.925933 - 1.3s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.717653 - 1.3s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.777416 - 1.1s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.891392 - 1.2s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.706867 - 1.1s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.824358 - 1.2s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.713003 - 1.3s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.620509 - 1.2s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.864680 - 1.1s
[CV] c1=0.0977605809688258, c2=0.02758489827313711 ...................
[CV] c1=0.0977605809688258, c2=0.02758489827313711, score=0.842052 - 1.1s
[CV] c1=0.14456252410554848, c2=0.011570925278244349 .................
[CV] c1=0.14456252410554848, c2=0.011570925278244349, score=0.927980 - 1.3s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.752310 - 1.3s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.946778 - 1.2s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.804379 - 1.2s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.717653 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.843508 - 1.3s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.884047 - 1.1s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.796008 - 1.2s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.777416 - 0.9s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.954937 - 1.2s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.788527 - 1.1s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.817065 - 1.1s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.876191 - 1.1s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.722395 - 1.1s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.799307 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.859890 - 1.2s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.878774 - 1.2s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.796238 - 1.2s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.954937 - 1.1s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.612120 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.722395 - 1.2s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.626801 - 1.2s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.777310 - 1.3s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.889632 - 1.0s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.866353 - 1.2s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.701275 - 1.2s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.801130 - 1.2s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.915357 - 1.2s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.931814 - 1.0s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.722395 - 1.1s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.945584 - 1.2s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.694375 - 1.3s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.796785 - 1.3s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.913214 - 1.2s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.884038 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.874448 - 1.1s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.783151 - 1.3s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.806478 - 1.1s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.796785 - 1.2s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.900231 - 1.3s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.803280 - 1.1s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.934983 - 1.1s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.884047 - 1.1s
[CV] c1=0.09869732897335494, c2=0.023452935233575632 .................
[CV] c1=0.09869732897335494, c2=0.023452935233575632, score=0.842052 - 1.1s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.805308 - 1.3s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.858736 - 1.1s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.796785 - 1.2s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.844494 - 1.2s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.866806 - 1.0s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.909061 - 1.3s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.620509 - 1.2s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.864680 - 1.2s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.925790 - 1.2s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.803280 - 0.9s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.722395 - 1.3s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.881724 - 1.1s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.841204 - 1.2s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.850992 - 1.2s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.777310 - 1.0s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.893442 - 1.1s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.783151 - 1.2s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.900894 - 1.2s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.889632 - 1.1s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.612120 - 1.1s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.876191 - 1.2s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.796785 - 1.3s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.863374 - 1.2s
[CV] c1=1.1335935695692325, c2=0.045601607829839186 ..................
[CV] c1=1.1335935695692325, c2=0.045601607829839186, score=0.855013 - 1.3s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.697995 - 1.1s
[CV] c1=0.05355864292308304, c2=0.0537875036655877 ...................
[CV] c1=0.05355864292308304, c2=0.0537875036655877, score=0.796785 - 1.2s
[CV] c1=0.25945079081541905, c2=0.010397595986328969 .................
[CV] c1=0.25945079081541905, c2=0.010397595986328969, score=0.927980 - 1.2s
[CV] c1=1.3026087883632722, c2=0.0508985293942068 ....................
[CV] c1=1.3026087883632722, c2=0.0508985293942068, score=0.816360 - 1.2s
[CV] c1=0.12284069651421997, c2=0.07728931563717421 ..................
[CV] c1=0.12284069651421997, c2=0.07728931563717421, score=0.903868 - 1.3s
[CV] c1=0.6718735077115858, c2=0.005745367898834753 ..................
[CV] c1=0.6718735077115858, c2=0.005745367898834753, score=0.943246 - 1.1s
[CV] c1=0.16188575490577647, c2=0.010872239640626618 .................
[CV] c1=0.16188575490577647, c2=0.010872239640626618, score=0.927980 - 1.2s
[CV] c1=1.0207079957485827, c2=0.004519504876816081 ..................
[CV] c1=1.0207079957485827, c2=0.004519504876816081, score=0.801130 - 1.2s
[CV] c1=0.008182384829545907, c2=0.06802178300715349 .................
[CV] c1=0.008182384829545907, c2=0.06802178300715349, score=0.854811 - 1.1s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.796785 - 1.2s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.867125 - 1.0s
[CV] c1=1.3592042869129366, c2=0.07476636430730615 ...................
[CV] c1=1.3592042869129366, c2=0.07476636430730615, score=0.844358 - 1.3s
[CV] c1=0.09124769571379378, c2=0.04714194115622477 ..................
[CV] c1=0.09124769571379378, c2=0.04714194115622477, score=0.935724 - 1.2s
[CV] c1=0.8596830833517516, c2=0.025827069173659647 ..................
[CV] c1=0.8596830833517516, c2=0.025827069173659647, score=0.934870 - 1.2s
[CV] c1=0.026900741799377164, c2=0.022970822090078655 ................
[CV] c1=0.026900741799377164, c2=0.022970822090078655, score=0.722395 - 1.2s
[CV] c1=1.28661684935985, c2=0.0006449825527911529 ...................
[CV] c1=1.28661684935985, c2=0.0006449825527911529, score=0.806520 - 1.1s
Training done in: 7.767506s
Saving training model...
Saving training model done in: 0.012868s
*********************************
Prediction done in: 0.030345s
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: True False
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003627s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 lemma[:1] 2
9 -2:lemma Cra
10 -2:postag NNP
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 hUpper True
7 hLower True
8 hGreek False
9 symb True
10 lemma[:1] d
11 lemma[:2] de
12 -2:lemma affyexp
13 -2:postag JJ
14 +2:lemma glucose
15 +2:postag NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.890024 - 1.2s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.880403 - 1.3s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.690341 - 1.5s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.890024 - 1.4s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.869691 - 1.4s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.744355 - 1.2s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.786360 - 1.4s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.846486 - 1.5s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.826344 - 1.4s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.843948 - 1.5s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
[CV] c1=0.9074915652851482, c2=0.02543187379319682, score=0.804014 - 1.0s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.804464 - 1.5s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.874372 - 1.4s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.852277 - 1.4s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.815278 - 1.5s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.819477 - 1.2s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.898446 - 1.3s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.813790 - 1.5s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.804464 - 1.5s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.867416 - 1.4s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.635785 - 1.2s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.603359 - 1.5s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.908587 - 1.4s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.635785 - 1.6s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.926731 - 1.4s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.934128 - 1.1s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.879259 - 1.5s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.893806 - 1.4s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.899473 - 1.6s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.856700 - 1.3s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.826344 - 1.1s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.723972 - 1.5s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.858021 - 1.4s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.752973 - 1.6s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.679842 - 1.6s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
[CV] c1=0.9074915652851482, c2=0.02543187379319682, score=0.890024 - 1.4s
[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
[CV] c1=0.216886783747496, c2=0.06401679314680564, score=0.694229 - 1.5s
[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
[CV] c1=0.004133060166992575, c2=0.011901439513382527, score=0.910493 - 1.3s
[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
[CV] c1=0.0563192166145737, c2=0.09059169860484621, score=0.855584 - 1.5s
[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
[CV] c1=0.5293995858269901, c2=0.03117434046987838, score=0.694229 - 1.4s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.804464 - 1.3s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.767841 - 1.5s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.921722 - 1.5s
[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
[CV] c1=0.0563192166145737, c2=0.09059169860484621, score=0.685251 - 1.5s
[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
[CV] c1=0.5293995858269901, c2=0.03117434046987838, score=0.899776 - 1.4s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.932900 - 1.3s
[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
[CV] c1=0.216886783747496, c2=0.06401679314680564, score=0.832818 - 1.5s
[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
[CV] c1=0.004133060166992575, c2=0.011901439513382527, score=0.841420 - 1.3s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.819477 - 1.4s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.858878 - 1.6s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.854189 - 1.4s
[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
[CV] c1=0.216886783747496, c2=0.06401679314680564, score=0.862461 - 1.4s
[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
[CV] c1=0.004133060166992575, c2=0.011901439513382527, score=0.876867 - 1.4s
[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
[CV] c1=0.0563192166145737, c2=0.09059169860484621, score=0.867297 - 1.4s
[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
[CV] c1=0.5293995858269901, c2=0.03117434046987838, score=0.804464 - 1.5s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.868123 - 1.3s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.920290 - 1.5s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.848986 - 1.5s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.810774 - 1.6s
[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
[CV] c1=0.5293995858269901, c2=0.03117434046987838, score=0.872936 - 1.3s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
[CV] c1=0.9074915652851482, c2=0.02543187379319682, score=0.619521 - 1.5s
[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
[CV] c1=0.216886783747496, c2=0.06401679314680564, score=0.897095 - 1.2s
[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
[CV] c1=0.004133060166992575, c2=0.011901439513382527, score=0.769842 - 1.5s
[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
[CV] c1=0.0563192166145737, c2=0.09059169860484621, score=0.926731 - 1.3s
[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
[CV] c1=0.5293995858269901, c2=0.03117434046987838, score=0.802648 - 1.4s
[CV] c1=0.7397744394629708, c2=0.06206881872725856 ...................
[CV] c1=0.7397744394629708, c2=0.06206881872725856, score=0.810774 - 1.2s
[CV] c1=1.2941973038793777, c2=0.037888887789770925 ..................
[CV] c1=1.2941973038793777, c2=0.037888887789770925, score=0.793199 - 1.4s
[CV] c1=0.19824146496587178, c2=0.013797540793034142 .................
[CV] c1=0.19824146496587178, c2=0.013797540793034142, score=0.956017 - 1.6s
[CV] c1=0.7032936215118566, c2=0.10066980363880543 ...................
[CV] c1=0.7032936215118566, c2=0.10066980363880543, score=0.937766 - 1.5s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.941948 - 1.4s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.909675 - 1.4s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.839218 - 1.5s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.739063 - 1.3s
[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
[CV] c1=0.0563192166145737, c2=0.09059169860484621, score=0.871884 - 1.4s
[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
[CV] c1=0.5293995858269901, c2=0.03117434046987838, score=0.946646 - 1.4s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
[CV] c1=0.9074915652851482, c2=0.02543187379319682, score=0.868596 - 1.5s
[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
[CV] c1=0.216886783747496, c2=0.06401679314680564, score=0.950725 - 1.5s
[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
[CV] c1=0.004133060166992575, c2=0.011901439513382527, score=0.854858 - 1.5s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.835814 - 1.6s
[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.881118 - 1.1s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
[CV] c1=0.9074915652851482, c2=0.02543187379319682, score=0.804464 - 1.4s
[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
[CV] c1=0.216886783747496, c2=0.06401679314680564, score=0.877252 - 1.3s
[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
[CV] c1=0.004133060166992575, c2=0.011901439513382527, score=0.833135 - 1.5s
[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
[CV] c1=0.0563192166145737, c2=0.09059169860484621, score=0.877252 - 1.4s
[CV] c1=0.07958217736939746, c2=0.14062673161534342 ..................
[CV] c1=0.07958217736939746, c2=0.14062673161534342, score=0.843508 - 1.4s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
[CV] c1=0.9074915652851482, c2=0.02543187379319682, score=0.927009 - 1.5s
[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
[CV] c1=0.216886783747496, c2=0.06401679314680564, score=0.925560 - 1.4s
[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
[CV] c1=0.004133060166992575, c2=0.011901439513382527, score=0.886827 - 1.4s
[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
[CV] c1=0.0563192166145737, c2=0.09059169860484621, score=0.873517 - 1.5s
[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
[CV] c1=0.5293995858269901, c2=0.03117434046987838, score=0.909115 - 1.3s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
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[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
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[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
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[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
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[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
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[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
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[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
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[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
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[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
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[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
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[CV] c1=0.216886783747496, c2=0.06401679314680564 ....................
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[CV] c1=0.004133060166992575, c2=0.011901439513382527 ................
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[CV] c1=0.0563192166145737, c2=0.09059169860484621 ...................
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[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
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[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
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[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
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[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
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[CV] c1=0.5293995858269901, c2=0.03117434046987838 ...................
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[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
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[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
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[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.867416 - 1.3s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.862461 - 1.4s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.694229 - 1.7s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.749548 - 1.4s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.931609 - 1.6s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.866956 - 1.0s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.850736 - 1.3s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.928660 - 1.6s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.804464 - 1.5s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.873246 - 1.4s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.919144 - 1.1s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.694229 - 1.5s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.867416 - 1.5s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.882373 - 1.4s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.679842 - 1.6s
[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.843508 - 1.2s
[CV] c1=0.9074915652851482, c2=0.02543187379319682 ...................
[CV] c1=0.9074915652851482, c2=0.02543187379319682, score=0.926892 - 1.5s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.884477 - 1.5s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.573561 - 1.5s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.926731 - 1.4s
[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.820238 - 1.4s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.839383 - 1.4s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.893806 - 1.4s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.847032 - 1.4s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.867416 - 1.3s
[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.679842 - 1.4s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.876690 - 1.4s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.858068 - 1.5s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.899473 - 1.5s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.889289 - 1.3s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.862528 - 1.1s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.925107 - 1.3s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.727632 - 1.5s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.752973 - 1.5s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.918674 - 1.3s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.810648 - 1.3s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.865193 - 1.5s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.823313 - 1.5s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.789187 - 1.5s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.894971 - 1.4s
[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.894971 - 1.3s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.925560 - 1.5s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.934128 - 1.4s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.810774 - 1.5s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.824101 - 1.5s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.912532 - 1.0s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.729474 - 1.4s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.826344 - 1.3s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.860604 - 1.5s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.856700 - 1.3s
[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.926731 - 1.5s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.925560 - 1.5s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.635785 - 1.5s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.868123 - 1.4s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.718921 - 1.5s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.804464 - 1.3s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.813790 - 1.5s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.899473 - 1.5s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.838488 - 1.4s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.917297 - 1.6s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.917115 - 1.0s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.849701 - 1.4s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.804464 - 1.4s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.635785 - 1.5s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.804464 - 1.6s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.950725 - 1.1s
[CV] c1=0.17182804981226535, c2=0.002428872515053027 .................
[CV] c1=0.17182804981226535, c2=0.002428872515053027, score=0.852560 - 1.5s
[CV] c1=0.792515464743646, c2=0.08571303528654414 ....................
[CV] c1=0.792515464743646, c2=0.08571303528654414, score=0.890024 - 1.4s
[CV] c1=0.6990936193316816, c2=0.08367320545887141 ...................
[CV] c1=0.6990936193316816, c2=0.08367320545887141, score=0.826344 - 1.3s
[CV] c1=0.10386122891558734, c2=0.11287630527447601 ..................
[CV] c1=0.10386122891558734, c2=0.11287630527447601, score=0.843508 - 1.4s
[CV] c1=0.10847613698559176, c2=0.14660104510709368 ..................
[CV] c1=0.10847613698559176, c2=0.14660104510709368, score=0.848700 - 1.5s
[CV] c1=0.1784170122015291, c2=0.026491135561658566 ..................
[CV] c1=0.1784170122015291, c2=0.026491135561658566, score=0.950725 - 1.5s
[CV] c1=0.18847706548586152, c2=0.04745708358881413 ..................
[CV] c1=0.18847706548586152, c2=0.04745708358881413, score=0.925560 - 1.5s
[CV] c1=1.5252837713021872, c2=0.40678698586680273 ...................
[CV] c1=1.5252837713021872, c2=0.40678698586680273, score=0.873786 - 1.5s
[CV] c1=0.4861162646712438, c2=0.023054491303730287 ..................
[CV] c1=0.4861162646712438, c2=0.023054491303730287, score=0.802648 - 1.5s
[CV] c1=0.41184922423682174, c2=0.021708165205365473 .................
[CV] c1=0.41184922423682174, c2=0.021708165205365473, score=0.694229 - 1.3s
Training done in: 9.576261s
Saving training model...
Saving training model done in: 0.014119s
*********************************
Prediction done in: 0.040201s
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: False True
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003575s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 word 2
5 isUpper False
6 isLower False
7 isGreek False
8 isNumber True
9 -1:word fructose
10 -2:lemma Cra
11 -2:postag NNP
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 word delta-arcA
7 isUpper False
8 isLower False
9 isGreek False
10 isNumber False
11 -1:word _
12 +1:word _
13 -2:lemma affyexp
14 -2:postag JJ
15 +2:lemma glucose
16 +2:postag NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.778117 - 1.3s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.853767 - 1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.931253 - 1.4s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.593248 - 1.6s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.927267 - 1.4s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.798145 - 0.9s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.885817 - 1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.856059 - 1.4s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.766544 - 1.6s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.897630 - 1.4s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.885973 - 1.0s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.866353 - 1.4s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.938157 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.907533 - 1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.794758 - 1.6s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.853967 - 1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.931991 - 1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.695368 - 1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.793626 - 1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.798753 - 1.5s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.812996 - 1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.836597 - 1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.853767 - 1.5s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.880703 - 1.4s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.707282 - 1.6s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.601824 - 1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.717781 - 1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.814418 - 1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.813706 - 1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.848812 - 1.5s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.818821 - 1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.892921 - 1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.913784 - 1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.800038 - 1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.913784 - 1.5s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.903311 - 1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.765908 - 1.6s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.845227 - 1.4s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.738812 - 1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.868921 - 1.4s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.889602 - 1.1s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.913784 - 1.8s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.818750 - 1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.867753 - 1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.631304 - 1.2s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.764357 - 1.3s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.827578 - 1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.811515 - 1.5s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.866963 - 1.6s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.783556 - 1.5s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.852879 - 1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.913784 - 1.6s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.912193 - 1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.866353 - 1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.900039 - 1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.866353 - 1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.853559 - 1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.900039 - 1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.869996 - 1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.859362 - 1.3s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.863001 - 1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.849838 - 1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.925823 - 1.4s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.913214 - 1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.906331 - 1.4s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.818254 - 1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.686298 - 1.5s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.680687 - 1.6s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.931991 - 1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.867607 - 1.4s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV] c1=1.1125641437191895, c2=0.06613233343219797, score=0.902496 - 1.5s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.790902 - 1.6s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.857043 - 1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.809731 - 1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.840372 - 1.3s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.727697 - 1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.917874 - 1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.797760 - 1.6s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.727697 - 1.5s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.819378 - 1.5s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.833325 - 1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.888803 - 1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.851826 - 1.4s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.969518 - 1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.917037 - 1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.832339 - 1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.847604 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.798145 - 1.3s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.884921 - 1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.722395 - 1.2s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.931814 - 1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.939034 - 1.6s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.842339 - 1.4s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.842929 - 1.5s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.804932 - 1.4s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.951585 - 1.5s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.780124 - 1.5s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV] c1=0.6198895769639643, c2=0.0028009206253587736, score=0.803867 - 1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.923193 - 1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.866911 - 1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.848812 - 1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.913784 - 1.6s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.849422 - 1.4s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.853767 - 1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.931991 - 1.3s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.931991 - 1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV] c1=0.24222541975427525, c2=0.02858668949001732, score=0.927980 - 1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.928742 - 1.6s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV] c1=0.03780171336875179, c2=0.012718090480016972, score=0.889602 - 1.4s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV] c1=0.31697105278313065, c2=0.1627674927353806, score=0.942868 - 1.5s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.928742 - 1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.808180 - 1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.804932 - 1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.808180 - 1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.931814 - 1.1s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV] c1=0.1250735526885256, c2=0.03442702231914988, score=0.847604 - 1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV] c1=0.41912632470724565, c2=0.1640401199474577, score=0.855349 - 1.4s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.892921 - 1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.902216 - 1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV] c1=0.6177967356330287, c2=0.0501823034129141, score=0.795123 - 1.6s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.808180 - 1.6s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.939034 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.795123 - 1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.707282 - 1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.885973 - 1.1s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.778117 - 1.6s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.826198 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.896776 - 1.4s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.884219 - 1.3s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.858948 - 1.1s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.864761 - 1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.848812 - 1.4s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.917433 - 1.4s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.866714 - 1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.854195 - 1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.601824 - 1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.707282 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.812996 - 1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.927267 - 1.3s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.798145 - 1.2s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.696344 - 1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.804491 - 1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.686298 - 1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.931991 - 1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.826012 - 1.4s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.913784 - 1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.884106 - 1.4s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.900039 - 1.6s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.928742 - 1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.838813 - 1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.885714 - 1.6s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.931991 - 1.3s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.790054 - 1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.696344 - 1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.869958 - 1.4s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.818750 - 1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.906003 - 1.4s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.612088 - 1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.830299 - 1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.848792 - 1.1s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.922396 - 1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.712608 - 1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.827116 - 1.6s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.913784 - 1.6s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.778117 - 1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV] c1=0.4089586111008682, c2=0.07211995679529591, score=0.827116 - 1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV] c1=0.3431081113231949, c2=0.10070913156646599, score=0.785941 - 1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.859362 - 1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV] c1=0.35050990293106027, c2=0.062158504077829205, score=0.814418 - 1.6s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV] c1=0.11098709687950105, c2=0.0012964773754647193, score=0.939803 - 1.4s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.907533 - 1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV] c1=0.3531857394293691, c2=0.028403481397008597, score=0.839546 - 1.5s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV] c1=1.7692696573575095, c2=0.014769125134101722, score=0.719375 - 1.3s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.849255 - 1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.806478 - 1.2s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.896776 - 1.4s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.884219 - 1.4s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV] c1=0.5525328047238595, c2=0.09184172427704333, score=0.910483 - 1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.841204 - 1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.601824 - 1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.806478 - 1.4s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.863344 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.854202 - 1.4s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.856387 - 1.3s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.812996 - 1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.908387 - 1.6s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.869996 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.908387 - 1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.854811 - 1.4s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.902496 - 1.2s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV] c1=0.9489299883913463, c2=0.08651523595457483, score=0.792413 - 1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV] c1=0.004944498956920931, c2=0.035071672138884735, score=0.859339 - 1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV] c1=1.064584223532424, c2=0.010140146677527086, score=0.818821 - 1.4s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV] c1=0.004633722592074594, c2=0.10886882710897013, score=0.952892 - 1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV] c1=1.138816237017488, c2=0.03695236961293207, score=0.792413 - 1.2s
Training done in: 9.689625s
Saving training model...
Saving training model done in: 0.014153s
*********************************
Prediction done in: 0.041572s
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: True True
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003530s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 lemma[:1] 2
9 word 2
10 isUpper False
11 isLower False
12 isGreek False
13 isNumber True
14 -1:word fructose
15 -2:lemma Cra
16 -2:postag NNP
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 hUpper True
7 hLower True
8 hGreek False
9 symb True
10 lemma[:1] d
11 lemma[:2] de
12 word delta-arcA
13 isUpper False
14 isLower False
15 isGreek False
16 isNumber False
17 -1:word _
18 +1:word _
19 -2:lemma affyexp
20 -2:postag JJ
21 +2:lemma glucose
22 +2:postag NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.855584 - 1.4s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.839443 - 1.6s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
[CV] c1=1.320423767018736, c2=0.0006342386585221799, score=0.744355 - 1.9s
[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.837423 - 1.7s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.786374 - 1.9s
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.894214 - 1.4s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.927296 - 1.6s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
[CV] c1=1.320423767018736, c2=0.0006342386585221799, score=0.769561 - 1.6s
[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.820276 - 1.8s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.852241 - 1.8s
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.701018 - 1.5s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.823313 - 1.8s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
[CV] c1=1.320423767018736, c2=0.0006342386585221799, score=0.810806 - 1.7s
[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.862528 - 1.8s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.917821 - 1.7s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.927296 - 1.4s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
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[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
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[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
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[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.877672 - 1.7s
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.947560 - 1.5s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.827435 - 1.7s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
[CV] c1=1.320423767018736, c2=0.0006342386585221799, score=0.934961 - 1.8s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.871999 - 1.7s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.877726 - 1.6s
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.832180 - 1.6s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.905285 - 1.6s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
[CV] c1=1.320423767018736, c2=0.0006342386585221799, score=0.908266 - 1.7s
[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.712673 - 1.9s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.818750 - 1.8s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.844088 - 1.3s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.876526 - 1.8s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
[CV] c1=1.320423767018736, c2=0.0006342386585221799, score=0.786169 - 1.6s
[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.917821 - 1.6s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.677786 - 1.9s
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.854858 - 1.5s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.827337 - 1.7s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.854189 - 1.8s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.797575 - 1.8s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.936486 - 1.7s
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.882807 - 1.2s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
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[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
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[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.813790 - 2.0s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.932900 - 1.9s
[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.867297 - 1.5s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.945654 - 2.0s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
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[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.927509 - 1.9s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
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[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
[CV] c1=0.014622839747769914, c2=0.061827531030816944, score=0.945871 - 1.4s
[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.940537 - 1.7s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
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[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
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[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
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[CV] c1=0.014622839747769914, c2=0.061827531030816944 ................
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[CV] c1=0.2546256913180655, c2=0.08567888835212083 ...................
[CV] c1=0.2546256913180655, c2=0.08567888835212083, score=0.701018 - 1.8s
[CV] c1=1.320423767018736, c2=0.0006342386585221799 ..................
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[CV] c1=0.3895794958853977, c2=0.008826457669620126 ..................
[CV] c1=0.3895794958853977, c2=0.008826457669620126, score=0.950725 - 2.0s
[CV] c1=0.6190712080838937, c2=0.07176205729861096 ...................
[CV] c1=0.6190712080838937, c2=0.07176205729861096, score=0.824101 - 1.9s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.844088 - 1.6s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.874253 - 1.6s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.927296 - 1.6s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.686282 - 1.8s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.818750 - 1.8s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.849406 - 1.8s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.701018 - 1.8s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.812996 - 1.7s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.841763 - 1.5s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.772963 - 1.6s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.950946 - 1.7s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.927296 - 1.6s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.729474 - 1.8s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.917821 - 1.6s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.744355 - 1.8s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.898170 - 1.7s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.947560 - 1.7s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.898170 - 1.7s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.946646 - 1.8s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.932900 - 1.7s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.876526 - 1.7s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.927296 - 1.6s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.777170 - 1.7s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.816898 - 1.8s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.931245 - 1.6s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.950876 - 1.6s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.879222 - 1.6s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.964555 - 1.8s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.892910 - 1.7s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.908266 - 1.7s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.849406 - 1.5s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.714964 - 1.9s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.813790 - 1.8s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.868123 - 1.8s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.794077 - 1.7s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.839383 - 1.8s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
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[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.925645 - 1.8s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.850628 - 1.8s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.839785 - 1.6s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.701018 - 1.7s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.824097 - 1.7s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.888272 - 1.7s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.818750 - 1.8s
[CV] c1=1.1730395683067192, c2=0.04136085455259575 ...................
[CV] c1=1.1730395683067192, c2=0.04136085455259575, score=0.832561 - 1.7s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.898170 - 1.7s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.912922 - 1.7s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.774381 - 1.6s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.889771 - 1.6s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.872077 - 1.5s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.876526 - 1.7s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.854858 - 1.8s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.745317 - 1.8s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.687982 - 1.8s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.694284 - 1.6s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.898170 - 1.7s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.867297 - 1.7s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.859655 - 1.6s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.818750 - 1.8s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.917821 - 1.5s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.927296 - 1.6s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.865754 - 1.8s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.601194 - 1.8s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.917821 - 1.7s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.818750 - 1.5s
[CV] c1=0.16796773996321945, c2=0.051466183184993 ....................
[CV] c1=0.16796773996321945, c2=0.051466183184993, score=0.823313 - 1.9s
[CV] c1=0.00632707477587882, c2=0.032688081217957285 .................
[CV] c1=0.00632707477587882, c2=0.032688081217957285, score=0.939823 - 1.7s
[CV] c1=0.12475431096451621, c2=0.013861677898849787 .................
[CV] c1=0.12475431096451621, c2=0.013861677898849787, score=0.864462 - 1.8s
[CV] c1=0.6186211042682789, c2=0.021841056417535254 ..................
[CV] c1=0.6186211042682789, c2=0.021841056417535254, score=0.923585 - 1.8s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.803283 - 1.7s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.842165 - 1.6s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.947560 - 1.8s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.767841 - 1.7s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.824101 - 1.6s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.950725 - 1.5s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.926731 - 1.7s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.839785 - 1.8s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.744355 - 1.7s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.923585 - 1.7s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.827435 - 1.4s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.701018 - 1.8s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.832180 - 1.8s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.810806 - 1.7s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.869758 - 1.8s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.905285 - 1.5s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.940537 - 1.8s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.945871 - 1.8s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.930867 - 1.8s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.848003 - 1.7s
[CV] c1=0.35540949764912066, c2=0.05344196426839372 ..................
[CV] c1=0.35540949764912066, c2=0.05344196426839372, score=0.931225 - 1.5s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.813790 - 1.8s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.950725 - 1.8s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.932900 - 1.8s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.920469 - 1.6s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.818750 - 1.3s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.950946 - 1.8s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.854858 - 1.7s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.812988 - 1.6s
[CV] c1=0.5174874167807753, c2=0.020703126745445985 ..................
[CV] c1=0.5174874167807753, c2=0.020703126745445985, score=0.946646 - 1.9s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.850628 - 1.5s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.929483 - 1.8s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.927302 - 1.7s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.825027 - 1.7s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.950725 - 1.7s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.912264 - 1.2s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.883482 - 1.8s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.872077 - 1.8s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.862659 - 1.7s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.917821 - 1.6s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.841763 - 1.5s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.839383 - 1.7s
[CV] c1=0.022485418318991247, c2=0.07226838517970073 .................
[CV] c1=0.022485418318991247, c2=0.07226838517970073, score=0.886214 - 1.7s
[CV] c1=1.4962368934644148, c2=0.005609305438174272 ..................
[CV] c1=1.4962368934644148, c2=0.005609305438174272, score=0.907688 - 1.9s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.902802 - 1.8s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.677786 - 1.5s
[CV] c1=0.190929240598343, c2=0.04355186228965651 ....................
[CV] c1=0.190929240598343, c2=0.04355186228965651, score=0.813790 - 1.9s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.865505 - 1.8s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.609476 - 1.8s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.813790 - 1.8s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.946646 - 1.4s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.847957 - 1.8s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.824101 - 1.7s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.931245 - 1.7s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.927509 - 1.7s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.824101 - 1.3s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.844455 - 1.9s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.818750 - 1.8s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.818750 - 1.8s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.862528 - 1.7s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.882795 - 1.4s
[CV] c1=0.1736092848065649, c2=0.02070619498632359 ...................
[CV] c1=0.1736092848065649, c2=0.02070619498632359, score=0.711517 - 1.8s
[CV] c1=0.3890080123705456, c2=0.06863542905418545 ...................
[CV] c1=0.3890080123705456, c2=0.06863542905418545, score=0.694284 - 1.9s
[CV] c1=0.9907276867534006, c2=0.015068999673777204 ..................
[CV] c1=0.9907276867534006, c2=0.015068999673777204, score=0.908266 - 1.6s
[CV] c1=0.37993592904226775, c2=0.001287546330642171 .................
[CV] c1=0.37993592904226775, c2=0.001287546330642171, score=0.696477 - 1.8s
[CV] c1=0.5132989845379167, c2=0.04018212909012408 ...................
[CV] c1=0.5132989845379167, c2=0.04018212909012408, score=0.917821 - 1.5s
Training done in: 11.427793s
Saving training model...
Saving training model done in: 0.013545s
*********************************
Prediction done in: 0.047166s
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.17555398242003323, 'c2': 0.0008367558417380293}
best CV score:0.8636034196474707
model size: 0.06M
Flat F1: 0.7624930609829998
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 0.955 0.913 0.933 23
Med 1.000 0.925 0.961 53
Temp 1.000 0.690 0.816 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.543 0.362 0.435 69
Anti 0.786 1.000 0.880 11
Strain 0.000 0.000 0.000 1
Gtype 0.873 0.812 0.841 85
Substrain 0.000 0.000 0.000 0
Supp 0.627 0.791 0.700 134
Gversion 0.000 0.000 0.000 0
avg / total 0.782 0.761 0.762 451
Top likely transitions:
Temp -> Temp 6.236783
Agit -> Agit 5.977368
Supp -> Supp 5.723953
Med -> Med 5.445232
Anti -> Anti 5.324268
OD -> OD 5.311513
Phase -> Phase 4.992339
O -> O 4.981091
Gtype -> Gtype 4.717730
Gversion -> Gversion 4.330989
Air -> Air 4.201627
Technique -> Technique 3.925712
pH -> pH 2.615370
O -> Supp 1.837983
Substrain -> Gtype 1.799206
O -> Technique 1.591877
Gtype -> Supp 1.476534
O -> Gtype 1.337075
Air -> O 1.306525
O -> Temp 0.991053
Supp -> O 0.824285
Temp -> O 0.739357
O -> Phase 0.680154
Gtype -> pH 0.472477
Med -> O 0.436738
Gtype -> Air 0.397033
O -> Anti 0.333293
O -> Gversion 0.293983
Phase -> O 0.274110
O -> Med 0.270711
O -> pH 0.265830
Technique -> Air 0.239225
O -> OD 0.208609
OD -> O 0.168573
Anti -> O 0.047017
Strain -> O 0.043724
Technique -> Gtype -0.000116
Gtype -> Anti -0.013188
Technique -> O -0.023355
Supp -> Med -0.155280
Gtype -> Med -0.630390
Gtype -> O -0.667165
O -> Air -0.778473
Phase -> OD -1.117260
Med -> Supp -1.179521
Substrain -> O -1.530930
Top unlikely transitions:
Temp -> Temp 6.236783
Agit -> Agit 5.977368
Supp -> Supp 5.723953
Med -> Med 5.445232
Anti -> Anti 5.324268
OD -> OD 5.311513
Phase -> Phase 4.992339
O -> O 4.981091
Gtype -> Gtype 4.717730
Gversion -> Gversion 4.330989
Air -> Air 4.201627
Technique -> Technique 3.925712
pH -> pH 2.615370
O -> Supp 1.837983
Substrain -> Gtype 1.799206
O -> Technique 1.591877
Gtype -> Supp 1.476534
O -> Gtype 1.337075
Air -> O 1.306525
O -> Temp 0.991053
Supp -> O 0.824285
Temp -> O 0.739357
O -> Phase 0.680154
Gtype -> pH 0.472477
Med -> O 0.436738
Gtype -> Air 0.397033
O -> Anti 0.333293
O -> Gversion 0.293983
Phase -> O 0.274110
O -> Med 0.270711
O -> pH 0.265830
Technique -> Air 0.239225
O -> OD 0.208609
OD -> O 0.168573
Anti -> O 0.047017
Strain -> O 0.043724
Technique -> Gtype -0.000116
Gtype -> Anti -0.013188
Technique -> O -0.023355
Supp -> Med -0.155280
Gtype -> Med -0.630390
Gtype -> O -0.667165
O -> Air -0.778473
Phase -> OD -1.117260
Med -> Supp -1.179521
Substrain -> O -1.530930
Top positive:
10.045367 Supp b'lemma:Iron'
9.100880 O b'lemma:_'
8.242002 Strain b'+1:lemma:substr'
8.132268 O b'lemma:Custom'
7.734397 Air b'lemma:anaerobic'
7.632513 Med b'lemma:MOPS'
7.625936 Technique b'lemma:ChIP-exo'
7.390329 O b'lemma:-'
7.321441 Phase b'lemma:exponential'
7.321441 Phase b'lemma:stationary'
7.253404 O b'lemma:2'
7.222756 Supp b'lemma:pq'
7.207380 Air b'-1:lemma:ChIP-Seq'
7.155349 Air b'lemma:aerobic'
6.813539 Gtype b'lemma:wt'
6.702581 Technique b'lemma:chipseq'
6.645365 O b'lemma:rpob'
6.639496 Phase b'lemma:mid-log'
6.639111 Gtype b'lemma:type'
6.622009 Air b'lemma:Aerobic'
6.527859 O b'lemma:3'
6.516390 Gtype b'lemma:\xce\xb4cra'
6.499705 O b'lemma:1'
6.263452 O b'-1:lemma:tag'
6.173201 O b'lemma:b'
6.155179 O b'-1:lemma:ChIP-exo'
6.024948 Gversion b'lemma:asm584v2'
6.012376 Gtype b'lemma:wild-type'
5.936435 Supp b'+1:lemma:\xc2\xb5m'
5.737282 O b'lemma:Cra'
5.711321 O b'lemma:a'
5.696390 Gversion b'lemma:nc'
5.639739 Gtype b'lemma:flag-tag'
5.639739 Gtype b'-1:lemma:c-terminal'
5.628162 O b'lemma:rep1'
5.614254 O b'lemma:rep3'
5.494137 Gtype b'+1:lemma:type'
5.430135 Supp b'lemma:nacl'
5.262704 Technique b'lemma:ChIP-Seq'
4.943606 Supp b'-1:lemma:Cra'
4.865297 O b'lemma:\xcf\x8332'
4.856195 Gtype b'lemma:\xce\xb4fur'
4.812215 Gtype b'lemma:arca8myc'
4.661623 Supp b'lemma:rifampicin'
4.591681 Technique b'lemma:rna-seq'
4.567002 O b'+1:lemma:pq'
4.496950 O b'-1:lemma:type'
4.491357 OD b'lemma:od450'
4.482197 O b'postag:IN'
4.479634 Supp b'lemma:acetate'
4.472507 Med b'-1:lemma:ml'
4.471210 Gtype b'lemma:dfnr'
4.467873 Supp b'lemma:nitrate'
4.378040 Technique b'lemma:rnaseq'
4.342911 O b'lemma:ompr'
4.332518 Supp b'-1:lemma:+'
4.328989 Supp b'lemma:glucose'
4.308726 O b'lemma:chip'
4.302072 Gtype b'lemma:fnr8myc'
4.273847 Gtype b'lemma:\xce\xb4soxr'
4.190264 Gtype b'lemma:pk4854'
4.098705 Anti b'lemma:none'
4.079404 Supp b'lemma:nh4cl'
3.957229 Anti b'lemma:\xcf\x8332'
3.956003 Gtype b'-1:lemma:\xe2\x88\x86'
3.953278 Agit b'+1:lemma:rpm'
3.941726 Gtype b'lemma:\xe2\x88\x86'
3.907768 Technique b'lemma:chip-seq'
3.905761 Agit b'lemma:rpm'
3.904057 Supp b'-1:lemma:with'
3.875117 O b'lemma:with'
3.849561 Gtype b'lemma:nsrr'
3.837199 Strain b'lemma:k-12'
3.821133 O b'-1:lemma:0.3'
3.819067 Substrain b'lemma:mg1655'
3.801355 Air b'postag:RB'
3.742394 Gtype b'lemma:delta-fnr'
3.723431 O b'lemma:.'
3.723431 O b'postag:.'
3.712638 Gtype b'+1:lemma:ph5'
3.706468 Technique b'+1:lemma:chip-exo'
3.704888 O b'-1:lemma:lb'
3.700597 O b'postag:VBN'
3.687731 Med b'lemma:lb'
3.613975 O b'lemma:rep2'
3.608532 Med b'+1:lemma:0.4'
3.574989 Temp b'+1:lemma:in'
3.569955 Gtype b'lemma:delta-arca'
3.550905 O b'-1:lemma:Aerobic'
3.528303 Anti b'lemma:seqa'
3.503539 Supp b'lemma:Fe'
3.492004 Supp b'lemma:no3'
3.441556 O b'postag::'
3.422006 O b'lemma:s'
3.421977 Air b'-1:lemma:-'
3.409494 Anti b'+1:lemma:antibody'
3.369142 Supp b'lemma:Leu'
3.366238 Gversion b'lemma:chip-seq'
3.352237 pH b'lemma:5.5'
3.322800 Supp b'lemma:dpd'
3.313361 O b'postag:CC'
3.300844 Air b'lemma:anaerobically'
3.294952 O b'-1:lemma:glucose'
3.283475 Gtype b'lemma:\xce\xb4ompr'
3.272195 Gversion b'lemma:000913'
3.262789 Air b'lemma:aerobically'
3.220393 Temp b'-1:lemma:43'
3.217440 Temp b'lemma:43'
3.214588 O b'+1:lemma:arca-8myc'
3.198442 Gtype b'-1:lemma:rpob'
3.188606 O b'+1:lemma:250'
3.187173 O b'lemma:harbor'
3.185320 Gversion b'lemma:u00096'
3.185320 Gversion b'+1:lemma:.2'
3.175362 Substrain b'+1:lemma:phtpg'
3.172542 Gtype b'lemma:\xce\xb4oxyr'
3.170170 Supp b'lemma:Adenine'
3.164012 Supp b'lemma:arginine'
3.136227 O b'postag:VBG'
3.104172 Med b'+1:lemma:2.0'
3.096505 Temp b'-1:lemma:\xcf\x8332'
3.074944 Technique b'-1:lemma:IP'
3.067448 O b'-1:lemma:0.3-0.35'
3.065444 Med b'lemma:L'
3.065444 Med b'+1:lemma:broth'
3.060118 O b'lemma:CEL'
3.054281 O b'+1:lemma:coli'
3.051410 O b'-1:lemma:\xc2\xb0c'
3.034615 Temp b'-1:lemma:sample'
3.029536 Air b'lemma:anaeroibc'
3.023155 Substrain b'lemma:mg1655star'
3.019933 Gtype b'+1:lemma:pq'
2.995596 O b'+1:lemma:acetate'
2.984619 Gversion b'-1:lemma:nc'
2.925612 Vess b'lemma:flask'
2.925612 Vess b'-1:lemma:warm'
2.899963 O b'-1:lemma:into'
2.891018 Technique b'-1:lemma:chip-exo'
2.890525 O b'+1:lemma:od600'
2.858430 Supp b'-1:lemma:vol'
2.849587 Supp b'+1:lemma:1'
2.828369 pH b'lemma:ph5'
2.828369 pH b'+1:lemma:.5'
2.824538 Technique b'+1:lemma:rna-seq'
2.822954 O b'lemma:ml'
2.817516 Med b'lemma:m63'
2.799830 O b'+1:lemma:chip-seq'
2.787598 Gtype b'-1:lemma:delta'
2.779697 Supp b'lemma:fructose'
2.767969 Anti b'lemma:anti-myc'
2.763373 Med b'lemma:minimal'
2.743566 Gversion b'lemma:.2'
2.743566 Gversion b'-1:lemma:u00096'
2.740028 O b'lemma:at'
2.726573 O b'+1:lemma:mid-log'
2.723830 Med b'lemma:media'
2.690230 Gtype b'-1:lemma:ptac'
2.654749 Phase b'-1:lemma:mid-log'
2.599977 Temp b'-1:lemma:37'
2.596352 Supp b'+1:lemma:mm'
2.585123 O b'lemma:genotype/variation'
2.571508 pH b'+1:lemma:5.5'
2.562718 O b'+1:postag:RB'
2.562005 Med b'lemma:broth'
2.562005 Med b'-1:lemma:L'
2.554222 O b'+1:postag:NNP'
2.535600 Gtype b'+1:lemma:_'
2.518199 pH b'+1:postag:CD'
2.518124 Gtype b'+1:lemma:with'
2.491187 Supp b'-1:lemma:sodium'
2.469590 Gtype b'-1:postag:VBG'
2.467682 O b'lemma::'
2.457707 Gtype b'+1:lemma:flagtag'
2.438605 Supp b'-1:lemma:\xc2\xb5m'
2.431369 O b'lemma:delta'
2.383985 O b'-1:lemma:rpm'
2.377086 O b'lemma:condition'
2.376152 Gtype b'-1:lemma:factor'
2.371623 Med b'-1:lemma:fresh'
2.370677 O b'lemma:agitation'
2.284942 O b'-1:lemma:l1'
2.275556 Supp b'lemma:2h'
2.275556 Supp b'-1:lemma:additional'
2.274947 Phase b'lemma:phase'
2.266504 Gtype b'+1:postag::'
2.261288 Supp b'+1:lemma:2'
2.260087 O b'lemma:culture'
2.253128 Temp b'lemma:\xc2\xb0c'
2.230044 Gtype b'lemma:deltaseqa'
2.230044 Gtype b'-1:lemma:old'
2.227831 O b'+1:lemma:or'
2.192592 O b'+1:lemma:sparging'
2.165330 O b'lemma:chip-arca'
2.117423 Gtype b'lemma:ptac'
2.114952 Temp b'lemma:37'
2.108020 Med b'-1:lemma:glucose'
2.104393 Supp b'+1:lemma:_'
2.087736 Med b'+1:lemma:g/l'
2.077989 Vess b'+1:lemma:at'
2.059857 Phase b'-1:lemma:until'
Top negative:
0.000742 Supp b'postag::'
0.000442 Air b'-1:lemma:phase'
0.000211 Supp b'lemma:,'
0.000211 Supp b'postag:,'
0.000137 O b'+1:postag:CD'
0.000131 Supp b'lemma:;'
0.000131 Supp b'-1:lemma:7.6'
0.000123 Air b'lemma:-lrb-'
0.000116 Air b'postag:-LRB-'
0.000115 Temp b'postag:CD'
0.000114 Air b'lemma:95'
0.000098 O b'lemma:IP'
0.000087 Supp b'+1:lemma:10'
0.000082 Air b'+1:postag:CC'
0.000081 O b'+1:lemma:phase'
0.000081 Air b'+1:lemma:n2'
0.000068 Air b'-1:lemma:and'
0.000067 O b'lemma:dpd'
0.000062 Temp b'-1:postag:IN'
0.000059 Air b'+1:lemma:-rrb-'
0.000058 Air b'+1:postag:-RRB-'
0.000057 Air b'postag:CC'
0.000036 Supp b'lemma:m'
0.000028 Med b'+1:postag:VBG'
0.000020 Gversion b'-1:postag::'
0.000008 Air b'-1:lemma:-lrb-'
0.000007 Air b'-1:postag:-LRB-'
0.000001 O b'+1:lemma:anti-fur'
-0.000004 O b'+1:lemma:contain'
-0.000005 O b'+1:lemma:7.6'
-0.000018 O b'-1:lemma:95'
-0.000026 O b'-1:lemma:anaerobically'
-0.000028 O b'lemma:m'
-0.000035 O b'lemma:co2'
-0.000041 Supp b'+1:postag:IN'
-0.000044 O b'lemma:n2'
-0.000052 Gtype b'-1:postag:NNP'
-0.000060 O b'lemma:;'
-0.000060 O b'-1:lemma:7.6'
-0.000139 O b'+1:lemma:95'
-0.000142 O b'lemma:phase'
-0.000218 O b'lemma:7.6'
-0.000218 O b'+1:lemma:;'
-0.000325 O b'-1:lemma:rifampicin'
-0.000388 Med b'postag:JJ'
-0.000590 Gtype b'+1:lemma:\xe2\x88\x86'
-0.000903 O b'lemma:fecl2'
-0.001037 Med b'-1:postag:CD'
-0.002018 OD b'postag:NN'
-0.002219 O b'-1:postag:DT'
-0.002619 Agit b'-1:postag:NN'
-0.002670 Agit b'postag:NN'
-0.002713 Supp b'-1:lemma:,'
-0.002713 Supp b'-1:postag:,'
-0.002864 O b'-1:lemma:rpob'
-0.004052 Gtype b'+1:lemma:-rrb-'
-0.005593 O b'lemma:%'
-0.005800 Supp b'+1:lemma:of'
-0.006031 O b'-1:postag:-RRB-'
-0.006630 Supp b'lemma:and'
-0.008960 O b'+1:lemma:5'
-0.009041 Gtype b'-1:lemma:mg1655'
-0.010663 O b'+1:lemma:-lrb-'
-0.011765 O b'+1:lemma:for'
-0.012164 Gtype b'+1:postag:CD'
-0.013897 Supp b'-1:lemma:dpd'
-0.017334 Gtype b'-1:postag:NN'
-0.017694 Gtype b'postag:VBG'
-0.017980 O b'lemma:dissolve'
-0.019810 O b'+1:lemma:co2'
-0.022198 Supp b'-1:lemma:10'
-0.025394 Med b'-1:postag:NN'
-0.025755 Air b'-1:postag:CC'
-0.043211 Supp b'-1:lemma:.'
-0.043211 Supp b'-1:postag:.'
-0.051959 O b'-1:lemma:g/l'
-0.055702 O b'-1:lemma:with'
-0.063942 Supp b'lemma:mm'
-0.068985 Technique b'postag:NN'
-0.073087 Air b'postag:CD'
-0.077219 O b'lemma:1m'
-0.080485 O b'-1:lemma:~'
-0.085050 O b'+1:lemma:-rrb-'
-0.092426 Supp b'-1:lemma:;'
-0.092628 Gtype b'-1:postag:CD'
-0.096816 Gtype b'postag:CD'
-0.119110 O b'lemma:aerobic'
-0.126644 O b'-1:lemma:of'
-0.131761 Supp b'-1:postag:NN'
-0.134231 Phase b'-1:lemma:at'
-0.136658 O b'+1:lemma:%'
-0.141146 O b'-1:lemma:iptg'
-0.144992 O b'+1:lemma:ph'
-0.157744 Phase b'+1:postag:NN'
-0.157765 Anti b'+1:postag:JJ'
-0.163999 O b'lemma:wt'
-0.189704 O b'+1:lemma:fnr'
-0.198314 Gversion b'+1:postag:NN'
-0.216819 Technique b'-1:lemma::'
-0.221198 O b'-1:lemma:from'
-0.226083 Med b'postag:CD'
-0.230714 O b'-1:lemma:until'
-0.237769 Supp b'postag:NN'
-0.242723 O b'-1:lemma:m'
-0.263854 O b'-1:lemma:1m'
-0.266928 O b'+1:postag:-LRB-'
-0.269887 O b'lemma:od600'
-0.286157 Supp b'postag:CD'
-0.303058 Supp b'lemma:10'
-0.318379 O b'lemma:37'
-0.338883 O b'lemma:medium'
-0.349993 Supp b'postag:CC'
-0.363924 Gtype b'+1:lemma:-lrb-'
-0.367167 O b'+1:lemma:.'
-0.367167 O b'+1:postag:.'
-0.369526 O b'-1:postag:IN'
-0.374776 O b'-1:lemma:-lrb-'
-0.396666 O b'lemma:minimal'
-0.401132 Supp b'+1:lemma:nacl'
-0.401200 O b'lemma:20'
-0.413658 O b'+1:lemma:+'
-0.420906 O b'+1:lemma:supplement'
-0.422140 O b'-1:lemma:37'
-0.449399 O b'-1:lemma:final'
-0.475371 Supp b'+1:lemma:rifampicin'
-0.479924 O b'-1:postag:-LRB-'
-0.482195 Med b'+1:postag:NN'
-0.502676 Med b'-1:postag:IN'
-0.510386 O b'lemma:aerobically'
-0.534746 O b'lemma:ph'
-0.537042 Supp b'+1:lemma:dpd'
-0.553037 O b'lemma:\xe2\x88\x86'
-0.562667 Supp b'+1:lemma:fructose'
-0.579922 O b'+1:postag:-RRB-'
-0.590146 Air b'-1:lemma:or'
-0.593093 O b'lemma:mid-log'
-0.607111 O b'-1:lemma:n2'
-0.610949 Supp b'-1:lemma:-lrb-'
-0.623891 O b'-1:lemma:cra'
-0.632807 pH b'postag:NN'
-0.636218 O b'lemma:nitrogen'
-0.650697 Technique b'-1:postag::'
-0.667765 Supp b'-1:postag:-LRB-'
-0.674159 O b'+1:lemma:2.0'
-0.694197 O b'-1:lemma:co2'
-0.701703 O b'-1:lemma:ml'
-0.713992 O b'-1:lemma:\xe2\x88\x86'
-0.749394 O b'-1:lemma:mm'
-0.789720 O b'lemma:2h'
-0.789720 O b'-1:lemma:additional'
-0.820603 O b'+1:lemma:until'
-0.839385 O b'lemma:methanol'
-0.843808 O b'lemma:anaerobically'
-0.860222 O b'-1:lemma:delta'
-0.871696 O b'+1:lemma:1m'
-0.880227 O b'+1:postag:IN'
-0.923850 Supp b'+1:postag:VBN'
-0.934662 Supp b'+1:lemma:acetate'
-0.987240 O b'+1:lemma:g/l'
-0.987424 O b'-1:postag::'
-1.031889 O b'lemma:media'
-1.050292 O b'-1:lemma:dissolve'
-1.050292 O b'+1:lemma:methanol'
-1.063258 O b'+1:lemma:at'
-1.121215 O b'-1:lemma:ph'
-1.124241 Supp b'-1:postag:NNP'
-1.124243 O b'-1:lemma:nsrr'
-1.178115 Anti b'postag:NNP'
-1.210563 O b'lemma:of'
-1.231717 O b'+1:lemma:mm'
-1.234806 Air b'postag:NN'
-1.361331 Air b'+1:postag:JJ'
-1.388315 O b'+1:postag:VBG'
-1.395520 O b'postag:VBP'
-1.437329 Temp b'postag:NN'
-1.497705 O b'-1:lemma:30'
-1.515627 Phase b'-1:postag:JJ'
-1.587348 O b'-1:lemma:fresh'
-1.648330 O b'-1:lemma:sample'
-1.699219 Supp b'+1:lemma:-lrb-'
-1.725672 O b'+1:lemma:1'
-1.740394 O b'lemma:30'
-1.747868 Supp b'+1:postag:-LRB-'
-1.758948 O b'-1:lemma:IP'
-1.840034 Supp b'+1:lemma:,'
-1.840034 Supp b'+1:postag:,'
-1.883643 Phase b'postag:JJ'
-1.897236 O b'-1:lemma:2'
-1.932081 OD b'+1:postag:NN'
-1.999100 O b'lemma:rifampicin'
-2.008414 O b'+1:lemma:in'
-2.134731 O b'-1:lemma:1'
-2.149272 Supp b'postag:JJ'
-2.244551 O b'lemma:0.3'
-2.273539 O b'+1:lemma:2'
-2.385609 O b'-1:postag:VBG'
-2.393117 O b'-1:lemma:vol'
-2.614797 Temp b'+1:postag:IN'
-4.634459 O b'-1:lemma:_'
-4.978327 O b'-1:lemma::'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.14843910146742284, 'c2': 0.03226312504680252}
best CV score:0.8612823170568367
model size: 0.07M
Flat F1: 0.7860849079440478
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 0.955 0.913 0.933 23
Med 1.000 0.925 0.961 53
Temp 1.000 0.690 0.816 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.543 0.362 0.435 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.878 0.847 0.862 85
Substrain 0.000 0.000 0.000 0
Supp 0.731 0.791 0.760 134
Gversion 0.000 0.000 0.000 0
avg / total 0.819 0.765 0.786 451
Top likely transitions:
Temp -> Temp 5.530931
Agit -> Agit 5.252892
Med -> Med 5.060058
OD -> OD 5.010656
Supp -> Supp 4.868977
Anti -> Anti 4.778087
Phase -> Phase 4.545953
Gtype -> Gtype 4.505488
O -> O 4.397808
Air -> Air 4.207182
Gversion -> Gversion 4.184434
Technique -> Technique 3.303412
pH -> pH 2.824139
Gtype -> Supp 1.667731
O -> Supp 1.652196
Substrain -> Gtype 1.583082
Air -> O 1.417656
O -> Technique 1.331982
O -> Gtype 1.241437
Gtype -> Air 0.970767
O -> Temp 0.956558
Technique -> Air 0.825884
Supp -> O 0.782386
Gtype -> pH 0.768653
Med -> O 0.684439
Temp -> O 0.624874
O -> Anti 0.553272
O -> Phase 0.459901
O -> Gversion 0.367975
Strain -> O 0.312627
O -> Med 0.232469
Phase -> O 0.226758
OD -> O 0.226193
O -> OD 0.174193
O -> pH 0.160341
Anti -> O 0.049474
Phase -> Supp -0.001306
Anti -> Gtype -0.002165
Anti -> Med -0.020656
Temp -> Med -0.024123
Supp -> Technique -0.033921
Phase -> Technique -0.039561
Supp -> Gtype -0.050932
Gtype -> Technique -0.103217
Gtype -> O -0.123668
Supp -> Air -0.177566
Gtype -> Gversion -0.243460
Air -> Phase -0.247860
Technique -> OD -0.306784
Gtype -> Anti -0.344939
Top unlikely transitions:
Air -> Air 4.207182
Gversion -> Gversion 4.184434
Technique -> Technique 3.303412
pH -> pH 2.824139
Gtype -> Supp 1.667731
O -> Supp 1.652196
Substrain -> Gtype 1.583082
Air -> O 1.417656
O -> Technique 1.331982
O -> Gtype 1.241437
Gtype -> Air 0.970767
O -> Temp 0.956558
Technique -> Air 0.825884
Supp -> O 0.782386
Gtype -> pH 0.768653
Med -> O 0.684439
Temp -> O 0.624874
O -> Anti 0.553272
O -> Phase 0.459901
O -> Gversion 0.367975
Strain -> O 0.312627
O -> Med 0.232469
Phase -> O 0.226758
OD -> O 0.226193
O -> OD 0.174193
O -> pH 0.160341
Anti -> O 0.049474
Phase -> Supp -0.001306
Anti -> Gtype -0.002165
Anti -> Med -0.020656
Temp -> Med -0.024123
Supp -> Technique -0.033921
Phase -> Technique -0.039561
Supp -> Gtype -0.050932
Gtype -> Technique -0.103217
Gtype -> O -0.123668
Supp -> Air -0.177566
Gtype -> Gversion -0.243460
Air -> Phase -0.247860
Technique -> OD -0.306784
Gtype -> Anti -0.344939
O -> Air -0.501788
Supp -> Med -0.605352
OD -> Air -0.613240
Technique -> pH -0.690682
Gtype -> Med -0.722078
Phase -> OD -0.801917
Technique -> Gtype -1.071131
Substrain -> O -1.244706
Med -> Supp -1.620782
Top positive:
7.616993 O b'lemma:_'
6.105092 Supp b'lemma:Iron'
6.103829 Air b'lemma:anaerobic'
5.778936 O b'lemma:2'
5.395636 Technique b'lemma:ChIP-exo'
5.204401 O b'lemma:1'
5.144386 Supp b'lemma:pq'
5.103835 Phase b'lemma:mid-log'
5.083193 Air b'lemma:Aerobic'
5.031561 Technique b'lemma:chipseq'
5.005363 Gtype b'lemma:wt'
4.790043 O b'postag:IN'
4.685173 O b'lemma:3'
4.622144 Gtype b'lemma:\xce\xb4cra'
4.524605 Air b'lemma:aerobic'
4.365549 O b'lemma:rpob'
4.310154 O b'lemma:-'
4.272698 Gtype b'lemma:wild-type'
4.264401 Phase b'lemma:exponential'
4.264401 Phase b'lemma:stationary'
4.248629 Gversion b'lemma:asm584v2'
4.178525 Supp b'+1:lemma:\xc2\xb5m'
4.162767 Supp b'lemma:glucose'
4.086811 O b'lemma:b'
4.074447 O b'lemma:Cra'
4.061821 Gtype b'lemma:flag-tag'
4.061821 Gtype b'-1:lemma:c-terminal'
4.047125 O b'-1:lemma:tag'
4.029539 Med b'lemma:MOPS'
4.012096 Air b'-1:lemma:ChIP-Seq'
3.859049 Strain b'+1:lemma:substr'
3.808960 Gtype b'lemma:type'
3.796393 Gtype b'lemma:arca8myc'
3.770798 Gtype b'+1:lemma:type'
3.739682 Substrain b'lemma:mg1655'
3.729115 O b'postag::'
3.712923 Supp b'lemma:acetate'
3.671833 O b'lemma:a'
3.624682 O b'postag:CC'
3.612738 Technique b'lemma:rna-seq'
3.596048 Gtype b'lemma:\xe2\x88\x86'
3.593479 O b'lemma:rep1'
3.583965 Supp b'lemma:nh4cl'
3.580142 O b'-1:lemma:ChIP-exo'
3.553131 Supp b'lemma:nacl'
3.491025 Strain b'lemma:k-12'
3.486896 Gversion b'lemma:nc'
3.433417 Med b'lemma:lb'
3.397151 O b'lemma:Custom'
3.387581 O b'lemma:rep3'
3.356308 O b'lemma:.'
3.356308 O b'postag:.'
3.347331 Gtype b'-1:lemma:\xe2\x88\x86'
3.332260 O b'postag:VBN'
3.317828 Technique b'lemma:chip-seq'
3.289766 Technique b'lemma:rnaseq'
3.273328 Supp b'lemma:rifampicin'
3.260083 Air b'postag:RB'
3.239788 O b'lemma:\xcf\x8332'
3.184025 Supp b'lemma:no3'
3.179953 Supp b'-1:lemma:with'
3.167149 Gtype b'lemma:fnr8myc'
3.116958 Supp b'lemma:nitrate'
3.090571 Gtype b'+1:lemma:ph5'
3.048182 O b'lemma:rep2'
3.022284 Gtype b'lemma:\xce\xb4fur'
3.020572 Supp b'-1:lemma:Cra'
2.950744 O b'-1:lemma:type'
2.942210 Supp b'lemma:dpd'
2.937225 Technique b'lemma:ChIP-Seq'
2.936793 Gtype b'lemma:\xce\xb4soxr'
2.927620 Gtype b'lemma:delta-fnr'
2.925981 O b'-1:lemma:lb'
2.918937 Gtype b'lemma:dfnr'
2.900745 Anti b'lemma:none'
2.897719 Gtype b'+1:lemma:with'
2.890673 O b'+1:lemma:pq'
2.880633 Agit b'+1:lemma:rpm'
2.873201 O b'lemma:CEL'
2.867468 Agit b'lemma:rpm'
2.840511 Air b'-1:lemma:-'
2.820801 Technique b'-1:lemma:IP'
2.805716 Anti b'lemma:\xcf\x8332'
2.773458 O b'lemma:ompr'
2.771820 Med b'-1:lemma:ml'
2.757736 Supp b'lemma:Leu'
2.751066 O b'lemma:chip'
2.746879 Med b'+1:lemma:0.4'
2.739214 O b'lemma:with'
2.708793 Gversion b'-1:lemma:nc'
2.677018 Gtype b'lemma:nsrr'
2.670707 Anti b'lemma:seqa'
2.659020 O b'-1:lemma:glucose'
2.657995 Air b'lemma:anaeroibc'
2.657818 Supp b'+1:lemma:Deficient'
2.656948 O b'-1:lemma:0.3'
2.632783 Supp b'-1:lemma:vol'
2.623222 Supp b'-1:lemma:+'
2.618308 Med b'lemma:m63'
2.613887 Gtype b'lemma:pk4854'
2.602756 Anti b'+1:lemma:antibody'
2.584538 Gversion b'lemma:chip-seq'
2.544864 Gversion b'lemma:u00096'
2.544864 Gversion b'+1:lemma:.2'
2.544234 Air b'lemma:anaerobically'
2.544093 O b'postag:VBG'
2.528939 Gtype b'-1:lemma:ptac'
2.520188 Gtype b'lemma:delta-arca'
2.516132 Gversion b'lemma:000913'
2.509681 Vess b'lemma:flask'
2.509681 Vess b'-1:lemma:warm'
2.499520 Supp b'lemma:Fe'
2.491894 Substrain b'+1:lemma:phtpg'
2.487911 O b'-1:lemma:Aerobic'
2.475312 Temp b'-1:lemma:43'
2.473537 Phase b'-1:lemma:mid-log'
2.445140 pH b'+1:postag:CD'
2.435584 O b'-1:lemma:stpa'
2.432404 O b'+1:lemma:coli'
2.392472 Technique b'-1:lemma:chip-exo'
2.379148 Air b'lemma:aerobically'
2.378189 Gversion b'lemma:.2'
2.378189 Gversion b'-1:lemma:u00096'
2.373909 Med b'lemma:media'
2.372719 Temp b'lemma:\xc2\xb0c'
2.370280 O b'lemma:affyexp'
2.367475 Supp b'lemma:fructose'
2.367118 pH b'lemma:ph5'
2.367118 pH b'+1:lemma:.5'
2.365883 O b'lemma:harbor'
2.365510 Gtype b'+1:lemma:_'
2.364550 O b'lemma:chip-arca'
2.364293 Supp b'+1:lemma:1'
2.351215 Supp b'lemma:arginine'
2.338576 O b'+1:lemma:od600'
2.338214 Phase b'lemma:phase'
2.325110 O b'lemma:s'
2.324133 Supp b'+1:lemma:mm'
2.321311 Gtype b'+1:lemma:pq'
2.296132 Supp b'-1:lemma:sodium'
2.261992 Temp b'-1:lemma:\xcf\x8332'
2.260351 Substrain b'lemma:mg1655star'
2.248740 Gtype b'lemma:WT'
2.246446 Supp b'lemma:Adenine'
2.241646 Temp b'+1:lemma:in'
2.224289 Anti b'lemma:anti-myc'
2.211744 Med b'lemma:broth'
2.211744 Med b'-1:lemma:L'
2.206966 O b'+1:lemma:arca-8myc'
2.206282 Med b'+1:lemma:2.0'
2.189025 Med b'lemma:L'
2.189025 Med b'+1:lemma:broth'
2.156370 Air b'lemma:Anaerobic'
2.151046 Temp b'lemma:43'
2.123118 Temp b'+1:lemma:\xc2\xb0c'
2.116886 Gtype b'lemma:\xce\xb4oxyr'
2.111247 O b'-1:lemma:0.3-0.35'
2.110756 Gtype b'lemma:\xce\xb4ompr'
2.098031 O b'+1:lemma:250'
2.072829 OD b'lemma:od450'
2.054078 O b'-1:lemma:l1'
2.027132 O b'postag:DT'
2.020949 Technique b'+1:lemma:chip-exo'
2.012421 Med b'lemma:minimal'
2.004375 Gtype b'+1:lemma:flagtag'
1.990269 O b'-1:lemma:\xc2\xb0c'
1.950886 O b'+1:postag:RB'
1.941939 Supp b'+1:lemma:2'
1.933357 O b'lemma:culture'
1.927257 O b'-1:lemma:anaerobic'
1.918285 O b'+1:lemma:mid-log'
1.906662 O b'postag:NNS'
1.903182 Gtype b'lemma:deltaseqa'
1.903182 Gtype b'-1:lemma:old'
1.889101 Gtype b'lemma:ptac'
1.886365 Gtype b'-1:postag:VBG'
1.879594 O b'+1:lemma:chip-seq'
1.877669 O b'lemma:contain'
1.875514 O b'lemma:ml'
1.873847 O b'+1:lemma:43'
1.872843 O b'lemma:genotype/variation'
1.866446 O b'lemma:soxs'
1.866446 O b'lemma:soxr'
1.865566 Gversion b'lemma:_'
1.858956 Temp b'-1:lemma:sample'
1.836548 O b'+1:postag:NNP'
1.835787 O b'lemma::'
1.805360 Technique b'-1:lemma:rna-seq'
1.803739 O b'-1:lemma:into'
1.801193 Supp b'-1:lemma:mm'
1.798395 Temp b'lemma:37'
1.798227 Technique b'-1:lemma:_'
1.796930 Gtype b'-1:lemma:rpob'
1.786304 Air b'-1:postag::'
1.781423 Med b'+1:lemma:+'
1.773280 Supp b'-1:lemma:\xc2\xb5m'
1.770143 O b'-1:lemma:phase'
1.766358 Temp b'-1:lemma:37'
1.764495 O b'lemma:condition'
1.753857 O b'lemma:argr'
Top negative:
0.000080 Gtype b'+1:lemma:-rcb-'
0.000058 O b"lemma:'s"
0.000058 O b'postag:POS'
0.000058 O b'-1:lemma:manufacturer'
0.000058 O b'+1:lemma:instruction'
0.000036 O b'-1:lemma:0.1'
0.000003 Air b'+1:lemma:n2'
0.000003 O b'-1:lemma:4'
-0.000081 O b'+1:lemma:1/100'
-0.000104 O b'+1:lemma:m'
-0.000105 O b'-1:lemma:phosphate'
-0.000227 O b'-1:lemma:0.2'
-0.000342 O b'-1:lemma:with'
-0.000398 Gversion b'-1:postag:NN'
-0.000464 O b'lemma:%'
-0.001787 O b'lemma:7.6'
-0.001787 O b'+1:lemma:;'
-0.002156 Med b'-1:postag:CD'
-0.002253 O b'lemma:;'
-0.002253 O b'-1:lemma:7.6'
-0.002551 O b'+1:lemma:c'
-0.002951 O b'+1:lemma:gadw'
-0.004097 O b'+1:lemma:gade'
-0.008822 Gtype b'+1:postag:CD'
-0.009586 Med b'postag:JJ'
-0.010831 Agit b'-1:postag:NN'
-0.013524 O b'+1:lemma:antibody'
-0.014706 Anti b'+1:postag:JJ'
-0.015602 Supp b'-1:postag:VBN'
-0.020869 O b'-1:postag:DT'
-0.021186 Gtype b'+1:lemma:\xe2\x88\x86'
-0.025812 OD b'postag:NN'
-0.032647 Gtype b'-1:postag:NNP'
-0.035397 O b'lemma:1m'
-0.038554 O b'+1:lemma:rep2'
-0.041306 Gtype b'-1:postag:NN'
-0.042250 O b'+1:lemma:95'
-0.042668 O b'-1:lemma:contain'
-0.044065 Supp b'-1:lemma:.'
-0.044065 Supp b'-1:postag:.'
-0.055911 Supp b'postag:NN'
-0.056075 O b'lemma:anaerobic'
-0.061212 Agit b'postag:NN'
-0.062946 Supp b'-1:lemma:;'
-0.069294 O b'+1:lemma:%'
-0.071027 O b'+1:lemma:~'
-0.078046 O b'+1:lemma:Aerobic'
-0.079728 O b'lemma:m'
-0.082704 O b'-1:lemma:250'
-0.083986 O b'lemma:150'
-0.083986 O b'+1:lemma:mg/ml'
-0.093290 Gtype b'postag:CD'
-0.098235 Temp b'postag:JJ'
-0.102223 Supp b'+1:postag:NNS'
-0.108761 O b'-1:lemma:of'
-0.112579 O b'lemma:nitrate'
-0.112840 O b'+1:lemma:-rrb-'
-0.114513 O b'-1:lemma:~'
-0.115788 Supp b'+1:postag:-RRB-'
-0.126267 Gtype b'+1:lemma:-rrb-'
-0.133344 O b'-1:lemma:chip-exo'
-0.133967 O b'+1:lemma:arginine'
-0.142732 Air b'postag:CD'
-0.146065 O b'-1:lemma:the'
-0.160763 Supp b'postag:CD'
-0.162843 O b'+1:lemma:for'
-0.169917 Gtype b'-1:lemma:mg1655'
-0.174714 Gversion b'+1:postag:NN'
-0.177235 O b'lemma:dissolve'
-0.186720 Air b'-1:postag:JJ'
-0.197341 Supp b'+1:lemma:glucose'
-0.197861 O b'lemma:fructose'
-0.199130 Med b'+1:postag:IN'
-0.212273 Supp b'lemma:mm'
-0.221938 O b'lemma:soxs-8myc'
-0.223055 O b'lemma:nh4cl'
-0.233773 Phase b'-1:lemma:at'
-0.236512 Gtype b'-1:postag:CD'
-0.242620 Technique b'-1:lemma::'
-0.244933 O b'+1:lemma:ph'
-0.246714 O b'lemma:medium'
-0.248246 O b'+1:postag:-LRB-'
-0.257991 O b'-1:lemma:from'
-0.261029 O b'+1:lemma:.'
-0.261029 O b'+1:postag:.'
-0.263252 Med b'-1:postag:NN'
-0.265835 Supp b'-1:lemma:dpd'
-0.268481 O b'lemma:\xe2\x88\x86'
-0.270497 Med b'postag:CD'
-0.275308 O b'lemma:m63'
-0.280878 O b'+1:lemma:_'
-0.290836 O b'lemma:c'
-0.297682 Gtype b'lemma:control'
-0.298656 O b'lemma:oxyr-8myc'
-0.301488 O b'-1:lemma:-lrb-'
-0.302521 Supp b'lemma:10'
-0.313280 O b'-1:lemma:g/l'
-0.314256 Temp b'-1:lemma:\xc2\xb0c'
-0.320715 O b'-1:lemma:cra'
-0.339495 O b'lemma:od600'
-0.344406 O b'lemma:37'
-0.344682 O b'lemma:purify'
-0.346138 O b'lemma:k-12'
-0.356822 O b'lemma:20'
-0.371207 Med b'+1:postag:NN'
-0.380751 O b'-1:lemma:1m'
-0.381781 O b'+1:lemma:fnr'
-0.384037 Supp b'postag:CC'
-0.394501 Phase b'+1:postag:NN'
-0.399220 O b'-1:postag:-LRB-'
-0.413224 Air b'-1:lemma:or'
-0.419362 O b'-1:lemma:iptg'
-0.424394 O b'-1:lemma:m'
-0.428528 O b'-1:lemma:37'
-0.428627 O b'-1:postag:IN'
-0.429204 Supp b'+1:lemma:dpd'
-0.431781 Supp b'+1:lemma:nacl'
-0.443043 Supp b'+1:lemma:rifampicin'
-0.443466 O b'lemma:minimal'
-0.507877 O b'-1:lemma:n2'
-0.508911 Anti b'+1:lemma:anti-fur'
-0.509943 Gtype b'+1:lemma:-lrb-'
-0.514268 O b'+1:postag:IN'
-0.520329 Phase b'postag:JJ'
-0.539205 O b'lemma:ph'
-0.579756 Supp b'-1:lemma:-lrb-'
-0.580872 Supp b'+1:postag:VBN'
-0.593989 Technique b'-1:postag::'
-0.601568 O b'-1:lemma:final'
-0.601806 O b'+1:lemma:supplement'
-0.607385 pH b'postag:NN'
-0.616692 Med b'-1:postag:IN'
-0.619922 O b'lemma:mid-log'
-0.636160 Supp b'-1:postag:-LRB-'
-0.639809 O b'-1:lemma:dfnr'
-0.664912 O b'+1:postag:-RRB-'
-0.668954 O b'lemma:aerobically'
-0.675066 Supp b'-1:postag:NNP'
-0.687148 O b'-1:lemma:mm'
-0.708508 O b'+1:lemma:until'
-0.783735 O b'-1:postag::'
-0.785090 Gtype b'postag:VBG'
-0.800517 O b'-1:lemma:\xe2\x88\x86'
-0.823546 O b'lemma:wt'
-0.853934 O b'lemma:anaerobically'
-0.856870 O b'-1:lemma:until'
-0.876446 O b'-1:lemma:delta'
-0.913178 O b'-1:lemma:co2'
-0.927211 O b'+1:lemma:1m'
-0.944621 Supp b'+1:lemma:acetate'
-0.951325 O b'lemma:methanol'
-0.963142 O b'lemma:aerobic'
-0.977606 Supp b'+1:lemma:fructose'
-0.979652 O b'lemma:nitrogen'
-1.005488 O b'+1:lemma:g/l'
-1.033787 O b'+1:lemma:at'
-1.033823 O b'-1:lemma:rpob'
-1.043256 O b'lemma:2h'
-1.043256 O b'-1:lemma:additional'
-1.063486 O b'+1:lemma:2.0'
-1.064526 O b'lemma:media'
-1.081067 O b'+1:postag:VBG'
-1.106410 O b'-1:lemma:dissolve'
-1.106410 O b'+1:lemma:methanol'
-1.110835 Temp b'postag:NN'
-1.163232 O b'lemma:\xce\xb4fur'
-1.176341 Air b'postag:NN'
-1.224656 O b'-1:lemma:ph'
-1.256518 O b'lemma:of'
-1.275712 Temp b'+1:postag:IN'
-1.278051 O b'postag:VBP'
-1.280734 O b'lemma:30'
-1.283875 Air b'+1:postag:JJ'
-1.295409 O b'-1:lemma:30'
-1.304660 O b'+1:lemma:+'
-1.311794 O b'-1:lemma:1'
-1.371031 O b'-1:lemma:nsrr'
-1.376731 O b'-1:lemma:fresh'
-1.379175 O b'-1:lemma:ml'
-1.408674 O b'-1:lemma:sample'
-1.445343 Anti b'postag:NNP'
-1.459575 Supp b'+1:lemma:-lrb-'
-1.506932 O b'+1:lemma:mm'
-1.510376 Supp b'+1:postag:-LRB-'
-1.529217 Supp b'postag:JJ'
-1.624777 Supp b'+1:lemma:,'
-1.624777 Supp b'+1:postag:,'
-1.649260 Phase b'-1:postag:JJ'
-1.668731 O b'+1:lemma:in'
-1.717464 O b'lemma:0.3'
-1.719606 OD b'+1:postag:NN'
-1.847089 O b'-1:lemma:2'
-1.871052 O b'lemma:rifampicin'
-1.883719 O b'+1:lemma:1'
-1.954580 O b'-1:postag:VBG'
-2.049608 O b'-1:lemma:IP'
-2.191282 O b'-1:lemma:vol'
-2.323780 O b'+1:lemma:2'
-3.283742 O b'-1:lemma:_'
-3.922389 O b'-1:lemma::'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.1779311060486324, 'c2': 0.0005619148999585256}
best CV score:0.8815860410516979
model size: 0.07M
Flat F1: 0.7874835473429163
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.913 0.955 23
Med 1.000 0.962 0.981 53
Temp 1.000 0.931 0.964 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.543 0.362 0.435 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.893 0.788 0.837 85
Substrain 0.000 0.000 0.000 0
Supp 0.677 0.799 0.733 134
Gversion 0.000 0.000 0.000 0
avg / total 0.808 0.778 0.787 451
Top likely transitions:
Agit -> Agit 7.599672
Temp -> Temp 6.866268
OD -> OD 6.223914
Med -> Med 6.223896
Anti -> Anti 5.733249
Supp -> Supp 5.501969
Phase -> Phase 5.255937
Air -> Air 5.242444
Gversion -> Gversion 4.759517
Technique -> Technique 4.572796
Gtype -> Gtype 4.408618
pH -> pH 4.148766
O -> O 3.770155
O -> Technique 1.394833
Air -> O 0.934701
O -> Supp 0.603143
Gtype -> Supp 0.602203
O -> Temp 0.531294
O -> Gtype 0.244043
Substrain -> Gtype 0.178777
Temp -> O 0.116666
O -> Anti 0.073374
Technique -> Air 0.057205
O -> Phase 0.016593
Med -> O 0.014656
O -> OD 0.003771
O -> pH 0.001976
Anti -> O -0.000356
Phase -> O -0.013827
Supp -> O -0.037801
Gversion -> O -0.118955
OD -> O -0.146201
Air -> Temp -0.162047
O -> Med -0.221356
Gtype -> Anti -0.235366
OD -> Air -0.430187
Technique -> O -0.658505
Supp -> Med -0.680587
O -> Air -1.100972
Gtype -> O -1.334900
Med -> Supp -1.533125
Substrain -> O -2.088700
Top unlikely transitions:
Agit -> Agit 7.599672
Temp -> Temp 6.866268
OD -> OD 6.223914
Med -> Med 6.223896
Anti -> Anti 5.733249
Supp -> Supp 5.501969
Phase -> Phase 5.255937
Air -> Air 5.242444
Gversion -> Gversion 4.759517
Technique -> Technique 4.572796
Gtype -> Gtype 4.408618
pH -> pH 4.148766
O -> O 3.770155
O -> Technique 1.394833
Air -> O 0.934701
O -> Supp 0.603143
Gtype -> Supp 0.602203
O -> Temp 0.531294
O -> Gtype 0.244043
Substrain -> Gtype 0.178777
Temp -> O 0.116666
O -> Anti 0.073374
Technique -> Air 0.057205
O -> Phase 0.016593
Med -> O 0.014656
O -> OD 0.003771
O -> pH 0.001976
Anti -> O -0.000356
Phase -> O -0.013827
Supp -> O -0.037801
Gversion -> O -0.118955
OD -> O -0.146201
Air -> Temp -0.162047
O -> Med -0.221356
Gtype -> Anti -0.235366
OD -> Air -0.430187
Technique -> O -0.658505
Supp -> Med -0.680587
O -> Air -1.100972
Gtype -> O -1.334900
Med -> Supp -1.533125
Substrain -> O -2.088700
Top positive:
10.204453 Air b'word[:2]:Ae'
7.959700 Strain b'+1:lemma:substr'
7.931315 Gtype b'word[:1]:\xce\x94'
7.211296 O b'lemma:2'
6.951384 Technique b'word[:2]:Ch'
6.897705 Air b'word[:2]:An'
6.430948 O b'word[:2]:re'
6.304459 Supp b'+1:lemma:\xc2\xb5m'
6.277176 O b'lemma:3'
6.259509 O b'-1:lemma:tag'
5.784951 Phase b'lemma:stationary'
5.680889 O b'lemma:1'
5.565991 Air b'lemma:anaerobic'
5.496150 O b'lemma:-'
5.307683 Phase b'lemma:mid-log'
5.051659 O b'lemma:a'
4.964154 O b'+1:lemma:pq'
4.949696 O b'lemma:with'
4.849415 Gversion b'-1:lemma:nc'
4.834323 Substrain b'word[:2]:MG'
4.807181 O b'lemma:_'
4.807181 O b'word[:1]:_'
4.804254 Supp b'-1:lemma:Cra'
4.759024 Gtype b'lemma:wt'
4.715524 Supp b'lemma:Iron'
4.715524 Supp b'word[:2]:Ir'
4.706542 Supp b'lemma:arginine'
4.646874 Supp b'-1:lemma:vol'
4.197413 O b'word[:2]:Cr'
4.195753 O b'-1:lemma:lb'
4.181423 Gtype b'word[:2]:Fl'
4.134022 OD b'word[:1]:O'
4.052226 Med b'lemma:MOPS'
4.052226 Med b'word[:2]:MO'
4.022958 pH b'word[:2]:pH'
3.975313 Temp b'-1:lemma:sample'
3.962014 Gversion b'lemma:chip-seq'
3.951951 Phase b'word[:2]:ex'
3.931899 Supp b'-1:lemma:with'
3.883643 Gtype b'lemma:arca8myc'
3.879479 Supp b'word[:2]:ni'
3.856134 Temp b'+1:lemma:in'
3.810759 Gtype b'-1:lemma:\xe2\x88\x86'
3.789132 Supp b'-1:lemma:+'
3.786509 O b'word[:2]:ha'
3.757509 Gtype b'word[:1]:d'
3.684952 Supp b'lemma:nacl'
3.663349 O b'word[:2]:Cu'
3.647265 O b'word[:2]:ge'
3.618268 Technique b'word[:2]:RN'
3.420924 Med b'-1:lemma:ml'
3.399171 O b'lemma:.'
3.399171 O b'postag:.'
3.399171 O b'postag[:1]:.'
3.295302 O b'-1:lemma:0.3'
3.233537 O b'-1:lemma:glucose'
3.232228 Anti b'+1:lemma:antibody'
3.166537 O b'word[:1]:B'
3.151800 Gtype b'lemma:type'
3.151800 Gtype b'word[:2]:ty'
3.074513 Supp b'word[:1]:I'
3.066493 O b'word[:1]:G'
3.049541 O b'-1:lemma:into'
2.995715 O b'word[:2]:Rp'
2.974033 Temp b'-1:lemma:\xcf\x8332'
2.939937 O b'lemma:delta'
2.929545 O b'word[:1]:E'
2.889138 Supp b'lemma:acetate'
2.884567 O b'word[:1]:S'
2.849582 Supp b'lemma:pq'
2.849582 Supp b'word[:2]:PQ'
2.796468 Med b'+1:lemma:0.4'
2.748041 Gtype b'word[:2]:cr'
2.715155 O b'postag::'
2.715155 O b'postag[:1]::'
2.711740 Gtype b'word[:1]:w'
2.648443 O b'-1:lemma:0.3-0.35'
2.642979 Temp b'-1:lemma:43'
2.605602 Supp b'+1:lemma:1'
2.584485 Med b'word[:1]:M'
2.543511 Gtype b'lemma:nsrr'
2.543511 Gtype b'word[:2]:Ns'
2.528316 Supp b'+1:lemma:mm'
2.526101 Gtype b'word[:1]:W'
2.518551 Supp b'+1:lemma:2'
2.493071 Technique b'lemma:ChIP-exo'
2.492470 Gtype b'word[:2]:PK'
2.417633 O b'lemma:ompr'
2.417633 O b'word[:2]:Om'
2.403384 O b'lemma:purr'
2.399480 Air b'-1:lemma:ChIP-Seq'
2.385701 Phase b'-1:lemma:until'
2.383512 Gtype b'word[:1]:t'
2.374150 Gtype b'-1:lemma:rpob'
2.368626 O b'word[:1]:R'
2.336211 Supp b'-1:lemma:final'
2.331497 Gversion b'word[:2]:00'
2.322056 O b'+1:lemma:od600'
2.317008 O b'lemma:Custom'
2.307666 Gversion b'lemma:asm584v2'
2.307666 Gversion b'word[:2]:AS'
2.305354 Med b'lemma:L'
2.305354 Med b'+1:lemma:broth'
2.285067 Supp b'lemma:sodium'
2.270312 O b'postag:CC'
2.270312 O b'postag[:2]:CC'
2.257396 Air b'word[:1]:a'
2.233372 Med b'+1:lemma:g/l'
2.223950 Supp b'+1:lemma:phosphate'
2.222780 O b'+1:lemma:mid-log'
2.221972 O b'-1:lemma:type'
2.203153 O b'word[:1]:C'
2.199367 Med b'+1:lemma:2.0'
2.195464 Gversion b'lemma:nc'
2.195464 Gversion b'word[:2]:NC'
2.192101 O b'+1:postag:RB'
2.162744 O b'lemma:b'
2.159358 Air b'-1:lemma:co2'
2.157857 Supp b'+1:lemma:1m'
2.150708 O b'-1:lemma:Aerobic'
2.149348 Air b'+1:postag:IN'
2.138880 Anti b'hGreek'
2.137978 O b'+1:lemma:43'
2.122867 O b'postag:IN'
2.122867 O b'postag[:1]:I'
2.122867 O b'postag[:2]:IN'
2.118447 Supp b'word[:2]:Fe'
2.105815 Anti b'word[:2]:an'
2.075029 Supp b'+1:lemma:and'
2.072990 Gtype b'symb'
2.065880 O b'+1:postag:NNP'
2.062690 O b'+1:lemma:250'
2.020409 Gtype b'-1:postag:VBG'
2.013701 Gtype b'lemma:flag-tag'
2.013701 Gtype b'-1:lemma:c-terminal'
1.989019 Substrain b'word[:1]:M'
1.972823 Agit b'+1:lemma:rpm'
1.953612 Supp b'lemma:Fe'
1.940845 O b'lemma:chip'
1.936105 Med b'word[:1]:L'
1.928291 Supp b'lemma:rifampicin'
1.926687 Supp b'word[:2]:gl'
1.915939 Supp b'word[:2]:ri'
1.913797 Gversion b'lemma:.2'
1.913797 Gversion b'-1:lemma:u00096'
1.913797 Gversion b'word[:2]:.2'
1.910063 Supp b'lemma:fructose'
1.909338 Supp b'word[:2]:30'
1.896702 O b'lemma:growth'
1.895943 Supp b'postag:VBP'
1.892910 Gtype b'+1:lemma:type'
1.889532 O b'lemma:0.4'
1.871889 Gtype b'lemma:\xe2\x88\x86'
1.871889 Gtype b'word[:1]:\xe2\x88\x86'
1.871050 O b'lemma:at'
1.869248 O b'word[:2]:In'
1.859503 Gtype b'word[:1]:F'
1.851083 Supp b'word[:2]:ac'
1.849424 O b'-1:lemma:anaerobic'
1.842373 O b'-1:lemma:media'
1.841449 Supp b'-1:postag:CC'
1.836269 O b'lemma:ml'
1.836269 O b'word[:2]:ml'
1.828600 O b'word[:1]:i'
1.828258 Gtype b'word[:1]:f'
1.827189 Technique b'word[:1]:R'
1.813413 O b'-1:lemma:mg1655'
1.805298 Temp b'lemma:43'
1.805298 Temp b'word[:2]:43'
1.800703 Med b'lemma:broth'
1.800703 Med b'-1:lemma:L'
1.800703 Med b'word[:2]:br'
1.795613 O b'word[:1]:u'
1.759212 O b'postag[:1]:V'
1.759212 O b'postag[:2]:VB'
1.754974 Gtype b'-1:lemma:_'
1.745663 Supp b'word[:1]:1'
1.723877 Supp b'lemma:Leu'
1.723877 Supp b'word[:2]:Le'
1.721581 Technique b'lemma:chipseq'
1.707824 Phase b'+1:postag:NNS'
1.696873 Gtype b'-1:lemma:vector'
1.690920 Air b'word[:2]:an'
1.681189 Gtype b'word[:2]:Ar'
1.652222 O b'+1:postag:VBZ'
1.635512 O b'+1:lemma:30'
1.623155 Med b'+1:lemma:-lrb-'
1.621988 O b'-1:lemma:stpa'
1.619973 Substrain b'+1:lemma:phtpg'
1.619895 Vess b'lemma:flask'
1.619895 Vess b'-1:lemma:warm'
1.613546 Supp b'+1:lemma:min'
1.611072 Vess b'word[:2]:fl'
1.610373 O b'+1:postag:VBN'
1.603394 Air b'+1:lemma:until'
1.591021 Temp b'-1:lemma:degree'
1.586003 O b'word[:1]:-'
1.583870 O b'-1:lemma:phase'
1.582561 Supp b'lemma:2h'
1.582561 Supp b'-1:lemma:additional'
Top negative:
-0.059848 OD b'postag[:1]:N'
-0.059848 OD b'postag[:2]:NN'
-0.059922 O b'-1:lemma:phosphate'
-0.060173 Technique b'-1:lemma::'
-0.060454 O b'word[:1]:2'
-0.061725 OD b'+1:lemma:0.4'
-0.062364 Technique b'postag[:1]:N'
-0.062364 Technique b'postag[:2]:NN'
-0.063877 Gtype b'word[:1]:-'
-0.063940 O b'-1:lemma:-lrb-'
-0.065863 Supp b'-1:postag:NN'
-0.066673 OD b'lemma:0.4'
-0.067069 O b'word[:2]:fi'
-0.068494 O b'word[:1]:.'
-0.070950 Air b'postag:CC'
-0.070950 Air b'postag[:2]:CC'
-0.078141 O b'word[:1]:g'
-0.079781 Supp b'word[:2]:10'
-0.085611 O b'-1:postag:-LRB-'
-0.085744 O b'lemma:minimal'
-0.086337 O b'word[:1]:d'
-0.087082 Supp b'word[:2]:vo'
-0.091121 Gtype b'+1:postag:NN'
-0.094589 Supp b'postag:CD'
-0.094589 Supp b'postag[:2]:CD'
-0.098403 Temp b'-1:lemma:\xc2\xb0c'
-0.099548 O b'+1:postag:-LRB-'
-0.099870 O b'+1:lemma:rep2'
-0.103006 O b'+1:lemma:1/100'
-0.107449 Gversion b'+1:postag:NN'
-0.108265 Temp b'postag[:1]:N'
-0.108265 Temp b'postag[:2]:NN'
-0.108397 Supp b'-1:lemma:.'
-0.108397 Supp b'-1:postag:.'
-0.109037 Gtype b'postag[:1]:V'
-0.109037 Gtype b'postag[:2]:VB'
-0.109312 Supp b'lemma:10'
-0.113057 O b'+1:lemma:%'
-0.120224 Phase b'-1:lemma:at'
-0.130743 O b'+1:postag:CD'
-0.133476 Supp b'lemma:,'
-0.133476 Supp b'postag:,'
-0.133476 Supp b'word[:1]:,'
-0.133476 Supp b'postag[:1]:,'
-0.136463 Air b'hUpper'
-0.136463 Air b'hLower'
-0.150682 O b'word[:2]:OD'
-0.151965 O b'-1:lemma:rpob'
-0.154235 O b'+1:lemma:-rrb-'
-0.158600 Gtype b'-1:lemma:mg1655'
-0.164950 O b'word[:1]:M'
-0.174920 Air b'+1:postag:-LRB-'
-0.176710 Med b'lemma:m9'
-0.176710 Med b'word[:2]:M9'
-0.178022 Med b'postag[:1]:C'
-0.180125 O b'-1:lemma:of'
-0.181701 Phase b'+1:postag:NN'
-0.183270 Supp b'postag[:1]:C'
-0.184142 Med b'-1:lemma:m9'
-0.185330 OD b'lemma:od600'
-0.194943 O b'word[:2]:ae'
-0.196910 Technique b'-1:postag::'
-0.198688 Supp b'word[:1]:C'
-0.198890 Gtype b'-1:lemma:-lrb-'
-0.199882 pH b'postag[:1]:N'
-0.199882 pH b'postag[:2]:NN'
-0.200375 Air b'-1:lemma:grow'
-0.201809 O b'lemma:2h'
-0.201809 O b'-1:lemma:additional'
-0.201809 O b'word[:2]:2h'
-0.205749 Supp b'+1:lemma:10'
-0.216714 Gtype b'+1:postag:CD'
-0.224065 O b'+1:postag:-RRB-'
-0.226472 O b'lemma:co2'
-0.226472 O b'word[:2]:CO'
-0.232140 Air b'-1:postag:VBN'
-0.241573 Air b'-1:postag:CC'
-0.242963 Air b'symb'
-0.250464 Phase b'postag[:1]:J'
-0.250464 Phase b'postag[:2]:JJ'
-0.270255 O b'lemma:aerobically'
-0.270737 O b'lemma:media'
-0.271988 O b'word[:2]:gl'
-0.275321 O b'+1:lemma:supplement'
-0.276089 O b'-1:postag:IN'
-0.281202 O b'word[:2]:ce'
-0.282921 O b'-1:lemma:250'
-0.284342 Air b'+1:postag:JJ'
-0.285982 O b'lemma:of'
-0.285982 O b'word[:2]:of'
-0.299888 Supp b'word[:2]:an'
-0.300445 O b'word[:1]:F'
-0.311626 O b'+1:lemma:for'
-0.312645 Phase b'postag:JJ'
-0.314439 Temp b'postag:NN'
-0.318498 O b'+1:lemma:mm'
-0.321300 Supp b'-1:lemma:-lrb-'
-0.328758 O b'lemma:1m'
-0.328758 O b'word[:2]:1M'
-0.333791 O b'-1:lemma:sodium'
-0.336871 Med b'+1:postag:NN'
-0.348304 Gtype b'+1:lemma:-lrb-'
-0.350520 Med b'-1:postag:CD'
-0.352516 O b'lemma:37'
-0.352516 O b'word[:2]:37'
-0.362946 O b'+1:lemma:.'
-0.362946 O b'+1:postag:.'
-0.363307 Med b'-1:postag:NN'
-0.370538 Air b'postag:NN'
-0.375679 Supp b'-1:postag:-LRB-'
-0.378467 O b'+1:postag:VBG'
-0.380556 O b'-1:lemma:ml'
-0.380799 O b'-1:lemma:final'
-0.381345 O b'+1:lemma:ph'
-0.383546 O b'-1:lemma:n2'
-0.385967 O b'lemma:mid-log'
-0.387867 Air b'postag[:1]:N'
-0.387867 Air b'postag[:2]:NN'
-0.397798 Supp b'postag:JJ'
-0.400326 Supp b'postag[:1]:J'
-0.400326 Supp b'postag[:2]:JJ'
-0.407602 O b'-1:lemma:mm'
-0.431970 Med b'-1:postag:IN'
-0.434055 O b'-1:lemma:1m'
-0.445787 Temp b'hGreek'
-0.452175 Med b'symb'
-0.460332 O b'-1:lemma:IP'
-0.467068 O b'-1:lemma:37'
-0.478293 O b'+1:lemma:phosphate'
-0.537372 O b'word[:2]:ni'
-0.545269 O b'-1:lemma:until'
-0.548531 O b'word[:2]:0.'
-0.623964 O b'word[:1]:0'
-0.624246 Supp b'-1:postag:NNP'
-0.632176 O b'lemma:c'
-0.637617 O b'+1:postag:IN'
-0.640663 OD b'hUpper'
-0.640663 OD b'hLower'
-0.643238 O b'lemma:sodium'
-0.678960 O b'word[:2]:pH'
-0.686405 O b'word[:2]:ri'
-0.690472 Air b'-1:lemma:or'
-0.706445 O b'-1:lemma:delta'
-0.723520 O b'+1:lemma:g/l'
-0.736143 Supp b'hGreek'
-0.746481 O b'lemma:methanol'
-0.769671 O b'-1:lemma:nsrr'
-0.784252 Air b'-1:postag:JJ'
-0.788281 Med b'+1:postag:IN'
-0.822122 Supp b'+1:lemma:rifampicin'
-0.838923 Supp b'symb'
-0.852449 Agit b'symb'
-0.867354 O b'-1:lemma:co2'
-0.874419 O b'-1:lemma:30'
-0.894271 O b'word[:2]:me'
-0.895822 O b'word[:2]:mg'
-0.898915 O b'-1:lemma:1'
-0.904279 O b'lemma:0.3'
-0.910372 O b'+1:lemma:at'
-0.910865 Phase b'hUpper'
-0.910865 Phase b'hLower'
-1.005990 O b'-1:postag::'
-1.027364 O b'+1:lemma:1m'
-1.029400 O b'-1:lemma:dissolve'
-1.029400 O b'+1:lemma:methanol'
-1.037454 Gtype b'lemma:delta'
-1.044796 O b'-1:lemma:fresh'
-1.052334 O b'+1:lemma:until'
-1.062610 O b'word[:1]:N'
-1.076834 O b'word[:2]:fl'
-1.106973 O b'word[:2]:30'
-1.108666 Phase b'-1:postag:JJ'
-1.184488 Gtype b'+1:lemma:-rrb-'
-1.190874 Agit b'hUpper'
-1.190874 Agit b'hLower'
-1.198537 Anti b'postag:NNP'
-1.237479 Technique b'postag:NN'
-1.254724 Gtype b'word[:1]:C'
-1.285720 O b'+1:lemma:2.0'
-1.319520 O b'-1:lemma:cra'
-1.367368 O b'-1:lemma:sample'
-1.499105 O b'-1:postag:VBG'
-1.499318 O b'+1:lemma:in'
-1.578496 O b'-1:lemma:ph'
-1.679574 OD b'+1:postag:NN'
-1.738083 O b'word[:2]:Ch'
-1.860176 O b'+1:lemma:1'
-1.912082 O b'lemma:rifampicin'
-1.975467 Supp b'+1:lemma:-lrb-'
-2.013762 Supp b'+1:postag:-LRB-'
-2.120131 O b'+1:lemma:2'
-2.321555 Supp b'+1:lemma:,'
-2.321555 Supp b'+1:postag:,'
-2.461859 O b'word[:1]:P'
-2.555572 Temp b'+1:postag:IN'
-2.561836 O b'-1:lemma:2'
-3.242599 O b'postag:VBP'
-3.584101 O b'-1:lemma:vol'
-5.325671 O b'-1:lemma:_'
-5.823992 O b'-1:lemma::'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.13330184503096318, 'c2': 0.015952382909212963}
best CV score:0.8603877155764311
model size: 0.08M
Flat F1: 0.7890643233991025
precision recall f1-score support
OD 0.857 0.818 0.837 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.913 0.955 23
Med 1.000 0.943 0.971 53
Temp 1.000 0.690 0.816 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.543 0.362 0.435 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.868 0.776 0.820 85
Substrain 0.000 0.000 0.000 0
Supp 0.779 0.813 0.796 134
Gversion 0.000 0.000 0.000 0
avg / total 0.826 0.763 0.789 451
Top likely transitions:
Agit -> Agit 6.893287
Temp -> Temp 6.021557
Med -> Med 5.295918
OD -> OD 5.124787
Anti -> Anti 5.077725
Phase -> Phase 4.805244
Supp -> Supp 4.676680
Gversion -> Gversion 4.270632
O -> O 4.151009
Gtype -> Gtype 4.130084
Air -> Air 4.099435
Technique -> Technique 3.483421
pH -> pH 2.997159
Substrain -> Gtype 1.124559
O -> Technique 1.003751
O -> Supp 0.947717
Air -> O 0.873831
Temp -> O 0.565967
O -> Temp 0.479055
O -> Gtype 0.462638
Gtype -> Air 0.167055
Supp -> O 0.160803
Technique -> Air 0.116967
O -> OD 0.109397
Med -> O 0.103673
O -> Phase 0.083258
Gtype -> Supp 0.074101
OD -> O 0.051003
Phase -> O 0.029928
Strain -> O 0.000886
O -> Anti 0.000637
O -> Gversion 0.000062
Anti -> Air -0.001399
Phase -> Supp -0.014135
Gtype -> Gversion -0.023045
Technique -> Gtype -0.145953
Supp -> Technique -0.164756
Technique -> pH -0.188040
Supp -> Air -0.262229
Gtype -> Technique -0.360196
OD -> Air -0.397656
Air -> Phase -0.403726
Gtype -> Med -0.439722
Gversion -> O -0.476476
Air -> Supp -0.501806
Gtype -> Anti -0.567560
Supp -> Gtype -0.583004
Air -> Temp -0.652068
Technique -> O -0.816523
O -> Air -0.975032
Top unlikely transitions:
Anti -> Anti 5.077725
Phase -> Phase 4.805244
Supp -> Supp 4.676680
Gversion -> Gversion 4.270632
O -> O 4.151009
Gtype -> Gtype 4.130084
Air -> Air 4.099435
Technique -> Technique 3.483421
pH -> pH 2.997159
Substrain -> Gtype 1.124559
O -> Technique 1.003751
O -> Supp 0.947717
Air -> O 0.873831
Temp -> O 0.565967
O -> Temp 0.479055
O -> Gtype 0.462638
Gtype -> Air 0.167055
Supp -> O 0.160803
Technique -> Air 0.116967
O -> OD 0.109397
Med -> O 0.103673
O -> Phase 0.083258
Gtype -> Supp 0.074101
OD -> O 0.051003
Phase -> O 0.029928
Strain -> O 0.000886
O -> Anti 0.000637
O -> Gversion 0.000062
Anti -> Air -0.001399
Phase -> Supp -0.014135
Gtype -> Gversion -0.023045
Technique -> Gtype -0.145953
Supp -> Technique -0.164756
Technique -> pH -0.188040
Supp -> Air -0.262229
Gtype -> Technique -0.360196
OD -> Air -0.397656
Air -> Phase -0.403726
Gtype -> Med -0.439722
Gversion -> O -0.476476
Air -> Supp -0.501806
Gtype -> Anti -0.567560
Supp -> Gtype -0.583004
Air -> Temp -0.652068
Technique -> O -0.816523
O -> Air -0.975032
Gtype -> O -1.058292
Supp -> Med -1.159468
Med -> Supp -1.481426
Substrain -> O -1.534528
Top positive:
6.792977 Technique b'lemma[:2]:Ch'
6.185501 O b'lemma:2'
5.372196 O b'lemma:3'
5.171879 O b'-1:lemma:tag'
5.142744 Gtype b'lemma[:1]:\xce\xb4'
4.788508 O b'lemma:1'
4.739414 O b'postag:IN'
4.709882 O b'lemma:-'
4.462687 Technique b'lemma:chipseq'
4.337449 O b'lemma[:2]:re'
4.272091 Supp b'+1:lemma:\xc2\xb5m'
4.219425 O b'lemma:with'
4.162550 O b'+1:lemma:pq'
4.046798 O b'lemma:_'
4.046798 O b'lemma[:1]:_'
4.040972 Gtype b'-1:lemma:\xe2\x88\x86'
4.018468 Phase b'lemma:mid-log'
3.950059 Air b'lemma[:2]:ae'
3.882373 O b'postag::'
3.866328 Supp b'lemma:Iron'
3.866328 Supp b'lemma[:2]:Ir'
3.865451 O b'lemma:b'
3.666419 O b'lemma:a'
3.658095 Substrain b'lemma[:2]:mg'
3.641844 Air b'-1:lemma:ChIP-Seq'
3.630211 Supp b'-1:lemma:Cra'
3.616609 O b'postag:CC'
3.541072 Air b'lemma:anaerobic'
3.460006 Air b'lemma[:2]:an'
3.437202 O b'lemma:rpob'
3.400149 Gtype b'lemma:arca8myc'
3.376119 Strain b'+1:lemma:substr'
3.310669 O b'lemma:.'
3.310669 O b'postag:.'
3.265211 O b'-1:lemma:lb'
3.262791 Supp b'-1:lemma:with'
3.123788 Supp b'-1:lemma:vol'
3.100190 Air b'-1:lemma:-'
3.079730 Supp b'lemma:pq'
3.079730 Supp b'lemma[:2]:pq'
3.061798 Agit b'+1:lemma:rpm'
3.060071 O b'-1:lemma:0.3'
2.985771 Supp b'lemma:arginine'
2.958596 O b'lemma[:1]:h'
2.939765 O b'lemma[:2]:ge'
2.920828 O b'lemma:delta'
2.918295 Phase b'lemma:stationary'
2.910332 Supp b'-1:lemma:+'
2.845649 Technique b'lemma[:2]:ch'
2.823670 Gversion b'lemma:chip-seq'
2.791251 O b'postag:VBN'
2.770882 Anti b'+1:lemma:antibody'
2.759206 Gtype b'lemma:type'
2.759206 Gtype b'lemma[:2]:ty'
2.752479 Temp b'+1:lemma:in'
2.715434 Med b'-1:lemma:ml'
2.707247 Air b'lemma:Aerobic'
2.707247 Air b'lemma[:2]:Ae'
2.706748 Med b'+1:lemma:0.4'
2.704634 O b'-1:lemma:glucose'
2.684854 Phase b'lemma[:2]:ex'
2.662573 Anti b'lemma[:2]:an'
2.630158 Technique b'lemma[:2]:rn'
2.608017 Supp b'lemma:acetate'
2.554332 OD b'lemma[:1]:o'
2.549906 Gtype b'lemma:fnr8myc'
2.524063 O b'-1:lemma:0.3-0.35'
2.521537 O b'-1:lemma:Aerobic'
2.508216 Supp b'lemma:rifampicin'
2.505724 O b'lemma:ompr'
2.499756 Supp b'lemma[:2]:ri'
2.491716 O b'lemma:chip'
2.488425 Supp b'-1:lemma:final'
2.473021 Gtype b'lemma[:2]:cr'
2.448300 Med b'lemma:MOPS'
2.448300 Med b'lemma[:1]:M'
2.448300 Med b'lemma[:2]:MO'
2.444945 Supp b'+1:lemma:1'
2.444634 Gtype b'lemma:wt'
2.444634 Gtype b'lemma[:2]:wt'
2.439447 Gtype b'lemma[:2]:ar'
2.423220 Gtype b'lemma[:2]:pk'
2.411016 Technique b'lemma[:1]:C'
2.409772 O b'postag:DT'
2.401919 Supp b'+1:lemma:mm'
2.397549 Supp b'-1:lemma:sodium'
2.386531 Agit b'lemma:rpm'
2.384742 Med b'lemma:broth'
2.384742 Med b'-1:lemma:L'
2.384742 Med b'lemma[:2]:br'
2.380245 Supp b'lemma[:1]:I'
2.354434 O b'lemma[:1]:C'
2.351237 Technique b'-1:lemma:input'
2.341179 Air b'postag:RB'
2.337517 O b'-1:lemma:into'
2.316952 Gtype b'lemma[:2]:de'
2.308227 Gversion b'lemma:asm584v2'
2.304126 Gtype b'lemma:nsrr'
2.304126 Gtype b'lemma[:2]:ns'
2.302775 Gversion b'lemma[:2]:as'
2.247462 Gtype b'lemma[:1]:W'
2.232742 Supp b'lemma[:2]:ni'
2.228857 Gtype b'-1:lemma:_'
2.228364 Med b'lemma:L'
2.228364 Med b'+1:lemma:broth'
2.215606 Gtype b'+1:lemma:type'
2.215192 Supp b'lemma:fructose'
2.213388 O b'-1:lemma:ChIP-exo'
2.205310 Gversion b'lemma[:2]:00'
2.189511 O b'lemma:Custom'
2.189511 O b'lemma[:2]:Cu'
2.189327 Gversion b'lemma:nc'
2.189327 Gversion b'lemma[:2]:nc'
2.187007 Anti b'lemma:none'
2.170324 O b'+1:lemma:or'
2.165483 Phase b'lemma[:1]:e'
2.157215 Air b'lemma[:1]:a'
2.155510 O b'+1:lemma:acetate'
2.137294 O b'-1:lemma:phase'
2.120304 O b'lemma[:2]:om'
2.109931 Temp b'-1:lemma:43'
2.093355 pH b'+1:postag:CD'
2.087626 O b'lemma[:1]:e'
2.082218 Gtype b'+1:lemma::'
2.080609 O b'+1:lemma:mid-log'
2.064412 O b'-1:lemma:type'
2.055018 Temp b'-1:lemma:sample'
2.048893 Temp b'-1:lemma:\xcf\x8332'
2.048779 O b'+1:lemma:od600'
2.037410 Med b'+1:lemma:2.0'
2.035956 O b'+1:postag:NNP'
2.030314 O b'+1:postag:RB'
2.027123 Gtype b'lemma[:1]:w'
2.011116 O b'-1:lemma:anaerobic'
2.006058 Gtype b'lemma[:1]:f'
1.994696 pH b'lemma[:2]:ph'
1.971101 Supp b'lemma:no3'
1.963975 Technique b'+1:lemma:rna-seq'
1.963032 O b'lemma:purr'
1.954191 O b'lemma:Cra'
1.953081 Gtype b'lemma:flag-tag'
1.953081 Gtype b'-1:lemma:c-terminal'
1.929362 Technique b'+1:lemma:chip-exo'
1.926848 Med b'lemma[:1]:m'
1.913449 Substrain b'lemma[:1]:m'
1.912657 Gtype b'-1:lemma:vector'
1.903374 Gtype b'lemma:\xe2\x88\x86'
1.903374 Gtype b'lemma[:1]:\xe2\x88\x86'
1.901605 O b'lemma[:2]:Cr'
1.900522 Supp b'lemma[:2]:gl'
1.899158 O b'lemma[:1]:s'
1.875620 O b'postag:VBG'
1.860683 O b'lemma:n'
1.859831 Strain b'lemma:k-12'
1.859831 Strain b'lemma[:2]:k-'
1.859641 Supp b'lemma[:2]:ac'
1.834220 Supp b'lemma:nacl'
1.834220 Supp b'lemma[:2]:na'
1.829854 Supp b'+1:lemma:2'
1.820248 Strain b'lemma[:1]:k'
1.810126 Temp b'lemma:43'
1.810126 Temp b'lemma[:2]:43'
1.789121 Gtype b'+1:lemma:with'
1.787780 Gversion b'-1:lemma:nc'
1.784140 Med b'-1:lemma:fresh'
1.776852 Gtype b'-1:postag:VBG'
1.769935 Supp b'lemma:Leu'
1.769935 Supp b'lemma[:2]:Le'
1.761067 Gtype b'symb'
1.756726 O b'-1:lemma:stpa'
1.755310 Phase b'-1:lemma:until'
1.753083 Supp b'-1:postag:CC'
1.751530 Anti b'-1:lemma::'
1.746658 O b'lemma:argr'
1.741299 O b'lemma:\xcf\x8332'
1.741299 O b'lemma[:1]:\xcf\x83'
1.741299 O b'lemma[:2]:\xcf\x833'
1.735808 Supp b'lemma:Fe'
1.735808 Supp b'lemma[:2]:Fe'
1.734847 Anti b'hGreek'
1.731060 Gtype b'-1:lemma:knock-out'
1.724076 O b'-1:lemma:aerobically'
1.721770 O b'lemma:A'
1.714736 O b'lemma:0.4'
1.713906 Gtype b'lemma[:1]:t'
1.706889 Air b'+1:postag:IN'
1.699701 Supp b'lemma:glucose'
1.698973 O b'lemma:chip-arca'
1.681807 O b'+1:lemma:coli'
1.680743 O b'+1:lemma:sparging'
1.679592 O b'-1:postag:NNS'
1.678415 Air b'-1:lemma:co2'
1.676578 O b'lemma[:1]:-'
1.669982 pH b'lemma:ph5'
1.669982 pH b'+1:lemma:.5'
1.659378 Substrain b'+1:lemma:phtpg'
1.658130 Gtype b'-1:lemma:rpob'
1.643206 O b'lemma[:1]:c'
1.637539 Gtype b'lemma[:2]:wi'
1.628222 Supp b'+1:lemma:min'
Top negative:
-0.048858 Air b'lemma:-rrb-'
-0.053617 OD b'-1:lemma:od600'
-0.056105 Supp b'+1:lemma:dpd'
-0.058525 O b'+1:lemma:95'
-0.061956 Supp b'-1:lemma:%'
-0.062560 O b'+1:lemma:cell'
-0.065163 Supp b'lemma:vol'
-0.065163 Supp b'-1:lemma:1/100'
-0.067871 O b'+1:lemma:antibody'
-0.069248 Gtype b'+1:postag:NN'
-0.072048 O b'lemma:2.0'
-0.078220 Supp b'lemma[:2]:vo'
-0.079573 Supp b'-1:postag::'
-0.084349 Supp b'-1:lemma:;'
-0.085848 O b'-1:lemma:-lrb-'
-0.097584 O b'+1:lemma:phosphate'
-0.098013 Supp b'+1:lemma:rifampicin'
-0.104233 Phase b'-1:lemma:at'
-0.109073 O b'lemma:7.6'
-0.109073 O b'+1:lemma:;'
-0.109073 O b'lemma[:2]:7.'
-0.110982 Air b'-1:postag:CC'
-0.115095 O b'+1:lemma:0.3'
-0.124835 Gtype b'lemma[:1]:g'
-0.138288 O b'-1:lemma:g/l'
-0.139335 O b'-1:lemma:control'
-0.140398 O b'lemma:1/100'
-0.140398 O b'+1:lemma:vol'
-0.140398 O b'lemma[:2]:1/'
-0.142417 O b'lemma[:2]:ph'
-0.150417 Supp b'-1:lemma:dpd'
-0.152181 Air b'postag:CC'
-0.156096 Supp b'lemma[:2]:mm'
-0.170571 Supp b'lemma[:1]:v'
-0.176750 Supp b'-1:lemma:.'
-0.176750 Supp b'-1:postag:.'
-0.177644 Air b'+1:postag:JJ'
-0.183264 O b'lemma:ph'
-0.194456 O b'+1:lemma:_'
-0.198008 O b'lemma[:1]:I'
-0.198858 Med b'lemma[:1]:c'
-0.200600 Supp b'postag:CD'
-0.200922 Supp b'lemma[:2]:10'
-0.225778 O b'lemma:sodium'
-0.227988 O b'lemma:150'
-0.227988 O b'+1:lemma:mg/ml'
-0.227988 O b'lemma[:2]:15'
-0.230044 Air b'-1:lemma:grow'
-0.230726 O b'lemma[:1]:L'
-0.242707 OD b'+1:lemma:0.4'
-0.247792 O b'lemma:aerobic'
-0.250676 Gtype b'postag:CD'
-0.251160 O b'lemma:37'
-0.251160 O b'lemma[:2]:37'
-0.252456 Supp b'lemma[:1]:o'
-0.257318 Supp b'lemma:mm'
-0.261677 O b'lemma:minimal'
-0.264264 O b'-1:lemma:phosphate'
-0.265979 O b'lemma:1m'
-0.265979 O b'lemma[:2]:1m'
-0.266597 O b'lemma:media'
-0.267452 O b'lemma[:2]:an'
-0.267991 Supp b'lemma:10'
-0.278125 O b'lemma[:2]:0.'
-0.280995 Supp b'lemma[:1]:a'
-0.282672 Phase b'+1:postag:NN'
-0.283800 O b'-1:lemma:iptg'
-0.286359 O b'+1:lemma:1/100'
-0.296570 O b'-1:postag:IN'
-0.303339 O b'lemma:wt'
-0.303339 O b'lemma[:2]:wt'
-0.304954 O b'-1:lemma:n2'
-0.305002 O b'+1:lemma:for'
-0.313331 O b'+1:lemma:ph'
-0.315827 O b'+1:lemma:rep2'
-0.316914 Supp b'-1:postag:NNP'
-0.317533 O b'+1:lemma:.'
-0.317533 O b'+1:postag:.'
-0.319317 O b'lemma[:2]:od'
-0.321743 Supp b'+1:lemma:fructose'
-0.325179 Gtype b'-1:lemma:-lrb-'
-0.327448 Technique b'-1:lemma::'
-0.332177 O b'+1:lemma:supplement'
-0.340289 O b'lemma:of'
-0.340289 O b'lemma[:2]:of'
-0.346020 pH b'postag:NN'
-0.348702 O b'-1:lemma:1m'
-0.348772 O b'-1:lemma:of'
-0.353402 O b'-1:postag:-LRB-'
-0.353653 Gtype b'lemma[:1]:-'
-0.370016 Air b'+1:postag:-LRB-'
-0.378377 Med b'+1:postag:NN'
-0.386701 O b'lemma:co2'
-0.387052 O b'+1:lemma:-rrb-'
-0.410253 O b'lemma:anaerobically'
-0.410584 O b'-1:lemma:from'
-0.411044 Med b'-1:postag:NN'
-0.423352 Med b'+1:postag:IN'
-0.425947 O b'lemma:glucose'
-0.439413 O b'+1:postag:-RRB-'
-0.439693 O b'+1:postag:IN'
-0.445043 O b'lemma:c'
-0.449206 Air b'-1:postag:JJ'
-0.454193 Med b'symb'
-0.455690 O b'lemma:2h'
-0.455690 O b'-1:lemma:additional'
-0.455690 O b'lemma[:2]:2h'
-0.456326 OD b'hUpper'
-0.456326 OD b'hLower'
-0.457470 O b'-1:lemma:mm'
-0.459860 O b'lemma[:1]:0'
-0.476971 Anti b'+1:lemma:anti-fur'
-0.481570 Air b'-1:lemma:or'
-0.487911 Med b'-1:postag:IN'
-0.497805 O b'-1:lemma:37'
-0.503733 O b'postag:RB'
-0.518906 Gtype b'-1:lemma:mg1655'
-0.521608 O b'lemma[:2]:mg'
-0.539310 Supp b'-1:lemma:-lrb-'
-0.544818 Air b'-1:postag:VBN'
-0.554971 Air b'+1:lemma:-lrb-'
-0.564728 O b'+1:lemma:at'
-0.575151 O b'lemma[:2]:gl'
-0.586132 Temp b'hGreek'
-0.613309 O b'lemma:methanol'
-0.622499 Supp b'lemma[:1]:s'
-0.648351 Supp b'-1:postag:-LRB-'
-0.649606 Air b'symb'
-0.665356 O b'-1:lemma:delta'
-0.666424 Technique b'postag:NN'
-0.679462 O b'lemma[:2]:ar'
-0.680103 Med b'-1:postag:CD'
-0.690689 O b'-1:lemma:\xe2\x88\x86'
-0.694572 Supp b'symb'
-0.699321 Supp b'+1:postag:VBN'
-0.711427 Agit b'symb'
-0.727728 Gtype b'lemma[:1]:c'
-0.728934 O b'lemma:mid-log'
-0.732994 Supp b'postag:JJ'
-0.763056 O b'-1:lemma:final'
-0.787433 Technique b'-1:postag::'
-0.799920 Phase b'postag:JJ'
-0.805670 O b'+1:postag:VBG'
-0.811006 O b'-1:lemma:nsrr'
-0.817629 Gtype b'+1:lemma:-rrb-'
-0.826953 Phase b'hUpper'
-0.826953 Phase b'hLower'
-0.832803 O b'-1:lemma:30'
-0.866445 O b'+1:lemma:2.0'
-0.869353 O b'-1:lemma:dissolve'
-0.869353 O b'+1:lemma:methanol'
-0.879555 Phase b'-1:postag:JJ'
-0.902450 Agit b'hUpper'
-0.902450 Agit b'hLower'
-0.908311 O b'-1:lemma:cra'
-0.913033 O b'-1:lemma:IP'
-0.913247 Temp b'postag:NN'
-0.923496 O b'-1:lemma:co2'
-0.928549 O b'+1:lemma:until'
-0.945079 O b'+1:lemma:1m'
-0.973593 O b'postag:VBP'
-0.977346 O b'-1:lemma:rpob'
-0.993918 O b'+1:lemma:g/l'
-0.995081 O b'-1:lemma:ph'
-1.012606 O b'lemma[:2]:ri'
-1.015626 O b'-1:lemma:until'
-1.019941 Gtype b'lemma[:1]:r'
-1.020871 Anti b'postag:NNP'
-1.021292 Gtype b'lemma[:1]:a'
-1.043259 O b'+1:lemma:+'
-1.064769 O b'-1:lemma:ml'
-1.086182 O b'lemma[:2]:30'
-1.110227 O b'lemma:soxs-8myc'
-1.112350 O b'lemma:rifampicin'
-1.121024 O b'+1:lemma:mm'
-1.200742 O b'lemma:0.3'
-1.229817 O b'lemma[:2]:me'
-1.241013 O b'-1:postag::'
-1.292670 Supp b'hGreek'
-1.298761 O b'-1:lemma:1'
-1.329722 Supp b'+1:lemma:-lrb-'
-1.340009 O b'lemma[:2]:ae'
-1.343861 Supp b'+1:postag:-LRB-'
-1.407876 OD b'+1:postag:NN'
-1.634875 O b'-1:lemma:fresh'
-1.659704 O b'+1:lemma:1'
-1.811326 Supp b'lemma[:1]:c'
-1.853339 O b'-1:lemma:sample'
-1.870273 Air b'postag:NN'
-2.008997 Supp b'+1:lemma:,'
-2.008997 Supp b'+1:postag:,'
-2.030519 O b'+1:lemma:in'
-2.074714 O b'-1:postag:VBG'
-2.120965 Temp b'+1:postag:IN'
-2.153912 O b'+1:lemma:2'
-2.533264 O b'-1:lemma:vol'
-2.654052 O b'-1:lemma:2'
-2.901215 O b'lemma[:2]:fl'
-4.156418 O b'-1:lemma:_'
-4.945535 O b'-1:lemma::'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.11720815886647881, 'c2': 0.026187454028628224}
best CV score:0.8623150078546968
model size: 0.12M
Flat F1: 0.7729583914691408
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 0.955 0.913 0.933 23
Med 1.000 0.925 0.961 53
Temp 1.000 0.690 0.816 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.556 0.362 0.439 69
Anti 0.579 1.000 0.733 11
Strain 0.000 0.000 0.000 1
Gtype 0.877 0.753 0.810 85
Substrain 0.000 0.000 0.000 0
Supp 0.735 0.806 0.769 134
Gversion 0.000 0.000 0.000 0
avg / total 0.811 0.752 0.773 451
Top likely transitions:
Temp -> Temp 5.534350
Anti -> Anti 5.202035
OD -> OD 5.162013
Agit -> Agit 5.101850
Supp -> Supp 4.862669
Med -> Med 4.742631
Gtype -> Gtype 4.690492
Gversion -> Gversion 4.253159
Phase -> Phase 4.193306
O -> O 4.143359
Air -> Air 4.079274
Technique -> Technique 3.737825
pH -> pH 2.701172
Substrain -> Gtype 1.413086
Gtype -> Supp 1.215131
O -> Gtype 1.183861
O -> Technique 1.124196
Gtype -> Air 0.906865
O -> Supp 0.894361
Air -> O 0.782291
Technique -> Air 0.697709
Gtype -> pH 0.616305
Temp -> O 0.413091
Supp -> O 0.344753
O -> Temp 0.252965
O -> Anti 0.243401
Med -> O 0.118001
O -> pH 0.044367
Strain -> O 0.008900
O -> Phase 0.000404
O -> Gversion 0.000174
O -> Agit -0.000001
OD -> O -0.000957
O -> OD -0.000978
Anti -> Med -0.003482
Phase -> O -0.006839
Technique -> O -0.130344
Agit -> O -0.145879
Air -> Supp -0.189667
O -> Med -0.260087
Phase -> Supp -0.337496
Gtype -> Anti -0.357408
Phase -> OD -0.410012
OD -> Air -0.412447
Air -> Temp -0.475634
Gtype -> Med -0.476794
Air -> Phase -0.503738
Gtype -> O -0.571166
Air -> Med -0.589897
O -> Air -0.677813
Top unlikely transitions:
Med -> Med 4.742631
Gtype -> Gtype 4.690492
Gversion -> Gversion 4.253159
Phase -> Phase 4.193306
O -> O 4.143359
Air -> Air 4.079274
Technique -> Technique 3.737825
pH -> pH 2.701172
Substrain -> Gtype 1.413086
Gtype -> Supp 1.215131
O -> Gtype 1.183861
O -> Technique 1.124196
Gtype -> Air 0.906865
O -> Supp 0.894361
Air -> O 0.782291
Technique -> Air 0.697709
Gtype -> pH 0.616305
Temp -> O 0.413091
Supp -> O 0.344753
O -> Temp 0.252965
O -> Anti 0.243401
Med -> O 0.118001
O -> pH 0.044367
Strain -> O 0.008900
O -> Phase 0.000404
O -> Gversion 0.000174
O -> Agit -0.000001
OD -> O -0.000957
O -> OD -0.000978
Anti -> Med -0.003482
Phase -> O -0.006839
Technique -> O -0.130344
Agit -> O -0.145879
Air -> Supp -0.189667
O -> Med -0.260087
Phase -> Supp -0.337496
Gtype -> Anti -0.357408
Phase -> OD -0.410012
OD -> Air -0.412447
Air -> Temp -0.475634
Gtype -> Med -0.476794
Air -> Phase -0.503738
Gtype -> O -0.571166
Air -> Med -0.589897
O -> Air -0.677813
Technique -> pH -0.697146
Supp -> Med -0.874957
Technique -> Gtype -0.966031
Substrain -> O -1.152021
Med -> Supp -1.883468
Top positive:
5.346056 Air b'word:Aerobic'
4.814989 O b'lemma:_'
4.814989 O b'word:_'
4.683626 Air b'lemma:anaerobic'
4.137422 O b'word:Cra'
3.717067 Air b'postag:RB'
3.648734 Technique b'word:ChIP-Seq'
3.591761 O b'postag:IN'
3.527991 Gtype b'lemma:wt'
3.502005 O b'-1:lemma:ChIP-exo'
3.404088 Gtype b'lemma:wild-type'
3.374603 Air b'word:Anaerobic'
3.313814 Technique b'lemma:ChIP-exo'
3.289286 Supp b'lemma:nh4cl'
3.261253 O b'postag::'
3.210614 Supp b'lemma:Iron'
3.210614 Supp b'word:Iron'
3.210614 Supp b'+1:word:Deficient'
3.205283 Technique b'word:ChIP-exo'
3.177621 Supp b'lemma:pq'
3.177621 Supp b'word:PQ'
3.149226 Technique b'word:ChIPSeq'
3.063798 O b'lemma:2'
3.063798 O b'word:2'
3.039767 Supp b'-1:word:Cra'
2.926997 Strain b'+1:lemma:substr'
2.926997 Strain b'+1:word:substr'
2.924815 Gtype b'lemma:type'
2.924815 Gtype b'word:type'
2.895571 Med b'lemma:MOPS'
2.895571 Med b'word:MOPS'
2.886364 Phase b'lemma:mid-log'
2.886364 Phase b'word:mid-log'
2.877854 O b'lemma:-'
2.877854 O b'word:-'
2.870915 Technique b'lemma:rna-seq'
2.819786 Gtype b'word:WT'
2.808619 O b'lemma:rpob'
2.808619 O b'word:RpoB'
2.775553 O b'lemma:1'
2.775553 O b'word:1'
2.716320 Gversion b'lemma:asm584v2'
2.716320 Gversion b'word:ASM584v2'
2.606208 O b'-1:lemma:tag'
2.586384 O b'lemma:Custom'
2.586384 O b'word:Custom'
2.582328 O b'lemma:.'
2.582328 O b'postag:.'
2.582328 O b'word:.'
2.554026 Gtype b'lemma:\xce\xb4cra'
2.550784 Gtype b'word:\xce\x94cra'
2.548130 O b'lemma:chip'
2.540102 Phase b'lemma:exponential'
2.540102 Phase b'word:exponential'
2.540102 Phase b'lemma:stationary'
2.540102 Phase b'word:stationary'
2.534852 O b'lemma:3'
2.534852 O b'word:3'
2.483583 Supp b'+1:lemma:\xc2\xb5m'
2.483583 Supp b'+1:word:\xc2\xb5M'
2.428266 Gtype b'+1:lemma:type'
2.428266 Gtype b'+1:word:type'
2.423833 Technique b'lemma:chipseq'
2.335552 Supp b'lemma:glucose'
2.335552 Supp b'word:glucose'
2.303572 O b'lemma:b'
2.303572 O b'word:B'
2.275983 Supp b'lemma:arginine'
2.258897 O b'postag:CC'
2.258702 Supp b'lemma:nacl'
2.258702 Supp b'word:NaCl'
2.248340 O b'lemma:a'
2.240067 O b'-1:word:tag'
2.219665 O b'+1:lemma:pq'
2.219665 O b'+1:word:PQ'
2.201128 O b'lemma:ompr'
2.201128 O b'word:OmpR'
2.196031 Supp b'lemma:rifampicin'
2.196031 Supp b'word:rifampicin'
2.166584 Substrain b'lemma:mg1655'
2.166584 Substrain b'word:MG1655'
2.150321 Gtype b'lemma:flag-tag'
2.150321 Gtype b'-1:lemma:c-terminal'
2.150321 Gtype b'word:Flag-tag'
2.150321 Gtype b'-1:word:C-terminal'
2.144846 Gtype b'-1:postag:VBG'
2.133181 pH b'+1:postag:CD'
2.127721 O b'word:A'
2.115852 O b'-1:word:Aerobic'
2.096172 Gtype b'lemma:delta-fnr'
2.096172 Gtype b'word:delta-fnr'
2.095669 Gversion b'lemma:nc'
2.095669 Gversion b'word:NC'
2.056559 Technique b'lemma:rnaseq'
2.056559 Technique b'word:RNASeq'
2.056377 Air b'word:anaerobic'
2.035701 O b'+1:postag:RB'
2.004258 Supp b'lemma:acetate'
2.004258 Supp b'word:acetate'
1.965988 O b'+1:postag:NNP'
1.964752 Gtype b'-1:lemma:\xe2\x88\x86'
1.964752 Gtype b'-1:word:\xe2\x88\x86'
1.910185 Gtype b'lemma:\xe2\x88\x86'
1.910185 Gtype b'word:\xe2\x88\x86'
1.904605 Strain b'lemma:k-12'
1.904605 Strain b'word:K-12'
1.891315 Gtype b'postag:-LRB-'
1.887141 Air b'-1:lemma:ChIP-Seq'
1.887141 Air b'-1:word:ChIP-Seq'
1.880957 Agit b'+1:lemma:rpm'
1.880957 Agit b'+1:word:rpm'
1.877174 O b'postag:VBN'
1.877047 Supp b'-1:lemma:with'
1.877047 Supp b'-1:word:with'
1.865462 Gversion b'-1:lemma:nc'
1.865462 Gversion b'-1:word:NC'
1.861443 Gtype b'lemma:arca8myc'
1.861443 Gtype b'word:ArcA8myc'
1.839749 O b'+1:word:were'
1.838491 O b'+1:word:ChIP-Seq'
1.824231 O b'lemma:rep1'
1.824231 O b'word:rep1'
1.824111 Supp b'lemma:nitrate'
1.824111 Supp b'word:nitrate'
1.816106 O b'-1:lemma:lb'
1.816106 O b'-1:word:LB'
1.809240 Technique b'-1:lemma:chip-exo'
1.802237 Gtype b'word:cra'
1.797362 Agit b'lemma:rpm'
1.797362 Agit b'word:rpm'
1.796466 Anti b'lemma:seqa'
1.796466 Anti b'word:SeqA'
1.788369 Supp b'-1:lemma:Cra'
1.787306 O b'lemma:rep3'
1.787306 O b'word:rep3'
1.759779 O b'isLower'
1.740278 O b'lemma:Cra'
1.724562 O b'lemma:with'
1.724562 O b'word:with'
1.722881 Med b'+1:lemma:0.4'
1.722881 Med b'+1:word:0.4'
1.704798 O b'lemma:at'
1.698923 Gversion b'lemma:chip-seq'
1.683530 Gtype b'lemma:pk4854'
1.683530 Gtype b'word:PK4854'
1.671411 Air b'lemma:aerobic'
1.666004 Vess b'lemma:flask'
1.666004 Vess b'-1:lemma:warm'
1.666004 Vess b'word:flask'
1.666004 Vess b'-1:word:warmed'
1.665360 Gtype b'postag:NN'
1.664894 Supp b'lemma:no3'
1.664894 Supp b'word:NO3'
1.657234 Anti b'lemma:none'
1.657234 Anti b'word:none'
1.654372 O b'lemma:culture'
1.643899 Supp b'-1:lemma:+'
1.643899 Supp b'-1:word:+'
1.641571 Air b'-1:postag::'
1.637039 Supp b'-1:lemma:vol'
1.637039 Supp b'-1:word:vol'
1.618213 Supp b'lemma:dpd'
1.618213 Supp b'word:DPD'
1.611503 O b'-1:lemma:glucose'
1.611503 O b'-1:word:glucose'
1.609875 Anti b'lemma:\xcf\x8332'
1.609875 Anti b'word:\xcf\x8332'
1.607928 Gtype b'lemma:\xce\xb4soxr'
1.607928 Gtype b'word:\xce\x94soxR'
1.605256 Med b'-1:lemma:ml'
1.605256 Med b'-1:word:ml'
1.602162 Technique b'word:RNA-Seq'
1.589352 Air b'lemma:Aerobic'
1.584726 Gversion b'word:ChIP-Seq'
1.580172 Air b'lemma:anaeroibc'
1.580172 Air b'word:Anaeroibc'
1.571537 O b'lemma:\xcf\x8332'
1.571537 O b'word:\xcf\x8332'
1.571064 Supp b'lemma:Leu'
1.571064 Supp b'word:Leu'
1.570481 Gtype b'lemma:\xce\xb4fur'
1.570481 Gtype b'word:\xce\x94fur'
1.563108 O b'-1:lemma:0.3'
1.563108 O b'-1:word:0.3'
1.559415 Vess b'-1:postag:VBN'
1.558118 O b'lemma::'
1.558118 O b'word::'
1.538469 Med b'lemma:broth'
1.538469 Med b'-1:lemma:L'
1.538469 Med b'word:broth'
1.538469 Med b'-1:word:L'
1.521808 Gtype b'+1:lemma:with'
1.521808 Gtype b'+1:word:with'
1.520140 Air b'lemma:anaerobically'
1.520140 Air b'word:anaerobically'
1.513230 Supp b'lemma:Fe'
1.513230 Supp b'word:Fe'
1.508184 O b'-1:lemma:wt'
1.482348 Gtype b'word:Wild-type'
1.478153 O b'lemma:harbor'
Top negative:
-0.165864 O b'word:glucose'
-0.166177 Supp b'lemma:10'
-0.166177 Supp b'word:10'
-0.167098 Air b'isLower'
-0.167761 O b'-1:word:from'
-0.171430 O b'-1:lemma:delta'
-0.171430 O b'-1:word:delta'
-0.173899 O b'+1:word:was'
-0.175064 O b'-1:lemma:final'
-0.175064 O b'-1:word:final'
-0.175415 O b'+1:lemma:for'
-0.175588 O b'-1:lemma:sodium'
-0.175588 O b'-1:word:Sodium'
-0.176424 O b'-1:lemma:m'
-0.176424 O b'-1:word:M'
-0.177631 O b'-1:postag:DT'
-0.184729 Supp b'+1:lemma:rifampicin'
-0.184729 Supp b'+1:word:rifampicin'
-0.185903 O b'lemma:fructose'
-0.185903 O b'word:fructose'
-0.186123 Air b'-1:postag:VBN'
-0.189612 O b'word:cells'
-0.196713 O b'-1:lemma:1m'
-0.196713 O b'-1:word:1M'
-0.207755 O b'-1:lemma:cra'
-0.208558 O b'+1:word:C'
-0.208657 Med b'+1:postag:NN'
-0.233153 O b'word:ChIP-exo'
-0.245194 Supp b'+1:lemma:dpd'
-0.245194 Supp b'+1:word:DPD'
-0.252316 O b'-1:word:the'
-0.254853 O b'+1:lemma:.'
-0.254853 O b'+1:postag:.'
-0.254853 O b'+1:word:.'
-0.256451 O b'+1:lemma:until'
-0.256451 O b'+1:word:until'
-0.258020 O b'-1:postag:JJ'
-0.259972 O b'lemma:20'
-0.259972 O b'word:20'
-0.260590 Med b'+1:postag:IN'
-0.262788 O b'-1:lemma:the'
-0.270489 Phase b'+1:postag:NN'
-0.272030 Gtype b'+1:postag:CD'
-0.288673 pH b'postag:NN'
-0.294614 O b'+1:lemma:supplement'
-0.294614 O b'+1:word:supplemented'
-0.295450 Technique b'-1:postag::'
-0.298173 OD b'isNumber'
-0.300823 O b'+1:postag:-LRB-'
-0.316781 O b'lemma:minimal'
-0.316781 O b'word:minimal'
-0.331660 O b'-1:postag:-LRB-'
-0.339761 O b'-1:lemma:mm'
-0.339761 O b'-1:word:mM'
-0.342651 O b'-1:lemma:n2'
-0.342651 O b'-1:word:N2'
-0.348976 O b'-1:lemma:37'
-0.348976 O b'-1:word:37'
-0.350719 pH b'isUpper'
-0.355836 O b'lemma:medium'
-0.355836 O b'word:medium'
-0.358797 O b'-1:lemma:co2'
-0.358797 O b'-1:word:CO2'
-0.360206 O b'lemma:37'
-0.360206 O b'word:37'
-0.363212 Anti b'isUpper'
-0.363229 O b'lemma:aerobically'
-0.363229 O b'word:aerobically'
-0.387107 O b'-1:lemma:ph'
-0.387107 O b'-1:word:pH'
-0.388937 Air b'-1:postag:CC'
-0.403999 Supp b'+1:lemma:acetate'
-0.403999 Supp b'+1:word:acetate'
-0.405755 O b'+1:postag:IN'
-0.405984 Supp b'-1:lemma:-lrb-'
-0.405984 Supp b'-1:word:-LRB-'
-0.407871 O b'lemma:\xce\xb4fur'
-0.407871 O b'word:\xce\x94fur'
-0.410756 O b'lemma:mid-log'
-0.410756 O b'word:mid-log'
-0.413451 Gtype b'+1:lemma:-lrb-'
-0.413451 Gtype b'+1:word:-LRB-'
-0.415001 O b'lemma:nitrate'
-0.415001 O b'word:nitrate'
-0.418409 Gtype b'-1:postag:CD'
-0.421257 Supp b'+1:lemma:fructose'
-0.421257 Supp b'+1:word:fructose'
-0.422476 O b'+1:postag:-RRB-'
-0.439758 Supp b'+1:lemma:nacl'
-0.439758 Supp b'+1:word:NaCl'
-0.439850 Supp b'-1:postag:-LRB-'
-0.441680 O b'+1:lemma:2.0'
-0.441680 O b'+1:word:2.0'
-0.451586 O b'-1:lemma:until'
-0.451586 O b'-1:word:until'
-0.452607 Air b'-1:lemma:or'
-0.452607 Air b'-1:word:or'
-0.458248 Med b'-1:postag:NN'
-0.459831 O b'+1:lemma:+'
-0.459831 O b'+1:word:+'
-0.460799 O b'-1:lemma:dissolve'
-0.460799 O b'+1:lemma:methanol'
-0.460799 O b'-1:word:dissolved'
-0.460799 O b'+1:word:methanol'
-0.475659 O b'-1:lemma:rpob'
-0.475659 O b'-1:word:RpoB'
-0.489439 O b'-1:lemma:chip-exo'
-0.516959 O b'lemma:methanol'
-0.516959 O b'word:methanol'
-0.519060 O b'lemma:0.3'
-0.519060 O b'word:0.3'
-0.521823 O b'-1:lemma:\xe2\x88\x86'
-0.521823 O b'-1:word:\xe2\x88\x86'
-0.532528 Supp b'postag:CC'
-0.555308 O b'+1:lemma:at'
-0.555308 O b'+1:word:at'
-0.568935 O b'+1:word:ChIP-exo'
-0.587243 pH b'isLower'
-0.598998 O b'lemma:anaerobically'
-0.598998 O b'word:anaerobically'
-0.601761 O b'lemma:30'
-0.601761 O b'word:30'
-0.604543 Phase b'isUpper'
-0.609562 O b'+1:lemma:1m'
-0.609562 O b'+1:word:1M'
-0.624149 O b'+1:lemma:g/l'
-0.624149 O b'+1:word:g/L'
-0.632418 O b'-1:lemma:30'
-0.632418 O b'-1:word:30'
-0.633125 O b'lemma:2h'
-0.633125 O b'-1:lemma:additional'
-0.633125 O b'word:2h'
-0.633125 O b'-1:word:additional'
-0.634616 O b'+1:lemma:mm'
-0.634616 O b'+1:word:mM'
-0.640250 Air b'+1:postag:JJ'
-0.653940 O b'lemma:of'
-0.653940 O b'word:of'
-0.659372 O b'-1:postag:IN'
-0.692700 O b'-1:lemma:nsrr'
-0.692700 O b'-1:word:NsrR'
-0.702058 O b'lemma:wt'
-0.715997 Supp b'-1:postag:NNP'
-0.732594 O b'-1:lemma:ml'
-0.732594 O b'-1:word:ml'
-0.739666 Supp b'+1:postag:VBN'
-0.740410 O b'lemma:nitrogen'
-0.740410 O b'word:nitrogen'
-0.774393 O b'-1:lemma:1'
-0.774393 O b'-1:word:1'
-0.775963 Med b'-1:postag:IN'
-0.800588 O b'-1:lemma:2'
-0.800588 O b'-1:word:2'
-0.803460 O b'lemma:media'
-0.803460 O b'word:media'
-0.804540 O b'-1:postag::'
-0.811529 O b'-1:lemma:IP'
-0.811529 O b'-1:word:IP'
-0.838460 Air b'postag:NN'
-0.839107 O b'postag:RB'
-0.861540 O b'-1:lemma:fresh'
-0.861540 O b'-1:word:fresh'
-0.888556 O b'+1:lemma:1'
-0.888556 O b'+1:word:1'
-0.893910 Temp b'postag:NN'
-0.912818 O b'-1:lemma:sample'
-0.918416 O b'+1:postag:VBG'
-0.932692 Gtype b'isUpper'
-0.946508 Agit b'isUpper'
-0.991033 Gtype b'isLower'
-1.014529 O b'+1:lemma:in'
-1.014529 O b'+1:word:in'
-1.018421 Technique b'isNumber'
-1.123268 O b'lemma:rifampicin'
-1.123268 O b'word:rifampicin'
-1.152939 Technique b'isLower'
-1.187285 Supp b'+1:lemma:-lrb-'
-1.187285 Supp b'+1:word:-LRB-'
-1.223419 Supp b'+1:postag:-LRB-'
-1.268612 O b'postag:VBP'
-1.279408 O b'+1:lemma:2'
-1.279408 O b'+1:word:2'
-1.359325 Gtype b'isNumber'
-1.384781 Supp b'+1:lemma:,'
-1.384781 Supp b'+1:postag:,'
-1.384781 Supp b'+1:word:,'
-1.428559 O b'-1:lemma:vol'
-1.428559 O b'-1:word:vol'
-1.432202 Gversion b'isLower'
-1.530158 Supp b'postag:JJ'
-1.621285 OD b'+1:postag:NN'
-1.631452 Phase b'postag:JJ'
-1.756839 Temp b'+1:postag:IN'
-1.806660 Anti b'postag:NNP'
-1.859199 Phase b'-1:postag:JJ'
-1.984210 O b'-1:lemma:_'
-1.984210 O b'-1:word:_'
-2.026219 O b'-1:postag:VBG'
-2.285116 O b'-1:lemma::'
-2.285116 O b'-1:word::'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.025397838188738985, 'c2': 0.010943674737961755}
best CV score:0.866151069813274
model size: 0.15M
Flat F1: 0.7919663066130411
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 0.955 0.913 0.933 23
Med 1.000 0.925 0.961 53
Temp 1.000 0.724 0.840 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.556 0.362 0.439 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.886 0.824 0.854 85
Substrain 0.000 0.000 0.000 0
Supp 0.745 0.806 0.774 134
Gversion 0.000 0.000 0.000 0
avg / total 0.826 0.769 0.792 451
Top likely transitions:
Temp -> Temp 5.760887
Med -> Med 5.678477
Anti -> Anti 5.326115
Agit -> Agit 5.286360
Supp -> Supp 5.206097
Gtype -> Gtype 5.054366
OD -> OD 4.762019
O -> O 4.584226
Gversion -> Gversion 4.568451
Phase -> Phase 4.187286
Technique -> Technique 4.138629
Air -> Air 4.000035
pH -> pH 2.729965
Substrain -> Gtype 1.627917
O -> Technique 1.124864
O -> Gtype 0.872372
Technique -> Air 0.731367
Gtype -> Supp 0.637844
Gtype -> Air 0.628544
Gtype -> pH 0.590887
Temp -> O 0.369557
Air -> O 0.111207
O -> Temp 0.069854
Strain -> O 0.060323
O -> pH 0.012969
O -> Gversion 0.008119
O -> Anti 0.005882
O -> Strain -0.000031
O -> Substrain -0.000043
Supp -> Gversion -0.000207
Vess -> O -0.012750
Phase -> Anti -0.021251
Supp -> OD -0.026454
Gtype -> OD -0.036196
O -> Phase -0.036759
pH -> O -0.045025
Phase -> Air -0.050032
Phase -> Technique -0.056805
Gtype -> Technique -0.057557
Supp -> Phase -0.061193
Med -> O -0.061484
O -> Supp -0.071678
Agit -> O -0.081937
Anti -> Gtype -0.086639
Anti -> Phase -0.088763
OD -> Med -0.098634
Supp -> pH -0.101552
Supp -> O -0.105915
Gtype -> Phase -0.115027
pH -> Supp -0.117891
Top unlikely transitions:
O -> Supp -0.071678
Agit -> O -0.081937
Anti -> Gtype -0.086639
Anti -> Phase -0.088763
OD -> Med -0.098634
Supp -> pH -0.101552
Supp -> O -0.105915
Gtype -> Phase -0.115027
pH -> Supp -0.117891
Gtype -> Gversion -0.121895
Anti -> O -0.201256
Technique -> Supp -0.229809
Gversion -> O -0.230521
Med -> Air -0.267137
O -> Agit -0.281266
Gversion -> Supp -0.287197
Supp -> Gtype -0.291702
Anti -> Supp -0.353269
Technique -> OD -0.362376
Technique -> O -0.381273
Supp -> Anti -0.420491
Anti -> Temp -0.442117
Air -> OD -0.473267
Temp -> Air -0.506469
O -> OD -0.516111
Air -> Agit -0.518285
OD -> Supp -0.549851
OD -> O -0.692796
Gtype -> O -0.708611
Supp -> Air -0.710521
Gtype -> Anti -0.742633
Gtype -> Med -0.747450
Phase -> Med -0.781570
OD -> Air -0.812786
O -> Med -0.889466
Agit -> Air -0.930785
Phase -> OD -0.941459
Technique -> pH -1.069982
Phase -> Supp -1.109907
Air -> Med -1.179927
Air -> Phase -1.299860
Substrain -> O -1.308161
Temp -> Med -1.308517
Phase -> O -1.327800
Air -> Temp -1.331056
Air -> Supp -1.346362
O -> Air -1.390028
Technique -> Gtype -1.424338
Supp -> Med -1.619256
Med -> Supp -2.800528
Top positive:
5.583316 Air b'word:Aerobic'
5.568452 O b'lemma:_'
5.568452 O b'word:_'
5.408845 O b'word:Cra'
4.999592 Air b'lemma:anaerobic'
4.519603 Supp b'-1:word:Cra'
4.085441 Technique b'word:ChIP-Seq'
4.045495 Gtype b'lemma:wt'
4.028624 Phase b'lemma:exponential'
4.028624 Phase b'word:exponential'
4.028624 Phase b'lemma:stationary'
4.028624 Phase b'word:stationary'
3.845256 Gtype b'lemma:wild-type'
3.774295 Supp b'lemma:Iron'
3.774295 Supp b'word:Iron'
3.774295 Supp b'+1:word:Deficient'
3.734294 O b'lemma:-'
3.734294 O b'word:-'
3.706486 Supp b'lemma:nh4cl'
3.556725 O b'+1:postag:RB'
3.535557 Phase b'lemma:mid-log'
3.535557 Phase b'word:mid-log'
3.518403 Air b'word:Anaerobic'
3.506387 Air b'postag:RB'
3.497482 O b'-1:lemma:ChIP-exo'
3.467179 Med b'lemma:MOPS'
3.467179 Med b'word:MOPS'
3.455080 Gtype b'word:WT'
3.454991 Technique b'lemma:ChIP-exo'
3.420923 Gtype b'lemma:\xce\xb4cra'
3.417588 Gtype b'word:\xce\x94cra'
3.314327 Supp b'lemma:pq'
3.314327 Supp b'word:PQ'
3.305655 Technique b'word:ChIPSeq'
3.233996 O b'lemma:rpob'
3.233996 O b'word:RpoB'
3.230643 O b'-1:word:tag'
3.215437 Technique b'word:ChIP-exo'
3.209263 Gversion b'lemma:asm584v2'
3.209263 Gversion b'word:ASM584v2'
3.172641 O b'lemma:at'
3.144467 O b'lemma:Custom'
3.144467 O b'word:Custom'
3.098885 Technique b'lemma:rna-seq'
3.054449 O b'lemma:2'
3.054449 O b'word:2'
3.034553 Supp b'+1:lemma:\xc2\xb5m'
3.034553 Supp b'+1:word:\xc2\xb5M'
3.000931 O b'-1:lemma:tag'
2.989138 O b'lemma:.'
2.989138 O b'postag:.'
2.989138 O b'word:.'
2.981955 Strain b'+1:lemma:substr'
2.981955 Strain b'+1:word:substr'
2.977816 Technique b'lemma:chipseq'
2.916006 O b'lemma:1'
2.916006 O b'word:1'
2.871451 Supp b'postag:VBP'
2.856639 Gtype b'lemma:delta-fnr'
2.856639 Gtype b'word:delta-fnr'
2.843912 O b'lemma:ompr'
2.843912 O b'word:OmpR'
2.751390 Supp b'lemma:nacl'
2.751390 Supp b'word:NaCl'
2.716201 O b'+1:lemma:pq'
2.716201 O b'+1:word:PQ'
2.704016 O b'postag:CC'
2.702834 O b'lemma:a'
2.688516 O b'lemma:b'
2.688516 O b'word:B'
2.677526 Gtype b'lemma:flag-tag'
2.677526 Gtype b'-1:lemma:c-terminal'
2.677526 Gtype b'word:Flag-tag'
2.677526 Gtype b'-1:word:C-terminal'
2.654486 O b'lemma:with'
2.654486 O b'word:with'
2.651693 O b'postag:IN'
2.649950 Gtype b'lemma:type'
2.649950 Gtype b'word:type'
2.636720 O b'lemma:3'
2.636720 O b'word:3'
2.631937 O b'-1:lemma:lb'
2.631937 O b'-1:word:LB'
2.618290 Supp b'lemma:glucose'
2.618290 Supp b'word:glucose'
2.608453 O b'-1:word:Aerobic'
2.600667 Supp b'lemma:arginine'
2.585328 O b'lemma:chip'
2.578251 Supp b'lemma:rifampicin'
2.578251 Supp b'word:rifampicin'
2.573636 Supp b'+1:lemma:Deficient'
2.514589 O b'postag::'
2.492658 O b'lemma:Cra'
2.487492 Substrain b'lemma:mg1655'
2.487492 Substrain b'word:MG1655'
2.478149 Air b'word:anaerobic'
2.456656 Gversion b'-1:lemma:nc'
2.456656 Gversion b'-1:word:NC'
2.452611 Anti b'lemma:seqa'
2.452611 Anti b'word:SeqA'
2.445869 O b'postag:VBN'
2.441392 O b'word:A'
2.434041 O b'+1:postag:NNP'
2.430022 O b'-1:lemma:0.3'
2.430022 O b'-1:word:0.3'
2.411145 Air b'lemma:Aerobic'
2.390202 Supp b'lemma:Leu'
2.390202 Supp b'word:Leu'
2.387116 Gtype b'lemma:arca8myc'
2.387116 Gtype b'word:ArcA8myc'
2.375840 Technique b'word:RNA-Seq'
2.359444 O b'-1:lemma:glucose'
2.359444 O b'-1:word:glucose'
2.351625 Strain b'lemma:k-12'
2.351625 Strain b'word:K-12'
2.318240 Supp b'-1:lemma:Cra'
2.291182 Gversion b'lemma:chip-seq'
2.291116 Anti b'lemma:none'
2.291116 Anti b'word:none'
2.290566 Gversion b'lemma:nc'
2.290566 Gversion b'word:NC'
2.284268 O b'+1:lemma:or'
2.284268 O b'+1:word:or'
2.283438 O b'lemma::'
2.283438 O b'word::'
2.263553 Supp b'lemma:acetate'
2.263553 Supp b'word:acetate'
2.260492 O b'-1:lemma:0.3-0.35'
2.260492 O b'-1:word:0.3-0.35'
2.253939 Gversion b'word:ChIP-Seq'
2.250232 Technique b'lemma:rnaseq'
2.250232 Technique b'word:RNASeq'
2.232794 O b'+1:word:ChIP-Seq'
2.229103 Med b'-1:lemma:ml'
2.229103 Med b'-1:word:ml'
2.227590 O b'lemma:culture'
2.224596 Gtype b'+1:lemma:type'
2.224596 Gtype b'+1:word:type'
2.200566 O b'lemma:rep3'
2.200566 O b'word:rep3'
2.182661 Anti b'lemma:\xcf\x8332'
2.182661 Anti b'word:\xcf\x8332'
2.181231 Air b'lemma:anaeroibc'
2.181231 Air b'word:Anaeroibc'
2.181006 Gtype b'lemma:wildtype'
2.179557 Supp b'lemma:no3'
2.179557 Supp b'word:NO3'
2.168687 O b'+1:word:were'
2.168597 O b'lemma:rep1'
2.168597 O b'word:rep1'
2.167529 Air b'lemma:aerobically'
2.167529 Air b'word:aerobically'
2.141925 Supp b'-1:lemma:+'
2.141925 Supp b'-1:word:+'
2.141556 Air b'-1:lemma:ChIP-Seq'
2.141556 Air b'-1:word:ChIP-Seq'
2.136723 Temp b'+1:lemma:in'
2.136723 Temp b'+1:word:in'
2.120975 Vess b'lemma:flask'
2.120975 Vess b'-1:lemma:warm'
2.120975 Vess b'word:flask'
2.120975 Vess b'-1:word:warmed'
2.115337 Gtype b'-1:lemma:\xe2\x88\x86'
2.115337 Gtype b'-1:word:\xe2\x88\x86'
2.111591 Gtype b'lemma:\xce\xb4soxr'
2.111591 Gtype b'word:\xce\x94soxR'
2.087111 Technique b'-1:lemma:chip-exo'
2.073917 Gtype b'word:cra'
2.071081 Agit b'+1:lemma:rpm'
2.071081 Agit b'+1:word:rpm'
2.070334 Agit b'lemma:rpm'
2.070334 Agit b'word:rpm'
2.067325 Gtype b'lemma:dfnr'
2.067325 Gtype b'word:dFNR'
2.061229 Air b'lemma:anaerobically'
2.061229 Air b'word:anaerobically'
2.054028 Supp b'-1:lemma:with'
2.054028 Supp b'-1:word:with'
2.046181 O b'postag:VBG'
2.032013 Supp b'lemma:Fe'
2.032013 Supp b'word:Fe'
2.030145 pH b'+1:postag:CD'
2.022741 Med b'-1:lemma:fresh'
2.022741 Med b'-1:word:fresh'
2.019221 Gtype b'+1:lemma:with'
2.019221 Gtype b'+1:word:with'
2.012561 Air b'lemma:aerobic'
2.012064 Gtype b'-1:postag:VBG'
2.011339 Med b'+1:lemma:0.4'
2.011339 Med b'+1:word:0.4'
2.009320 Supp b'lemma:Adenine'
2.009320 Supp b'word:Adenine'
2.007291 Air b'-1:postag::'
1.983786 Anti b'+1:postag:VBN'
1.983224 O b'-1:lemma:into'
1.983224 O b'-1:word:into'
1.964035 O b'lemma:rep2'
1.964035 O b'word:rep2'
1.959783 Gtype b'lemma:pk4854'
1.959783 Gtype b'word:PK4854'
Top negative:
-0.303383 Temp b'isLower'
-0.309535 Air b'-1:postag:JJ'
-0.310017 Supp b'postag:-LRB-'
-0.317396 O b'+1:lemma:_'
-0.317396 O b'+1:word:_'
-0.325240 Technique b'-1:postag::'
-0.330686 O b'lemma:20'
-0.330686 O b'word:20'
-0.332939 Gtype b'-1:postag:CD'
-0.338184 O b'+1:lemma:minimal'
-0.338184 O b'+1:word:minimal'
-0.344465 Gtype b'+1:lemma:-lrb-'
-0.344465 Gtype b'+1:word:-LRB-'
-0.348653 O b'+1:postag:IN'
-0.349230 Strain b'isLower'
-0.358539 O b'-1:lemma:n2'
-0.358539 O b'-1:word:N2'
-0.360467 O b'-1:lemma:ph'
-0.360467 O b'-1:word:pH'
-0.372464 O b'lemma:anaerobic'
-0.376573 O b'-1:lemma:with'
-0.376573 O b'-1:word:with'
-0.386822 O b'-1:lemma:delta'
-0.386822 O b'-1:word:delta'
-0.388023 pH b'isNumber'
-0.388961 O b'-1:postag:IN'
-0.389061 O b'-1:lemma:mm'
-0.389061 O b'-1:word:mM'
-0.402376 O b'+1:lemma:rep2'
-0.402376 O b'+1:word:rep2'
-0.428619 Supp b'+1:lemma:rifampicin'
-0.428619 Supp b'+1:word:rifampicin'
-0.428641 O b'lemma:k-12'
-0.428641 O b'word:K-12'
-0.437232 O b'-1:lemma:co2'
-0.437232 O b'-1:word:CO2'
-0.452931 O b'lemma:glucose'
-0.452931 O b'word:glucose'
-0.457255 O b'lemma:aerobically'
-0.457255 O b'word:aerobically'
-0.457512 O b'+1:lemma:for'
-0.459154 Anti b'+1:lemma:anti-fur'
-0.459154 Anti b'+1:word:anti-Fur'
-0.468795 O b'-1:lemma:dissolve'
-0.468795 O b'+1:lemma:methanol'
-0.468795 O b'-1:word:dissolved'
-0.468795 O b'+1:word:methanol'
-0.471109 Supp b'lemma:and'
-0.471109 Supp b'word:and'
-0.472339 O b'lemma:aerobic'
-0.475261 O b'lemma:0.3'
-0.475261 O b'word:0.3'
-0.483590 Air b'postag:CD'
-0.483923 O b'+1:postag:-RRB-'
-0.497463 Med b'-1:postag:NN'
-0.499049 Supp b'-1:lemma:-lrb-'
-0.499049 Supp b'-1:word:-LRB-'
-0.501219 O b'+1:lemma:1m'
-0.501219 O b'+1:word:1M'
-0.502085 Supp b'+1:postag::'
-0.515749 Supp b'+1:postag:VBN'
-0.519934 O b'+1:lemma:supplement'
-0.519934 O b'+1:word:supplemented'
-0.531150 O b'+1:lemma:until'
-0.531150 O b'+1:word:until'
-0.531590 O b'lemma:methanol'
-0.531590 O b'word:methanol'
-0.534769 O b'lemma:medium'
-0.534769 O b'word:medium'
-0.537022 O b'lemma:fructose'
-0.537022 O b'word:fructose'
-0.537520 O b'lemma:of'
-0.537520 O b'word:of'
-0.537621 O b'+1:lemma:2.0'
-0.537621 O b'+1:word:2.0'
-0.541851 O b'+1:lemma:g/l'
-0.541851 O b'+1:word:g/L'
-0.542060 Supp b'-1:postag:-LRB-'
-0.549971 Med b'lemma:-lrb-'
-0.549971 Med b'word:-LRB-'
-0.564385 O b'word:cells'
-0.577014 Anti b'isUpper'
-0.580839 O b'-1:postag:JJ'
-0.595778 Med b'+1:postag:IN'
-0.613291 Med b'postag:CD'
-0.630342 O b'+1:word:C'
-0.633021 O b'lemma:purify'
-0.636573 Supp b'+1:lemma:acetate'
-0.636573 Supp b'+1:word:acetate'
-0.639384 O b'-1:lemma:2'
-0.639384 O b'-1:word:2'
-0.641103 O b'lemma:37'
-0.641103 O b'word:37'
-0.657693 O b'lemma:mid-log'
-0.657693 O b'word:mid-log'
-0.669108 O b'-1:lemma:chip-exo'
-0.676699 O b'-1:lemma:rpob'
-0.676699 O b'-1:word:RpoB'
-0.683926 Supp b'+1:lemma:fructose'
-0.683926 Supp b'+1:word:fructose'
-0.696629 O b'lemma:\xce\xb4fur'
-0.696629 O b'word:\xce\x94fur'
-0.716858 Med b'postag:-LRB-'
-0.717563 O b'-1:lemma:37'
-0.717563 O b'-1:word:37'
-0.742255 pH b'isUpper'
-0.751253 Air b'postag:NN'
-0.760807 O b'-1:lemma:\xe2\x88\x86'
-0.760807 O b'-1:word:\xe2\x88\x86'
-0.762242 O b'lemma:30'
-0.762242 O b'word:30'
-0.778777 O b'+1:lemma:mm'
-0.778777 O b'+1:word:mM'
-0.782724 O b'lemma:nitrate'
-0.782724 O b'word:nitrate'
-0.783200 O b'-1:lemma:1'
-0.783200 O b'-1:word:1'
-0.788591 Phase b'isUpper'
-0.789080 O b'-1:lemma:30'
-0.789080 O b'-1:word:30'
-0.790624 Supp b'postag:CC'
-0.796125 Gtype b'postag:VBG'
-0.802899 O b'-1:lemma:nsrr'
-0.802899 O b'-1:word:NsrR'
-0.828431 Gtype b'postag::'
-0.831044 O b'lemma:2h'
-0.831044 O b'-1:lemma:additional'
-0.831044 O b'word:2h'
-0.831044 O b'-1:word:additional'
-0.839187 O b'lemma:media'
-0.839187 O b'word:media'
-0.840728 Supp b'postag::'
-0.863650 Air b'-1:lemma:or'
-0.863650 Air b'-1:word:or'
-0.885820 Temp b'postag:NN'
-0.897688 Med b'-1:postag:CD'
-0.900253 pH b'isLower'
-0.911088 O b'-1:lemma:until'
-0.911088 O b'-1:word:until'
-0.944420 O b'+1:word:ChIP-exo'
-0.948977 O b'lemma:anaerobically'
-0.948977 O b'word:anaerobically'
-0.951515 Agit b'isUpper'
-0.983125 Gtype b'isUpper'
-0.988396 O b'+1:lemma:at'
-0.988396 O b'+1:word:at'
-0.995833 Supp b'+1:lemma:nacl'
-0.995833 Supp b'+1:word:NaCl'
-0.997040 O b'-1:lemma:ml'
-0.997040 O b'-1:word:ml'
-1.018669 Supp b'-1:postag:NNP'
-1.037921 O b'lemma:nitrogen'
-1.037921 O b'word:nitrogen'
-1.040146 O b'+1:lemma:1'
-1.040146 O b'+1:word:1'
-1.045534 Med b'-1:postag:IN'
-1.056151 O b'word:ChIP-exo'
-1.089520 O b'lemma:wt'
-1.114097 O b'+1:lemma:+'
-1.114097 O b'+1:word:+'
-1.120376 Gtype b'isLower'
-1.143082 O b'-1:lemma:IP'
-1.143082 O b'-1:word:IP'
-1.158305 OD b'+1:postag:NN'
-1.159364 O b'-1:postag::'
-1.163927 O b'+1:lemma:in'
-1.163927 O b'+1:word:in'
-1.192075 O b'+1:postag:VBG'
-1.203597 O b'postag:RB'
-1.328635 O b'+1:lemma:2'
-1.328635 O b'+1:word:2'
-1.418108 Technique b'isLower'
-1.442615 O b'-1:lemma:sample'
-1.516830 O b'lemma:rifampicin'
-1.516830 O b'word:rifampicin'
-1.534388 Supp b'+1:lemma:-lrb-'
-1.534388 Supp b'+1:word:-LRB-'
-1.563425 Supp b'+1:postag:-LRB-'
-1.574320 Supp b'postag:JJ'
-1.581559 O b'-1:lemma:fresh'
-1.581559 O b'-1:word:fresh'
-1.612036 Gversion b'isLower'
-1.656921 Anti b'postag:NNP'
-1.709765 O b'-1:lemma:vol'
-1.709765 O b'-1:word:vol'
-1.748581 Air b'+1:postag:JJ'
-1.800378 Technique b'isNumber'
-1.802484 O b'postag:VBP'
-1.806249 Supp b'+1:lemma:,'
-1.806249 Supp b'+1:postag:,'
-1.806249 Supp b'+1:word:,'
-2.105469 O b'-1:lemma:_'
-2.105469 O b'-1:word:_'
-2.207206 Gtype b'isNumber'
-2.372723 Phase b'-1:postag:JJ'
-2.553668 O b'-1:postag:VBG'
-2.823830 O b'-1:lemma::'
-2.823830 O b'-1:word::'
-3.368572 Temp b'+1:postag:IN'
-3.402875 Phase b'postag:JJ'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.10934136756341511, 'c2': 0.11233592223188592}
best CV score:0.880070585228673
model size: 0.16M
Flat F1: 0.7987637165072743
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.913 0.955 23
Med 1.000 0.962 0.981 53
Temp 0.909 0.690 0.784 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.556 0.362 0.439 69
Anti 0.917 1.000 0.957 11
Strain 0.000 0.000 0.000 1
Gtype 0.882 0.788 0.832 85
Substrain 0.000 0.000 0.000 0
Supp 0.848 0.791 0.819 134
Gversion 0.000 0.000 0.000 0
avg / total 0.850 0.758 0.799 451
Top likely transitions:
OD -> OD 4.835421
Med -> Med 4.432130
Temp -> Temp 4.381858
Supp -> Supp 4.249606
Anti -> Anti 4.153912
Agit -> Agit 3.968681
Air -> Air 3.831359
Gtype -> Gtype 3.677992
Gversion -> Gversion 3.265155
O -> O 3.210778
Phase -> Phase 3.136151
Technique -> Technique 2.609081
pH -> pH 2.036266
Substrain -> Gtype 0.689009
Air -> O 0.614440
O -> Supp 0.599670
O -> Technique 0.575931
Gtype -> Supp 0.484890
O -> Gtype 0.452540
Technique -> Air 0.313681
Gtype -> Air 0.150938
Med -> O 0.101880
Supp -> O 0.080361
Gtype -> pH 0.018366
O -> Strain -0.000117
Supp -> Temp -0.004625
Air -> Agit -0.004733
O -> OD -0.005112
Anti -> Med -0.010247
pH -> Supp -0.019865
Gversion -> Air -0.021135
Technique -> Gversion -0.026379
Vess -> O -0.027766
Gtype -> OD -0.029261
O -> Substrain -0.033985
Air -> Technique -0.035861
O -> Phase -0.036615
OD -> O -0.041954
Gversion -> Gtype -0.044992
OD -> Supp -0.048485
O -> Gversion -0.055499
Phase -> Gtype -0.077815
Anti -> Temp -0.081500
Phase -> Med -0.087481
Temp -> Med -0.102584
Anti -> Supp -0.104656
Gtype -> Phase -0.110657
Supp -> pH -0.119733
Agit -> Air -0.121190
Gtype -> Temp -0.124907
Top unlikely transitions:
OD -> O -0.041954
Gversion -> Gtype -0.044992
OD -> Supp -0.048485
O -> Gversion -0.055499
Phase -> Gtype -0.077815
Anti -> Temp -0.081500
Phase -> Med -0.087481
Temp -> Med -0.102584
Anti -> Supp -0.104656
Gtype -> Phase -0.110657
Supp -> pH -0.119733
Agit -> Air -0.121190
Gtype -> Temp -0.124907
OD -> Technique -0.148325
Supp -> Air -0.175860
Anti -> Gtype -0.176413
Phase -> OD -0.183709
Supp -> Anti -0.184780
Air -> Med -0.197230
O -> Agit -0.219762
Gtype -> Gversion -0.221487
Phase -> Supp -0.230211
Air -> Supp -0.237948
Phase -> Technique -0.238586
Gversion -> Supp -0.239381
Technique -> Supp -0.246780
Supp -> Phase -0.249929
Technique -> OD -0.257903
Air -> Phase -0.275963
Agit -> O -0.288627
Anti -> O -0.319981
Supp -> Gversion -0.332251
OD -> Air -0.336991
Air -> Temp -0.361852
Gtype -> Technique -0.399331
Supp -> Technique -0.405956
Phase -> O -0.432789
Technique -> Gtype -0.440396
Supp -> Gtype -0.441214
Technique -> pH -0.443537
Gtype -> Anti -0.491458
O -> Med -0.522931
Gtype -> Med -0.545579
Gversion -> O -0.619815
O -> Air -0.714655
Gtype -> O -0.835271
Technique -> O -0.871817
Supp -> Med -0.890595
Med -> Supp -0.986516
Substrain -> O -1.034601
Top positive:
2.709537 Gtype b'word[:1]:\xce\x94'
2.682016 Technique b'word[:2]:Ch'
2.639969 O b'word[:2]:re'
2.530056 O b'lemma:_'
2.530056 O b'word[:1]:_'
2.530056 O b'word:_'
2.312646 Air b'lemma:anaerobic'
2.190494 O b'lemma:2'
2.190494 O b'word:2'
2.027500 O b'word:A'
1.983858 Air b'word[:2]:An'
1.950019 Air b'word[:2]:Ae'
1.950019 Air b'word:Aerobic'
1.947205 Gtype b'lemma:wt'
1.940543 Gtype b'word[:1]:W'
1.844619 Supp b'-1:word:Cra'
1.822143 Air b'word[:1]:A'
1.818988 O b'word[:1]:S'
1.775674 Technique b'word[:2]:RN'
1.765741 O b'lemma:1'
1.765741 O b'word:1'
1.724942 Phase b'lemma:mid-log'
1.724942 Phase b'word:mid-log'
1.723723 Supp b'word[:1]:I'
1.723541 Gtype b'word[:1]:d'
1.713163 O b'postag::'
1.713163 O b'postag[:1]::'
1.712969 Supp b'+1:lemma:\xc2\xb5m'
1.712969 Supp b'+1:word:\xc2\xb5M'
1.705742 O b'lemma:3'
1.705742 O b'word:3'
1.679949 Gtype b'hGreek'
1.676513 Air b'word[:1]:a'
1.653704 Supp b'-1:postag:CC'
1.616788 O b'-1:lemma:tag'
1.599401 Air b'word[:2]:an'
1.579379 O b'isLower'
1.575060 O b'-1:word:tag'
1.543882 O b'word[:1]:G'
1.542332 Substrain b'word[:2]:MG'
1.517878 Anti b'word[:2]:an'
1.501383 O b'lemma:a'
1.478818 Supp b'word[:2]:ni'
1.475795 Supp b'-1:lemma:with'
1.475795 Supp b'-1:word:with'
1.470736 Gtype b'word[:2]:Fl'
1.468144 Gversion b'word[:2]:00'
1.466264 Gtype b'symb'
1.463246 Gtype b'word[:1]:w'
1.451800 O b'lemma:.'
1.451800 O b'postag:.'
1.451800 O b'postag[:1]:.'
1.451800 O b'word:.'
1.449609 pH b'+1:postag:CD'
1.443950 Supp b'lemma:Iron'
1.443950 Supp b'word[:2]:Ir'
1.443950 Supp b'word:Iron'
1.443950 Supp b'+1:word:Deficient'
1.440541 O b'postag:IN'
1.440541 O b'postag[:1]:I'
1.440541 O b'postag[:2]:IN'
1.432941 O b'word[:2]:ch'
1.423481 O b'word[:2]:ge'
1.416303 O b'word[:1]:-'
1.412935 Strain b'+1:lemma:substr'
1.412935 Strain b'+1:word:substr'
1.409982 O b'lemma:with'
1.409982 O b'word:with'
1.409286 Substrain b'word[:1]:M'
1.405314 O b'lemma:-'
1.405314 O b'word:-'
1.400041 Technique b'word[:1]:R'
1.397927 O b'word[:2]:Rp'
1.391254 O b'word[:1]:B'
1.385270 Technique b'word[:1]:C'
1.383408 O b'word[:1]:C'
1.375474 Supp b'lemma:pq'
1.375474 Supp b'word[:2]:PQ'
1.375474 Supp b'word:PQ'
1.368840 Gtype b'word[:2]:PK'
1.361629 Supp b'word[:2]:gl'
1.355258 Supp b'lemma:arginine'
1.351941 Gtype b'lemma:arca8myc'
1.351941 Gtype b'word:ArcA8myc'
1.348800 pH b'word[:2]:pH'
1.345187 O b'+1:lemma:pq'
1.345187 O b'+1:word:PQ'
1.341451 Gtype b'-1:lemma:\xe2\x88\x86'
1.341451 Gtype b'-1:word:\xe2\x88\x86'
1.330835 Supp b'word[:2]:Fe'
1.329888 Gtype b'word[:1]:t'
1.324689 O b'-1:word:Aerobic'
1.311273 Phase b'word[:2]:ex'
1.293669 Air b'word:anaerobic'
1.281678 OD b'word[:1]:O'
1.279382 Air b'+1:postag:IN'
1.278560 O b'postag:CC'
1.278560 O b'postag[:2]:CC'
1.274647 O b'-1:lemma:lb'
1.274647 O b'-1:word:LB'
1.273896 Phase b'word[:1]:e'
1.263423 O b'word[:2]:Cr'
1.244847 Gtype b'word[:2]:WT'
1.244847 Gtype b'word:WT'
1.236647 Gtype b'word[:1]:F'
1.232072 Technique b'lemma:ChIP-exo'
1.218565 Supp b'lemma:acetate'
1.218565 Supp b'word:acetate'
1.218411 O b'word:Cra'
1.214505 Med b'isUpper'
1.210174 Gtype b'word[:2]:Ar'
1.197926 Supp b'word[:1]:N'
1.194956 Air b'word:Anaerobic'
1.192780 O b'+1:word:were'
1.191655 Supp b'-1:lemma:Cra'
1.188100 Med b'word[:1]:L'
1.185467 O b'+1:postag:RB'
1.185391 Gversion b'-1:lemma:nc'
1.185391 Gversion b'-1:word:NC'
1.182343 Med b'word[:1]:M'
1.178948 Gtype b'word[:2]:cr'
1.165949 pH b'word[:1]:p'
1.163893 O b'word[:1]:R'
1.163629 O b'word[:1]:c'
1.155830 Phase b'lemma:stationary'
1.155830 Phase b'word:stationary'
1.142993 O b'+1:postag:NNP'
1.134168 O b'word[:1]:E'
1.133170 O b'-1:lemma:glucose'
1.133170 O b'-1:word:glucose'
1.132500 Supp b'word[:2]:ac'
1.130901 O b'+1:word:ChIP-Seq'
1.120305 Gtype b'lemma:flag-tag'
1.120305 Gtype b'-1:lemma:c-terminal'
1.120305 Gtype b'word:Flag-tag'
1.120305 Gtype b'-1:word:C-terminal'
1.110588 Supp b'postag:NNP'
1.109954 Technique b'symb'
1.108629 Supp b'+1:lemma:1'
1.108629 Supp b'+1:word:1'
1.105428 O b'lemma:b'
1.105428 O b'word:B'
1.104286 Gtype b'lemma:type'
1.104286 Gtype b'word[:2]:ty'
1.104286 Gtype b'word:type'
1.089168 Gtype b'word[:1]:f'
1.087372 Gversion b'lemma:nc'
1.087372 Gversion b'word[:2]:NC'
1.087372 Gversion b'word:NC'
1.083150 O b'-1:lemma:0.3'
1.083150 O b'-1:word:0.3'
1.081216 O b'lemma:Custom'
1.081216 O b'word:Custom'
1.074470 O b'-1:lemma:anaerobic'
1.073417 Gtype b'lemma:nsrr'
1.073417 Gtype b'word[:2]:Ns'
1.073417 Gtype b'word:NsrR'
1.073408 Gtype b'-1:postag:VBG'
1.057426 Supp b'lemma:rifampicin'
1.057426 Supp b'word:rifampicin'
1.055166 Med b'+1:lemma:0.4'
1.055166 Med b'+1:word:0.4'
1.052666 Supp b'word[:2]:ri'
1.044391 Anti b'word[:1]:a'
1.039713 Supp b'lemma:nacl'
1.039713 Supp b'word:NaCl'
1.030612 Gversion b'lemma:asm584v2'
1.030612 Gversion b'word[:2]:AS'
1.030612 Gversion b'word:ASM584v2'
1.030597 Gversion b'lemma:chip-seq'
1.029930 Med b'word[:1]:m'
1.029515 Gtype b'+1:postag::'
1.026311 Med b'lemma:MOPS'
1.026311 Med b'word[:2]:MO'
1.026311 Med b'word:MOPS'
1.021842 O b'-1:lemma:ChIP-exo'
1.020313 Med b'+1:postag:CD'
1.017584 Anti b'+1:lemma:antibody'
1.017584 Anti b'+1:word:antibody'
1.017141 O b'isNumber'
1.015378 O b'+1:lemma:od600'
1.015378 O b'+1:word:OD600'
1.014672 Gversion b'word:ChIP-Seq'
1.011776 Strain b'lemma:k-12'
1.011776 Strain b'word[:2]:K-'
1.011776 Strain b'word:K-12'
1.008575 Agit b'+1:lemma:rpm'
1.008575 Agit b'+1:word:rpm'
1.005191 O b'word[:2]:Cu'
1.002792 Technique b'-1:lemma:chip-exo'
1.000546 Air b'postag:RB'
1.000546 Air b'postag[:1]:R'
1.000546 Air b'postag[:2]:RB'
0.992188 Supp b'-1:lemma:+'
0.992188 Supp b'-1:word:+'
0.991416 Gtype b'word[:1]:P'
0.986807 O b'lemma:rpob'
0.986807 O b'word:RpoB'
0.985164 Supp b'+1:lemma:mm'
0.985164 Supp b'+1:word:mM'
Top negative:
-0.277257 O b'-1:lemma:iptg'
-0.277257 O b'-1:word:IPTG'
-0.279683 O b'-1:lemma:37'
-0.279683 O b'-1:word:37'
-0.279732 O b'word[:2]:ce'
-0.280808 O b'lemma:sodium'
-0.280808 O b'word:Sodium'
-0.283552 O b'lemma:37'
-0.283552 O b'word[:2]:37'
-0.283552 O b'word:37'
-0.285904 O b'-1:lemma:cra'
-0.287226 O b'lemma:fructose'
-0.287226 O b'word:fructose'
-0.287570 O b'word[:2]:gl'
-0.288146 O b'+1:word:C'
-0.288657 O b'postag:RB'
-0.288657 O b'postag[:1]:R'
-0.288657 O b'postag[:2]:RB'
-0.290394 O b'+1:lemma:phosphate'
-0.290394 O b'+1:word:phosphate'
-0.291469 Anti b'+1:lemma:anti-fur'
-0.291469 Anti b'+1:word:anti-Fur'
-0.291608 Med b'-1:postag:CD'
-0.292517 O b'+1:lemma:antibody'
-0.292517 O b'+1:word:antibody'
-0.293015 Temp b'postag:NN'
-0.293202 O b'word:cells'
-0.295080 Substrain b'isLower'
-0.301504 Technique b'-1:postag::'
-0.301563 O b'+1:lemma:rep2'
-0.301563 O b'+1:word:rep2'
-0.303285 Gtype b'-1:lemma:mg1655'
-0.303285 Gtype b'-1:word:MG1655'
-0.312135 pH b'isUpper'
-0.315986 O b'word[:1]:\xce\x94'
-0.318042 O b'-1:lemma:control'
-0.318042 O b'-1:word:control'
-0.320219 O b'word[:1]:F'
-0.320234 O b'-1:lemma:mm'
-0.320234 O b'-1:word:mM'
-0.325890 Phase b'postag[:1]:J'
-0.325890 Phase b'postag[:2]:JJ'
-0.329319 Air b'isUpper'
-0.337579 O b'lemma:of'
-0.337579 O b'word[:2]:of'
-0.337579 O b'word:of'
-0.338232 O b'lemma:30'
-0.338232 O b'word:30'
-0.338512 Gtype b'+1:postag:CD'
-0.340489 pH b'isNumber'
-0.349750 Phase b'postag:JJ'
-0.351290 O b'-1:postag:IN'
-0.351993 Gtype b'postag[:1]:V'
-0.351993 Gtype b'postag[:2]:VB'
-0.352349 OD b'symb'
-0.354429 Gtype b'+1:lemma:-rrb-'
-0.354429 Gtype b'+1:word:-RRB-'
-0.356978 O b'-1:lemma:chip-exo'
-0.365676 Air b'postag[:1]:N'
-0.365676 Air b'postag[:2]:NN'
-0.369913 O b'+1:lemma:at'
-0.369913 O b'+1:word:at'
-0.374701 Supp b'-1:lemma:-lrb-'
-0.374701 Supp b'-1:word:-LRB-'
-0.385565 Supp b'+1:postag:VBN'
-0.385693 O b'word[:1]:4'
-0.396082 Technique b'isNumber'
-0.396613 Med b'-1:postag:NN'
-0.398175 O b'word[:1]:0'
-0.400398 Air b'isLower'
-0.400541 O b'+1:lemma:1m'
-0.400541 O b'+1:word:1M'
-0.406455 O b'+1:lemma:until'
-0.406455 O b'+1:word:until'
-0.406467 O b'lemma:0.3'
-0.406467 O b'word:0.3'
-0.406862 Supp b'-1:postag:NNP'
-0.407709 Vess b'hUpper'
-0.407709 Vess b'hLower'
-0.409808 Air b'-1:lemma:or'
-0.409808 Air b'-1:word:or'
-0.411518 Supp b'-1:postag:-LRB-'
-0.413893 O b'word[:2]:mg'
-0.416294 O b'-1:lemma:\xe2\x88\x86'
-0.416294 O b'-1:word:\xe2\x88\x86'
-0.416443 O b'-1:lemma:dissolve'
-0.416443 O b'+1:lemma:methanol'
-0.416443 O b'-1:word:dissolved'
-0.416443 O b'+1:word:methanol'
-0.416730 O b'-1:lemma:rpob'
-0.416730 O b'-1:word:RpoB'
-0.420106 O b'lemma:mid-log'
-0.420106 O b'word:mid-log'
-0.424246 Supp b'postag:JJ'
-0.424315 Med b'+1:postag:IN'
-0.425368 O b'lemma:2h'
-0.425368 O b'-1:lemma:additional'
-0.425368 O b'word[:2]:2h'
-0.425368 O b'word:2h'
-0.425368 O b'-1:word:additional'
-0.427387 Supp b'postag[:1]:J'
-0.427387 Supp b'postag[:2]:JJ'
-0.432272 O b'-1:lemma:ph'
-0.432272 O b'-1:word:pH'
-0.437208 Agit b'symb'
-0.450378 Air b'+1:postag:JJ'
-0.451134 Med b'symb'
-0.452272 O b'-1:lemma:nsrr'
-0.452272 O b'-1:word:NsrR'
-0.452987 O b'-1:lemma:1'
-0.452987 O b'-1:word:1'
-0.453419 OD b'hUpper'
-0.453419 OD b'hLower'
-0.455390 O b'-1:lemma:30'
-0.455390 O b'-1:word:30'
-0.458645 Strain b'isLower'
-0.473382 O b'+1:word:ChIP-exo'
-0.477433 O b'word[:1]:M'
-0.478284 Air b'-1:postag:JJ'
-0.481981 Med b'-1:postag:IN'
-0.490205 O b'-1:lemma:final'
-0.490205 O b'-1:word:final'
-0.498623 O b'+1:lemma:mm'
-0.498623 O b'+1:word:mM'
-0.504915 O b'-1:lemma:IP'
-0.504915 O b'-1:word:IP'
-0.508549 O b'+1:postag:IN'
-0.527183 O b'-1:lemma:until'
-0.527183 O b'-1:word:until'
-0.534060 O b'+1:lemma:+'
-0.534060 O b'+1:word:+'
-0.536386 O b'-1:lemma:co2'
-0.536386 O b'-1:word:CO2'
-0.546923 Technique b'isLower'
-0.549653 O b'+1:lemma:g/l'
-0.549653 O b'+1:word:g/L'
-0.556331 Agit b'hUpper'
-0.556331 Agit b'hLower'
-0.566036 O b'-1:lemma:fresh'
-0.566036 O b'-1:word:fresh'
-0.589166 O b'word[:2]:pH'
-0.606308 Gtype b'isNumber'
-0.608954 O b'-1:lemma:ml'
-0.608954 O b'-1:word:ml'
-0.636500 Air b'postag:NN'
-0.644243 Air b'symb'
-0.644631 O b'-1:lemma:sample'
-0.645479 O b'word[:1]:K'
-0.647685 O b'word[:2]:ri'
-0.648673 Supp b'symb'
-0.654648 Supp b'word[:1]:C'
-0.655830 O b'word[:1]:N'
-0.669514 O b'+1:postag:VBG'
-0.678570 O b'lemma:rifampicin'
-0.678570 O b'word:rifampicin'
-0.685362 O b'+1:lemma:2.0'
-0.685362 O b'+1:word:2.0'
-0.697373 pH b'isLower'
-0.723949 O b'+1:lemma:1'
-0.723949 O b'+1:word:1'
-0.725696 O b'word[:2]:30'
-0.733745 O b'word[:1]:d'
-0.746229 Technique b'postag:NN'
-0.746793 Anti b'postag:NNP'
-0.772686 Phase b'hUpper'
-0.772686 Phase b'hLower'
-0.779562 Supp b'+1:lemma:-lrb-'
-0.779562 Supp b'+1:word:-LRB-'
-0.785425 O b'lemma:wt'
-0.793464 Supp b'+1:postag:-LRB-'
-0.807612 O b'+1:lemma:in'
-0.807612 O b'+1:word:in'
-0.809771 O b'-1:lemma:2'
-0.809771 O b'-1:word:2'
-0.827384 O b'word[:2]:me'
-0.843493 O b'word[:2]:fl'
-0.892217 Temp b'+1:postag:IN'
-0.911652 O b'word[:2]:ni'
-0.928268 O b'-1:lemma:vol'
-0.928268 O b'-1:word:vol'
-0.929689 Gversion b'isLower'
-0.937497 Phase b'-1:postag:JJ'
-0.939661 Supp b'+1:lemma:,'
-0.939661 Supp b'+1:postag:,'
-0.939661 Supp b'+1:word:,'
-0.945384 Supp b'hGreek'
-1.033862 O b'+1:lemma:2'
-1.033862 O b'+1:word:2'
-1.049369 O b'postag:VBP'
-1.064806 Gtype b'word[:1]:C'
-1.103635 OD b'+1:postag:NN'
-1.146336 Gtype b'isUpper'
-1.184986 O b'-1:postag::'
-1.221339 O b'word[:1]:P'
-1.586036 O b'word[:2]:Ch'
-1.596486 O b'-1:postag:VBG'
-1.615380 O b'-1:lemma:_'
-1.615380 O b'-1:word:_'
-1.888889 O b'-1:lemma::'
-1.888889 O b'-1:word::'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.10224977118326696, 'c2': 0.08574073868552615}
best CV score:0.8625521557665096
model size: 0.15M
Flat F1: 0.7911337627473737
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 0.955 0.913 0.933 23
Med 1.000 0.962 0.981 53
Temp 1.000 0.621 0.766 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.556 0.362 0.439 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.880 0.776 0.825 85
Substrain 0.000 0.000 0.000 0
Supp 0.820 0.784 0.802 134
Gversion 0.000 0.000 0.000 0
avg / total 0.847 0.749 0.791 451
Top likely transitions:
Supp -> Supp 4.853883
Med -> Med 4.656088
Temp -> Temp 4.510100
Agit -> Agit 4.465117
OD -> OD 4.340142
Anti -> Anti 4.196466
Air -> Air 3.821484
Gtype -> Gtype 3.782966
Gversion -> Gversion 3.606921
O -> O 3.495921
Phase -> Phase 3.323762
Technique -> Technique 2.563651
pH -> pH 2.180795
O -> Supp 0.898100
Substrain -> Gtype 0.754641
Air -> O 0.647741
O -> Technique 0.571928
O -> Gtype 0.481770
Supp -> O 0.402376
Gtype -> Supp 0.324453
Med -> O 0.307057
Technique -> Air 0.224294
Gtype -> Air 0.168729
O -> Anti 0.038118
O -> Temp 0.032123
Gtype -> pH 0.002908
Temp -> O 0.000361
Strain -> O 0.000160
Technique -> Gversion -0.000416
Air -> Agit -0.005831
Supp -> pH -0.007270
OD -> O -0.014197
Gversion -> Supp -0.015735
Gtype -> OD -0.028160
Supp -> Phase -0.029631
Anti -> Temp -0.035006
Phase -> Gtype -0.044350
OD -> Supp -0.044521
Gtype -> Temp -0.059821
Temp -> Med -0.060792
Gtype -> Phase -0.069441
OD -> Technique -0.077261
Air -> Technique -0.079069
O -> Agit -0.096763
Anti -> Supp -0.100222
Phase -> OD -0.103283
Supp -> Gversion -0.124409
Anti -> Air -0.126752
O -> OD -0.131232
Supp -> Anti -0.144899
Top unlikely transitions:
OD -> O -0.014197
Gversion -> Supp -0.015735
Gtype -> OD -0.028160
Supp -> Phase -0.029631
Anti -> Temp -0.035006
Phase -> Gtype -0.044350
OD -> Supp -0.044521
Gtype -> Temp -0.059821
Temp -> Med -0.060792
Gtype -> Phase -0.069441
OD -> Technique -0.077261
Air -> Technique -0.079069
O -> Agit -0.096763
Anti -> Supp -0.100222
Phase -> OD -0.103283
Supp -> Gversion -0.124409
Anti -> Air -0.126752
O -> OD -0.131232
Supp -> Anti -0.144899
Agit -> Air -0.145881
Supp -> Air -0.148035
Anti -> Gtype -0.148967
Phase -> O -0.182539
Gtype -> Gversion -0.218235
Phase -> Supp -0.220677
Agit -> O -0.221526
Supp -> Technique -0.230155
Air -> Med -0.252173
Anti -> O -0.256819
Technique -> Supp -0.258507
Phase -> Technique -0.308300
O -> Med -0.322260
Air -> Phase -0.344611
OD -> Air -0.369099
Air -> Supp -0.381831
Technique -> OD -0.386625
Supp -> Gtype -0.423661
Gversion -> O -0.442929
Gtype -> Med -0.466529
Gtype -> Technique -0.486041
Air -> Temp -0.495035
Technique -> Gtype -0.512140
O -> Air -0.557928
Gtype -> Anti -0.639624
Supp -> Med -0.666805
Technique -> pH -0.687130
Technique -> O -0.804221
Gtype -> O -0.839737
Substrain -> O -1.005940
Med -> Supp -1.140134
Top positive:
2.992522 O b'postag:IN'
2.933510 Gtype b'lemma[:1]:\xce\xb4'
2.698175 O b'lemma:_'
2.698175 O b'lemma[:1]:_'
2.698175 O b'word:_'
2.580892 Technique b'lemma[:2]:Ch'
2.528828 Air b'lemma[:2]:an'
2.520301 O b'postag::'
2.475598 Air b'word:Aerobic'
2.397019 O b'lemma[:2]:re'
2.343308 O b'lemma:2'
2.343308 O b'word:2'
2.187375 OD b'lemma[:1]:o'
2.132214 Air b'lemma:anaerobic'
2.102690 O b'lemma:1'
2.102690 O b'word:1'
2.069208 Air b'postag:RB'
2.011921 Supp b'-1:word:Cra'
2.008921 O b'postag:CC'
1.985815 O b'word:Cra'
1.954962 O b'word:A'
1.945886 O b'-1:lemma:tag'
1.944651 Air b'lemma[:1]:a'
1.942100 Gtype b'lemma[:1]:w'
1.941658 O b'isLower'
1.941416 O b'lemma:3'
1.941416 O b'word:3'
1.928794 Anti b'lemma[:2]:an'
1.904875 O b'lemma:-'
1.904875 O b'word:-'
1.894461 Air b'lemma[:2]:ae'
1.837551 Supp b'+1:lemma:\xc2\xb5m'
1.837551 Supp b'+1:word:\xc2\xb5M'
1.827021 O b'lemma:with'
1.827021 O b'word:with'
1.820722 O b'lemma:.'
1.820722 O b'postag:.'
1.820722 O b'word:.'
1.782610 Phase b'lemma:mid-log'
1.782610 Phase b'word:mid-log'
1.757467 Technique b'lemma:chipseq'
1.743523 Technique b'lemma[:1]:C'
1.733249 Technique b'word:ChIPSeq'
1.723058 O b'-1:word:tag'
1.679894 Gtype b'lemma[:2]:pk'
1.670517 Technique b'lemma[:2]:rn'
1.646145 O b'lemma[:2]:ge'
1.642888 Gtype b'word:WT'
1.641812 Air b'word:Anaerobic'
1.636107 Supp b'lemma:pq'
1.636107 Supp b'lemma[:2]:pq'
1.636107 Supp b'word:PQ'
1.616520 Gtype b'lemma:wt'
1.616520 Gtype b'lemma[:2]:wt'
1.602692 Substrain b'lemma[:2]:mg'
1.595791 Gtype b'symb'
1.591226 Gtype b'hGreek'
1.580745 Gtype b'lemma[:2]:ar'
1.553690 O b'isNumber'
1.549681 Supp b'-1:lemma:with'
1.549681 Supp b'-1:word:with'
1.538810 Med b'isUpper'
1.524255 Supp b'lemma:Iron'
1.524255 Supp b'lemma[:2]:Ir'
1.524255 Supp b'word:Iron'
1.524255 Supp b'+1:word:Deficient'
1.523875 Med b'lemma[:1]:m'
1.507350 Supp b'lemma:arginine'
1.506721 O b'-1:word:Aerobic'
1.504743 O b'lemma:b'
1.504743 O b'word:B'
1.503810 O b'+1:lemma:pq'
1.503810 O b'+1:word:PQ'
1.485328 Gtype b'lemma:arca8myc'
1.485328 Gtype b'word:ArcA8myc'
1.478520 Phase b'lemma[:2]:ex'
1.477705 Supp b'-1:postag:CC'
1.473033 Strain b'+1:lemma:substr'
1.473033 Strain b'+1:word:substr'
1.471852 O b'lemma[:1]:h'
1.470534 Gtype b'lemma[:1]:f'
1.432902 Technique b'word:ChIP-Seq'
1.432272 Gtype b'-1:lemma:\xe2\x88\x86'
1.432272 Gtype b'-1:word:\xe2\x88\x86'
1.431861 Supp b'lemma:acetate'
1.431861 Supp b'word:acetate'
1.426205 pH b'+1:postag:CD'
1.426130 O b'lemma:a'
1.423474 Phase b'lemma[:1]:e'
1.416394 Gtype b'lemma[:2]:cr'
1.412091 O b'-1:lemma:lb'
1.412091 O b'-1:word:LB'
1.409559 O b'+1:postag:NNP'
1.396235 Supp b'-1:lemma:Cra'
1.391229 Technique b'lemma:ChIP-exo'
1.387275 Supp b'lemma[:2]:gl'
1.381222 O b'postag:VBN'
1.357861 Technique b'lemma[:2]:ch'
1.349464 O b'-1:lemma:ChIP-exo'
1.337510 Supp b'lemma:rifampicin'
1.337510 Supp b'word:rifampicin'
1.333930 Supp b'lemma[:2]:ri'
1.331717 Supp b'lemma[:2]:ni'
1.308373 Air b'+1:postag:IN'
1.302031 Gtype b'lemma[:2]:de'
1.301579 Supp b'lemma[:1]:I'
1.295057 Gtype b'lemma:type'
1.295057 Gtype b'lemma[:2]:ty'
1.295057 Gtype b'word:type'
1.293141 Technique b'symb'
1.290443 Air b'-1:lemma:ChIP-Seq'
1.290443 Air b'-1:word:ChIP-Seq'
1.286791 Gversion b'lemma[:2]:00'
1.282084 pH b'lemma[:2]:ph'
1.264843 Gversion b'word:ChIP-Seq'
1.249803 Supp b'lemma[:2]:ac'
1.237133 O b'postag:DT'
1.232242 Gversion b'lemma:chip-seq'
1.230130 Gversion b'-1:lemma:nc'
1.230130 Gversion b'-1:word:NC'
1.230000 O b'lemma:rpob'
1.230000 O b'word:RpoB'
1.206427 Air b'lemma:Aerobic'
1.206427 Air b'lemma[:2]:Ae'
1.198600 Technique b'-1:lemma:chip-exo'
1.196166 Phase b'lemma:stationary'
1.196166 Phase b'word:stationary'
1.186607 Supp b'-1:lemma:vol'
1.186607 Supp b'-1:word:vol'
1.185194 Gtype b'-1:postag:VBG'
1.185039 Gversion b'lemma:nc'
1.185039 Gversion b'lemma[:2]:nc'
1.185039 Gversion b'word:NC'
1.183740 O b'-1:lemma:0.3'
1.183740 O b'-1:word:0.3'
1.183722 Substrain b'lemma[:1]:m'
1.178060 Med b'lemma:MOPS'
1.178060 Med b'lemma[:1]:M'
1.178060 Med b'lemma[:2]:MO'
1.178060 Med b'word:MOPS'
1.176455 Agit b'+1:lemma:rpm'
1.176455 Agit b'+1:word:rpm'
1.173660 Air b'lemma[:1]:A'
1.171020 O b'lemma[:1]:C'
1.169586 O b'lemma:Custom'
1.169586 O b'lemma[:2]:Cu'
1.169586 O b'word:Custom'
1.169290 Supp b'lemma[:1]:n'
1.164574 O b'lemma[:1]:r'
1.163122 O b'+1:word:were'
1.161543 O b'+1:postag:RB'
1.160553 Med b'+1:lemma:0.4'
1.160553 Med b'+1:word:0.4'
1.157301 Gtype b'lemma[:1]:t'
1.139447 O b'-1:lemma:glucose'
1.139447 O b'-1:word:glucose'
1.136363 Gtype b'lemma[:1]:W'
1.123777 Gversion b'lemma:asm584v2'
1.123777 Gversion b'word:ASM584v2'
1.122043 Gversion b'lemma[:2]:as'
1.119834 Technique b'word:ChIP-exo'
1.116571 Supp b'+1:lemma:1'
1.116571 Supp b'+1:word:1'
1.109080 O b'-1:lemma:anaerobic'
1.107414 O b'lemma:ompr'
1.107414 O b'word:OmpR'
1.104893 Gtype b'+1:lemma:type'
1.104893 Gtype b'+1:word:type'
1.101638 O b'lemma:chip'
1.101186 Temp b'isUpper'
1.098068 Gtype b'lemma:nsrr'
1.098068 Gtype b'lemma[:2]:ns'
1.098068 Gtype b'word:NsrR'
1.097533 Strain b'lemma:k-12'
1.097533 Strain b'lemma[:2]:k-'
1.097533 Strain b'word:K-12'
1.094717 Agit b'lemma:rpm'
1.094717 Agit b'word:rpm'
1.093697 Anti b'+1:lemma:antibody'
1.093697 Anti b'+1:word:antibody'
1.090349 Supp b'-1:lemma:+'
1.090349 Supp b'-1:word:+'
1.089812 Med b'lemma:broth'
1.089812 Med b'-1:lemma:L'
1.089812 Med b'lemma[:2]:br'
1.089812 Med b'word:broth'
1.089812 Med b'-1:word:L'
1.089439 O b'lemma[:1]:s'
1.089354 Supp b'lemma:glucose'
1.089354 Supp b'word:glucose'
1.075102 Gtype b'-1:lemma:_'
1.075102 Gtype b'-1:word:_'
1.074174 OD b'-1:postag:IN'
1.069035 Air b'-1:lemma:-'
1.069035 Air b'-1:word:-'
1.064267 O b'lemma[:2]:om'
1.059425 Med b'-1:lemma:ml'
1.059425 Med b'-1:word:ml'
1.055151 O b'lemma[:2]:ga'
1.051054 Temp b'isNumber'
Top negative:
-0.269566 Med b'+1:postag:NN'
-0.271003 O b'+1:word:C'
-0.272991 Gtype b'lemma[:1]:g'
-0.281915 Substrain b'isLower'
-0.285097 Supp b'+1:lemma:acetate'
-0.285097 Supp b'+1:word:acetate'
-0.289196 O b'-1:lemma:control'
-0.289196 O b'-1:word:control'
-0.291783 O b'lemma:30'
-0.291783 O b'word:30'
-0.296669 Supp b'+1:lemma:nacl'
-0.296669 Supp b'+1:word:NaCl'
-0.299139 Gtype b'lemma[:2]:rp'
-0.299802 Supp b'lemma[:1]:a'
-0.300346 Supp b'isNumber'
-0.302212 Anti b'+1:lemma:anti-fur'
-0.302212 Anti b'+1:word:anti-Fur'
-0.302389 O b'+1:lemma:rep2'
-0.302389 O b'+1:word:rep2'
-0.302698 O b'lemma:methanol'
-0.302698 O b'word:methanol'
-0.303420 Supp b'+1:lemma:fructose'
-0.303420 Supp b'+1:word:fructose'
-0.305531 O b'lemma:aerobically'
-0.305531 O b'word:aerobically'
-0.306175 pH b'isNumber'
-0.306838 O b'lemma[:1]:d'
-0.308262 Gtype b'+1:lemma:-rrb-'
-0.308262 Gtype b'+1:word:-RRB-'
-0.312558 O b'-1:lemma:mm'
-0.312558 O b'-1:word:mM'
-0.313202 O b'-1:postag:-LRB-'
-0.317810 O b'lemma:of'
-0.317810 O b'lemma[:2]:of'
-0.317810 O b'word:of'
-0.319439 O b'-1:lemma:final'
-0.319439 O b'-1:word:final'
-0.321317 O b'lemma:anaerobically'
-0.321317 O b'word:anaerobically'
-0.325460 O b'lemma[:1]:L'
-0.330481 O b'lemma[:1]:A'
-0.332032 O b'+1:lemma:at'
-0.332032 O b'+1:word:at'
-0.333829 OD b'hUpper'
-0.333829 OD b'hLower'
-0.334342 O b'lemma[:1]:\xce\xb4'
-0.338105 O b'-1:lemma:37'
-0.338105 O b'-1:word:37'
-0.345520 O b'lemma[:1]:4'
-0.346277 Vess b'hUpper'
-0.346277 Vess b'hLower'
-0.351779 O b'-1:lemma:cra'
-0.354108 Supp b'-1:lemma:-lrb-'
-0.354108 Supp b'-1:word:-LRB-'
-0.354176 O b'lemma:0.3'
-0.354176 O b'word:0.3'
-0.357826 O b'+1:lemma:1m'
-0.357826 O b'+1:word:1M'
-0.365975 O b'-1:lemma:rpob'
-0.365975 O b'-1:word:RpoB'
-0.369791 Supp b'lemma[:2]:an'
-0.382535 Technique b'-1:postag::'
-0.385806 O b'-1:lemma:ph'
-0.385806 O b'-1:word:pH'
-0.390600 Strain b'isLower'
-0.390996 Med b'+1:postag:IN'
-0.397681 Technique b'isUpper'
-0.402341 O b'lemma[:2]:ph'
-0.407916 O b'-1:lemma:nsrr'
-0.407916 O b'-1:word:NsrR'
-0.408181 pH b'isUpper'
-0.408383 O b'lemma[:1]:p'
-0.410419 O b'-1:lemma:dissolve'
-0.410419 O b'+1:lemma:methanol'
-0.410419 O b'-1:word:dissolved'
-0.410419 O b'+1:word:methanol'
-0.411632 O b'+1:lemma:until'
-0.411632 O b'+1:word:until'
-0.422310 O b'+1:postag:IN'
-0.422805 O b'lemma:wt'
-0.422805 O b'lemma[:2]:wt'
-0.429703 Air b'-1:lemma:or'
-0.429703 Air b'-1:word:or'
-0.430609 O b'lemma:soxs-8myc'
-0.430609 O b'word:soxS-8myc'
-0.437708 O b'word:cells'
-0.439438 Supp b'-1:postag:-LRB-'
-0.443616 O b'lemma[:2]:mg'
-0.447807 O b'-1:postag:IN'
-0.454881 Technique b'postag:NN'
-0.455283 O b'-1:lemma:30'
-0.455283 O b'-1:word:30'
-0.455942 Med b'-1:postag:CD'
-0.456974 O b'-1:lemma:chip-exo'
-0.463642 O b'lemma:2h'
-0.463642 O b'-1:lemma:additional'
-0.463642 O b'lemma[:2]:2h'
-0.463642 O b'word:2h'
-0.463642 O b'-1:word:additional'
-0.463824 O b'lemma[:2]:ni'
-0.473738 O b'-1:lemma:\xe2\x88\x86'
-0.473738 O b'-1:word:\xe2\x88\x86'
-0.483472 Air b'-1:postag:JJ'
-0.485640 O b'lemma[:1]:k'
-0.489700 Agit b'symb'
-0.491876 O b'lemma[:2]:gl'
-0.493145 O b'-1:lemma:1'
-0.493145 O b'-1:word:1'
-0.493324 Supp b'lemma[:1]:s'
-0.495721 O b'-1:lemma:until'
-0.495721 O b'-1:word:until'
-0.510059 O b'+1:word:ChIP-exo'
-0.532260 Supp b'-1:postag:NNP'
-0.532617 O b'lemma:mid-log'
-0.532617 O b'word:mid-log'
-0.538747 O b'lemma[:2]:ar'
-0.539864 Temp b'postag:NN'
-0.544326 Gtype b'postag::'
-0.550034 O b'lemma[:1]:n'
-0.552433 Technique b'isNumber'
-0.552875 O b'-1:lemma:co2'
-0.552875 O b'-1:word:CO2'
-0.553836 O b'+1:lemma:mm'
-0.553836 O b'+1:word:mM'
-0.575360 Agit b'hUpper'
-0.575360 Agit b'hLower'
-0.587589 O b'+1:lemma:2.0'
-0.587589 O b'+1:word:2.0'
-0.589156 Air b'symb'
-0.593266 O b'-1:lemma:IP'
-0.593266 O b'-1:word:IP'
-0.606709 O b'+1:lemma:+'
-0.606709 O b'+1:word:+'
-0.623013 O b'word:ChIP-exo'
-0.624809 Med b'-1:postag:IN'
-0.644672 Med b'symb'
-0.652610 O b'lemma[:2]:an'
-0.663037 O b'+1:postag:VBG'
-0.669924 Air b'isLower'
-0.670219 O b'+1:lemma:g/l'
-0.670219 O b'+1:word:g/L'
-0.695683 pH b'isLower'
-0.700730 O b'-1:lemma:ml'
-0.700730 O b'-1:word:ml'
-0.708528 Technique b'isLower'
-0.713532 Gtype b'lemma[:1]:c'
-0.723267 O b'postag:VBP'
-0.726763 Med b'-1:postag:NN'
-0.730007 O b'-1:lemma:fresh'
-0.730007 O b'-1:word:fresh'
-0.732472 Gtype b'isNumber'
-0.754791 Anti b'postag:NNP'
-0.763751 O b'lemma[:1]:I'
-0.765472 Phase b'hUpper'
-0.765472 Phase b'hLower'
-0.777034 O b'postag:RB'
-0.783888 O b'+1:lemma:1'
-0.783888 O b'+1:word:1'
-0.819356 Supp b'+1:postag:VBN'
-0.832076 Supp b'+1:postag:-LRB-'
-0.834887 Supp b'+1:lemma:-lrb-'
-0.834887 Supp b'+1:word:-LRB-'
-0.845588 O b'lemma[:2]:ri'
-0.859382 O b'+1:lemma:in'
-0.859382 O b'+1:word:in'
-0.863969 O b'-1:lemma:2'
-0.863969 O b'-1:word:2'
-0.863985 Supp b'postag:JJ'
-0.879910 O b'lemma:rifampicin'
-0.879910 O b'word:rifampicin'
-0.890013 O b'-1:lemma:sample'
-0.908122 O b'lemma[:2]:me'
-0.918685 O b'lemma[:2]:30'
-0.977725 Supp b'symb'
-0.998621 Gtype b'lemma[:1]:a'
-1.009514 O b'lemma[:2]:ae'
-1.010867 Supp b'lemma[:1]:c'
-1.019909 Supp b'hGreek'
-1.025689 Gversion b'isLower'
-1.028787 O b'-1:postag::'
-1.033347 Gtype b'lemma[:1]:r'
-1.058669 Phase b'postag:JJ'
-1.063118 OD b'+1:postag:NN'
-1.085470 O b'+1:lemma:2'
-1.085470 O b'+1:word:2'
-1.097595 Temp b'+1:postag:IN'
-1.104571 O b'-1:lemma:vol'
-1.104571 O b'-1:word:vol'
-1.105747 Phase b'-1:postag:JJ'
-1.193803 Supp b'+1:lemma:,'
-1.193803 Supp b'+1:postag:,'
-1.193803 Supp b'+1:word:,'
-1.225152 Gtype b'isUpper'
-1.342867 Air b'postag:NN'
-1.648816 O b'-1:postag:VBG'
-1.734459 O b'-1:lemma:_'
-1.734459 O b'-1:word:_'
-1.809222 O b'lemma[:2]:fl'
-2.034354 O b'-1:lemma::'
-2.034354 O b'-1:word::'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.08547853139018363, 'c2': 0.0718223925603791}
best CV score:0.8618282789423788
model size: 0.12M
Flat F1: 0.7935612512742225
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.870 0.930 23
Med 1.000 0.925 0.961 53
Temp 1.000 0.828 0.906 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.545 0.348 0.425 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.847 0.847 0.847 85
Substrain 0.000 0.000 0.000 0
Supp 0.764 0.799 0.781 134
Gversion 0.000 0.000 0.000 0
avg / total 0.825 0.772 0.794 451
Top likely transitions:
Temp -> Temp 4.726292
Med -> Med 4.671738
Supp -> Supp 4.522188
Agit -> Agit 4.377673
OD -> OD 4.308572
Gversion -> Gversion 3.866864
O -> O 3.748552
Air -> Air 3.677475
Anti -> Anti 3.637881
Phase -> Phase 3.501884
Gtype -> Gtype 3.413911
Technique -> Technique 2.611020
pH -> pH 2.492174
Substrain -> Gtype 1.323299
O -> Supp 1.082471
Gtype -> Supp 1.059136
Air -> O 1.056595
O -> Technique 0.788425
Gtype -> Air 0.726982
Supp -> O 0.721855
Technique -> Air 0.676898
Med -> O 0.566862
Temp -> O 0.505913
Gtype -> pH 0.499557
O -> Gtype 0.492671
O -> Temp 0.193445
OD -> O 0.066099
O -> Phase 0.015467
Phase -> O 0.005269
O -> Anti 0.001662
O -> Med 0.000880
Phase -> Technique -0.000017
Gversion -> Technique -0.000081
Supp -> Gversion -0.001487
Supp -> Temp -0.006942
Anti -> Air -0.014046
OD -> Med -0.020526
Air -> Temp -0.030082
O -> Strain -0.036678
Strain -> Supp -0.037261
Anti -> Technique -0.039379
O -> Agit -0.039632
Anti -> O -0.064909
Med -> Gtype -0.069251
Gversion -> Air -0.073290
Supp -> Anti -0.079850
Air -> Phase -0.086231
Gtype -> Agit -0.087068
Technique -> Med -0.107591
Temp -> Supp -0.117927
Top unlikely transitions:
Gtype -> Agit -0.087068
Technique -> Med -0.107591
Temp -> Supp -0.117927
Phase -> Med -0.126236
Agit -> Supp -0.127001
Air -> Technique -0.146743
Gtype -> Phase -0.148852
Gversion -> O -0.153972
Temp -> Air -0.155016
Gversion -> Gtype -0.163400
Supp -> pH -0.165945
Technique -> OD -0.170573
Gtype -> OD -0.180802
Supp -> OD -0.185729
Agit -> O -0.186520
Gtype -> Temp -0.191678
Temp -> Med -0.203334
Anti -> Med -0.213478
Med -> Air -0.254265
Supp -> Phase -0.272052
O -> OD -0.284249
Air -> Agit -0.299878
Gtype -> Gversion -0.302074
Technique -> O -0.304509
Supp -> Technique -0.323807
Gversion -> Supp -0.330543
OD -> Supp -0.332686
Supp -> Air -0.350244
Agit -> Air -0.351443
Air -> Med -0.356425
pH -> Supp -0.356600
Phase -> Supp -0.367295
Anti -> Supp -0.388606
Anti -> Gtype -0.420057
Gtype -> Anti -0.437171
Gtype -> O -0.469909
Air -> Gtype -0.491506
Air -> Supp -0.517679
Supp -> Gtype -0.551144
Technique -> Supp -0.555659
OD -> Air -0.572756
Gtype -> Technique -0.574688
O -> Air -0.585607
Phase -> OD -0.592622
Technique -> pH -0.602711
Supp -> Med -0.656480
Gtype -> Med -0.782031
Substrain -> O -1.224113
Technique -> Gtype -1.370410
Med -> Supp -1.466233
Top positive:
4.763784 O b'lemma:2'
4.403357 O b'lemma:1'
4.351529 O b'lemma:_'
4.235059 Anti b'-2:lemma:antibody'
4.043801 O b'-2:lemma:_'
3.996162 Air b'lemma:anaerobic'
3.806351 Gtype b'lemma:wt'
3.749108 O b'postag:IN'
3.736227 Supp b'lemma:pq'
3.494745 Air b'lemma:Aerobic'
3.463151 Technique b'lemma:ChIP-exo'
3.331237 Technique b'lemma:chipseq'
3.321703 Phase b'lemma:mid-log'
3.250497 Gtype b'lemma:\xce\xb4cra'
3.170468 Supp b'lemma:acetate'
3.124411 O b'lemma:3'
3.062209 O b'lemma:rpob'
3.054282 Phase b'-2:lemma:phase'
3.044351 Gtype b'lemma:\xe2\x88\x86'
2.982673 O b'postag::'
2.975009 O b'-2:lemma:flagtag'
2.948451 Gtype b'-2:lemma:genotype/variation'
2.880650 O b'postag:VBN'
2.875525 O b'lemma:.'
2.875525 O b'postag:.'
2.856618 O b'lemma:-'
2.842211 Technique b'lemma:rna-seq'
2.822332 O b'lemma:b'
2.802827 Gtype b'lemma:type'
2.797366 Gtype b'-1:lemma:\xe2\x88\x86'
2.793829 Supp b'lemma:glucose'
2.734817 Gtype b'-2:lemma:genotype'
2.701420 Supp b'lemma:no3'
2.661946 Air b'lemma:aerobic'
2.652084 Technique b'lemma:chip-seq'
2.649025 O b'lemma:Cra'
2.638351 Air b'postag:RB'
2.590966 O b'-1:lemma:ChIP-exo'
2.579299 Supp b'lemma:Iron'
2.579299 Supp b'-2:lemma:Anaerobic'
2.569436 O b'lemma:a'
2.546577 Med b'lemma:lb'
2.511450 Supp b'-1:lemma:with'
2.503214 Supp b'lemma:nacl'
2.478452 Substrain b'lemma:mg1655'
2.473536 Technique b'+2:lemma:ph5'
2.456529 Supp b'+1:lemma:1'
2.452327 O b'postag:CC'
2.423475 Gtype b'lemma:\xce\xb4fur'
2.368070 Gtype b'lemma:\xce\xb4soxr'
2.360449 Gtype b'lemma:wild-type'
2.352917 Supp b'lemma:nh4cl'
2.349539 O b'+2:lemma:\xc2\xb0c'
2.337254 Med b'lemma:MOPS'
2.321526 Gtype b'lemma:flag-tag'
2.321526 Gtype b'-1:lemma:c-terminal'
2.314837 O b'lemma:CEL'
2.294955 Gtype b'+1:lemma:with'
2.257644 Gtype b'+1:lemma:type'
2.196496 Supp b'+2:lemma:iptg'
2.196469 Supp b'-1:lemma:Cra'
2.175786 Phase b'-1:lemma:mid-log'
2.173685 O b'postag:VBG'
2.163806 pH b'+1:postag:CD'
2.100627 O b'lemma:with'
2.088770 Gversion b'lemma:chip-seq'
2.085539 O b'-1:lemma:tag'
2.069738 O b'lemma:rep2'
2.069674 Supp b'+1:lemma:\xc2\xb5m'
2.060929 O b'lemma:harbor'
2.060390 Temp b'+1:lemma:\xc2\xb0c'
2.022385 Supp b'lemma:nitrate'
1.998316 pH b'lemma:ph5'
1.998316 pH b'+1:lemma:.5'
1.988849 Air b'-1:lemma:ChIP-Seq'
1.977405 Med b'lemma:m63'
1.976213 Temp b'lemma:\xc2\xb0c'
1.971324 Gtype b'lemma:dfnr'
1.969127 O b'+1:lemma:arca-8myc'
1.955303 O b'-1:lemma:0.3'
1.951821 O b'-2:lemma:medium'
1.942893 Supp b'+1:lemma:_'
1.937510 Gtype b'-2:lemma:affyexp'
1.929115 Air b'-2:lemma:IP'
1.905706 Substrain b'+1:lemma:phtpg'
1.898318 Supp b'+1:lemma:2'
1.895488 Technique b'lemma:rnaseq'
1.881491 Supp b'lemma:arginine'
1.871246 Technique b'-2:lemma:Fur'
1.871212 Med b'+2:lemma:b2'
1.868278 Substrain b'-2:lemma:substr'
1.833742 Gtype b'lemma:nsrr'
1.826714 O b'-1:lemma:media'
1.824754 O b'-1:lemma:anaerobic'
1.808509 Supp b'-2:lemma:agent'
1.807657 O b'+1:postag:RB'
1.807328 Gtype b'-1:lemma:rpob'
1.803500 O b'postag:NNS'
1.797656 Technique b'lemma:ChIP-Seq'
1.773838 O b'lemma:chip'
1.773424 Strain b'+1:lemma:substr'
1.773424 Strain b'-2:lemma:str'
1.772977 O b'-1:lemma:glucose'
1.769253 Anti b'+1:lemma:antibody'
1.768929 Gversion b'lemma:.2'
1.768929 Gversion b'-1:lemma:u00096'
1.753884 O b'lemma:\xcf\x8332'
1.753283 O b'-2:lemma:myc'
1.752434 Anti b'+2:lemma:antibody'
1.746191 Gtype b'lemma:pk4854'
1.745489 Technique b'-1:lemma:IP'
1.733914 Supp b'lemma:Leu'
1.733914 Supp b'-2:lemma:Lrp'
1.720315 O b'postag:DT'
1.720167 Strain b'lemma:k-12'
1.714367 Med b'+2:postag:CC'
1.702196 Gtype b'-2:lemma:delta'
1.700861 O b'lemma:argr'
1.699626 O b'+2:postag:JJ'
1.699572 O b'lemma:affyexp'
1.698615 Air b'-1:lemma:-'
1.698323 Air b'lemma:anaeroibc'
1.697509 Temp b'lemma:43'
1.686900 Supp b'lemma:Adenine'
1.667205 O b'lemma:soxs'
1.667205 O b'lemma:soxr'
1.665708 Supp b'lemma:fructose'
1.663126 O b'lemma:ompr'
1.657174 O b'lemma:purr'
1.642276 Technique b'-1:lemma:chip-exo'
1.640609 Gtype b'+1:lemma:ph5'
1.640609 Gtype b'+2:lemma:.5'
1.635130 Temp b'-1:lemma:43'
1.629117 Med b'+1:lemma:0.4'
1.624603 Supp b'-1:postag:CC'
1.623648 O b'+1:lemma:pq'
1.620057 Med b'-1:lemma:in'
1.607167 Technique b'-1:lemma:_'
1.597588 Technique b'-2:lemma:wt'
1.594913 Med b'lemma:minimal'
1.582538 Temp b'-2:lemma:\xcf\x8332'
1.579977 Gversion b'-2:lemma:nc'
1.577928 O b'-1:lemma:\xc2\xb0c'
1.574442 O b'+1:lemma:wt'
1.571857 Supp b'-1:lemma:+'
1.571133 O b'lemma:trpr'
1.568931 O b'lemma:culture'
1.568914 O b'lemma:genotype/variation'
1.567478 Technique b'-1:lemma:input'
1.560894 O b'+1:postag:NNP'
1.559633 O b'-1:lemma:lb'
1.558911 Gtype b'lemma:\xce\xb4ompr'
1.557164 Phase b'+1:lemma:phase'
1.552494 O b'+2:lemma:cra'
1.551712 Supp b'-2:lemma:for'
1.548775 Gtype b'+2:lemma:glucose'
1.548228 Med b'lemma:media'
1.546489 Supp b'lemma:rifampicin'
1.538993 Air b'lemma:anaerobically'
1.538769 Gtype b'lemma:\xce\xb4oxyr'
1.527888 Gversion b'lemma:u00096'
1.527888 Gversion b'+1:lemma:.2'
1.510740 Phase b'lemma:exponential'
1.510740 Phase b'lemma:stationary'
1.504271 O b'+1:lemma:chip-seq'
1.500405 Gversion b'-2:lemma:build'
1.494395 Gtype b'lemma:ptac'
1.491733 O b'-1:lemma:Aerobic'
1.489191 Agit b'lemma:rpm'
1.488153 Technique b'postag:NNP'
1.481440 pH b'lemma:.5'
1.481440 pH b'-1:lemma:ph5'
1.479765 O b'-2:lemma:min'
1.461483 Med b'+2:lemma:b1'
1.458322 O b'lemma:-lrb-'
1.457545 O b'lemma:ml'
1.456515 O b'-1:lemma:type'
1.455521 Phase b'lemma:phase'
1.454471 Temp b'-1:lemma:\xcf\x8332'
1.445071 Gtype b'-2:postag:DT'
1.444366 O b'+1:lemma:od600'
1.441153 Med b'+1:lemma:minimal'
1.435416 O b'-1:lemma:wt'
1.433093 O b'+1:lemma:coli'
1.432963 Gtype b'+1:lemma:_'
1.414930 Gtype b'+1:lemma:flagtag'
1.409771 Med b'lemma:broth'
1.409771 Med b'-1:lemma:L'
1.404102 Gtype b'-1:postag:VBG'
1.402997 O b'+1:lemma:condition'
1.385125 O b'-2:lemma:ChIP-Seq'
1.378975 O b'lemma:Custom'
1.368428 Gtype b'-1:lemma:ptac'
1.367249 Supp b'-2:lemma:condition'
1.365896 Supp b'-1:lemma:_'
1.360344 Gversion b'-2:postag:VB'
1.358613 Gtype b'lemma:arca8myc'
1.358613 Gtype b'-2:lemma:chip-arca'
1.355013 O b'lemma:s'
1.352241 Technique b'-1:lemma:rna-seq'
Top negative:
-0.240864 O b'-1:lemma:n2'
-0.241870 Supp b'+2:postag::'
-0.244948 Supp b'-1:postag:-LRB-'
-0.245788 O b'+1:lemma:_'
-0.250584 O b'+1:lemma:\xc2\xb0c'
-0.251484 Supp b'+1:postag:VBN'
-0.251630 Technique b'-2:postag:NN'
-0.255068 O b'+1:lemma:culture'
-0.255092 O b'lemma:ph'
-0.257956 OD b'+2:postag:NN'
-0.258052 O b'+1:lemma:gade'
-0.259067 Gtype b'-2:postag:CD'
-0.259245 O b'lemma:250'
-0.260012 Phase b'+1:postag:NN'
-0.261463 O b'-1:lemma:sodium'
-0.261463 O b'+2:lemma:1/100'
-0.261641 O b'-1:lemma:1m'
-0.261641 O b'+2:lemma:7.6'
-0.267912 Strain b'postag:NN'
-0.268585 O b'-2:lemma:aerobically'
-0.270821 O b'lemma:0.2'
-0.271046 O b'-2:lemma:2'
-0.273281 Temp b'-1:lemma:\xc2\xb0c'
-0.273389 O b'+1:lemma:mg1655'
-0.275465 Med b'-1:postag:CD'
-0.279720 Supp b'+1:lemma:rifampicin'
-0.282890 O b'+1:postag:IN'
-0.290800 Supp b'+2:lemma:acetate'
-0.293273 O b'-2:lemma:mg1655'
-0.294116 Anti b'+2:postag:JJ'
-0.299017 Supp b'lemma:1'
-0.301190 O b'-1:postag:IN'
-0.309209 Supp b'+1:postag:-RRB-'
-0.311352 Supp b'+2:postag:CC'
-0.313923 O b'+1:postag:VBG'
-0.315176 Supp b'-1:lemma:dpd'
-0.321987 O b'+1:lemma:gadw'
-0.325650 Med b'-1:postag:NN'
-0.327648 O b'lemma:methanol'
-0.327648 O b'-2:lemma:dissolve'
-0.328318 O b'-1:lemma:0.2'
-0.334852 O b'lemma:fecl2'
-0.339654 O b'lemma:anaerobic'
-0.341230 O b'-1:lemma:chip-exo'
-0.353401 O b'-1:lemma:cra'
-0.354424 O b'-2:lemma:anaerobically'
-0.355426 O b'-2:lemma:rpob'
-0.355678 O b'-1:lemma:contain'
-0.361362 O b'+1:lemma:g/l'
-0.361781 O b'lemma:dissolve'
-0.361781 O b'+2:lemma:methanol'
-0.366638 O b'lemma:lb'
-0.367583 Supp b'+1:lemma:fructose'
-0.369374 Med b'+1:postag:NN'
-0.369510 O b'lemma:m63'
-0.370064 O b'-2:lemma:phase'
-0.370439 O b'+1:lemma:minimal'
-0.370982 O b'-2:lemma:pahse'
-0.371136 Supp b'-2:lemma:grow'
-0.375991 Vess b'postag:NN'
-0.378096 O b'+1:lemma:rep2'
-0.378255 O b'+2:lemma:-rrb-'
-0.380278 O b'+2:lemma:at'
-0.384210 O b'-1:lemma:minimal'
-0.388239 O b'-2:lemma:glucose'
-0.391106 Air b'-1:postag:JJ'
-0.391908 O b'-1:lemma:until'
-0.392584 Supp b'+2:lemma:-rrb-'
-0.394595 O b'+1:lemma:Aerobic'
-0.396109 O b'-1:lemma:final'
-0.396858 Med b'+1:postag:IN'
-0.398638 O b'-1:lemma:iptg'
-0.405984 O b'-2:lemma:mm'
-0.412751 O b'-1:lemma:37'
-0.423858 O b'+1:lemma:dissolve'
-0.428909 O b'-2:lemma:supplement'
-0.431989 O b'+1:lemma:m'
-0.436777 Supp b'+2:postag:-RRB-'
-0.437255 Supp b'-1:postag:VBN'
-0.440236 O b'+2:lemma:tag'
-0.446461 Supp b'+1:postag:NNS'
-0.448337 O b'lemma:nitrogen'
-0.452881 Supp b'postag:CC'
-0.454287 Supp b'+2:lemma:glucose'
-0.459760 O b'lemma:minimal'
-0.470804 O b'-2:lemma:nh4cl'
-0.491402 O b'postag:RB'
-0.494015 O b'lemma:37'
-0.499646 O b'-1:lemma:g/l'
-0.502121 O b'+2:lemma:a'
-0.507239 Supp b'+1:lemma:acetate'
-0.509993 O b'-1:lemma:dissolve'
-0.509993 O b'+1:lemma:methanol'
-0.518444 Supp b'-1:postag:NNP'
-0.522170 O b'-1:lemma:grow'
-0.523412 O b'-2:lemma:a'
-0.531453 O b'+1:lemma:1m'
-0.531453 O b'-2:lemma:vol'
-0.534602 O b'+2:lemma:250'
-0.538057 Gtype b'-2:lemma:\xe2\x88\x86'
-0.549372 O b'+2:lemma:then'
-0.549638 O b'+2:lemma:genome'
-0.550134 Supp b'-2:lemma:treat'
-0.556977 O b'-1:lemma:fresh'
-0.558288 O b'-1:lemma:dfnr'
-0.565708 O b'+1:lemma:supplement'
-0.569022 O b'lemma:fructose'
-0.575610 O b'lemma:anaerobically'
-0.577376 O b'-2:lemma:genome'
-0.595858 O b'-2:lemma:fresh'
-0.603206 O b'-2:postag:DT'
-0.608051 O b'+1:lemma:mm'
-0.613648 O b'lemma:glucose'
-0.624344 O b'lemma:k-12'
-0.635426 Supp b'+1:lemma:,'
-0.635426 Supp b'+1:postag:,'
-0.639334 O b'-1:lemma:mm'
-0.646392 O b'-1:lemma:\xe2\x88\x86'
-0.646596 Med b'-2:lemma:grow'
-0.652076 O b'-2:lemma:until'
-0.661116 O b'lemma:2h'
-0.661116 O b'-1:lemma:additional'
-0.663482 O b'-2:postag:RB'
-0.673788 O b'-2:lemma::'
-0.674569 O b'+2:lemma:reference'
-0.683036 O b'+2:lemma:add'
-0.685189 pH b'postag:NN'
-0.685297 O b'postag:VBP'
-0.688346 Med b'+2:postag:VBN'
-0.688555 Supp b'+1:lemma:-lrb-'
-0.690175 Supp b'-2:postag:JJ'
-0.690245 Phase b'postag:JJ'
-0.697689 O b'+2:lemma:10'
-0.703863 Supp b'+1:postag:-LRB-'
-0.708967 Anti b'+1:lemma:anti-fur'
-0.728829 O b'+1:lemma:until'
-0.747693 O b'-1:lemma:ml'
-0.751276 O b'-2:lemma:dpd'
-0.756088 O b'lemma:aerobically'
-0.760131 O b'-1:lemma:30'
-0.766561 O b'lemma:\xe2\x88\x86'
-0.771321 O b'-2:postag:SYM'
-0.778341 O b'-1:lemma:2'
-0.802560 O b'lemma:of'
-0.802884 Med b'-2:postag:VBN'
-0.806377 O b'-1:postag::'
-0.826105 O b'+2:lemma:mid-log'
-0.849054 O b'-2:lemma:media'
-0.867470 O b'-1:lemma:vol'
-0.867470 O b'-2:lemma:1/100'
-0.867470 O b'+2:lemma:1m'
-0.867875 Phase b'-1:postag:JJ'
-0.884642 O b'lemma:nh4cl'
-0.898025 O b'+2:postag:-RRB-'
-0.915346 Temp b'postag:NN'
-0.917405 O b'+2:lemma:+'
-0.919858 O b'-1:lemma:1'
-0.926225 O b'-1:lemma:rpob'
-0.927298 O b'-2:lemma:IP'
-0.934298 O b'lemma:mid-log'
-0.947126 O b'-1:lemma:co2'
-0.947829 Air b'+1:postag:JJ'
-0.976905 O b'+2:lemma:fnr'
-0.983443 Anti b'+2:lemma:polyclonal'
-0.983730 O b'lemma:nitrate'
-0.994076 Supp b'+2:lemma:fructose'
-0.999100 Air b'postag:NN'
-0.999246 O b'-1:lemma:ph'
-1.004751 OD b'+1:postag:NN'
-1.006120 O b'+1:lemma:+'
-1.012830 O b'-2:lemma:0.3'
-1.019854 O b'+2:lemma:b'
-1.020397 O b'+1:lemma:2.0'
-1.043510 O b'-1:lemma:sample'
-1.049774 OD b'+2:lemma:aerobically'
-1.060960 O b'lemma:30'
-1.076454 O b'lemma:rifampicin'
-1.098762 Supp b'+2:postag:CD'
-1.112282 O b'lemma:aerobic'
-1.121896 Gtype b'+2:lemma:cra'
-1.139537 Supp b'+2:lemma:2'
-1.152551 Supp b'+2:lemma:1'
-1.156894 O b'lemma:media'
-1.166267 O b'+1:lemma:at'
-1.166551 O b'-1:lemma:nsrr'
-1.176235 O b'+1:lemma:in'
-1.183711 O b'+2:lemma:rifampicin'
-1.212779 O b'lemma:wt'
-1.245458 O b'-2:lemma:rifampicin'
-1.334770 O b'lemma:\xce\xb4fur'
-1.335529 O b'-1:lemma:IP'
-1.335617 Anti b'postag:NNP'
-1.392108 O b'lemma:0.3'
-1.428060 Gtype b'postag:VBG'
-1.462629 O b'-1:postag:VBG'
-1.559454 Supp b'postag:JJ'
-1.728116 O b'+1:lemma:1'
-2.237261 O b'+1:lemma:2'
-2.735096 O b'-1:lemma::'
-3.093805 O b'-1:lemma:_'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.14456252410554848, 'c2': 0.011570925278244349}
best CV score:0.8716328545433987
model size: 0.08M
Flat F1: 0.7636412886634287
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.870 0.930 23
Med 1.000 0.925 0.961 53
Temp 0.923 0.828 0.873 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.545 0.348 0.425 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.867 0.847 0.857 85
Substrain 0.000 0.000 0.000 0
Supp 0.588 0.799 0.677 134
Gversion 0.000 0.000 0.000 0
avg / total 0.772 0.774 0.764 451
Top likely transitions:
Temp -> Temp 6.024803
Agit -> Agit 5.753028
Supp -> Supp 5.295546
Med -> Med 5.289039
OD -> OD 5.264385
Anti -> Anti 4.686479
Phase -> Phase 4.417910
Gversion -> Gversion 4.395019
Gtype -> Gtype 4.186766
Air -> Air 4.136213
O -> O 3.983716
Technique -> Technique 3.660895
pH -> pH 2.993749
Substrain -> Gtype 1.904754
Gtype -> Supp 1.311934
O -> Supp 1.064130
Air -> O 1.010529
O -> Technique 0.929538
O -> Gtype 0.674914
Gtype -> Air 0.657462
Technique -> Air 0.573565
Supp -> O 0.528829
Temp -> O 0.495755
Med -> O 0.454783
O -> Temp 0.096626
Phase -> O 0.074667
O -> Phase 0.052955
O -> Med 0.050244
Gtype -> pH 0.043509
O -> Anti 0.028320
Gtype -> Technique -0.027765
Agit -> O -0.075594
Technique -> O -0.250844
Gtype -> Med -0.292682
Supp -> Med -0.310233
OD -> Air -0.365882
O -> Air -0.729567
Phase -> OD -0.765060
Gtype -> O -0.784406
Technique -> Gtype -1.361493
Substrain -> O -1.377371
Med -> Supp -1.830126
Top unlikely transitions:
Temp -> Temp 6.024803
Agit -> Agit 5.753028
Supp -> Supp 5.295546
Med -> Med 5.289039
OD -> OD 5.264385
Anti -> Anti 4.686479
Phase -> Phase 4.417910
Gversion -> Gversion 4.395019
Gtype -> Gtype 4.186766
Air -> Air 4.136213
O -> O 3.983716
Technique -> Technique 3.660895
pH -> pH 2.993749
Substrain -> Gtype 1.904754
Gtype -> Supp 1.311934
O -> Supp 1.064130
Air -> O 1.010529
O -> Technique 0.929538
O -> Gtype 0.674914
Gtype -> Air 0.657462
Technique -> Air 0.573565
Supp -> O 0.528829
Temp -> O 0.495755
Med -> O 0.454783
O -> Temp 0.096626
Phase -> O 0.074667
O -> Phase 0.052955
O -> Med 0.050244
Gtype -> pH 0.043509
O -> Anti 0.028320
Gtype -> Technique -0.027765
Agit -> O -0.075594
Technique -> O -0.250844
Gtype -> Med -0.292682
Supp -> Med -0.310233
OD -> Air -0.365882
O -> Air -0.729567
Phase -> OD -0.765060
Gtype -> O -0.784406
Technique -> Gtype -1.361493
Substrain -> O -1.377371
Med -> Supp -1.830126
Top positive:
6.812438 O b'lemma:2'
6.703250 Phase b'lemma:mid-log'
6.559342 O b'lemma:1'
6.133494 Anti b'-2:lemma:antibody'
5.903347 Air b'lemma:anaerobic'
5.834979 O b'-2:lemma:_'
5.776253 Air b'lemma:Aerobic'
5.551637 Gtype b'lemma:wt'
5.548591 Gtype b'lemma:type'
5.516753 O b'lemma:3'
5.468775 O b'-2:lemma:flagtag'
5.270765 Supp b'lemma:pq'
5.224920 Technique b'lemma:chipseq'
5.217760 O b'lemma:_'
5.150603 Technique b'lemma:ChIP-exo'
4.842010 O b'-1:lemma:ChIP-exo'
4.788720 Air b'lemma:aerobic'
4.755345 Gtype b'lemma:\xce\xb4cra'
4.651993 Med b'lemma:MOPS'
4.537114 Gtype b'lemma:\xe2\x88\x86'
4.464327 Gtype b'lemma:wild-type'
4.427065 O b'postag:IN'
4.254029 Supp b'lemma:no3'
4.245214 Gtype b'lemma:flag-tag'
4.245214 Gtype b'-1:lemma:c-terminal'
4.223016 O b'lemma:b'
4.196865 Technique b'lemma:rna-seq'
4.184006 Gtype b'+1:lemma:type'
4.176776 O b'lemma:-'
4.152973 Phase b'-2:lemma:phase'
4.056463 Gtype b'-2:lemma:genotype/variation'
3.986855 Supp b'lemma:Iron'
3.986855 Supp b'-2:lemma:Anaerobic'
3.973602 O b'lemma:rpob'
3.966116 Supp b'lemma:acetate'
3.938991 O b'lemma:.'
3.938991 O b'postag:.'
3.894365 Supp b'lemma:nacl'
3.881738 Gtype b'lemma:\xce\xb4fur'
3.877245 Gtype b'-1:lemma:\xe2\x88\x86'
3.815337 Technique b'lemma:chip-seq'
3.743495 O b'lemma:with'
3.732573 Supp b'lemma:nh4cl'
3.716505 Air b'postag:RB'
3.640623 O b'+2:lemma:\xc2\xb0c'
3.608559 Med b'lemma:lb'
3.571656 O b'postag:VBN'
3.549390 O b'postag:CC'
3.503089 O b'-2:lemma:medium'
3.502227 Gtype b'lemma:dfnr'
3.494672 O b'lemma:a'
3.490805 Supp b'-1:lemma:Cra'
3.447774 Supp b'lemma:nitrate'
3.423108 O b'lemma:Cra'
3.418016 Gtype b'lemma:\xce\xb4soxr'
3.395324 Gtype b'-2:lemma:genotype'
3.386697 Supp b'lemma:glucose'
3.344372 Technique b'+2:lemma:ph5'
3.251866 Supp b'-1:lemma:with'
3.249713 O b'postag::'
3.200140 Gtype b'-2:lemma:affyexp'
3.182935 Supp b'lemma:arginine'
3.180726 Gversion b'lemma:chip-seq'
3.161435 Technique b'lemma:rnaseq'
3.148795 Supp b'+2:lemma:iptg'
3.067497 Substrain b'lemma:mg1655'
3.056568 O b'lemma:CEL'
3.013304 Med b'lemma:m63'
3.005306 Gtype b'-2:lemma:delta'
3.005008 O b'lemma:harbor'
3.001202 Air b'-1:lemma:ChIP-Seq'
2.966077 O b'-1:lemma:\xc2\xb0c'
2.927961 Gtype b'lemma:nsrr'
2.909022 Gtype b'lemma:pk4854'
2.878177 Air b'-2:lemma:IP'
2.876549 Technique b'lemma:ChIP-Seq'
2.870544 O b'+1:lemma:arca-8myc'
2.865302 O b'-2:lemma:myc'
2.847767 Technique b'-2:lemma:Fur'
2.847429 Gtype b'+1:lemma:with'
2.829243 O b'-1:lemma:0.3'
2.778649 O b'lemma:rep2'
2.776931 Technique b'-1:lemma:IP'
2.773491 Supp b'+1:lemma:\xc2\xb5m'
2.763337 O b'postag:DT'
2.746233 Supp b'+1:lemma:1'
2.744343 Anti b'+2:lemma:antibody'
2.730395 O b'lemma:chip'
2.728846 O b'-1:lemma:tag'
2.664541 O b'-1:lemma:media'
2.622991 Supp b'lemma:rifampicin'
2.586777 Temp b'-1:lemma:\xcf\x8332'
2.573215 Gtype b'+1:lemma:ph5'
2.573215 Gtype b'+2:lemma:.5'
2.566604 O b'-1:lemma:lb'
2.552670 Temp b'-2:lemma:\xcf\x8332'
2.541452 O b'-1:lemma:type'
2.526524 pH b'+1:postag:CD'
2.516979 O b'-1:lemma:glucose'
2.501080 Technique b'-1:lemma:chip-exo'
2.497698 Gtype b'lemma:\xce\xb4ompr'
2.495468 Substrain b'-2:lemma:substr'
2.481730 O b'postag:VBG'
2.475769 Med b'+2:lemma:b2'
2.463569 Gtype b'lemma:\xce\xb4oxyr'
2.457060 O b'+1:postag:RB'
2.438239 Temp b'lemma:43'
2.435108 Supp b'lemma:Leu'
2.435108 Supp b'-2:lemma:Lrp'
2.434323 O b'-2:lemma:min'
2.423093 Supp b'-2:lemma:agent'
2.399905 O b'+1:postag:NNP'
2.392843 Anti b'+1:lemma:antibody'
2.387723 Supp b'-1:lemma:+'
2.375278 O b'lemma:ompr'
2.375177 O b'lemma:ml'
2.351025 O b'+2:lemma:cra'
2.328145 Supp b'-2:lemma:media'
2.315613 pH b'lemma:ph5'
2.315613 pH b'+1:lemma:.5'
2.295509 Phase b'lemma:exponential'
2.295509 Phase b'lemma:stationary'
2.282923 Strain b'+1:lemma:substr'
2.282923 Strain b'-2:lemma:str'
2.282875 Gversion b'lemma:.2'
2.282875 Gversion b'-1:lemma:u00096'
2.271205 Supp b'+1:lemma:2'
2.268299 Air b'lemma:anaeroibc'
2.262222 Air b'-1:lemma:-'
2.253598 O b'lemma:s'
2.235400 Temp b'-1:lemma:43'
2.227662 Phase b'lemma:phase'
2.215669 Phase b'-1:lemma:mid-log'
2.203744 Med b'+2:postag:CC'
2.189036 Substrain b'+1:lemma:phtpg'
2.178331 Gtype b'-1:lemma:rpob'
2.173660 Strain b'lemma:k-12'
2.160417 Gtype b'-1:postag:VBG'
2.141054 Agit b'+2:lemma:at'
2.140046 Med b'lemma:broth'
2.140046 Med b'-1:lemma:L'
2.132754 Temp b'+1:lemma:\xc2\xb0c'
2.122883 O b'lemma:soxs'
2.122883 O b'lemma:soxr'
2.115213 O b'postag:VBD'
2.111512 O b'lemma:\xcf\x8332'
2.083781 Agit b'lemma:rpm'
2.051564 O b'lemma:culture'
2.049120 O b'+1:lemma:condition'
2.041245 Gversion b'lemma:nc'
2.038470 O b'+1:lemma:250'
2.033120 O b'lemma:Custom'
2.025823 O b'postag:NNS'
2.016924 O b'+2:lemma:70'
2.010539 O b'+2:postag:JJ'
2.006555 O b'-1:lemma:aerobically'
1.996814 O b'-2:lemma:~'
1.984709 O b'+2:lemma:polyclonal'
1.976905 Supp b'lemma:Adenine'
1.976120 Technique b'-1:lemma:input'
1.964721 Air b'lemma:aerobically'
1.957500 Gversion b'lemma:u00096'
1.957500 Gversion b'+1:lemma:.2'
1.944301 O b'+1:lemma:chip-seq'
1.944163 Temp b'-1:lemma:sample'
1.935179 O b'lemma:trpr'
1.934476 O b'+1:lemma:coli'
1.932800 Supp b'lemma:fructose'
1.929974 Med b'lemma:media'
1.923950 O b'-1:lemma:anaerobic'
1.922151 Gversion b'+2:lemma:000913'
1.917131 Temp b'lemma:\xc2\xb0c'
1.887292 OD b'lemma:od450'
1.883152 Agit b'+1:lemma:rpm'
1.879063 Gtype b'lemma:ptac'
1.875710 O b'+1:lemma:pq'
1.873042 O b'+2:lemma:fructose'
1.856178 Supp b'+1:lemma:_'
1.855822 Gtype b'-1:lemma:ptac'
1.853574 Supp b'+2:lemma:rifampicin'
1.850128 Med b'+2:lemma:b1'
1.848750 O b'-1:lemma:into'
1.826684 Gversion b'-2:lemma:nc'
1.820054 Supp b'+2:lemma:feso4'
1.808700 Supp b'-2:lemma:condition'
1.799712 O b'-1:lemma:Aerobic'
1.787048 Med b'+1:lemma:0.4'
1.768038 O b'lemma:argr'
1.752493 Supp b'-2:lemma:induce'
1.749745 O b'+1:lemma:acetate'
1.744647 O b'+1:lemma:od600'
1.730393 O b'lemma:genotype/variation'
1.700932 Gtype b'-2:postag:DT'
1.688694 Gtype b'+1:lemma:flagtag'
1.685861 Gversion b'-2:lemma:build'
1.683071 Supp b'-2:lemma:purr'
1.676299 Gversion b'lemma:asm584v2'
1.648539 Technique b'-1:lemma:rna-seq'
1.647830 Air b'+2:lemma:L'
1.643928 Med b'-1:lemma:in'
Top negative:
-0.078150 O b'-2:lemma:0.1'
-0.081643 O b'lemma:methanol'
-0.081643 O b'-2:lemma:dissolve'
-0.082341 Supp b'-2:postag:-LRB-'
-0.086140 Supp b'-1:lemma:dpd'
-0.088476 Air b'-1:lemma:or'
-0.088979 Supp b'+2:postag:NN'
-0.089036 Supp b'+2:postag:NNP'
-0.089839 O b'+1:lemma:ph'
-0.091080 O b'-1:lemma:0.2'
-0.092461 Technique b'-1:postag::'
-0.092726 Agit b'postag:NN'
-0.097852 Med b'-1:postag:IN'
-0.100389 Supp b'+2:lemma:.'
-0.100389 Supp b'+2:postag:.'
-0.100772 Strain b'postag:NN'
-0.101155 O b'lemma:\xe2\x88\x86'
-0.101175 O b'+2:lemma:supplement'
-0.103582 O b'+1:lemma:of'
-0.104478 O b'-1:lemma:37'
-0.104623 Technique b'-2:postag:NN'
-0.106509 O b'-1:lemma:iptg'
-0.106780 O b'+2:lemma:ph'
-0.107862 Air b'-2:postag:CC'
-0.109728 O b'+1:lemma:.'
-0.109728 O b'+1:postag:.'
-0.113993 Supp b'-1:lemma:10'
-0.114214 O b'lemma:7.6'
-0.114214 O b'+1:lemma:;'
-0.115982 Agit b'-1:postag:NN'
-0.119361 O b'-1:lemma:until'
-0.124272 Gtype b'-2:postag:CD'
-0.129779 O b'lemma:;'
-0.129779 O b'-1:lemma:7.6'
-0.136518 O b'+1:postag:-LRB-'
-0.139593 O b'-1:lemma:of'
-0.140386 O b'+1:lemma:a'
-0.142883 O b'+1:lemma:95'
-0.143055 O b'-2:lemma:pahse'
-0.149480 O b'-2:lemma:the'
-0.150711 O b'-1:lemma:contain'
-0.151497 Temp b'-2:postag:NN'
-0.151937 O b'-2:postag::'
-0.153171 O b'+2:lemma:-rrb-'
-0.153549 Supp b'postag:CC'
-0.158194 O b'+1:lemma:fecl2'
-0.160887 Supp b'+1:lemma:-rrb-'
-0.161707 Supp b'+2:lemma:dpd'
-0.166764 O b'-2:lemma:phase'
-0.171348 Supp b'+1:lemma:acetate'
-0.171861 O b'-1:lemma:sodium'
-0.171861 O b'+2:lemma:1/100'
-0.178092 Supp b'-1:lemma:-lrb-'
-0.181338 O b'lemma:dissolve'
-0.181338 O b'+2:lemma:methanol'
-0.187811 Supp b'+2:lemma:glucose'
-0.194739 O b'-1:lemma:1m'
-0.194739 O b'+2:lemma:7.6'
-0.197753 Supp b'-1:postag:-LRB-'
-0.199612 Med b'-1:postag:NN'
-0.202024 O b'-1:lemma:n2'
-0.203121 Med b'+1:postag:IN'
-0.207404 O b'lemma:ph'
-0.210173 O b'-2:lemma:aerobically'
-0.225375 O b'-1:lemma:cra'
-0.226782 O b'+2:lemma:reference'
-0.229562 O b'-2:lemma:genome'
-0.233367 O b'-2:lemma:dpd'
-0.239153 Supp b'+1:postag:VBN'
-0.249635 O b'-1:postag:IN'
-0.252658 Med b'postag:CD'
-0.254030 Med b'+1:postag:NN'
-0.256499 O b'lemma:fecl2'
-0.259528 Supp b'-2:postag:NNS'
-0.262022 O b'-1:lemma:ml'
-0.263583 Air b'+2:postag:IN'
-0.268766 O b'-2:lemma:mm'
-0.270868 O b'+1:postag:IN'
-0.271998 O b'+2:lemma:250'
-0.273382 O b'+1:lemma:%'
-0.280464 Supp b'+1:postag:-RRB-'
-0.288772 O b'+2:lemma:.'
-0.288772 O b'+2:postag:.'
-0.293729 Gtype b'-1:postag:NN'
-0.294905 Med b'-1:postag:CD'
-0.308324 Phase b'-2:postag:NN'
-0.328837 O b'-2:lemma:anaerobically'
-0.334523 O b'lemma:37'
-0.338413 O b'-1:lemma:fresh'
-0.346729 O b'-2:lemma:rpob'
-0.351198 Gtype b'-2:lemma:\xe2\x88\x86'
-0.355232 Supp b'+2:lemma:-rrb-'
-0.356631 O b'lemma:mid-log'
-0.357653 O b'-1:lemma:minimal'
-0.359546 O b'+1:lemma:+'
-0.363243 O b'+1:lemma:minimal'
-0.365382 O b'-2:lemma:until'
-0.385235 O b'+2:lemma:at'
-0.389156 Anti b'+2:postag:JJ'
-0.391480 O b'+1:lemma:g/l'
-0.399222 Supp b'+2:postag:-RRB-'
-0.412306 O b'lemma:minimal'
-0.429953 O b'+1:lemma:1m'
-0.429953 O b'-2:lemma:vol'
-0.431351 O b'lemma:nitrate'
-0.432398 O b'-2:lemma:media'
-0.449447 Supp b'+1:lemma:rifampicin'
-0.451303 O b'-2:lemma:fresh'
-0.457431 O b'+1:lemma:supplement'
-0.461836 Supp b'-1:postag:NNP'
-0.463561 O b'+1:postag:VBG'
-0.472320 Anti b'+1:lemma:anti-fur'
-0.484075 O b'lemma:aerobically'
-0.484194 O b'-1:postag::'
-0.498931 Supp b'+1:postag:NNS'
-0.503746 Supp b'+1:lemma:,'
-0.503746 Supp b'+1:postag:,'
-0.516754 Supp b'-2:lemma:treat'
-0.528514 O b'+2:lemma:add'
-0.529405 O b'-2:lemma:glucose'
-0.533457 O b'+1:lemma:mm'
-0.546157 Supp b'lemma:10'
-0.565127 Supp b'+1:lemma:-lrb-'
-0.566088 Med b'-2:postag:VBN'
-0.566661 O b'-1:lemma:dissolve'
-0.566661 O b'+1:lemma:methanol'
-0.570423 O b'lemma:wt'
-0.580351 O b'-2:lemma:supplement'
-0.586279 Phase b'+1:postag:NN'
-0.593248 Supp b'+1:postag:-LRB-'
-0.597210 O b'-1:lemma:grow'
-0.598482 O b'-1:lemma:co2'
-0.601257 O b'lemma:anaerobically'
-0.603375 O b'-2:lemma::'
-0.604605 O b'+2:lemma:10'
-0.608424 Med b'+2:postag:VBN'
-0.640686 O b'-1:lemma:rpob'
-0.648211 O b'-1:lemma:mm'
-0.677339 O b'+2:lemma:a'
-0.691258 pH b'postag:NN'
-0.714470 O b'-2:postag:SYM'
-0.753388 O b'-2:postag:RB'
-0.759391 O b'-1:lemma:vol'
-0.759391 O b'-2:lemma:1/100'
-0.759391 O b'+2:lemma:1m'
-0.777706 O b'+2:lemma:fnr'
-0.785687 O b'lemma:aerobic'
-0.789592 Air b'+1:postag:JJ'
-0.815302 O b'postag:VBP'
-0.841098 O b'lemma:2h'
-0.841098 O b'-1:lemma:additional'
-0.842931 O b'+2:lemma:mid-log'
-0.851282 O b'+2:lemma:then'
-0.861129 O b'+1:lemma:until'
-0.862940 Supp b'-2:postag:JJ'
-0.870874 O b'+2:postag:-RRB-'
-0.875415 O b'-2:lemma:2'
-0.885220 O b'lemma:of'
-0.896666 O b'-1:lemma:30'
-0.902553 Air b'postag:NN'
-0.931783 O b'+2:lemma:+'
-0.932080 O b'-2:postag:DT'
-1.044263 O b'+2:lemma:b'
-1.102463 O b'lemma:rifampicin'
-1.119605 O b'lemma:\xce\xb4fur'
-1.163234 O b'lemma:media'
-1.202846 O b'-1:lemma:ph'
-1.209159 O b'-1:lemma:nsrr'
-1.238185 O b'-1:lemma:2'
-1.242160 O b'+1:lemma:at'
-1.252527 Temp b'postag:NN'
-1.263981 Med b'-2:lemma:grow'
-1.295021 O b'-2:lemma:0.3'
-1.322790 Phase b'-1:postag:JJ'
-1.350768 O b'-1:lemma:IP'
-1.357106 Gtype b'+2:lemma:cra'
-1.384802 O b'+1:lemma:in'
-1.421905 O b'+1:lemma:2.0'
-1.436909 OD b'+1:postag:NN'
-1.437140 Anti b'+2:lemma:polyclonal'
-1.442674 Supp b'+2:lemma:2'
-1.474029 O b'-1:postag:VBG'
-1.510725 O b'-1:lemma:1'
-1.511208 O b'+2:lemma:rifampicin'
-1.539773 Supp b'+2:lemma:1'
-1.576652 O b'-1:lemma:sample'
-1.596285 Supp b'+2:postag:CD'
-1.602706 Supp b'+2:lemma:fructose'
-1.609888 OD b'+2:lemma:aerobically'
-1.653266 O b'-2:lemma:rifampicin'
-1.693828 O b'lemma:30'
-1.745628 Supp b'postag:JJ'
-1.754845 Phase b'postag:JJ'
-2.081244 Gtype b'postag:VBG'
-2.085569 O b'lemma:0.3'
-2.233412 O b'+1:lemma:1'
-2.309269 Anti b'postag:NNP'
-2.656990 O b'+1:lemma:2'
-3.924521 O b'-1:lemma::'
-4.650524 O b'-1:lemma:_'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.044162082189650204, 'c2': 0.029804343353737328}
best CV score:0.8706581096952577
model size: 0.14M
Flat F1: 0.7969827918323339
precision recall f1-score support
OD 0.818 0.818 0.818 22
pH 1.000 1.000 1.000 8
Technique 1.000 1.000 1.000 23
Med 1.000 0.962 0.981 53
Temp 0.923 0.828 0.873 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.556 0.362 0.439 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.875 0.824 0.848 85
Substrain 0.000 0.000 0.000 0
Supp 0.752 0.813 0.781 134
Gversion 0.000 0.000 0.000 0
avg / total 0.815 0.787 0.797 451
Top likely transitions:
Supp -> Supp 5.670083
Temp -> Temp 5.254231
Agit -> Agit 5.011354
Med -> Med 4.713332
OD -> OD 4.391989
Anti -> Anti 4.030410
O -> O 3.948161
Gtype -> Gtype 3.922534
Phase -> Phase 3.864108
Gversion -> Gversion 3.673104
Air -> Air 3.570167
Technique -> Technique 3.152316
pH -> pH 2.370151
Substrain -> Gtype 1.132148
O -> Technique 0.880743
Air -> O 0.699229
Supp -> O 0.507469
O -> Supp 0.436503
Gtype -> Supp 0.431300
Technique -> Air 0.416894
Gtype -> Air 0.341610
Temp -> O 0.264669
O -> Gtype 0.262204
O -> Temp 0.066407
Med -> O 0.014255
pH -> O 0.001942
OD -> Technique -0.000000
Supp -> Air -0.000026
Supp -> Gversion -0.000029
Med -> Air -0.000244
O -> Anti -0.000275
Gversion -> Technique -0.000419
Air -> Technique -0.005983
Gversion -> Gtype -0.043836
Supp -> Phase -0.058360
Technique -> Supp -0.061859
Gtype -> Substrain -0.064135
Phase -> O -0.078917
Phase -> Air -0.082322
Gtype -> Temp -0.084430
OD -> O -0.091084
Phase -> Med -0.098419
O -> Phase -0.106844
Anti -> Supp -0.110681
Gtype -> OD -0.111764
OD -> Supp -0.112906
O -> Gversion -0.170423
Gversion -> Supp -0.175049
Air -> Phase -0.184406
Supp -> Gtype -0.187183
Top unlikely transitions:
O -> Anti -0.000275
Gversion -> Technique -0.000419
Air -> Technique -0.005983
Gversion -> Gtype -0.043836
Supp -> Phase -0.058360
Technique -> Supp -0.061859
Gtype -> Substrain -0.064135
Phase -> O -0.078917
Phase -> Air -0.082322
Gtype -> Temp -0.084430
OD -> O -0.091084
Phase -> Med -0.098419
O -> Phase -0.106844
Anti -> Supp -0.110681
Gtype -> OD -0.111764
OD -> Supp -0.112906
O -> Gversion -0.170423
Gversion -> Supp -0.175049
Air -> Phase -0.184406
Supp -> Gtype -0.187183
Technique -> OD -0.190052
Gtype -> Gversion -0.198104
Phase -> Technique -0.204487
Phase -> Supp -0.209738
Gtype -> Phase -0.221329
Phase -> OD -0.244051
Anti -> Gtype -0.311771
Air -> Med -0.321626
Air -> Gtype -0.339099
Air -> Temp -0.358085
Air -> Agit -0.378119
Gtype -> Anti -0.413121
O -> Med -0.423939
Agit -> Air -0.427878
Technique -> pH -0.452260
Technique -> Gtype -0.453250
Gversion -> O -0.456685
Supp -> Technique -0.471510
Temp -> Med -0.480258
OD -> Air -0.496263
Air -> Supp -0.503893
Technique -> O -0.618334
O -> OD -0.660464
Gtype -> Med -0.752077
Gtype -> Technique -0.755956
Gtype -> O -0.808067
Supp -> Med -0.862326
Substrain -> O -1.074379
O -> Air -1.358505
Med -> Supp -1.446843
Top positive:
4.573871 O b'lemma:2'
4.517132 Anti b'-2:lemma:antibody'
3.918900 O b'lemma:1'
3.762153 O b'-2:lemma:_'
3.676989 Air b'word[:2]:Ae'
3.513121 Technique b'word[:2]:Ch'
3.487470 O b'word[:2]:re'
3.453615 O b'lemma:3'
3.410530 Gtype b'word[:1]:\xce\x94'
3.253388 Phase b'-2:lemma:phase'
3.161045 Supp b'lemma:acetate'
3.107117 O b'lemma:with'
3.044380 O b'lemma:_'
3.044380 O b'word[:1]:_'
2.983175 OD b'word[:1]:O'
2.941437 Supp b'-1:lemma:with'
2.930652 Gtype b'-1:lemma:\xe2\x88\x86'
2.920959 Phase b'lemma:mid-log'
2.889906 Air b'lemma:anaerobic'
2.870929 O b'lemma:a'
2.822057 Air b'word[:2]:An'
2.820469 Supp b'lemma:arginine'
2.801859 Air b'word[:1]:A'
2.780610 Supp b'-1:lemma:Cra'
2.651063 O b'lemma:-'
2.650338 Supp b'-1:lemma:final'
2.629666 O b'-2:lemma:myc'
2.548913 O b'-1:lemma:tag'
2.540238 Supp b'+2:lemma:iptg'
2.444337 Supp b'word[:1]:I'
2.424276 O b'-2:lemma:medium'
2.416308 O b'+2:lemma:\xc2\xb0c'
2.367304 Technique b'word[:2]:RN'
2.366428 Supp b'-1:postag:CC'
2.323976 Supp b'+1:lemma:1'
2.323481 Anti b'+1:lemma:antibody'
2.296032 O b'lemma:.'
2.296032 O b'postag:.'
2.296032 O b'postag[:1]:.'
2.293419 Gtype b'-2:lemma:genotype/variation'
2.263949 Substrain b'word[:2]:MG'
2.253514 Anti b'+2:lemma:antibody'
2.234802 Supp b'lemma:Iron'
2.234802 Supp b'word[:2]:Ir'
2.234802 Supp b'-2:lemma:Anaerobic'
2.224903 Supp b'lemma:pq'
2.224903 Supp b'word[:2]:PQ'
2.221321 Gtype b'lemma:type'
2.221321 Gtype b'word[:2]:ty'
2.211713 Supp b'+1:lemma:\xc2\xb5m'
2.185949 O b'-1:lemma:glucose'
2.178554 Gtype b'word[:2]:Fl'
2.176096 Gtype b'hGreek'
2.169798 O b'+1:postag:RB'
2.145528 O b'-1:lemma:0.3'
2.123487 Gtype b'lemma:wt'
2.107697 Supp b'-1:lemma:_'
2.097155 O b'word[:2]:Cr'
2.082178 Supp b'lemma:nacl'
2.060364 Med b'lemma:MOPS'
2.060364 Med b'word[:2]:MO'
2.053231 Med b'+2:postag:CC'
2.051275 Supp b'word[:2]:ni'
2.042917 pH b'word[:2]:pH'
2.031673 O b'word[:2]:ge'
2.021947 Substrain b'word[:1]:M'
2.011615 O b'lemma:argr'
2.001860 O b'-2:lemma:fructose'
1.996958 O b'lemma:purr'
1.986551 O b'+1:lemma:pq'
1.984749 O b'word[:1]:B'
1.982332 Technique b'word[:1]:R'
1.981990 Phase b'lemma:stationary'
1.934014 O b'word[:2]:Rp'
1.932482 O b'-1:lemma:anaerobic'
1.924219 Gtype b'lemma:\xe2\x88\x86'
1.924219 Gtype b'word[:1]:\xe2\x88\x86'
1.895338 Supp b'+1:lemma:2'
1.878701 Gtype b'word[:1]:W'
1.876510 O b'word[:1]:G'
1.858152 Gtype b'-2:postag:DT'
1.836059 O b'+2:lemma:cra'
1.828873 O b'word[:2]:Pu'
1.827035 OD b'word[:2]:OD'
1.822540 O b'word[:1]:S'
1.806311 O b'postag::'
1.806311 O b'postag[:1]::'
1.800600 pH b'+1:postag:CD'
1.791696 O b'word[:1]:c'
1.789516 O b'-2:lemma:ChIP-Seq'
1.783076 O b'+2:lemma:70'
1.779545 Air b'lemma:Aerobic'
1.771582 Gversion b'lemma:chip-seq'
1.766211 Med b'word[:1]:L'
1.758126 O b'+2:lemma:fructose'
1.756952 O b'-1:lemma:media'
1.756327 O b'lemma:b'
1.748259 O b'word[:2]:ch'
1.737653 O b'+1:lemma:250'
1.731658 Supp b'lemma:nitrate'
1.713215 Gtype b'+1:lemma:type'
1.710562 Med b'word[:1]:M'
1.691656 Phase b'+1:lemma:phase'
1.685599 Gtype b'word[:1]:d'
1.683678 Temp b'+1:lemma:\xc2\xb0c'
1.683098 Supp b'-1:lemma:+'
1.680349 O b'-1:lemma:aerobically'
1.679518 Supp b'+2:lemma:for'
1.667720 Phase b'word[:2]:ex'
1.664701 Supp b'word[:2]:ac'
1.660497 Gtype b'word[:1]:F'
1.651765 Gtype b'word[:2]:PK'
1.639770 Gtype b'lemma:flag-tag'
1.639770 Gtype b'-1:lemma:c-terminal'
1.636705 Supp b'-2:lemma:argr'
1.635237 Gtype b'word[:2]:WT'
1.629154 O b'lemma:Nac'
1.628538 Air b'word[:1]:a'
1.628414 Med b'lemma:minimal'
1.627212 O b'word[:2]:ha'
1.626169 Gtype b'+1:lemma:with'
1.625888 O b'+1:postag:NNP'
1.619736 O b'+1:lemma:chip-seq'
1.607311 Supp b'lemma:fructose'
1.604728 Gtype b'-2:lemma:genotype'
1.603557 Gtype b'lemma:nsrr'
1.603557 Gtype b'word[:2]:Ns'
1.603074 Supp b'lemma:glucose'
1.602745 O b'-1:lemma:\xc2\xb0c'
1.598758 Med b'+2:lemma:b2'
1.598354 Gtype b'-1:lemma:_'
1.594027 Supp b'lemma:Leu'
1.594027 Supp b'word[:2]:Le'
1.594027 Supp b'-2:lemma:Lrp'
1.591661 O b'lemma:A'
1.582547 O b'-1:lemma:Aerobic'
1.575327 Supp b'+1:lemma:_'
1.570281 O b'word[:1]:R'
1.568703 O b'-2:lemma:flagtag'
1.565893 Phase b'+2:lemma:o.d.'
1.551889 Supp b'lemma:no3'
1.551889 Supp b'word[:2]:NO'
1.548644 Gtype b'+1:lemma:flagtag'
1.540544 Supp b'-2:lemma:media'
1.538313 O b'+1:lemma:od600'
1.531185 Supp b'-2:lemma:induce'
1.528143 Temp b'-1:lemma:43'
1.521079 Supp b'word[:2]:Fe'
1.519815 Gtype b'+2:lemma:glucose'
1.509812 Supp b'word[:2]:gl'
1.505012 O b'-1:lemma:lb'
1.504397 Supp b'lemma:Adenine'
1.504397 Supp b'word[:2]:Ad'
1.493982 Air b'-2:lemma:%'
1.493425 Technique b'word[:1]:C'
1.484047 Technique b'lemma:ChIP-exo'
1.484009 Supp b'+2:lemma:rifampicin'
1.481786 Supp b'-2:lemma:purr'
1.476648 Supp b'-1:lemma:sodium'
1.476648 Supp b'+2:lemma:1/100'
1.475748 Temp b'lemma:43'
1.475748 Temp b'word[:2]:43'
1.475312 Anti b'word[:2]:an'
1.472220 Temp b'-2:lemma:\xcf\x8332'
1.460306 Supp b'-2:lemma:condition'
1.458045 Temp b'-1:lemma:\xcf\x8332'
1.452126 O b'postag:IN'
1.452126 O b'postag[:1]:I'
1.452126 O b'postag[:2]:IN'
1.446316 Gtype b'-1:lemma:rpob'
1.445179 O b'+2:postag:JJ'
1.441264 Gtype b'word[:1]:w'
1.409352 Supp b'-2:lemma:agent'
1.398563 Phase b'word[:1]:e'
1.391992 Gtype b'-2:lemma:delta'
1.390517 Strain b'+1:lemma:substr'
1.390517 Strain b'-2:lemma:str'
1.386478 O b'word[:1]:-'
1.383676 O b'-2:lemma:no3'
1.382867 Supp b'word[:1]:N'
1.379586 O b'lemma:growth'
1.375672 O b'word[:2]:In'
1.373601 O b'-2:lemma:='
1.372653 Air b'+1:postag:IN'
1.369649 Air b'-1:lemma:ChIP-Seq'
1.366267 Technique b'+2:lemma:ph5'
1.363638 O b'postag:CC'
1.363638 O b'postag[:2]:CC'
1.362930 Air b'-2:lemma:IP'
1.357050 Gtype b'-1:postag:VBG'
1.356760 Gtype b'word[:2]:Ar'
1.356125 pH b'word[:1]:p'
1.352664 Gtype b'lemma:arca8myc'
1.352664 Gtype b'-2:lemma:chip-arca'
1.351882 Gversion b'-2:lemma:build'
1.351286 Substrain b'+1:lemma:phtpg'
1.349261 Gtype b'symb'
1.346252 Gtype b'-2:lemma:affyexp'
1.345488 Air b'lemma:aerobic'
1.336503 pH b'lemma:ph5'
Top negative:
-0.330183 O b'lemma:aerobically'
-0.333091 Gtype b'word[:1]:-'
-0.337229 O b'+2:lemma:for'
-0.338988 Anti b'+2:postag:JJ'
-0.340025 Phase b'+1:lemma:pahse'
-0.345106 O b'+1:lemma:phosphate'
-0.350740 O b'-2:lemma:fresh'
-0.359220 Supp b'+2:postag:NNP'
-0.360686 O b'lemma:glucose'
-0.363021 Technique b'lemma:chip-exo'
-0.365042 O b'lemma:sodium'
-0.374157 Supp b'+2:postag::'
-0.387303 O b'-2:lemma:a'
-0.389190 Supp b'-2:postag:NNS'
-0.391761 O b'+2:lemma:0.2'
-0.392117 O b'-1:lemma:g/l'
-0.393789 O b'lemma:250'
-0.396500 Supp b'postag:JJ'
-0.398947 Supp b'postag[:1]:J'
-0.398947 Supp b'postag[:2]:JJ'
-0.401893 O b'-2:postag:SYM'
-0.403955 O b'word[:2]:me'
-0.405899 O b'-1:lemma:contain'
-0.407741 O b'+2:lemma:at'
-0.407872 O b'-2:postag:DT'
-0.409919 Vess b'hUpper'
-0.409919 Vess b'hLower'
-0.416096 Air b'postag:NN'
-0.419923 Supp b'-2:postag:NN'
-0.420193 Supp b'-1:lemma:-lrb-'
-0.422451 O b'+1:lemma:supplement'
-0.426042 Med b'+1:postag:IN'
-0.428819 Supp b'+2:lemma:acetate'
-0.433421 Temp b'postag:NN'
-0.442149 Supp b'+2:postag:NN'
-0.442542 O b'word[:1]:F'
-0.448178 Phase b'postag:JJ'
-0.453154 Temp b'hGreek'
-0.454481 O b'+2:lemma:genome'
-0.456569 Supp b'-2:lemma:grow'
-0.456675 Supp b'+2:lemma:glucose'
-0.461633 O b'lemma:methanol'
-0.461633 O b'-2:lemma:dissolve'
-0.463555 Supp b'-1:postag:-LRB-'
-0.470483 O b'word[:2]:ce'
-0.474148 O b'word[:1]:K'
-0.478774 OD b'+2:postag:NN'
-0.479416 O b'-1:lemma:iptg'
-0.482417 O b'-1:lemma:ml'
-0.482582 Med b'-2:postag:VBN'
-0.493533 O b'+1:postag:IN'
-0.494661 O b'-2:lemma:phase'
-0.500742 O b'lemma:37'
-0.500742 O b'word[:2]:37'
-0.503770 Gtype b'+1:lemma:-rrb-'
-0.509384 O b'-1:lemma:grow'
-0.512233 O b'+1:lemma:m'
-0.512351 Gtype b'word[:1]:h'
-0.529387 O b'+2:lemma:reference'
-0.532265 O b'lemma:anaerobically'
-0.540496 O b'word[:2]:mg'
-0.548480 O b'word[:2]:pH'
-0.550459 Gtype b'-1:lemma:mg1655'
-0.550831 Supp b'-1:postag:NNP'
-0.554325 O b'word[:2]:Fe'
-0.555780 O b'+2:lemma:.'
-0.555780 O b'+2:postag:.'
-0.565490 O b'word[:1]:\xce\x94'
-0.573716 O b'lemma:aerobic'
-0.581553 O b'-2:postag:RB'
-0.582735 O b'-1:lemma:dissolve'
-0.582735 O b'+1:lemma:methanol'
-0.583732 O b'-1:lemma:fresh'
-0.584010 O b'-2:lemma:nh4cl'
-0.585197 O b'word[:2]:ri'
-0.587643 Phase b'postag[:1]:J'
-0.587643 Phase b'postag[:2]:JJ'
-0.594097 O b'-2:lemma:genome'
-0.594675 Supp b'-2:lemma:treat'
-0.594880 O b'+1:lemma:1m'
-0.594880 O b'-2:lemma:vol'
-0.598558 O b'-1:lemma:30'
-0.612132 O b'lemma:2h'
-0.612132 O b'-1:lemma:additional'
-0.612132 O b'word[:2]:2h'
-0.614071 O b'-2:lemma:control'
-0.625762 O b'-1:lemma:until'
-0.628113 Agit b'hUpper'
-0.628113 Agit b'hLower'
-0.629464 O b'+1:postag:VBG'
-0.630986 O b'-2:lemma:aerobically'
-0.640153 O b'-2:lemma:pahse'
-0.640520 O b'lemma:media'
-0.645230 O b'+2:lemma:fnr'
-0.647923 O b'lemma:\xe2\x88\x86'
-0.647923 O b'word[:1]:\xe2\x88\x86'
-0.648261 Supp b'+1:lemma:-lrb-'
-0.648721 O b'+2:lemma:10'
-0.649047 Med b'symb'
-0.658009 O b'-1:lemma:vol'
-0.658009 O b'-2:lemma:1/100'
-0.658009 O b'+2:lemma:1m'
-0.658618 O b'lemma:rifampicin'
-0.660887 O b'+1:lemma:rep2'
-0.661727 Supp b'+1:postag:-LRB-'
-0.665690 Supp b'hGreek'
-0.675815 O b'-1:lemma:37'
-0.677865 O b'word[:2]:0.'
-0.679218 O b'+1:lemma:g/l'
-0.696412 O b'lemma:30'
-0.698147 O b'-1:lemma:cra'
-0.699397 Supp b'lemma:1'
-0.701578 O b'-2:lemma:supplement'
-0.702738 O b'-2:postag::'
-0.703354 O b'-1:lemma:IP'
-0.710621 O b'+2:postag:-RRB-'
-0.719378 Temp b'-2:postag:NN'
-0.722820 O b'+1:lemma:phase'
-0.725117 O b'word[:1]:M'
-0.725209 O b'word[:1]:L'
-0.728868 Supp b'+1:lemma:,'
-0.728868 Supp b'+1:postag:,'
-0.729747 O b'-1:lemma:co2'
-0.732049 O b'word[:1]:0'
-0.732854 O b'lemma:anaerobic'
-0.737211 Agit b'symb'
-0.737781 O b'+1:lemma:_'
-0.738890 O b'+1:lemma:until'
-0.746903 O b'-1:lemma:2'
-0.753105 Anti b'+2:lemma:polyclonal'
-0.756009 Supp b'+1:postag:NNS'
-0.762043 Supp b'word[:2]:an'
-0.766144 Gtype b'-2:lemma:\xe2\x88\x86'
-0.782585 O b'-1:lemma:1'
-0.783172 Technique b'postag:NN'
-0.791028 O b'-2:lemma:dpd'
-0.791117 Gtype b'postag[:1]:V'
-0.791117 Gtype b'postag[:2]:VB'
-0.795652 O b'+2:lemma:mid-log'
-0.814979 O b'lemma:fructose'
-0.818308 O b'+2:lemma:tag'
-0.819349 O b'word[:1]:4'
-0.827940 Phase b'-1:postag:JJ'
-0.840950 O b'+2:lemma:b'
-0.843002 O b'+2:lemma:+'
-0.847830 Supp b'-2:postag:JJ'
-0.872363 O b'word[:1]:d'
-0.873207 O b'lemma:nitrate'
-0.882236 O b'+2:lemma:250'
-0.891744 O b'-2:lemma:IP'
-0.894472 O b'-2:lemma::'
-0.913166 O b'-2:lemma:0.3'
-0.917548 O b'+2:lemma:then'
-0.918623 Air b'-1:postag:JJ'
-0.971796 O b'lemma:0.3'
-0.992363 Anti b'+1:lemma:anti-fur'
-1.000844 O b'word[:2]:fl'
-1.013750 O b'+1:lemma:2.0'
-1.026340 O b'lemma:mid-log'
-1.036499 O b'word[:2]:ni'
-1.065659 Phase b'hUpper'
-1.065659 Phase b'hLower'
-1.068286 O b'-1:postag::'
-1.083222 O b'word[:2]:30'
-1.097164 O b'+1:lemma:+'
-1.104071 O b'-2:lemma:until'
-1.119190 Supp b'word[:1]:C'
-1.133243 Supp b'symb'
-1.144789 O b'-1:lemma:\xe2\x88\x86'
-1.146624 O b'-2:lemma:rifampicin'
-1.150733 O b'-1:lemma:ph'
-1.195095 Gtype b'word[:1]:C'
-1.198322 OD b'+1:postag:NN'
-1.211645 Supp b'+2:lemma:1'
-1.218440 O b'-1:lemma:nsrr'
-1.228481 Anti b'postag:NNP'
-1.235955 Med b'+2:postag:VBN'
-1.254294 O b'word[:1]:N'
-1.260075 O b'-2:lemma:media'
-1.274766 O b'postag:VBP'
-1.280395 O b'-1:lemma:sample'
-1.291770 Supp b'+2:postag:CD'
-1.323295 Gtype b'+2:lemma:cra'
-1.334984 O b'lemma:wt'
-1.365178 Supp b'+2:lemma:2'
-1.369037 O b'+2:lemma:rifampicin'
-1.402494 O b'+1:lemma:in'
-1.453133 O b'+1:lemma:at'
-1.489269 O b'-1:lemma:rpob'
-1.489467 Med b'-2:lemma:grow'
-1.507468 O b'-1:lemma:final'
-1.645797 O b'word[:1]:P'
-1.693990 Supp b'+2:lemma:fructose'
-1.865218 O b'+1:lemma:1'
-1.868753 O b'-1:postag:VBG'
-1.947849 O b'+1:lemma:2'
-1.949557 OD b'+2:lemma:aerobically'
-1.994778 O b'word[:2]:Ch'
-3.488442 O b'-1:lemma::'
-3.970946 O b'-1:lemma:_'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.216886783747496, 'c2': 0.06401679314680564}
best CV score:0.8628969551909399
model size: 0.09M
Flat F1: 0.7959513846538584
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.913 0.955 23
Med 1.000 0.943 0.971 53
Temp 0.923 0.828 0.873 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.543 0.362 0.435 69
Anti 0.917 1.000 0.957 11
Strain 0.000 0.000 0.000 1
Gtype 0.814 0.824 0.819 85
Substrain 0.000 0.000 0.000 0
Supp 0.796 0.813 0.804 134
Gversion 0.000 0.000 0.000 0
avg / total 0.821 0.778 0.796 451
Top likely transitions:
Agit -> Agit 5.554988
Supp -> Supp 5.075372
Temp -> Temp 4.962367
OD -> OD 4.808863
Med -> Med 4.722789
Air -> Air 4.233855
O -> O 3.842262
Anti -> Anti 3.839550
Phase -> Phase 3.786109
Gversion -> Gversion 3.561515
Gtype -> Gtype 3.500625
Technique -> Technique 2.701288
pH -> pH 2.368505
Air -> O 1.248758
O -> Supp 1.184530
Supp -> O 1.041831
O -> Technique 0.884981
Substrain -> Gtype 0.835591
Gtype -> Supp 0.610921
Med -> O 0.552574
O -> Gtype 0.514570
Gtype -> Air 0.471576
Temp -> O 0.349650
Technique -> Air 0.330874
O -> Phase 0.267311
Phase -> O 0.188152
O -> Temp 0.115742
OD -> O 0.034158
pH -> O 0.026851
O -> Anti 0.018274
Supp -> Gtype -0.000011
Technique -> Supp -0.000552
O -> OD -0.010291
Gtype -> Gversion -0.047313
Anti -> Gtype -0.071853
Agit -> Air -0.100169
Gtype -> Anti -0.102605
Gversion -> O -0.105812
Supp -> Med -0.143033
Technique -> pH -0.232213
Technique -> Gtype -0.267078
OD -> Air -0.314439
O -> Air -0.465381
Gtype -> Med -0.468979
Technique -> O -0.504446
Gtype -> Technique -0.550704
Gtype -> O -0.582351
Substrain -> O -0.875234
Med -> Supp -1.007844
Top unlikely transitions:
Agit -> Agit 5.554988
Supp -> Supp 5.075372
Temp -> Temp 4.962367
OD -> OD 4.808863
Med -> Med 4.722789
Air -> Air 4.233855
O -> O 3.842262
Anti -> Anti 3.839550
Phase -> Phase 3.786109
Gversion -> Gversion 3.561515
Gtype -> Gtype 3.500625
Technique -> Technique 2.701288
pH -> pH 2.368505
Air -> O 1.248758
O -> Supp 1.184530
Supp -> O 1.041831
O -> Technique 0.884981
Substrain -> Gtype 0.835591
Gtype -> Supp 0.610921
Med -> O 0.552574
O -> Gtype 0.514570
Gtype -> Air 0.471576
Temp -> O 0.349650
Technique -> Air 0.330874
O -> Phase 0.267311
Phase -> O 0.188152
O -> Temp 0.115742
OD -> O 0.034158
pH -> O 0.026851
O -> Anti 0.018274
Supp -> Gtype -0.000011
Technique -> Supp -0.000552
O -> OD -0.010291
Gtype -> Gversion -0.047313
Anti -> Gtype -0.071853
Agit -> Air -0.100169
Gtype -> Anti -0.102605
Gversion -> O -0.105812
Supp -> Med -0.143033
Technique -> pH -0.232213
Technique -> Gtype -0.267078
OD -> Air -0.314439
O -> Air -0.465381
Gtype -> Med -0.468979
Technique -> O -0.504446
Gtype -> Technique -0.550704
Gtype -> O -0.582351
Substrain -> O -0.875234
Med -> Supp -1.007844
Top positive:
4.945315 O b'lemma:2'
4.341746 Anti b'-2:lemma:antibody'
4.195357 O b'lemma:1'
4.099828 O b'postag:IN'
4.036396 Technique b'lemma[:2]:Ch'
3.544794 O b'lemma:3'
3.385486 O b'-2:lemma:_'
3.361181 Gtype b'lemma[:1]:\xce\xb4'
3.048558 O b'lemma[:2]:re'
2.941595 Air b'lemma[:2]:ae'
2.883410 Gtype b'-1:lemma:\xe2\x88\x86'
2.795385 O b'lemma:.'
2.795385 O b'postag:.'
2.774702 O b'lemma:with'
2.761558 O b'postag:CC'
2.733259 Phase b'lemma:mid-log'
2.669708 Technique b'lemma:chipseq'
2.662398 O b'lemma:_'
2.662398 O b'lemma[:1]:_'
2.660918 Air b'lemma:anaerobic'
2.627297 O b'postag::'
2.598463 Gtype b'lemma:type'
2.598463 Gtype b'lemma[:2]:ty'
2.432498 Substrain b'lemma[:2]:mg'
2.400856 O b'postag:VBN'
2.383489 Supp b'-1:lemma:with'
2.343528 O b'lemma:b'
2.312992 O b'lemma[:1]:h'
2.296178 Supp b'lemma:acetate'
2.250448 OD b'lemma[:1]:o'
2.249155 O b'lemma:-'
2.239976 Supp b'+2:lemma:iptg'
2.231349 O b'lemma:a'
2.225541 Air b'lemma[:2]:an'
2.205886 O b'lemma[:1]:-'
2.191486 Supp b'lemma:arginine'
2.188955 Supp b'-1:lemma:Cra'
2.152971 Technique b'lemma[:2]:rn'
2.138683 O b'+2:lemma:\xc2\xb0c'
2.118949 O b'lemma[:2]:ge'
2.063110 Supp b'lemma:pq'
2.063110 Supp b'lemma[:2]:pq'
2.058471 Technique b'lemma[:2]:ch'
2.053130 Supp b'+1:lemma:1'
2.052724 Gtype b'-2:lemma:genotype/variation'
2.032657 Gtype b'+1:lemma:type'
2.018103 O b'-2:lemma:medium'
2.013044 Phase b'-2:lemma:phase'
1.969228 Anti b'+2:lemma:antibody'
1.917771 Med b'+2:postag:CC'
1.912680 O b'+1:lemma:pq'
1.908997 pH b'+1:postag:CD'
1.892742 O b'-2:lemma:myc'
1.861128 Supp b'+1:lemma:\xc2\xb5m'
1.848815 Substrain b'lemma[:1]:m'
1.826357 O b'-1:lemma:tag'
1.822886 Air b'lemma:Aerobic'
1.822886 Air b'lemma[:2]:Ae'
1.819467 Supp b'lemma:Iron'
1.819467 Supp b'lemma[:2]:Ir'
1.819467 Supp b'-2:lemma:Anaerobic'
1.817872 O b'-1:lemma:anaerobic'
1.815269 Air b'-1:lemma:ChIP-Seq'
1.810754 Gtype b'lemma:\xe2\x88\x86'
1.810754 Gtype b'lemma[:1]:\xe2\x88\x86'
1.802850 Anti b'+1:lemma:antibody'
1.793608 Gtype b'-2:lemma:delta'
1.790256 Anti b'lemma[:2]:an'
1.782356 O b'postag:DT'
1.779445 O b'-1:lemma:glucose'
1.758763 Gtype b'lemma:wt'
1.758763 Gtype b'lemma[:2]:wt'
1.738367 Gtype b'lemma[:2]:pk'
1.734234 Supp b'lemma[:2]:ac'
1.720838 Air b'lemma[:1]:a'
1.712115 Gtype b'hGreek'
1.699093 pH b'lemma[:2]:ph'
1.692913 O b'+1:postag:RB'
1.678980 Gtype b'lemma:nsrr'
1.678980 Gtype b'lemma[:2]:ns'
1.669471 Technique b'lemma[:1]:C'
1.654089 Med b'lemma:MOPS'
1.654089 Med b'lemma[:1]:M'
1.654089 Med b'lemma[:2]:MO'
1.627991 Air b'-2:lemma:IP'
1.617309 Gtype b'lemma[:1]:w'
1.595727 O b'lemma[:1]:b'
1.590514 Gversion b'lemma:chip-seq'
1.582529 O b'lemma:rpob'
1.580157 Air b'postag:RB'
1.561107 O b'lemma[:1]:c'
1.551094 Supp b'lemma:no3'
1.548068 O b'+2:lemma:cra'
1.540664 O b'+2:postag:JJ'
1.527844 Phase b'lemma[:2]:ex'
1.519293 O b'-1:lemma:0.3'
1.517005 Air b'-1:lemma:-'
1.516109 Supp b'+1:lemma:2'
1.511280 Supp b'lemma[:1]:I'
1.508371 O b'-1:lemma:lb'
1.496440 O b'lemma[:1]:r'
1.490081 Supp b'+1:lemma:_'
1.462019 Air b'-2:lemma:%'
1.448517 O b'+1:postag:NNP'
1.437005 Supp b'-2:lemma:agent'
1.427410 Med b'+2:lemma:b2'
1.427381 Supp b'-1:postag:CC'
1.427067 Gtype b'+1:lemma:with'
1.426523 Temp b'-1:lemma:\xcf\x8332'
1.417716 Gtype b'+2:lemma:glucose'
1.414055 Supp b'lemma[:2]:gl'
1.403575 O b'lemma:0.4'
1.399935 O b'lemma[:1]:s'
1.398381 O b'+1:lemma:coli'
1.396647 O b'-1:lemma:Aerobic'
1.395651 O b'lemma[:1]:a'
1.376438 Temp b'lemma[:1]:3'
1.375520 Med b'lemma:broth'
1.375520 Med b'-1:lemma:L'
1.375520 Med b'lemma[:2]:br'
1.370316 Temp b'lemma:43'
1.370316 Temp b'lemma[:2]:43'
1.364176 O b'-2:lemma:no3'
1.359800 Med b'+1:lemma:0.4'
1.358059 Gtype b'lemma[:1]:f'
1.356613 Temp b'-2:lemma:\xcf\x8332'
1.352851 Med b'lemma[:1]:m'
1.350253 Temp b'-1:lemma:sample'
1.345652 Supp b'-1:lemma:+'
1.343022 O b'-1:lemma:ChIP-exo'
1.341728 Temp b'+1:lemma:\xc2\xb0c'
1.341676 Supp b'-2:lemma:for'
1.334197 Med b'lemma:lb'
1.334197 Med b'lemma[:2]:lb'
1.323689 O b'+2:lemma:70'
1.320454 O b'lemma[:1]:C'
1.317446 Supp b'lemma:fructose'
1.316176 Temp b'-1:lemma:43'
1.310735 O b'+2:lemma:of'
1.307493 Gtype b'-1:lemma:_'
1.291050 Air b'lemma[:1]:A'
1.270256 Gtype b'+1:lemma::'
1.265788 Gtype b'lemma[:1]:W'
1.263375 Supp b'lemma:rifampicin'
1.260542 pH b'lemma:ph5'
1.260542 pH b'+1:lemma:.5'
1.256282 Supp b'lemma[:2]:ri'
1.248005 Gtype b'-2:lemma:genotype'
1.238880 Gtype b'lemma[:2]:ar'
1.230717 Supp b'lemma[:1]:n'
1.230211 Supp b'lemma[:2]:fr'
1.227615 Gtype b'-2:postag:DT'
1.223309 Phase b'-1:lemma:mid-log'
1.214876 O b'lemma:A'
1.212092 O b'-2:lemma:ChIP-Seq'
1.211550 Technique b'symb'
1.210489 Supp b'-1:postag:CD'
1.207243 Supp b'+2:lemma:rifampicin'
1.196436 Supp b'lemma:glucose'
1.194146 Technique b'-2:lemma:wt'
1.191991 Technique b'-1:lemma:input'
1.184869 Air b'+1:postag:IN'
1.180469 O b'lemma:chip'
1.176262 Gtype b'lemma[:2]:fl'
1.175702 Technique b'-1:lemma:_'
1.174787 Supp b'-2:lemma:media'
1.161899 Supp b'-2:lemma:induce'
1.161883 Technique b'+2:lemma:ph5'
1.160285 O b'+1:lemma:od600'
1.157966 Gtype b'-1:lemma:rpob'
1.157628 Supp b'-2:lemma:supplement'
1.156345 Supp b'-1:lemma:_'
1.152383 O b'postag:NNS'
1.151993 Gtype b'lemma[:2]:de'
1.151326 O b'-2:postag:FW'
1.150033 Gversion b'lemma:nc'
1.150033 Gversion b'lemma[:2]:nc'
1.146428 O b'-1:postag:NNS'
1.146219 Temp b'+2:postag:DT'
1.145615 Phase b'lemma[:1]:e'
1.141344 Technique b'-1:lemma:chip-exo'
1.138300 O b'+2:lemma:fructose'
1.135372 Strain b'+1:lemma:substr'
1.135372 Strain b'-2:lemma:str'
1.134450 Supp b'+1:lemma:mm'
1.134095 Technique b'lemma:ChIP-exo'
1.127452 O b'-1:lemma:\xc2\xb0c'
1.123950 O b'lemma[:2]:ga'
1.123563 O b'-1:lemma:aerobically'
1.121892 Air b'-1:lemma:co2'
1.121232 O b'lemma:Cra'
1.119372 Gtype b'-1:postag:VBG'
1.110682 Agit b'lemma:rpm'
1.102814 O b'lemma:ml'
1.102814 O b'lemma[:2]:ml'
1.100677 Gtype b'-2:postag::'
1.098179 Gversion b'lemma[:2]:00'
1.098179 Gversion b'-2:lemma:nc'
1.095659 O b'+1:postag:VBN'
1.095182 Gtype b'+1:lemma:flagtag'
Top negative:
-0.181799 O b'-1:lemma:minimal'
-0.182920 O b'lemma[:2]:an'
-0.183892 O b'+1:postag:-LRB-'
-0.185276 O b'-1:postag:-LRB-'
-0.186866 O b'lemma:co2'
-0.188027 Supp b'lemma[:1]:o'
-0.190218 Supp b'-2:lemma:treat'
-0.191930 O b'-1:lemma:g/l'
-0.195921 O b'lemma[:1]:I'
-0.197205 Supp b'lemma[:2]:an'
-0.197254 Gtype b'lemma[:1]:-'
-0.202475 Med b'-1:postag:CD'
-0.204438 O b'+1:lemma:1/100'
-0.204438 O b'-2:lemma:sodium'
-0.204438 O b'+2:lemma:vol'
-0.209335 Supp b'+2:lemma:glucose'
-0.209547 Med b'+1:postag:NN'
-0.209855 O b'-2:lemma:genome'
-0.217016 O b'-1:lemma:the'
-0.222607 O b'+1:lemma:_'
-0.224716 pH b'postag:NN'
-0.224816 O b'lemma[:2]:0.'
-0.226096 Gtype b'-2:postag:IN'
-0.230261 Air b'symb'
-0.237585 O b'lemma[:1]:d'
-0.238640 O b'lemma[:1]:k'
-0.241721 O b'-1:lemma:ml'
-0.242115 Technique b'-2:postag:NN'
-0.243901 O b'lemma:methanol'
-0.243901 O b'-2:lemma:dissolve'
-0.244002 Supp b'-2:postag:-LRB-'
-0.249340 O b'-1:lemma:1m'
-0.249340 O b'+2:lemma:7.6'
-0.249697 Supp b'-1:postag:-LRB-'
-0.249998 O b'lemma:30'
-0.253734 O b'-2:lemma:rpob'
-0.255409 O b'-2:lemma:fresh'
-0.256485 Supp b'lemma[:1]:a'
-0.264086 Supp b'lemma:1'
-0.271675 Gtype b'-1:lemma:-lrb-'
-0.272687 Gtype b'-1:lemma:mg1655'
-0.273508 Supp b'hGreek'
-0.275591 Supp b'postag:CD'
-0.277360 O b'lemma:wt'
-0.277360 O b'lemma[:2]:wt'
-0.279018 Gtype b'-2:postag:CD'
-0.285813 Supp b'+2:lemma:-rrb-'
-0.291830 Temp b'-2:postag:NN'
-0.293279 O b'lemma:media'
-0.299936 O b'-2:lemma:mm'
-0.303152 Med b'-1:postag:NN'
-0.305132 Gtype b'postag:VBG'
-0.311471 O b'lemma:2h'
-0.311471 O b'-1:lemma:additional'
-0.311471 O b'lemma[:2]:2h'
-0.315237 O b'lemma:anaerobic'
-0.317197 O b'-2:lemma:IP'
-0.321974 O b'-2:lemma:supplement'
-0.323791 O b'-2:lemma:nh4cl'
-0.325166 Temp b'hGreek'
-0.325746 O b'-2:lemma:anaerobically'
-0.331627 OD b'hUpper'
-0.331627 OD b'hLower'
-0.334399 Gtype b'lemma[:1]:g'
-0.334670 Supp b'+1:postag:-RRB-'
-0.335261 O b'-2:lemma:glucose'
-0.340278 O b'postag:VBP'
-0.347843 O b'lemma[:1]:L'
-0.348884 Air b'+1:postag:JJ'
-0.349719 O b'+1:lemma:1m'
-0.349719 O b'-2:lemma:vol'
-0.355444 Gtype b'+1:lemma:-rrb-'
-0.362398 O b'+2:lemma:a'
-0.363139 Supp b'+2:postag:NNP'
-0.363539 O b'+2:lemma:at'
-0.373919 O b'lemma:anaerobically'
-0.379359 Supp b'-2:postag:NNS'
-0.382724 O b'+1:lemma:.'
-0.382724 O b'+1:postag:.'
-0.388857 O b'-2:postag:-LRB-'
-0.407105 Supp b'+2:postag:-RRB-'
-0.412054 O b'+2:lemma:.'
-0.412054 O b'+2:postag:.'
-0.413334 Supp b'+1:lemma:-lrb-'
-0.416341 O b'lemma[:1]:n'
-0.418014 O b'lemma[:1]:0'
-0.424605 Med b'+1:postag:IN'
-0.427442 Supp b'+1:postag:-LRB-'
-0.429806 O b'+1:lemma:supplement'
-0.432187 O b'-2:lemma:until'
-0.435863 Gtype b'lemma[:1]:h'
-0.436389 Technique b'-1:postag::'
-0.438245 O b'-1:lemma:cra'
-0.439539 O b'-1:lemma:30'
-0.440803 Supp b'symb'
-0.443573 Med b'+2:postag:VBN'
-0.444210 O b'-1:lemma:dissolve'
-0.444210 O b'+1:lemma:methanol'
-0.445532 O b'-1:lemma:mm'
-0.446820 O b'-2:lemma:phase'
-0.450190 O b'+2:lemma:-rrb-'
-0.451058 Supp b'-1:postag:NNP'
-0.451224 O b'-1:lemma:iptg'
-0.453056 O b'-1:postag:IN'
-0.465158 Gtype b'lemma[:1]:c'
-0.465723 O b'+2:lemma:tag'
-0.468785 O b'lemma[:2]:ar'
-0.475738 Supp b'lemma[:1]:s'
-0.478308 O b'lemma:glucose'
-0.482478 O b'+2:lemma:10'
-0.492471 O b'lemma[:2]:gl'
-0.496458 Gtype b'-2:lemma:\xe2\x88\x86'
-0.510030 O b'-2:lemma:dpd'
-0.515565 O b'lemma:0.3'
-0.520091 O b'+1:postag:VBG'
-0.522258 O b'-2:lemma:pahse'
-0.522746 O b'-2:postag:SYM'
-0.537818 Supp b'-2:postag:JJ'
-0.545668 Gtype b'lemma[:1]:r'
-0.551002 Temp b'postag:NN'
-0.558760 Agit b'symb'
-0.559204 Phase b'postag:JJ'
-0.565136 Supp b'+1:lemma:,'
-0.565136 Supp b'+1:postag:,'
-0.571466 O b'-2:lemma:2'
-0.575665 O b'+1:lemma:until'
-0.577302 O b'-1:lemma:vol'
-0.577302 O b'-2:lemma:1/100'
-0.577302 O b'+2:lemma:1m'
-0.579486 Med b'symb'
-0.581741 O b'lemma:mid-log'
-0.584913 O b'+1:lemma:mm'
-0.585128 O b'+1:lemma:g/l'
-0.586101 Anti b'+1:lemma:anti-fur'
-0.588450 Technique b'postag:NN'
-0.588511 Phase b'-1:postag:JJ'
-0.588605 O b'+2:lemma:fnr'
-0.590129 O b'+2:lemma:+'
-0.590818 O b'+1:lemma:+'
-0.593171 O b'-1:lemma:IP'
-0.595139 O b'+2:lemma:mid-log'
-0.611364 O b'+1:postag:IN'
-0.617324 Agit b'hUpper'
-0.617324 Agit b'hLower'
-0.622906 O b'+2:lemma:then'
-0.626564 Gtype b'lemma[:1]:a'
-0.627601 O b'-1:lemma:rpob'
-0.628334 Supp b'+1:postag:NNS'
-0.636204 O b'-2:postag:DT'
-0.642751 Med b'-2:lemma:grow'
-0.647649 O b'postag:RB'
-0.649486 O b'-1:lemma:final'
-0.651235 O b'+2:lemma:b'
-0.655430 O b'-1:lemma:\xe2\x88\x86'
-0.667559 Anti b'+2:lemma:polyclonal'
-0.669485 O b'lemma:of'
-0.669485 O b'lemma[:2]:of'
-0.672853 O b'-2:lemma::'
-0.676614 O b'-1:lemma:ph'
-0.682840 O b'-1:lemma:nsrr'
-0.686283 O b'+2:postag:-RRB-'
-0.694618 Air b'-1:postag:JJ'
-0.738949 Anti b'postag:NNP'
-0.752290 O b'lemma[:2]:me'
-0.771704 Phase b'hUpper'
-0.771704 Phase b'hLower'
-0.788474 OD b'+2:lemma:aerobically'
-0.820144 Supp b'+2:lemma:fructose'
-0.836881 O b'-2:lemma:0.3'
-0.847160 Supp b'lemma[:1]:c'
-0.858158 Med b'-2:postag:VBN'
-0.861995 O b'-1:lemma:1'
-0.862880 Gtype b'+2:lemma:cra'
-0.873409 O b'+1:lemma:at'
-0.891828 OD b'+1:postag:NN'
-0.923198 Air b'postag:NN'
-0.925308 Supp b'+2:lemma:1'
-0.925325 O b'lemma[:2]:ri'
-0.933014 O b'+1:lemma:2.0'
-0.978288 O b'-2:lemma:media'
-0.980313 O b'lemma:rifampicin'
-1.014527 O b'-1:lemma:co2'
-1.018731 O b'-2:postag:RB'
-1.030401 Supp b'+2:lemma:2'
-1.065251 Supp b'postag:JJ'
-1.073645 O b'+2:lemma:rifampicin'
-1.083180 O b'-1:lemma:sample'
-1.101292 O b'lemma[:2]:ae'
-1.117896 O b'-2:lemma:rifampicin'
-1.140184 O b'-1:postag::'
-1.170288 O b'lemma[:2]:30'
-1.232648 Supp b'+2:postag:CD'
-1.238805 O b'-1:lemma:2'
-1.545952 O b'-1:postag:VBG'
-1.640423 O b'+1:lemma:in'
-1.646059 O b'+1:lemma:1'
-1.993830 O b'lemma[:2]:fl'
-2.235667 O b'+1:lemma:2'
-3.056150 O b'-1:lemma::'
-3.928545 O b'-1:lemma:_'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.19432865325703363, 'c2': 0.003040980714530674}
best CV score:0.8693465985146905
model size: 0.10M
Flat F1: 0.7784025356677224
precision recall f1-score support
OD 1.000 0.818 0.900 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.913 0.955 23
Med 1.000 0.943 0.971 53
Temp 0.923 0.828 0.873 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.556 0.362 0.439 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.895 0.906 0.901 85
Substrain 0.000 0.000 0.000 0
Supp 0.600 0.806 0.688 134
Gversion 0.000 0.000 0.000 0
avg / total 0.782 0.792 0.778 451
Top likely transitions:
Temp -> Temp 6.494919
OD -> OD 6.471344
Agit -> Agit 6.119106
Med -> Med 5.417640
Anti -> Anti 5.342032
Supp -> Supp 5.069696
Air -> Air 5.063209
Gversion -> Gversion 4.772781
Technique -> Technique 4.679875
Gtype -> Gtype 4.566983
Phase -> Phase 4.367362
O -> O 4.012480
pH -> pH 3.171066
Substrain -> Gtype 2.054037
Gtype -> Supp 1.338135
O -> Technique 1.254842
O -> Gtype 0.899456
Technique -> Air 0.733598
O -> Supp 0.690130
Gtype -> Air 0.439886
Air -> O 0.399521
Med -> O 0.355588
Temp -> O 0.164789
O -> Phase 0.092964
O -> OD 0.041552
Supp -> O 0.021371
O -> Anti 0.011391
Supp -> Med -0.000215
Phase -> OD -0.080887
Technique -> Gtype -0.187130
Air -> Supp -0.201431
O -> Air -0.303507
Technique -> O -0.393310
Gtype -> O -0.823321
Substrain -> O -0.979191
Med -> Supp -2.040767
Top unlikely transitions:
Temp -> Temp 6.494919
OD -> OD 6.471344
Agit -> Agit 6.119106
Med -> Med 5.417640
Anti -> Anti 5.342032
Supp -> Supp 5.069696
Air -> Air 5.063209
Gversion -> Gversion 4.772781
Technique -> Technique 4.679875
Gtype -> Gtype 4.566983
Phase -> Phase 4.367362
O -> O 4.012480
pH -> pH 3.171066
Substrain -> Gtype 2.054037
Gtype -> Supp 1.338135
O -> Technique 1.254842
O -> Gtype 0.899456
Technique -> Air 0.733598
O -> Supp 0.690130
Gtype -> Air 0.439886
Air -> O 0.399521
Med -> O 0.355588
Temp -> O 0.164789
O -> Phase 0.092964
O -> OD 0.041552
Supp -> O 0.021371
O -> Anti 0.011391
Supp -> Med -0.000215
Phase -> OD -0.080887
Technique -> Gtype -0.187130
Air -> Supp -0.201431
O -> Air -0.303507
Technique -> O -0.393310
Gtype -> O -0.823321
Substrain -> O -0.979191
Med -> Supp -2.040767
Top positive:
8.498661 Air b'word:Aerobic'
7.453902 O b'-1:lemma:ChIP-exo'
6.772658 Anti b'-2:lemma:antibody'
6.165081 Air b'lemma:anaerobic'
6.117950 O b'-2:lemma:flagtag'
5.590845 O b'-2:lemma:_'
5.177165 Gtype b'lemma:wild-type'
4.971807 O b'word:Cra'
4.836191 Technique b'word:ChIP-Seq'
4.497459 O b'+2:lemma:\xc2\xb0c'
4.382845 Air b'word:Anaerobic'
4.352125 Supp b'-1:word:Cra'
4.336687 Technique b'lemma:rna-seq'
4.283630 Technique b'lemma:ChIP-exo'
4.269702 Supp b'lemma:nh4cl'
4.218273 Gtype b'lemma:type'
4.218273 Gtype b'word:type'
3.961606 Phase b'-2:lemma:phase'
3.949218 Gtype b'-2:lemma:affyexp'
3.771576 O b'postag:IN'
3.727619 Technique b'word:ChIPSeq'
3.635085 Air b'postag:RB'
3.622942 Gtype b'-2:lemma:genotype/variation'
3.587121 O b'-2:lemma:medium'
3.544455 O b'lemma:_'
3.544455 O b'word:_'
3.459688 Med b'lemma:MOPS'
3.459688 Med b'word:MOPS'
3.426079 Gtype b'-2:lemma:delta'
3.413198 O b'lemma:2'
3.413198 O b'word:2'
3.403759 O b'lemma:3'
3.403759 O b'word:3'
3.349742 Technique b'word:ChIP-exo'
3.309028 Gtype b'word:WT'
3.276517 O b'lemma:1'
3.276517 O b'word:1'
3.197253 Supp b'lemma:arginine'
3.055830 Supp b'lemma:pq'
3.055830 Supp b'word:PQ'
3.028461 O b'lemma:.'
3.028461 O b'postag:.'
3.028461 O b'word:.'
3.006895 O b'postag:CC'
3.001330 Anti b'+2:lemma:antibody'
2.880709 Gtype b'-2:lemma:genotype'
2.876573 Gversion b'-2:lemma:nc'
2.875941 O b'lemma:-'
2.875941 O b'word:-'
2.850665 Phase b'lemma:mid-log'
2.850665 Phase b'word:mid-log'
2.801983 O b'-1:word:Aerobic'
2.799528 Supp b'lemma:Iron'
2.799528 Supp b'word:Iron'
2.799528 Supp b'+1:word:Deficient'
2.799528 Supp b'-2:lemma:Anaerobic'
2.786563 Supp b'+2:lemma:iptg'
2.718821 O b'+1:word:ChIP-Seq'
2.713296 O b'lemma:chip'
2.703351 Strain b'+1:lemma:substr'
2.703351 Strain b'+1:word:substr'
2.703351 Strain b'-2:lemma:str'
2.679277 O b'postag:VBN'
2.614364 O b'-2:lemma:~'
2.597408 O b'lemma:rpob'
2.597408 O b'word:RpoB'
2.536698 Gtype b'-1:lemma:\xe2\x88\x86'
2.536698 Gtype b'-1:word:\xe2\x88\x86'
2.524686 Substrain b'-2:lemma:substr'
2.524477 O b'lemma:b'
2.524477 O b'word:B'
2.516755 Gtype b'-2:postag:DT'
2.488117 Gtype b'lemma:\xce\xb4cra'
2.483993 Gtype b'lemma:wt'
2.482868 Gtype b'word:\xce\x94cra'
2.435143 O b'word:A'
2.415059 O b'lemma:a'
2.412868 O b'postag::'
2.406725 Supp b'-2:lemma:media'
2.390251 Gtype b'+1:lemma:type'
2.390251 Gtype b'+1:word:type'
2.339888 O b'+1:postag:RB'
2.333432 Supp b'lemma:no3'
2.333432 Supp b'word:NO3'
2.317239 pH b'+1:postag:CD'
2.276706 O b'+2:lemma:70'
2.257460 Med b'+2:postag:CC'
2.243390 O b'+2:postag:JJ'
2.197419 Gtype b'lemma:\xe2\x88\x86'
2.197419 Gtype b'word:\xe2\x88\x86'
2.180922 Supp b'-1:postag:CC'
2.172831 Gtype b'lemma:\xce\xb4fur'
2.172831 Gtype b'word:\xce\x94fur'
2.143238 Supp b'+1:lemma:\xc2\xb5m'
2.143238 Supp b'+1:word:\xc2\xb5M'
2.142465 Supp b'lemma:nacl'
2.142465 Supp b'word:NaCl'
2.120502 Supp b'-1:lemma:with'
2.120502 Supp b'-1:word:with'
2.074609 O b'+2:lemma:fructose'
2.072246 Technique b'lemma:rnaseq'
2.072246 Technique b'word:RNASeq'
2.017366 O b'+2:lemma:cra'
1.976126 O b'+1:postag:NNP'
1.970655 Supp b'-2:lemma:condition'
1.952514 Phase b'-2:lemma:until'
1.949624 Supp b'lemma:nitrate'
1.949624 Supp b'word:nitrate'
1.946689 O b'-1:word:tag'
1.943850 Substrain b'lemma:mg1655'
1.943850 Substrain b'word:MG1655'
1.927111 Gtype b'lemma:\xce\xb4soxr'
1.927111 Gtype b'word:\xce\x94soxR'
1.921168 O b'-1:lemma:media'
1.921168 O b'-1:word:media'
1.878986 Supp b'lemma:acetate'
1.878986 Supp b'word:acetate'
1.874636 Supp b'lemma:glucose'
1.874636 Supp b'word:glucose'
1.872148 O b'lemma:culture'
1.839801 Gtype b'lemma:pk4854'
1.839801 Gtype b'word:PK4854'
1.832298 Gtype b'lemma:flag-tag'
1.832298 Gtype b'-1:lemma:c-terminal'
1.832298 Gtype b'word:Flag-tag'
1.832298 Gtype b'-1:word:C-terminal'
1.820296 O b'lemma:harbor'
1.820296 O b'word:harboring'
1.815309 O b'-1:lemma:tag'
1.807546 O b'lemma:with'
1.807546 O b'word:with'
1.777512 Gversion b'lemma:chip-seq'
1.769268 O b'isLower'
1.765598 O b'-2:lemma:min'
1.763690 Gversion b'-2:lemma:build'
1.761248 Gtype b'+2:lemma:glucose'
1.755584 O b'postag:VBD'
1.743507 O b'lemma:Custom'
1.743507 O b'word:Custom'
1.740985 Med b'+2:lemma:b2'
1.731020 Agit b'+2:lemma:at'
1.725553 O b'+1:lemma:arca-8myc'
1.725553 O b'+1:word:ArcA-8myc'
1.720146 O b'lemma::'
1.720146 O b'word::'
1.712129 Gversion b'lemma:nc'
1.712129 Gversion b'word:NC'
1.707341 O b'-1:lemma:anaerobic'
1.686115 O b'+1:lemma:pq'
1.686115 O b'+1:word:PQ'
1.678834 O b'lemma:ompr'
1.678834 O b'word:OmpR'
1.675572 Gtype b'-2:postag::'
1.672750 Med b'lemma:lb'
1.672750 Med b'word:LB'
1.671736 Gtype b'+1:lemma:ph5'
1.671736 Gtype b'+1:word:pH5'
1.671736 Gtype b'+2:lemma:.5'
1.670759 Air b'lemma:aerobically'
1.670759 Air b'word:aerobically'
1.647866 Temp b'-2:lemma:\xcf\x8332'
1.640244 Supp b'lemma:rifampicin'
1.640244 Supp b'word:rifampicin'
1.626253 Gversion b'word:ChIP-Seq'
1.618940 O b'-2:lemma:myc'
1.612483 Temp b'+2:postag:DT'
1.611153 Technique b'lemma:chipseq'
1.599912 Supp b'-2:lemma:agent'
1.592000 Temp b'isNumber'
1.587160 Agit b'lemma:rpm'
1.587160 Agit b'word:rpm'
1.581472 O b'-2:lemma:with'
1.569842 Temp b'-1:lemma:\xcf\x8332'
1.569842 Temp b'-1:word:\xcf\x8332'
1.563059 Gversion b'-2:postag:VB'
1.527295 O b'postag:DT'
1.515816 O b'-2:lemma:\xe2\x88\x86'
1.507350 Vess b'lemma:flask'
1.507350 Vess b'-1:lemma:warm'
1.507350 Vess b'word:flask'
1.507350 Vess b'-1:word:warmed'
1.507350 Vess b'-2:lemma:pre'
1.507350 Vess b'+2:lemma:43'
1.506594 Gtype b'lemma:nsrr'
1.506594 Gtype b'word:NsrR'
1.504503 Gtype b'lemma:\xce\xb4ompr'
1.504503 Gtype b'word:\xce\x94ompR'
1.503447 O b'+2:lemma:polyclonal'
1.495379 O b'-1:lemma:lb'
1.495379 O b'-1:word:LB'
1.491679 Gtype b'-1:postag:VBG'
1.487841 Med b'isUpper'
1.483957 Gtype b'lemma:dfnr'
1.483957 Gtype b'word:dFNR'
1.474477 Technique b'+2:lemma:ph5'
1.473390 Gversion b'+2:lemma:000913'
1.470703 O b'+1:lemma:mid-log'
1.470703 O b'+1:word:mid-log'
1.470599 Med b'+2:lemma:+'
1.469928 Supp b'-2:lemma:for'
Top negative:
-0.126187 Supp b'-2:lemma:.'
-0.126187 Supp b'-2:postag:.'
-0.127621 Med b'+1:postag:IN'
-0.130732 O b'-2:lemma:dpd'
-0.132134 Technique b'postag:NN'
-0.132995 Air b'-2:postag:RB'
-0.133944 O b'-2:lemma:mm'
-0.135455 O b'-2:lemma:pahse'
-0.136661 O b'lemma:37'
-0.136661 O b'word:37'
-0.140067 OD b'+2:postag:NN'
-0.140101 Supp b'+2:lemma:.'
-0.140101 Supp b'+2:postag:.'
-0.140302 O b'-2:lemma:-lrb-'
-0.141434 Supp b'-1:postag:-LRB-'
-0.141915 Air b'+1:postag:JJ'
-0.144090 O b'-1:lemma:fresh'
-0.144090 O b'-1:word:fresh'
-0.153079 Supp b'+2:postag:NNP'
-0.166309 Supp b'+1:postag:VBN'
-0.166863 O b'+1:postag:-LRB-'
-0.175325 Phase b'-2:postag:NN'
-0.178557 O b'+1:lemma:mm'
-0.178557 O b'+1:word:mM'
-0.179047 Supp b'lemma:10'
-0.179047 Supp b'word:10'
-0.181748 O b'-2:lemma:minimal'
-0.181863 O b'-1:word:the'
-0.183178 O b'-1:lemma:of'
-0.183178 O b'-1:word:of'
-0.189370 Air b'+2:postag:CC'
-0.193112 O b'lemma:wt'
-0.194128 O b'-1:lemma:the'
-0.194149 O b'-1:lemma:at'
-0.202859 Temp b'isLower'
-0.206499 O b'+2:postag:RB'
-0.211728 O b'-2:lemma:media'
-0.217752 Supp b'-2:lemma:treat'
-0.226935 Med b'+1:postag:NN'
-0.228587 Phase b'+1:postag:NN'
-0.230504 O b'-1:postag:DT'
-0.231712 Temp b'-2:postag:NN'
-0.235534 Air b'-2:postag:CC'
-0.237756 Air b'-2:postag:-LRB-'
-0.239368 O b'-2:postag:-LRB-'
-0.243864 O b'+1:lemma:g/l'
-0.243864 O b'+1:word:g/L'
-0.244939 O b'lemma:aerobically'
-0.244939 O b'word:aerobically'
-0.253096 O b'-2:lemma:fresh'
-0.263628 O b'-1:postag:IN'
-0.268765 Supp b'+1:lemma:-lrb-'
-0.268765 Supp b'+1:word:-LRB-'
-0.269581 OD b'isUpper'
-0.271938 O b'+1:lemma:supplement'
-0.271938 O b'+1:word:supplemented'
-0.279427 Anti b'+2:postag:JJ'
-0.282509 Air b'-2:lemma:-lrb-'
-0.282587 Supp b'+1:lemma:,'
-0.282587 Supp b'+1:postag:,'
-0.282587 Supp b'+1:word:,'
-0.290826 Supp b'+1:postag:-LRB-'
-0.298496 O b'-2:lemma:supplement'
-0.301952 O b'-2:lemma:at'
-0.302829 O b'+2:lemma:add'
-0.310606 O b'+1:lemma:.'
-0.310606 O b'+1:postag:.'
-0.310606 O b'+1:word:.'
-0.313003 O b'-1:lemma:co2'
-0.313003 O b'-1:word:CO2'
-0.317690 O b'-1:lemma:dissolve'
-0.317690 O b'+1:lemma:methanol'
-0.317690 O b'-1:word:dissolved'
-0.317690 O b'+1:word:methanol'
-0.326174 O b'-1:lemma:minimal'
-0.326174 O b'-1:word:minimal'
-0.326216 O b'-1:lemma:IP'
-0.326216 O b'-1:word:IP'
-0.326756 Med b'-1:postag:NN'
-0.330968 O b'-1:lemma:2'
-0.330968 O b'-1:word:2'
-0.331123 Supp b'isNumber'
-0.331144 O b'+2:lemma:fnr'
-0.342326 Med b'+2:postag:VBN'
-0.348597 O b'-2:lemma:glucose'
-0.349154 O b'-2:lemma:until'
-0.353909 O b'+1:lemma:1m'
-0.353909 O b'+1:word:1M'
-0.353909 O b'-2:lemma:vol'
-0.354844 O b'lemma:media'
-0.354844 O b'word:media'
-0.364311 O b'+2:lemma:a'
-0.368051 O b'lemma:nitrate'
-0.368051 O b'word:nitrate'
-0.369958 Air b'-2:lemma:and'
-0.370055 O b'-2:lemma:aerobically'
-0.371442 O b'-1:lemma:mm'
-0.371442 O b'-1:word:mM'
-0.377685 O b'+2:lemma:10'
-0.378127 Supp b'postag:CC'
-0.381117 O b'+2:lemma:at'
-0.389688 pH b'isLower'
-0.391439 O b'+2:lemma:-rrb-'
-0.401482 O b'-2:lemma:anaerobically'
-0.403860 Air b'-1:postag:RB'
-0.405233 O b'lemma:2h'
-0.405233 O b'-1:lemma:additional'
-0.405233 O b'word:2h'
-0.405233 O b'-1:word:additional'
-0.407301 O b'-1:lemma:grow'
-0.410353 O b'lemma:minimal'
-0.410353 O b'word:minimal'
-0.415960 O b'lemma:anaerobically'
-0.415960 O b'word:anaerobically'
-0.431864 O b'+2:lemma:rifampicin'
-0.435994 Gtype b'+2:lemma:cra'
-0.448208 O b'+2:lemma:.'
-0.448208 O b'+2:postag:.'
-0.457862 O b'-1:lemma:ph'
-0.457862 O b'-1:word:pH'
-0.462522 O b'lemma:mid-log'
-0.462522 O b'word:mid-log'
-0.464717 O b'-1:postag::'
-0.478899 Gtype b'postag:VBG'
-0.480305 O b'+2:postag:-RRB-'
-0.486380 Supp b'-1:postag:NNP'
-0.487200 pH b'postag:NN'
-0.487808 O b'+2:lemma:+'
-0.495639 Air b'-1:postag:JJ'
-0.498421 Phase b'isUpper'
-0.501538 O b'+1:lemma:until'
-0.501538 O b'+1:word:until'
-0.508531 O b'-1:lemma:nsrr'
-0.508531 O b'-1:word:NsrR'
-0.515487 O b'-2:lemma:phase'
-0.515810 O b'-1:lemma:30'
-0.515810 O b'-1:word:30'
-0.523969 Med b'-2:postag:VBN'
-0.536049 Technique b'isNumber'
-0.539654 O b'lemma:of'
-0.539654 O b'word:of'
-0.555532 Supp b'-2:postag:JJ'
-0.605271 O b'postag:VBP'
-0.607462 O b'-1:lemma:1'
-0.607462 O b'-1:word:1'
-0.610401 O b'lemma:0.3'
-0.610401 O b'word:0.3'
-0.654660 O b'+1:lemma:in'
-0.654660 O b'+1:word:in'
-0.674407 Anti b'isUpper'
-0.680937 Air b'postag:NN'
-0.683120 O b'+1:postag:IN'
-0.694831 O b'-2:lemma::'
-0.711579 O b'+2:lemma:mid-log'
-0.717061 O b'postag:RB'
-0.727172 O b'+1:lemma:2.0'
-0.727172 O b'+1:word:2.0'
-0.727991 O b'+1:lemma:at'
-0.727991 O b'+1:word:at'
-0.750617 Gtype b'isNumber'
-0.754171 O b'-1:lemma:vol'
-0.754171 O b'-1:word:vol'
-0.754171 O b'-2:lemma:1/100'
-0.754171 O b'+2:lemma:1m'
-0.769142 Gversion b'isLower'
-0.799722 O b'lemma:rifampicin'
-0.799722 O b'word:rifampicin'
-0.813037 Gtype b'-2:lemma:\xe2\x88\x86'
-0.818783 O b'lemma:30'
-0.818783 O b'word:30'
-0.832669 Technique b'isLower'
-0.884252 O b'+1:postag:VBG'
-0.887424 O b'-2:postag:DT'
-0.937669 O b'-2:lemma:0.3'
-0.940717 Supp b'+2:lemma:fructose'
-0.972116 Supp b'+2:postag:CD'
-0.978709 Gtype b'isLower'
-1.016999 O b'-2:lemma:rifampicin'
-1.111059 Agit b'isUpper'
-1.130478 O b'-2:postag:RB'
-1.171981 O b'+2:lemma:then'
-1.242037 Phase b'postag:JJ'
-1.330863 O b'+1:lemma:1'
-1.330863 O b'+1:word:1'
-1.365191 Temp b'postag:NN'
-1.474036 Supp b'postag:JJ'
-1.619405 Phase b'-1:postag:JJ'
-1.653492 Supp b'+2:lemma:1'
-1.660082 O b'+1:lemma:2'
-1.660082 O b'+1:word:2'
-1.959474 O b'-1:postag:VBG'
-2.021801 Supp b'+2:lemma:2'
-2.109223 Med b'-2:lemma:grow'
-2.312172 OD b'+1:postag:NN'
-2.414666 O b'-1:lemma::'
-2.414666 O b'-1:word::'
-2.754541 O b'-1:lemma:_'
-2.754541 O b'-1:word:_'
-3.657725 OD b'+2:lemma:aerobically'
-4.070887 Anti b'postag:NNP'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.03780171336875179, 'c2': 0.012718090480016972}
best CV score:0.8741870589668248
model size: 0.16M
Flat F1: 0.764435455440298
precision recall f1-score support
OD 0.818 0.818 0.818 22
pH 1.000 1.000 1.000 8
Technique 0.955 0.913 0.933 23
Med 1.000 0.925 0.961 53
Temp 1.000 0.759 0.863 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.556 0.362 0.439 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.869 0.859 0.864 85
Substrain 0.000 0.000 0.000 0
Supp 0.593 0.806 0.684 134
Gversion 0.000 0.000 0.000 0
avg / total 0.769 0.778 0.764 451
Top likely transitions:
Temp -> Temp 5.633437
Agit -> Agit 5.242920
Med -> Med 5.205888
OD -> OD 4.820634
Supp -> Supp 4.795672
Anti -> Anti 4.563286
Gversion -> Gversion 4.480777
Gtype -> Gtype 4.410238
O -> O 4.309533
Phase -> Phase 4.099270
Air -> Air 3.591014
Technique -> Technique 3.585887
pH -> pH 2.997587
Substrain -> Gtype 1.829751
O -> Technique 0.949969
Gtype -> Supp 0.738864
O -> Gtype 0.585802
Gtype -> Air 0.391269
Gtype -> pH 0.344184
Technique -> Air 0.264778
O -> Supp 0.191022
Air -> O 0.116016
Temp -> O 0.097547
Med -> O 0.057304
O -> Anti 0.017577
pH -> Supp -0.028693
O -> Phase -0.048549
Technique -> OD -0.055283
Anti -> Med -0.056104
Supp -> O -0.109106
Air -> Temp -0.113829
OD -> Supp -0.116904
Gversion -> Supp -0.118460
Technique -> Supp -0.137571
Air -> OD -0.151166
Agit -> O -0.182410
Air -> Gtype -0.230985
Supp -> Gtype -0.235813
Med -> Air -0.245332
Phase -> O -0.254973
Supp -> Phase -0.254988
Phase -> Air -0.262541
OD -> O -0.278938
Anti -> O -0.285405
Air -> Phase -0.291613
Gtype -> Technique -0.321912
Anti -> Supp -0.329510
O -> OD -0.360061
Gtype -> Anti -0.380808
Gtype -> Med -0.399195
Top unlikely transitions:
Gtype -> pH 0.344184
Technique -> Air 0.264778
O -> Supp 0.191022
Air -> O 0.116016
Temp -> O 0.097547
Med -> O 0.057304
O -> Anti 0.017577
pH -> Supp -0.028693
O -> Phase -0.048549
Technique -> OD -0.055283
Anti -> Med -0.056104
Supp -> O -0.109106
Air -> Temp -0.113829
OD -> Supp -0.116904
Gversion -> Supp -0.118460
Technique -> Supp -0.137571
Air -> OD -0.151166
Agit -> O -0.182410
Air -> Gtype -0.230985
Supp -> Gtype -0.235813
Med -> Air -0.245332
Phase -> O -0.254973
Supp -> Phase -0.254988
Phase -> Air -0.262541
OD -> O -0.278938
Anti -> O -0.285405
Air -> Phase -0.291613
Gtype -> Technique -0.321912
Anti -> Supp -0.329510
O -> OD -0.360061
Gtype -> Anti -0.380808
Gtype -> Med -0.399195
Supp -> Air -0.399750
O -> Med -0.419285
Phase -> OD -0.436501
Air -> Agit -0.455472
Technique -> O -0.530788
Temp -> Med -0.544192
Technique -> pH -0.577493
Supp -> Med -0.646950
OD -> Air -0.730559
Phase -> Supp -0.748627
Air -> Med -0.810512
Gtype -> O -0.913442
Air -> Supp -0.986614
Agit -> Air -1.033744
O -> Air -1.071275
Substrain -> O -1.325541
Technique -> Gtype -1.554985
Med -> Supp -2.340793
Top positive:
5.181623 Air b'word:Aerobic'
5.069692 O b'-2:lemma:_'
4.702830 Anti b'-2:lemma:antibody'
4.290692 Air b'lemma:anaerobic'
4.139968 Gtype b'-2:lemma:genotype/variation'
4.052057 O b'word:Cra'
3.610352 Technique b'word:ChIP-Seq'
3.589676 O b'lemma:_'
3.589676 O b'word:_'
3.543264 O b'lemma:1'
3.543264 O b'word:1'
3.538307 O b'lemma:2'
3.538307 O b'word:2'
3.447474 Gtype b'-2:lemma:genotype'
3.421203 Air b'postag:RB'
3.390076 Phase b'-2:lemma:phase'
3.349265 Supp b'lemma:pq'
3.349265 Supp b'word:PQ'
3.332208 O b'-2:lemma:medium'
3.230628 O b'-1:lemma:ChIP-exo'
3.167256 Technique b'lemma:rna-seq'
3.159409 O b'-2:lemma:flagtag'
3.114586 Technique b'word:ChIP-exo'
3.101194 Technique b'lemma:ChIP-exo'
2.986312 Supp b'lemma:nh4cl'
2.980962 Technique b'word:ChIPSeq'
2.961365 Gtype b'lemma:type'
2.961365 Gtype b'word:type'
2.960004 Air b'word:Anaerobic'
2.947966 Gtype b'word:WT'
2.932783 O b'+2:lemma:\xc2\xb0c'
2.920653 Supp b'+2:lemma:iptg'
2.872474 O b'lemma:.'
2.872474 O b'postag:.'
2.872474 O b'word:.'
2.867743 Gtype b'lemma:wild-type'
2.834804 Supp b'-1:word:Cra'
2.831538 O b'lemma:-'
2.831538 O b'word:-'
2.798161 O b'lemma:3'
2.798161 O b'word:3'
2.798112 Gtype b'-2:lemma:affyexp'
2.692314 O b'lemma:rpob'
2.692314 O b'word:RpoB'
2.675098 O b'postag::'
2.664980 Gtype b'lemma:wt'
2.604579 Gtype b'lemma:\xce\xb4cra'
2.592394 O b'postag:VBN'
2.550258 Supp b'lemma:no3'
2.550258 Supp b'word:NO3'
2.533320 Gtype b'word:\xce\x94cra'
2.500008 Technique b'lemma:chipseq'
2.463493 Med b'lemma:MOPS'
2.463493 Med b'word:MOPS'
2.459381 O b'+2:lemma:70'
2.452341 Supp b'lemma:Iron'
2.452341 Supp b'word:Iron'
2.452341 Supp b'+1:word:Deficient'
2.452341 Supp b'-2:lemma:Anaerobic'
2.449771 Med b'+2:postag:CC'
2.435165 Phase b'+2:lemma:o.d.'
2.430391 O b'-1:lemma:tag'
2.425850 Phase b'lemma:mid-log'
2.425850 Phase b'word:mid-log'
2.407993 O b'postag:IN'
2.398217 Phase b'lemma:exponential'
2.398217 Phase b'word:exponential'
2.398217 Phase b'lemma:stationary'
2.398217 Phase b'word:stationary'
2.392837 Supp b'lemma:acetate'
2.392837 Supp b'word:acetate'
2.385444 Gtype b'+1:lemma:type'
2.385444 Gtype b'+1:word:type'
2.380980 Anti b'+2:lemma:antibody'
2.369810 Supp b'-2:lemma:agent'
2.356829 O b'word:A'
2.351468 Med b'+2:lemma:b2'
2.300790 Supp b'lemma:arginine'
2.298306 Supp b'lemma:nacl'
2.298306 Supp b'word:NaCl'
2.295477 O b'+1:postag:NNP'
2.243176 O b'-1:word:Aerobic'
2.239344 Air b'lemma:Aerobic'
2.178927 O b'lemma:b'
2.178927 O b'word:B'
2.167680 Gtype b'lemma:\xe2\x88\x86'
2.167680 Gtype b'word:\xe2\x88\x86'
2.163673 Supp b'lemma:glucose'
2.163673 Supp b'word:glucose'
2.149402 Technique b'+2:lemma:ph5'
2.131320 O b'lemma:with'
2.131320 O b'word:with'
2.107004 Substrain b'lemma:mg1655'
2.107004 Substrain b'word:MG1655'
2.093423 O b'+2:lemma:fructose'
2.092930 Supp b'-1:lemma:with'
2.092930 Supp b'-1:word:with'
2.072607 Supp b'-1:lemma:Cra'
2.061502 O b'+1:word:ChIP-Seq'
2.048739 O b'lemma:ompr'
2.048739 O b'word:OmpR'
2.041804 O b'lemma:culture'
2.035926 Gtype b'-2:postag:DT'
2.033981 Substrain b'-2:lemma:substr'
2.015820 Gtype b'lemma:\xce\xb4soxr'
2.015820 Gtype b'word:\xce\x94soxR'
2.002657 Gtype b'lemma:flag-tag'
2.002657 Gtype b'-1:lemma:c-terminal'
2.002657 Gtype b'word:Flag-tag'
2.002657 Gtype b'-1:word:C-terminal'
1.981109 Supp b'+1:lemma:\xc2\xb5m'
1.981109 Supp b'+1:word:\xc2\xb5M'
1.977275 O b'+2:lemma:cra'
1.976163 Strain b'+1:lemma:substr'
1.976163 Strain b'+1:word:substr'
1.976163 Strain b'-2:lemma:str'
1.966819 Technique b'lemma:rnaseq'
1.966819 Technique b'word:RNASeq'
1.966131 O b'-2:lemma:myc'
1.956221 O b'lemma:harbor'
1.956221 O b'word:harboring'
1.947790 Gtype b'-1:lemma:\xe2\x88\x86'
1.947790 Gtype b'-1:word:\xe2\x88\x86'
1.943715 O b'-1:lemma:lb'
1.943715 O b'-1:word:LB'
1.942277 O b'lemma:a'
1.929064 Gversion b'lemma:chip-seq'
1.918408 Technique b'word:RNA-Seq'
1.915726 pH b'+1:postag:CD'
1.882795 O b'+1:lemma:arca-8myc'
1.882795 O b'+1:word:ArcA-8myc'
1.881377 O b'-2:lemma:fructose'
1.853522 O b'+1:postag:RB'
1.851023 Supp b'postag:VBP'
1.845767 Supp b'-2:lemma:induce'
1.833461 Gtype b'lemma:\xce\xb4fur'
1.833461 Gtype b'word:\xce\x94fur'
1.825330 Gversion b'word:ChIP-Seq'
1.815756 O b'-1:lemma:glucose'
1.815756 O b'-1:word:glucose'
1.815639 Gtype b'+1:lemma:with'
1.815639 Gtype b'+1:word:with'
1.809036 Gtype b'-2:lemma:delta'
1.806217 Technique b'-1:lemma:chip-exo'
1.804393 Temp b'isNumber'
1.797896 O b'-1:word:tag'
1.786674 Supp b'-2:lemma:purr'
1.783032 Supp b'-2:lemma:argr'
1.765681 O b'+2:postag:JJ'
1.765181 Supp b'-1:postag:CC'
1.753024 Air b'word:anaerobic'
1.751122 Gtype b'-1:postag:VBG'
1.742490 Supp b'-2:lemma:media'
1.737277 Med b'+2:lemma:b1'
1.734728 O b'+2:lemma:_'
1.710506 Gtype b'+2:lemma:glucose'
1.709022 Supp b'lemma:Leu'
1.709022 Supp b'word:Leu'
1.709022 Supp b'-2:lemma:Lrp'
1.707829 Supp b'-2:lemma:condition'
1.695253 Gtype b'lemma:\xce\xb4ompr'
1.695253 Gtype b'word:\xce\x94ompR'
1.687283 Med b'+1:lemma:0.4'
1.687283 Med b'+1:word:0.4'
1.680612 Air b'+1:postag:IN'
1.676466 O b'lemma:soxs'
1.676466 O b'word:SoxS'
1.676466 O b'lemma:soxr'
1.676466 O b'word:SoxR'
1.666118 O b'lemma:Cra'
1.639338 O b'-1:lemma:anaerobic'
1.636477 O b'isLower'
1.632852 Med b'lemma:media'
1.632852 Med b'word:media'
1.629462 O b'-2:lemma:treat'
1.626732 Gtype b'lemma:dfnr'
1.626732 Gtype b'word:dFNR'
1.623468 O b'lemma:Custom'
1.623468 O b'word:Custom'
1.621644 O b'postag:CC'
1.618806 Gtype b'lemma:\xce\xb4oxyr'
1.618806 Gtype b'word:\xce\x94oxyR'
1.618168 Med b'lemma:lb'
1.618168 Med b'word:LB'
1.618066 O b'-1:lemma:media'
1.618066 O b'-1:word:media'
1.611062 Gtype b'postag:JJ'
1.608968 O b'lemma:argr'
1.608968 O b'word:ArgR'
1.603897 Gversion b'-2:lemma:nc'
1.594090 O b'lemma:trpr'
1.594090 O b'word:TrpR'
1.583791 Air b'lemma:aerobic'
1.567884 O b'+1:postag:VBP'
1.567340 O b'-1:lemma:0.3'
1.567340 O b'-1:word:0.3'
1.561344 O b'lemma::'
1.561344 O b'word::'
1.560411 O b'lemma:rep2'
1.560411 O b'word:rep2'
Top negative:
-0.317190 OD b'+2:postag:NN'
-0.317236 O b'-2:postag::'
-0.319090 O b'+1:lemma:2.0'
-0.319090 O b'+1:word:2.0'
-0.319182 O b'+2:lemma:30'
-0.325633 O b'lemma:nh4cl'
-0.326977 Temp b'+1:postag:IN'
-0.328963 O b'lemma:methanol'
-0.328963 O b'word:methanol'
-0.328963 O b'-2:lemma:dissolve'
-0.330771 O b'-1:lemma:rpob'
-0.330771 O b'-1:word:RpoB'
-0.332385 Supp b'+2:lemma:acetate'
-0.336346 O b'+2:lemma:reference'
-0.340150 Strain b'isLower'
-0.351888 Phase b'+2:postag:NN'
-0.354760 O b'-1:lemma:ph'
-0.354760 O b'-1:word:pH'
-0.356359 O b'word:tag'
-0.356948 O b'-1:lemma:dissolve'
-0.356948 O b'+1:lemma:methanol'
-0.356948 O b'-1:word:dissolved'
-0.356948 O b'+1:word:methanol'
-0.360165 O b'lemma:aerobic'
-0.361875 O b'-1:lemma:2'
-0.361875 O b'-1:word:2'
-0.364393 O b'lemma:medium'
-0.364393 O b'word:medium'
-0.364434 O b'lemma:anaerobic'
-0.365818 O b'-1:lemma:co2'
-0.365818 O b'-1:word:CO2'
-0.372268 O b'-1:lemma:\xe2\x88\x86'
-0.372268 O b'-1:word:\xe2\x88\x86'
-0.380490 Temp b'isLower'
-0.386775 O b'+1:lemma:1m'
-0.386775 O b'+1:word:1M'
-0.386775 O b'-2:lemma:vol'
-0.390297 Supp b'-2:lemma:.'
-0.390297 Supp b'-2:postag:.'
-0.405236 O b'+2:lemma:fnr'
-0.408221 O b'+2:lemma:mid-log'
-0.413792 O b'lemma:fructose'
-0.413792 O b'word:fructose'
-0.413863 Temp b'-2:postag:NN'
-0.414885 O b'-1:postag::'
-0.422156 O b'+1:lemma:+'
-0.422156 O b'+1:word:+'
-0.427210 O b'-1:lemma:37'
-0.427210 O b'-1:word:37'
-0.429642 Supp b'+1:lemma:,'
-0.429642 Supp b'+1:postag:,'
-0.429642 Supp b'+1:word:,'
-0.434934 O b'lemma:37'
-0.434934 O b'word:37'
-0.449375 O b'word:ChIP-exo'
-0.453085 pH b'isUpper'
-0.454154 O b'-2:lemma:IP'
-0.455382 Temp b'+2:postag:IN'
-0.460059 Air b'+1:postag:JJ'
-0.464417 O b'-1:lemma:mm'
-0.464417 O b'-1:word:mM'
-0.467555 O b'+2:lemma:at'
-0.467980 O b'lemma:anaerobically'
-0.467980 O b'word:anaerobically'
-0.470071 O b'-2:lemma:control'
-0.471057 O b'+2:lemma:add'
-0.480066 O b'+1:postag:IN'
-0.484390 O b'lemma:of'
-0.484390 O b'word:of'
-0.485748 O b'lemma:aerobically'
-0.485748 O b'word:aerobically'
-0.496119 O b'-2:lemma:pahse'
-0.501405 O b'-2:lemma:genome'
-0.513871 O b'-2:postag:RB'
-0.528240 O b'-2:postag:DT'
-0.554221 O b'-1:lemma:ml'
-0.554221 O b'-1:word:ml'
-0.555233 O b'lemma:nitrogen'
-0.555233 O b'word:nitrogen'
-0.557362 O b'lemma:2h'
-0.557362 O b'-1:lemma:additional'
-0.557362 O b'word:2h'
-0.557362 O b'-1:word:additional'
-0.574744 O b'+1:postag:VBG'
-0.577749 Supp b'+1:lemma:-lrb-'
-0.577749 Supp b'+1:word:-LRB-'
-0.584147 O b'-2:lemma:glucose'
-0.589012 O b'+1:lemma:g/l'
-0.589012 O b'+1:word:g/L'
-0.592857 O b'lemma:glucose'
-0.592857 O b'word:glucose'
-0.601655 O b'-1:lemma:fresh'
-0.601655 O b'-1:word:fresh'
-0.603478 Supp b'+1:postag:-LRB-'
-0.621366 O b'+1:lemma:in'
-0.621366 O b'+1:word:in'
-0.622465 O b'-1:lemma:30'
-0.622465 O b'-1:word:30'
-0.622636 Supp b'-1:postag:NNP'
-0.623045 Temp b'postag:NN'
-0.628719 O b'-2:lemma:minimal'
-0.629272 O b'+2:lemma:250'
-0.632193 Supp b'+1:postag:NNS'
-0.632244 O b'-2:lemma:nh4cl'
-0.639178 O b'+1:word:ChIP-exo'
-0.641094 Anti b'+1:lemma:anti-fur'
-0.641094 Anti b'+1:word:anti-Fur'
-0.652774 Supp b'postag:CC'
-0.659478 Agit b'isUpper'
-0.660753 O b'-2:lemma:rpob'
-0.662803 O b'+1:lemma:until'
-0.662803 O b'+1:word:until'
-0.684151 O b'-2:postag:SYM'
-0.701908 O b'lemma:0.3'
-0.701908 O b'word:0.3'
-0.708244 O b'-2:lemma:aerobically'
-0.717945 pH b'isLower'
-0.724124 O b'-1:lemma:1'
-0.724124 O b'-1:word:1'
-0.748149 O b'lemma:media'
-0.748149 O b'word:media'
-0.748561 O b'-2:lemma:fresh'
-0.766386 O b'-2:lemma:anaerobically'
-0.773055 O b'-1:lemma:nsrr'
-0.773055 O b'-1:word:NsrR'
-0.780146 O b'lemma:\xce\xb4fur'
-0.780146 O b'word:\xce\x94fur'
-0.780683 O b'-1:lemma:grow'
-0.793481 Supp b'+2:postag:CD'
-0.793996 Supp b'+2:lemma:glucose'
-0.802497 Phase b'isUpper'
-0.818377 O b'+2:lemma:b'
-0.827115 O b'lemma:nitrate'
-0.827115 O b'word:nitrate'
-0.842837 O b'-2:lemma:dpd'
-0.844530 Anti b'isUpper'
-0.848235 O b'lemma:wt'
-0.848520 Supp b'-2:lemma:treat'
-0.856415 O b'-1:lemma:chip-exo'
-0.857668 O b'-2:lemma:rifampicin'
-0.870943 Med b'-2:postag:VBN'
-0.880457 Med b'-1:postag:NN'
-0.892873 Supp b'-2:postag:JJ'
-0.904754 O b'+1:lemma:at'
-0.904754 O b'+1:word:at'
-0.911903 Med b'+2:postag:VBN'
-0.952984 Air b'postag:NN'
-0.961352 Technique b'isNumber'
-0.969534 O b'lemma:rifampicin'
-0.969534 O b'word:rifampicin'
-0.972230 Gtype b'isNumber'
-0.979689 O b'-1:lemma:vol'
-0.979689 O b'-1:word:vol'
-0.979689 O b'-2:lemma:1/100'
-0.979689 O b'+2:lemma:1m'
-0.994381 O b'lemma:mid-log'
-0.994381 O b'word:mid-log'
-0.998905 O b'-1:lemma:IP'
-0.998905 O b'-1:word:IP'
-1.010402 O b'-1:lemma:sample'
-1.039200 O b'+2:lemma:then'
-1.063285 Supp b'-2:lemma:grow'
-1.070057 Gversion b'isLower'
-1.088636 O b'-2:lemma::'
-1.111068 O b'+2:lemma:rifampicin'
-1.141806 O b'lemma:30'
-1.141806 O b'word:30'
-1.155863 Gtype b'isLower'
-1.158383 O b'-2:lemma:media'
-1.163155 Gtype b'-2:lemma:\xe2\x88\x86'
-1.183034 O b'-2:lemma:phase'
-1.187663 O b'-2:lemma:until'
-1.205548 O b'+2:lemma:+'
-1.219191 Technique b'isLower'
-1.223177 O b'postag:RB'
-1.253855 OD b'+1:postag:NN'
-1.256714 O b'+1:lemma:1'
-1.256714 O b'+1:word:1'
-1.263687 Anti b'+2:lemma:polyclonal'
-1.291590 O b'+2:lemma:for'
-1.317736 Gtype b'+2:lemma:cra'
-1.346822 Supp b'postag:JJ'
-1.369654 Gtype b'postag:VBG'
-1.433422 O b'postag:VBP'
-1.476722 O b'+1:lemma:2'
-1.476722 O b'+1:word:2'
-1.525519 O b'-2:lemma:0.3'
-1.666455 Supp b'+2:lemma:1'
-1.826364 Med b'-2:lemma:grow'
-1.900619 Phase b'-1:postag:JJ'
-1.925903 Supp b'+2:lemma:2'
-2.114791 O b'-1:postag:VBG'
-2.153462 Supp b'+2:lemma:fructose'
-2.237029 Anti b'postag:NNP'
-2.314282 O b'-1:lemma::'
-2.314282 O b'-1:word::'
-2.363285 O b'-1:lemma:_'
-2.363285 O b'-1:word:_'
-2.770952 OD b'+2:lemma:aerobically'
-3.794024 Phase b'postag:JJ'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.16987113834357556, 'c2': 0.04496913983225195}
best CV score:0.8747625195626942
model size: 0.13M
Flat F1: 0.7884082577489101
precision recall f1-score support
OD 0.818 0.818 0.818 22
pH 1.000 1.000 1.000 8
Technique 1.000 1.000 1.000 23
Med 1.000 0.962 0.981 53
Temp 0.923 0.828 0.873 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.875 0.933 0.903 15
Air 0.556 0.362 0.439 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.864 0.824 0.843 85
Substrain 0.000 0.000 0.000 0
Supp 0.712 0.813 0.760 134
Gversion 0.000 0.000 0.000 0
avg / total 0.801 0.785 0.788 451
Top likely transitions:
OD -> OD 5.257890
Temp -> Temp 5.205804
Med -> Med 4.966902
Supp -> Supp 4.928476
Agit -> Agit 4.916983
Anti -> Anti 4.149202
Air -> Air 3.992915
Gversion -> Gversion 3.819753
Gtype -> Gtype 3.718805
Phase -> Phase 3.610359
O -> O 3.452915
Technique -> Technique 3.113366
pH -> pH 2.349939
Substrain -> Gtype 0.775262
O -> Technique 0.770450
O -> Supp 0.669913
Air -> O 0.473830
Gtype -> Supp 0.462636
O -> Gtype 0.453324
Supp -> O 0.311331
Med -> O 0.264436
Gtype -> Air 0.183444
Temp -> O 0.158941
Technique -> Air 0.108884
O -> Phase 0.000506
Air -> Supp -0.000185
Supp -> Gtype -0.002878
O -> OD -0.009866
Supp -> Technique -0.043400
Technique -> Gtype -0.047071
Anti -> O -0.051496
Gtype -> Anti -0.117353
O -> Med -0.118983
Technique -> pH -0.211980
OD -> Air -0.228543
Gversion -> O -0.264567
Gtype -> Med -0.386243
Supp -> Med -0.413936
Gtype -> Technique -0.493289
O -> Air -0.579308
Technique -> O -0.694824
Gtype -> O -0.998730
Med -> Supp -1.066796
Substrain -> O -1.093891
Top unlikely transitions:
OD -> OD 5.257890
Temp -> Temp 5.205804
Med -> Med 4.966902
Supp -> Supp 4.928476
Agit -> Agit 4.916983
Anti -> Anti 4.149202
Air -> Air 3.992915
Gversion -> Gversion 3.819753
Gtype -> Gtype 3.718805
Phase -> Phase 3.610359
O -> O 3.452915
Technique -> Technique 3.113366
pH -> pH 2.349939
Substrain -> Gtype 0.775262
O -> Technique 0.770450
O -> Supp 0.669913
Air -> O 0.473830
Gtype -> Supp 0.462636
O -> Gtype 0.453324
Supp -> O 0.311331
Med -> O 0.264436
Gtype -> Air 0.183444
Temp -> O 0.158941
Technique -> Air 0.108884
O -> Phase 0.000506
Air -> Supp -0.000185
Supp -> Gtype -0.002878
O -> OD -0.009866
Supp -> Technique -0.043400
Technique -> Gtype -0.047071
Anti -> O -0.051496
Gtype -> Anti -0.117353
O -> Med -0.118983
Technique -> pH -0.211980
OD -> Air -0.228543
Gversion -> O -0.264567
Gtype -> Med -0.386243
Supp -> Med -0.413936
Gtype -> Technique -0.493289
O -> Air -0.579308
Technique -> O -0.694824
Gtype -> O -0.998730
Med -> Supp -1.066796
Substrain -> O -1.093891
Top positive:
4.452085 Anti b'-2:lemma:antibody'
3.689675 O b'word[:2]:re'
3.482630 Gtype b'word[:1]:\xce\x94'
3.342489 O b'-2:lemma:_'
3.175684 Technique b'word[:2]:Ch'
2.884271 OD b'word[:1]:O'
2.741246 Air b'word[:2]:An'
2.637598 Air b'word[:2]:Ae'
2.637598 Air b'word:Aerobic'
2.617531 Air b'lemma:anaerobic'
2.537522 O b'word:A'
2.494524 O b'lemma:2'
2.494524 O b'word:2'
2.467001 Air b'word[:1]:A'
2.363811 Technique b'word[:2]:RN'
2.310310 O b'-2:lemma:medium'
2.291922 Gtype b'-2:lemma:genotype/variation'
2.286103 Supp b'-1:word:Cra'
2.272015 Phase b'-2:lemma:phase'
2.201967 O b'word[:1]:S'
2.155778 O b'lemma:_'
2.155778 O b'word[:1]:_'
2.155778 O b'word:_'
2.134515 Med b'+2:postag:CC'
2.110513 O b'lemma:1'
2.110513 O b'word:1'
2.050395 Gtype b'lemma:wt'
2.025579 Supp b'lemma:arginine'
2.025478 O b'word[:1]:G'
2.007953 Gtype b'word[:1]:d'
1.995272 Gtype b'word[:1]:W'
1.982181 O b'lemma:3'
1.982181 O b'word:3'
1.957486 Gtype b'word[:2]:Fl'
1.925967 Supp b'word[:1]:I'
1.897045 O b'isNumber'
1.871338 Air b'word[:2]:an'
1.870496 Gtype b'hGreek'
1.858144 O b'+2:lemma:cra'
1.842813 Phase b'lemma:mid-log'
1.842813 Phase b'word:mid-log'
1.762000 Supp b'+2:lemma:iptg'
1.751693 Supp b'word[:2]:Fe'
1.733316 Air b'word[:1]:a'
1.731487 O b'isLower'
1.710681 Substrain b'word[:2]:MG'
1.697395 Anti b'+2:lemma:antibody'
1.693427 Gtype b'-1:lemma:\xe2\x88\x86'
1.693427 Gtype b'-1:word:\xe2\x88\x86'
1.672893 O b'postag:IN'
1.672893 O b'postag[:1]:I'
1.672893 O b'postag[:2]:IN'
1.663254 Anti b'word[:2]:an'
1.662524 Gtype b'-2:lemma:delta'
1.648718 Supp b'word[:2]:ni'
1.648211 pH b'word[:2]:pH'
1.646384 pH b'+1:postag:CD'
1.643762 O b'+2:lemma:\xc2\xb0c'
1.636843 Substrain b'word[:1]:M'
1.623586 Supp b'-1:lemma:with'
1.623586 Supp b'-1:word:with'
1.616923 O b'lemma:-'
1.616923 O b'word:-'
1.616244 O b'word[:2]:ge'
1.597930 Supp b'-1:postag:CC'
1.597275 Gtype b'word[:2]:PK'
1.582027 O b'-1:word:Aerobic'
1.576810 O b'lemma:.'
1.576810 O b'postag:.'
1.576810 O b'postag[:1]:.'
1.576810 O b'word:.'
1.554293 Gtype b'word[:1]:w'
1.551110 O b'word[:1]:B'
1.546507 O b'-1:word:tag'
1.529700 Gtype b'lemma:type'
1.529700 Gtype b'word[:2]:ty'
1.529700 Gtype b'word:type'
1.517044 Supp b'lemma:acetate'
1.517044 Supp b'word:acetate'
1.513375 O b'-2:lemma:myc'
1.510589 O b'-1:lemma:tag'
1.507823 O b'word[:2]:Rp'
1.507742 Technique b'word[:1]:R'
1.482889 Technique b'word[:1]:C'
1.482481 Supp b'lemma:pq'
1.482481 Supp b'word[:2]:PQ'
1.482481 Supp b'word:PQ'
1.481495 O b'word[:1]:-'
1.480627 O b'postag::'
1.480627 O b'postag[:1]::'
1.477504 Med b'isUpper'
1.439532 O b'word[:1]:C'
1.433463 Air b'+1:postag:IN'
1.417597 O b'word[:1]:R'
1.408489 Technique b'lemma:ChIP-exo'
1.399469 O b'lemma:a'
1.374497 Temp b'isNumber'
1.369743 O b'postag:CC'
1.369743 O b'postag[:2]:CC'
1.369445 O b'-1:lemma:anaerobic'
1.366915 Temp b'+2:postag:DT'
1.360275 Supp b'+1:lemma:\xc2\xb5m'
1.360275 Supp b'+1:word:\xc2\xb5M'
1.348179 Supp b'-1:lemma:Cra'
1.343465 Supp b'word[:2]:gl'
1.337575 O b'lemma:with'
1.337575 O b'word:with'
1.334448 O b'+2:postag:JJ'
1.332963 Supp b'word[:1]:N'
1.325155 Med b'word[:1]:L'
1.308365 Supp b'lemma:Iron'
1.308365 Supp b'word[:2]:Ir'
1.308365 Supp b'word:Iron'
1.308365 Supp b'+1:word:Deficient'
1.308365 Supp b'-2:lemma:Anaerobic'
1.291354 Med b'word[:1]:M'
1.290809 Gtype b'word[:1]:F'
1.288935 Med b'lemma:MOPS'
1.288935 Med b'word[:2]:MO'
1.288935 Med b'word:MOPS'
1.282537 Gtype b'word[:1]:t'
1.278434 O b'+1:word:ChIP-Seq'
1.273443 Supp b'-2:lemma:for'
1.255541 Gtype b'-2:postag:DT'
1.255203 Technique b'+2:lemma:ph5'
1.250661 Air b'word:Anaerobic'
1.236252 O b'word[:2]:ch'
1.233756 pH b'word[:1]:p'
1.233479 Gtype b'lemma:\xe2\x88\x86'
1.233479 Gtype b'word[:1]:\xe2\x88\x86'
1.233479 Gtype b'word:\xe2\x88\x86'
1.228084 Gtype b'+2:lemma:glucose'
1.223922 O b'+2:lemma:fructose'
1.218698 Gtype b'symb'
1.217647 O b'word[:2]:ha'
1.215512 Strain b'+1:lemma:substr'
1.215512 Strain b'+1:word:substr'
1.215512 Strain b'-2:lemma:str'
1.196793 O b'-1:lemma:glucose'
1.196793 O b'-1:word:glucose'
1.194057 Supp b'-2:lemma:media'
1.184144 O b'-1:lemma:0.3'
1.184144 O b'-1:word:0.3'
1.183310 OD b'-1:postag:IN'
1.178980 O b'word[:1]:c'
1.176425 Supp b'word[:2]:ac'
1.170284 Gversion b'lemma:chip-seq'
1.168235 Gtype b'-2:lemma:affyexp'
1.164552 Gtype b'word[:1]:P'
1.156202 Gversion b'word:ChIP-Seq'
1.156155 O b'-1:lemma:lb'
1.156155 O b'-1:word:LB'
1.149395 O b'-1:lemma:ChIP-exo'
1.146734 Phase b'word[:2]:ex'
1.142864 Gtype b'word[:2]:WT'
1.142864 Gtype b'word:WT'
1.140128 Agit b'+2:lemma:at'
1.135341 O b'+1:postag:VBN'
1.135006 Anti b'+1:lemma:antibody'
1.135006 Anti b'+1:word:antibody'
1.134467 O b'postag:VBN'
1.130287 Supp b'+1:lemma:1'
1.130287 Supp b'+1:word:1'
1.118529 Supp b'postag:VBP'
1.111752 Gtype b'-1:postag:VBG'
1.108134 O b'+1:postag:RB'
1.101074 Temp b'lemma:43'
1.101074 Temp b'word[:2]:43'
1.101074 Temp b'word:43'
1.096502 Supp b'lemma:nacl'
1.096502 Supp b'word:NaCl'
1.094797 O b'word[:2]:Cr'
1.090348 Gtype b'-2:lemma:genotype'
1.090152 Temp b'word[:1]:3'
1.085633 Temp b'-2:lemma:30'
1.082487 O b'-2:lemma:fructose'
1.079531 Gtype b'lemma:nsrr'
1.079531 Gtype b'word[:2]:Ns'
1.079531 Gtype b'word:NsrR'
1.079097 Technique b'symb'
1.077150 Temp b'isUpper'
1.072640 Phase b'word[:1]:e'
1.071712 O b'-2:lemma:flagtag'
1.071622 Technique b'lemma:rna-seq'
1.057972 O b'lemma:b'
1.057972 O b'word:B'
1.057103 Med b'+2:lemma:b2'
1.055515 O b'-1:lemma:media'
1.055515 O b'-1:word:media'
1.054647 O b'+2:lemma:70'
1.051568 Gtype b'+2:lemma:a'
1.051055 Med b'word[:2]:me'
1.050903 Supp b'+2:lemma:rifampicin'
1.049213 O b'word[:1]:E'
1.038966 O b'+1:lemma:pq'
1.038966 O b'+1:word:PQ'
1.036931 Substrain b'-2:lemma:substr'
1.036271 Med b'word[:1]:g'
1.024899 Supp b'-2:lemma:condition'
1.019819 O b'lemma:Custom'
Top negative:
-0.233766 O b'-1:lemma:final'
-0.233766 O b'-1:word:final'
-0.234091 O b'+2:lemma:-rrb-'
-0.234779 O b'-1:postag:-LRB-'
-0.238119 Phase b'postag[:1]:J'
-0.238119 Phase b'postag[:2]:JJ'
-0.239654 O b'-2:lemma:a'
-0.240870 O b'+2:lemma:add'
-0.242028 O b'lemma:nitrate'
-0.242028 O b'word:nitrate'
-0.245388 Supp b'-1:lemma:-lrb-'
-0.245388 Supp b'-1:word:-LRB-'
-0.248207 O b'-2:lemma:at'
-0.248837 Air b'isLower'
-0.249358 Supp b'+1:lemma:-lrb-'
-0.249358 Supp b'+1:word:-LRB-'
-0.254940 O b'-2:lemma:rpob'
-0.256776 Supp b'hGreek'
-0.256897 O b'-2:lemma:2'
-0.259614 Supp b'+1:postag:-LRB-'
-0.260142 O b'-2:lemma:fresh'
-0.261060 O b'+1:lemma:+'
-0.261060 O b'+1:word:+'
-0.262071 O b'lemma:2h'
-0.262071 O b'-1:lemma:additional'
-0.262071 O b'word[:2]:2h'
-0.262071 O b'word:2h'
-0.262071 O b'-1:word:additional'
-0.268722 Supp b'word[:2]:an'
-0.270059 Supp b'-1:postag:-LRB-'
-0.274315 O b'+1:lemma:g/l'
-0.274315 O b'+1:word:g/L'
-0.274906 O b'-2:lemma:IP'
-0.275720 Gtype b'isNumber'
-0.280363 O b'-2:lemma:anaerobically'
-0.282585 O b'lemma:0.3'
-0.282585 O b'word:0.3'
-0.284842 O b'word[:2]:gl'
-0.287099 O b'lemma:30'
-0.287099 O b'word:30'
-0.289399 O b'+2:lemma:tag'
-0.289844 Anti b'isUpper'
-0.292297 O b'-1:lemma:control'
-0.292297 O b'-1:word:control'
-0.292666 O b'+1:lemma:1m'
-0.292666 O b'+1:word:1M'
-0.292666 O b'-2:lemma:vol'
-0.294625 O b'+1:lemma:.'
-0.294625 O b'+1:postag:.'
-0.294625 O b'+1:word:.'
-0.294876 Temp b'postag:NN'
-0.297833 O b'-1:lemma:ph'
-0.297833 O b'-1:word:pH'
-0.298423 Technique b'isLower'
-0.300990 Temp b'-2:postag:NN'
-0.305286 O b'-1:lemma:dissolve'
-0.305286 O b'+1:lemma:methanol'
-0.305286 O b'-1:word:dissolved'
-0.305286 O b'+1:word:methanol'
-0.314748 O b'-2:lemma:pahse'
-0.315937 O b'-1:lemma:mm'
-0.315937 O b'-1:word:mM'
-0.322399 Gtype b'word[:1]:h'
-0.323125 OD b'hUpper'
-0.323125 OD b'hLower'
-0.331381 O b'-1:lemma:rpob'
-0.331381 O b'-1:word:RpoB'
-0.339459 O b'-1:postag:IN'
-0.341910 Gtype b'-2:lemma:\xe2\x88\x86'
-0.342651 O b'lemma:of'
-0.342651 O b'word[:2]:of'
-0.342651 O b'word:of'
-0.342819 O b'+2:lemma:fnr'
-0.347959 Med b'+1:postag:IN'
-0.356951 O b'-1:lemma:30'
-0.356951 O b'-1:word:30'
-0.358047 O b'-1:lemma:IP'
-0.358047 O b'-1:word:IP'
-0.360899 O b'+1:lemma:until'
-0.360899 O b'+1:word:until'
-0.364934 O b'-2:lemma:of'
-0.365442 Anti b'+1:lemma:anti-fur'
-0.365442 Anti b'+1:word:anti-Fur'
-0.367544 Med b'+1:postag:NN'
-0.372074 O b'word[:1]:0'
-0.374136 O b'word[:2]:pH'
-0.388322 Supp b'postag:JJ'
-0.391570 Supp b'postag[:1]:J'
-0.391570 Supp b'postag[:2]:JJ'
-0.405960 O b'word[:2]:mg'
-0.412894 O b'-2:lemma:dpd'
-0.416528 Supp b'+1:lemma:,'
-0.416528 Supp b'+1:postag:,'
-0.416528 Supp b'+1:word:,'
-0.419392 O b'+2:lemma:.'
-0.419392 O b'+2:postag:.'
-0.422296 O b'-1:lemma:nsrr'
-0.422296 O b'-1:word:NsrR'
-0.423145 O b'-2:lemma:phase'
-0.426000 O b'+2:lemma:10'
-0.432994 O b'-2:lemma:glucose'
-0.450062 Agit b'symb'
-0.450812 Agit b'hUpper'
-0.450812 Agit b'hLower'
-0.475356 pH b'isLower'
-0.476636 Air b'-1:postag:JJ'
-0.481749 O b'+2:lemma:a'
-0.485266 O b'+2:lemma:250'
-0.496343 O b'word[:2]:ri'
-0.500963 O b'-2:lemma:supplement'
-0.502478 O b'-1:lemma:1'
-0.502478 O b'-1:word:1'
-0.505892 O b'-1:lemma:vol'
-0.505892 O b'-1:word:vol'
-0.505892 O b'-2:lemma:1/100'
-0.505892 O b'+2:lemma:1m'
-0.509659 O b'-2:lemma:until'
-0.510236 O b'-2:postag:-LRB-'
-0.521161 O b'-1:lemma:co2'
-0.521161 O b'-1:word:CO2'
-0.528448 Supp b'+2:postag:NNP'
-0.528535 O b'-2:postag::'
-0.533872 O b'+2:lemma:at'
-0.534880 O b'word[:1]:K'
-0.535293 Med b'+2:postag:VBN'
-0.541773 Supp b'+2:lemma:glucose'
-0.545876 Phase b'postag:JJ'
-0.551702 O b'lemma:rifampicin'
-0.551702 O b'word:rifampicin'
-0.552442 Supp b'-1:postag:NNP'
-0.558246 Gtype b'postag[:1]:V'
-0.558246 Gtype b'postag[:2]:VB'
-0.563240 Med b'-1:postag:NN'
-0.571846 O b'+2:lemma:mid-log'
-0.577127 O b'lemma:wt'
-0.617765 Supp b'symb'
-0.618558 Supp b'-2:postag:JJ'
-0.624362 O b'+1:lemma:2.0'
-0.624362 O b'+1:word:2.0'
-0.628911 O b'word[:2]:fl'
-0.645255 O b'-2:lemma:media'
-0.647985 O b'lemma:mid-log'
-0.647985 O b'word:mid-log'
-0.657965 Anti b'+2:lemma:polyclonal'
-0.658210 O b'word[:2]:ni'
-0.659228 O b'+1:lemma:at'
-0.659228 O b'+1:word:at'
-0.660590 O b'+1:postag:VBG'
-0.660829 O b'-2:lemma::'
-0.663451 Supp b'word[:1]:C'
-0.672793 Med b'symb'
-0.694489 O b'+2:lemma:+'
-0.709178 O b'-1:lemma:2'
-0.709178 O b'-1:word:2'
-0.714094 Phase b'hUpper'
-0.714094 Phase b'hLower'
-0.761826 Gtype b'isUpper'
-0.767486 O b'+1:lemma:in'
-0.767486 O b'+1:word:in'
-0.770064 O b'+1:postag:IN'
-0.778369 O b'+2:lemma:rifampicin'
-0.779812 Air b'postag:NN'
-0.789169 Anti b'postag:NNP'
-0.794413 O b'-1:lemma:sample'
-0.827931 O b'+1:lemma:1'
-0.827931 O b'+1:word:1'
-0.858848 O b'word[:1]:N'
-0.876126 Gversion b'isLower'
-0.907230 O b'+2:postag:-RRB-'
-0.914704 Phase b'-1:postag:JJ'
-0.930998 Gtype b'word[:1]:C'
-0.934673 Med b'-2:lemma:grow'
-0.947305 O b'-2:lemma:rifampicin'
-0.949351 O b'word[:2]:30'
-0.965721 Technique b'postag:NN'
-0.968173 O b'-2:postag:DT'
-0.969881 O b'word[:1]:d'
-0.992013 O b'word[:2]:me'
-1.005304 Gtype b'+2:lemma:cra'
-1.016350 Supp b'+2:lemma:1'
-1.016868 O b'-2:postag:RB'
-1.018698 Med b'-2:postag:VBN'
-1.049404 O b'+2:lemma:then'
-1.070041 Supp b'+2:lemma:fructose'
-1.100907 O b'-2:lemma:0.3'
-1.187447 O b'+1:lemma:2'
-1.187447 O b'+1:word:2'
-1.201747 O b'postag:VBP'
-1.230600 Supp b'+2:postag:CD'
-1.246552 OD b'+2:lemma:aerobically'
-1.286136 Supp b'+2:lemma:2'
-1.312055 O b'word[:1]:P'
-1.352684 OD b'+1:postag:NN'
-1.428576 O b'-1:postag::'
-1.785805 O b'-1:lemma::'
-1.785805 O b'-1:word::'
-1.853048 O b'-1:postag:VBG'
-2.104444 O b'word[:2]:Ch'
-2.120158 O b'-1:lemma:_'
-2.120158 O b'-1:word:_'
********** TRAINING AND TESTING REPORT **********
Training file: training-data-set-70.txt
best params:{'c1': 0.12475431096451621, 'c2': 0.013861677898849787}
best CV score:0.8708258755708097
model size: 0.13M
Flat F1: 0.7686691050567419
precision recall f1-score support
OD 0.818 0.818 0.818 22
pH 1.000 1.000 1.000 8
Technique 1.000 0.913 0.955 23
Med 1.000 0.962 0.981 53
Temp 1.000 0.828 0.906 29
Vess 1.000 1.000 1.000 1
Agit 0.000 0.000 0.000 0
Phase 0.882 1.000 0.938 15
Air 0.556 0.362 0.439 69
Anti 1.000 1.000 1.000 11
Strain 0.000 0.000 0.000 1
Gtype 0.867 0.847 0.857 85
Substrain 0.000 0.000 0.000 0
Supp 0.586 0.813 0.681 134
Gversion 0.000 0.000 0.000 0
avg / total 0.769 0.787 0.769 451
Top likely transitions:
Agit -> Agit 6.648242
Temp -> Temp 6.282260
OD -> OD 5.656317
Med -> Med 5.374931
Supp -> Supp 5.024760
Gversion -> Gversion 4.860700
Anti -> Anti 4.808761
Phase -> Phase 4.070172
Air -> Air 4.046984
Gtype -> Gtype 3.891102
O -> O 3.673937
Technique -> Technique 3.298287
pH -> pH 2.863141
Substrain -> Gtype 0.869714
O -> Technique 0.537319
Air -> O 0.264430
O -> Gtype 0.222368
Temp -> O 0.130509
Gtype -> Supp 0.079007
Technique -> Air 0.075090
Med -> O 0.071813
O -> Anti 0.041836
O -> Supp 0.033164
Supp -> O -0.011764
Phase -> O -0.027870
OD -> O -0.058085
Gversion -> O -0.096750
O -> Phase -0.097534
Air -> Supp -0.189966
Technique -> pH -0.218375
Temp -> Med -0.224152
O -> Med -0.332474
O -> OD -0.383967
Gtype -> Med -0.624502
Gtype -> Technique -0.734455
Technique -> O -0.940389
O -> Air -1.114206
Gtype -> O -1.304969
Substrain -> O -1.345412
Med -> Supp -2.177917
Top unlikely transitions:
Agit -> Agit 6.648242
Temp -> Temp 6.282260
OD -> OD 5.656317
Med -> Med 5.374931
Supp -> Supp 5.024760
Gversion -> Gversion 4.860700
Anti -> Anti 4.808761
Phase -> Phase 4.070172
Air -> Air 4.046984
Gtype -> Gtype 3.891102
O -> O 3.673937
Technique -> Technique 3.298287
pH -> pH 2.863141
Substrain -> Gtype 0.869714
O -> Technique 0.537319
Air -> O 0.264430
O -> Gtype 0.222368
Temp -> O 0.130509
Gtype -> Supp 0.079007
Technique -> Air 0.075090
Med -> O 0.071813
O -> Anti 0.041836
O -> Supp 0.033164
Supp -> O -0.011764
Phase -> O -0.027870
OD -> O -0.058085
Gversion -> O -0.096750
O -> Phase -0.097534
Air -> Supp -0.189966
Technique -> pH -0.218375
Temp -> Med -0.224152
O -> Med -0.332474
O -> OD -0.383967
Gtype -> Med -0.624502
Gtype -> Technique -0.734455
Technique -> O -0.940389
O -> Air -1.114206
Gtype -> O -1.304969
Substrain -> O -1.345412
Med -> Supp -2.177917
Top positive:
5.778785 Anti b'-2:lemma:antibody'
5.099975 Technique b'lemma[:2]:Ch'
4.743651 O b'-2:lemma:_'
4.315336 Gtype b'lemma[:1]:\xce\xb4'
4.248364 O b'lemma[:2]:re'
4.215292 Air b'word:Aerobic'
3.511204 O b'postag:CC'
3.394617 O b'postag:IN'
3.322867 O b'lemma:2'
3.322867 O b'word:2'
3.302849 O b'-2:lemma:medium'
3.302673 Substrain b'lemma[:2]:mg'
3.165450 Technique b'lemma[:2]:rn'
3.016068 Med b'+2:postag:CC'
2.985942 Air b'word:Anaerobic'
2.966163 O b'lemma:1'
2.966163 O b'word:1'
2.923025 O b'lemma:3'
2.923025 O b'word:3'
2.877232 Phase b'-2:lemma:phase'
2.867093 Supp b'-1:word:Cra'
2.833973 Supp b'lemma:arginine'
2.812849 O b'+2:lemma:\xc2\xb0c'
2.760554 Air b'postag:RB'
2.740030 O b'lemma[:1]:h'
2.731812 Gtype b'-2:lemma:genotype/variation'
2.708235 Air b'lemma[:2]:an'
2.604774 O b'postag::'
2.584655 Anti b'+2:lemma:antibody'
2.582878 O b'lemma:-'
2.582878 O b'word:-'
2.571693 O b'word:Cra'
2.568004 O b'lemma:_'
2.568004 O b'lemma[:1]:_'
2.568004 O b'word:_'
2.567283 O b'-1:lemma:ChIP-exo'
2.560556 O b'word:A'
2.539743 Gtype b'word:WT'
2.513546 O b'lemma:.'
2.513546 O b'postag:.'
2.513546 O b'word:.'
2.499439 Gtype b'lemma:type'
2.499439 Gtype b'lemma[:2]:ty'
2.499439 Gtype b'word:type'
2.460970 Air b'lemma:anaerobic'
2.408658 O b'+1:postag:RB'
2.388183 Phase b'lemma:mid-log'
2.388183 Phase b'word:mid-log'
2.384478 Supp b'lemma[:2]:gl'
2.383895 O b'postag:VBN'
2.382299 Air b'lemma[:2]:ae'
2.358041 O b'lemma:with'
2.358041 O b'word:with'
2.353625 Supp b'+2:lemma:iptg'
2.350953 Phase b'lemma[:2]:ex'
2.322692 Technique b'word:ChIPSeq'
2.304893 Gtype b'-2:lemma:delta'
2.289460 O b'+2:lemma:fructose'
2.285493 O b'+2:lemma:cra'
2.276073 O b'lemma[:2]:ge'
2.256719 Supp b'-1:postag:CC'
2.250185 Air b'lemma[:1]:a'
2.234168 Gtype b'lemma[:2]:pk'
2.207665 O b'-1:lemma:tag'
2.164408 Technique b'lemma:chipseq'
2.073628 O b'+2:lemma:70'
2.050739 Supp b'lemma:pq'
2.050739 Supp b'lemma[:2]:pq'
2.050739 Supp b'word:PQ'
2.001826 Air b'+1:postag:IN'
1.975647 O b'isLower'
1.936376 O b'-1:word:Aerobic'
1.920820 Gtype b'-1:lemma:\xe2\x88\x86'
1.920820 Gtype b'-1:word:\xe2\x88\x86'
1.908896 O b'-1:lemma:anaerobic'
1.889420 pH b'+1:postag:CD'
1.888509 Supp b'lemma[:1]:n'
1.886729 O b'postag:DT'
1.858376 Supp b'lemma:Iron'
1.858376 Supp b'lemma[:2]:Ir'
1.858376 Supp b'word:Iron'
1.858376 Supp b'+1:word:Deficient'
1.858376 Supp b'-2:lemma:Anaerobic'
1.853608 O b'lemma:chip'
1.838366 Gversion b'lemma:chip-seq'
1.831815 O b'-1:word:tag'
1.820620 Anti b'lemma[:2]:an'
1.815550 Gtype b'lemma[:1]:w'
1.809178 Gtype b'hGreek'
1.792293 Gversion b'word:ChIP-Seq'
1.775178 Gtype b'-2:postag:DT'
1.768307 O b'+1:word:ChIP-Seq'
1.764667 Supp b'-1:lemma:with'
1.764667 Supp b'-1:word:with'
1.722957 Supp b'lemma:acetate'
1.722957 Supp b'word:acetate'
1.713832 Technique b'-1:lemma:chip-exo'
1.710287 Med b'isUpper'
1.709780 O b'lemma:b'
1.709780 O b'word:B'
1.704621 Technique b'word:ChIP-Seq'
1.694028 Phase b'lemma[:1]:e'
1.689430 Gtype b'+1:lemma:type'
1.689430 Gtype b'+1:word:type'
1.679770 Supp b'lemma[:1]:I'
1.670552 Supp b'+2:lemma:rifampicin'
1.664056 O b'lemma[:1]:b'
1.661667 Substrain b'lemma[:1]:m'
1.647294 Gtype b'lemma:wt'
1.647294 Gtype b'lemma[:2]:wt'
1.634965 O b'-2:lemma:myc'
1.622392 pH b'lemma[:2]:ph'
1.620704 Supp b'-2:lemma:agent'
1.618245 Technique b'lemma[:2]:ch'
1.617020 O b'+2:postag:JJ'
1.593807 Supp b'+1:lemma:\xc2\xb5m'
1.593807 Supp b'+1:word:\xc2\xb5M'
1.593155 O b'lemma:a'
1.582387 O b'+1:postag:NNP'
1.579370 Temp b'-1:word:sample'
1.576150 Gtype b'+2:lemma:glucose'
1.562990 O b'+1:lemma:pq'
1.562990 O b'+1:word:PQ'
1.555511 Gtype b'lemma[:2]:wi'
1.554537 Gtype b'lemma[:1]:f'
1.545677 Temp b'-1:lemma:sample'
1.540501 Med b'lemma:MOPS'
1.540501 Med b'lemma[:1]:M'
1.540501 Med b'lemma[:2]:MO'
1.540501 Med b'word:MOPS'
1.522098 OD b'lemma[:1]:o'
1.509875 Med b'lemma[:1]:m'
1.505327 Phase b'-2:lemma:until'
1.505027 O b'-1:lemma:lb'
1.505027 O b'-1:word:LB'
1.497714 Gtype b'-1:postag:VBG'
1.492176 Agit b'+2:lemma:at'
1.486489 O b'isNumber'
1.464199 Gtype b'-2:lemma:affyexp'
1.453424 Supp b'lemma[:2]:30'
1.450691 Gversion b'lemma[:2]:00'
1.450691 Gversion b'-2:lemma:nc'
1.450278 Technique b'lemma:ChIP-exo'
1.448397 O b'-1:lemma:media'
1.448397 O b'-1:word:media'
1.443477 Supp b'lemma[:2]:ni'
1.440399 O b'lemma:Custom'
1.440399 O b'lemma[:2]:Cu'
1.440399 O b'word:Custom'
1.429606 Supp b'-1:lemma:Cra'
1.425430 Supp b'-2:lemma:media'
1.418079 Med b'+2:lemma:b2'
1.404067 O b'-1:lemma:glucose'
1.404067 O b'-1:word:glucose'
1.396114 Phase b'+2:lemma:o.d.'
1.387435 Gtype b'lemma:\xe2\x88\x86'
1.387435 Gtype b'lemma[:1]:\xe2\x88\x86'
1.387435 Gtype b'word:\xe2\x88\x86'
1.349810 Temp b'-2:lemma:\xcf\x8332'
1.346540 Supp b'lemma:fructose'
1.346540 Supp b'word:fructose'
1.343114 Technique b'lemma[:1]:C'
1.341281 Gversion b'-2:lemma:build'
1.336703 O b'-2:lemma:flagtag'
1.328773 Med b'lemma:broth'
1.328773 Med b'-1:lemma:L'
1.328773 Med b'lemma[:2]:br'
1.328773 Med b'word:broth'
1.328773 Med b'-1:word:L'
1.325888 Supp b'+1:lemma:1'
1.325888 Supp b'+1:word:1'
1.321862 Anti b'+1:lemma:antibody'
1.321862 Anti b'+1:word:antibody'
1.316632 O b'+2:lemma:polyclonal'
1.311992 O b'-1:lemma:0.3'
1.311992 O b'-1:word:0.3'
1.295781 Gtype b'lemma[:2]:de'
1.284876 Gtype b'-2:lemma:genotype'
1.277004 Supp b'-2:lemma:condition'
1.273482 Supp b'-2:lemma:induce'
1.271728 Air b'-1:postag::'
1.268149 Phase b'lemma:stationary'
1.268149 Phase b'word:stationary'
1.262573 Technique b'-1:lemma:input'
1.262573 Technique b'-1:word:Input'
1.259324 Gversion b'-2:postag:VB'
1.259137 Supp b'lemma[:2]:ac'
1.259012 O b'+1:lemma:mid-log'
1.259012 O b'+1:word:mid-log'
1.253088 Temp b'-1:lemma:43'
1.253088 Temp b'-1:word:43'
1.253040 Gtype b'lemma:nsrr'
1.253040 Gtype b'lemma[:2]:ns'
1.253040 Gtype b'word:NsrR'
1.237967 O b'lemma:0.4'
1.237967 O b'word:0.4'
1.236427 O b'-1:lemma:type'
1.236427 O b'-1:word:type'
1.229582 O b'lemma:ompr'
1.229582 O b'word:OmpR'
Top negative:
-0.226109 O b'+1:word:+'
-0.228043 Supp b'-1:lemma:-lrb-'
-0.228043 Supp b'-1:word:-LRB-'
-0.230436 O b'-1:lemma:37'
-0.230436 O b'-1:word:37'
-0.231705 O b'-2:lemma:rpob'
-0.238413 Supp b'-2:lemma:treat'
-0.244411 O b'+1:lemma:supplement'
-0.244411 O b'+1:word:supplemented'
-0.245251 Supp b'-1:postag:-LRB-'
-0.247310 O b'+2:lemma:at'
-0.248881 Supp b'-2:lemma:grow'
-0.251177 O b'lemma[:1]:I'
-0.254376 Supp b'+2:lemma:glucose'
-0.259696 O b'-1:lemma:ph'
-0.259696 O b'-1:word:pH'
-0.264998 O b'-2:postag:-LRB-'
-0.269895 O b'lemma[:2]:0.'
-0.271060 O b'lemma:media'
-0.271060 O b'word:media'
-0.271346 O b'lemma:of'
-0.271346 O b'lemma[:2]:of'
-0.271346 O b'word:of'
-0.271681 Med b'-1:postag:CD'
-0.273156 Supp b'lemma[:1]:a'
-0.280251 O b'lemma:glucose'
-0.280251 O b'word:glucose'
-0.283644 O b'+1:lemma:1m'
-0.283644 O b'+1:word:1M'
-0.283644 O b'-2:lemma:vol'
-0.283702 Med b'+1:postag:NN'
-0.284709 O b'+2:lemma:a'
-0.285197 Anti b'+2:lemma:polyclonal'
-0.289677 O b'lemma:30'
-0.289677 O b'word:30'
-0.295454 O b'-2:lemma:of'
-0.296935 Phase b'+1:postag:NN'
-0.298375 Phase b'-2:postag:NN'
-0.304558 O b'+1:lemma:until'
-0.304558 O b'+1:word:until'
-0.306703 O b'-1:lemma:30'
-0.306703 O b'-1:word:30'
-0.313912 Supp b'+2:postag:NNP'
-0.316964 O b'+1:lemma:mm'
-0.316964 O b'+1:word:mM'
-0.318525 O b'lemma:0.3'
-0.318525 O b'word:0.3'
-0.320042 Supp b'+1:lemma:-lrb-'
-0.320042 Supp b'+1:word:-LRB-'
-0.320535 Gtype b'-2:postag:CD'
-0.321989 O b'-2:lemma:dpd'
-0.322258 O b'lemma:2h'
-0.322258 O b'-1:lemma:additional'
-0.322258 O b'lemma[:2]:2h'
-0.322258 O b'word:2h'
-0.322258 O b'-1:word:additional'
-0.322790 O b'-1:lemma:final'
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