Run_4.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 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 .................
[CV] c1=0.26433572200108835, c2=0.022956147621051873, score=0.922774 - 1.3s
[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
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Prediction done in: 0.045015s