Run6_v11.txt
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-------------------------------- 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: _v11
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003670s
-------------------------------- 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 postag[:1] C
10 postag[:2] CD
11 -2:lemma Cra
12 -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 postag[:1] N
12 lemma[:2] de
13 postag[:2] NN
14 -2:lemma affyexp
15 -2:postag JJ
16 +2:lemma glucose
17 +2:postag NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.744355 - 1.3s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.822757 - 1.4s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.918061 - 1.9s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.894139 - 1.6s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.864177 - 1.5s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.876836 - 1.2s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.820742 - 1.6s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.825305 - 1.4s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.918061 - 1.4s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.683730 - 1.5s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.862409 - 1.2s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.974589 - 1.8s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.852603 - 1.6s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.856825 - 1.4s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.823313 - 1.6s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.892089 - 1.5s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.862528 - 1.6s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.926731 - 1.4s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.839218 - 1.6s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.843508 - 1.3s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.808908 - 1.2s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.850984 - 1.6s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.844946 - 1.6s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.854858 - 2.1s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.913115 - 1.5s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.817270 - 1.8s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.927009 - 2.0s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.593314 - 1.9s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.893806 - 1.5s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.593314 - 1.8s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.727632 - 1.5s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.877930 - 1.4s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.931609 - 1.4s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.738299 - 1.4s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.884690 - 1.4s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.889202 - 1.4s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.928892 - 1.4s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.818750 - 1.3s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.621607 - 1.4s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.821991 - 1.5s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.901996 - 1.6s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.928660 - 1.9s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.825305 - 1.7s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.918674 - 1.5s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.932900 - 1.6s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.925560 - 1.6s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.841914 - 1.5s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.800885 - 1.7s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.871570 - 1.6s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.782611 - 1.4s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.729474 - 1.6s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.702472 - 1.6s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.810655 - 1.4s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.868123 - 1.5s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.759234 - 1.4s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.923594 - 1.5s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.825609 - 1.7s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.918674 - 1.4s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.929634 - 1.4s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.633367 - 1.5s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.946672 - 1.5s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.691973 - 1.7s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.818750 - 2.0s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.931609 - 1.7s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.872081 - 1.4s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.867416 - 1.6s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.876526 - 1.7s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.873607 - 2.0s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.812173 - 1.7s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.925560 - 1.6s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.839327 - 1.9s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.923229 - 2.0s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.927148 - 1.6s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.918835 - 1.6s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.818165 - 1.6s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.913446 - 1.5s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.818750 - 1.3s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.925560 - 1.2s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.946685 - 1.5s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.609476 - 1.7s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.888815 - 1.4s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.929634 - 1.5s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.969625 - 1.3s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.730024 - 1.6s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.905760 - 1.5s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.881315 - 1.7s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.916643 - 1.6s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.811582 - 1.6s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.860761 - 1.6s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.824101 - 1.6s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.858859 - 1.6s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.950946 - 1.6s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.845991 - 1.5s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.886827 - 1.5s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.927302 - 1.8s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.872077 - 1.5s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.868123 - 1.8s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.823092 - 1.2s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.894139 - 1.3s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.718921 - 1.6s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.823313 - 1.6s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.777170 - 1.6s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.839218 - 2.0s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.818750 - 1.7s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.824733 - 1.5s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.843508 - 1.6s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.767841 - 1.6s
[CV] c1=0.151964914335486, c2=0.06419525243307017 ....................
[CV] c1=0.151964914335486, c2=0.06419525243307017, score=0.900263 - 1.6s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.907943 - 1.6s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.827435 - 1.6s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.824101 - 1.5s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.861991 - 1.6s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.898170 - 1.3s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.908836 - 1.5s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.925560 - 1.6s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.923585 - 1.6s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.727632 - 1.4s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.837210 - 1.4s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.934961 - 1.6s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.700167 - 1.6s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.718975 - 1.7s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.871570 - 1.7s
[CV] c1=0.7691901366762777, c2=0.018786342851753436 ..................
[CV] c1=0.7691901366762777, c2=0.018786342851753436, score=0.820742 - 1.7s
[CV] c1=0.9362245178762235, c2=0.0036840823697806197 .................
[CV] c1=0.9362245178762235, c2=0.0036840823697806197, score=0.811582 - 1.6s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.801739 - 1.8s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.922590 - 1.7s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.839383 - 1.6s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.828771 - 1.6s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.827010 - 1.6s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.828771 - 1.5s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.886827 - 1.5s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.913115 - 1.7s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.850984 - 1.6s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.878770 - 1.4s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.834850 - 1.6s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.836321 - 1.6s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.691973 - 1.7s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.881315 - 1.5s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.873287 - 1.6s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.923259 - 1.5s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.931609 - 1.7s
[CV] c1=0.19547632362615144, c2=0.051817682646593026 .................
[CV] c1=0.19547632362615144, c2=0.051817682646593026, score=0.683730 - 2.0s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.913115 - 1.6s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.727632 - 1.2s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.848986 - 1.6s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.893806 - 1.3s
[CV] c1=1.1770464694382454, c2=0.07280122254622126 ...................
[CV] c1=1.1770464694382454, c2=0.07280122254622126, score=0.727632 - 1.6s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.918061 - 1.5s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.888270 - 1.0s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.790879 - 1.6s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.904751 - 1.5s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.918674 - 1.5s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.784927 - 1.6s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.729474 - 1.7s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.946685 - 1.2s
[CV] c1=0.21944861613366148, c2=0.007493367060064349 .................
[CV] c1=0.21944861613366148, c2=0.007493367060064349, score=0.813790 - 1.5s
[CV] c1=0.13542106358526157, c2=0.06613572987227866 ..................
[CV] c1=0.13542106358526157, c2=0.06613572987227866, score=0.917828 - 1.5s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.927564 - 1.6s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.803211 - 1.6s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.819619 - 1.1s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.864462 - 1.6s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.862528 - 1.5s
[CV] c1=0.41069923197664315, c2=0.02601572011706776 ..................
[CV] c1=0.41069923197664315, c2=0.02601572011706776, score=0.820742 - 1.9s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.777170 - 1.5s
[CV] c1=0.16617627893415826, c2=0.016246283722594547 .................
[CV] c1=0.16617627893415826, c2=0.016246283722594547, score=0.848986 - 1.6s
[CV] c1=1.508340551127507, c2=0.021335543550593316 ...................
[CV] c1=1.508340551127507, c2=0.021335543550593316, score=0.781951 - 1.5s
[CV] c1=0.3279727332028919, c2=0.004720316064409802 ..................
[CV] c1=0.3279727332028919, c2=0.004720316064409802, score=0.813790 - 1.8s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.830388 - 1.5s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.819787 - 1.7s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.679842 - 1.4s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.751773 - 1.7s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.818750 - 1.5s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.817260 - 1.7s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.633367 - 1.8s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.868123 - 1.3s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.854858 - 1.6s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.767841 - 1.6s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.905632 - 1.5s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.889572 - 1.5s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.828274 - 1.5s
[CV] c1=0.005294883330735351, c2=0.01797692767656751 .................
[CV] c1=0.005294883330735351, c2=0.01797692767656751, score=0.925560 - 1.4s
[CV] c1=0.4737963896619468, c2=0.010699938700759807 ..................
[CV] c1=0.4737963896619468, c2=0.010699938700759807, score=0.946646 - 1.6s
[CV] c1=0.09326310944142512, c2=0.02293857362257262 ..................
[CV] c1=0.09326310944142512, c2=0.02293857362257262, score=0.941948 - 1.7s
[CV] c1=0.6526918794500971, c2=0.014168653025375195 ..................
[CV] c1=0.6526918794500971, c2=0.014168653025375195, score=0.932900 - 1.7s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.775915 - 1.6s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.881315 - 1.6s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.874304 - 1.6s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.881315 - 1.7s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.821991 - 1.7s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.929634 - 1.3s
[CV] c1=0.015260815191617596, c2=0.010533468233650554 ................
[CV] c1=0.015260815191617596, c2=0.010533468233650554, score=0.856896 - 1.7s
[CV] c1=1.1791456131357725, c2=0.009905947625121205 ..................
[CV] c1=1.1791456131357725, c2=0.009905947625121205, score=0.791058 - 1.6s
[CV] c1=0.01625033152790397, c2=0.004437967561302151 .................
[CV] c1=0.01625033152790397, c2=0.004437967561302151, score=0.722450 - 1.9s
[CV] c1=1.0574768522936129, c2=0.010094693629619428 ..................
[CV] c1=1.0574768522936129, c2=0.010094693629619428, score=0.868514 - 1.6s
[CV] c1=0.4639226651882826, c2=0.1771708074662829 ....................
[CV] c1=0.4639226651882826, c2=0.1771708074662829, score=0.898935 - 1.4s
Training done in: 10.548893s
Saving training model...
Saving training model done in: 0.013080s
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Prediction done in: 0.041656s