Run_1.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: 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
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.794216 - 1.0s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.794216 - 1.1s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.921051 - 1.0s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.898568 - 1.0s
[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
[CV] c1=0.40043615725844317, c2=0.045177502071716565, score=0.894596 - 0.9s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.862491 - 1.1s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.902103 - 1.1s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.816050 - 1.1s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.920164 - 1.0s
[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
[CV] c1=0.40043615725844317, c2=0.045177502071716565, score=0.827517 - 0.9s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.865939 - 1.1s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.920093 - 1.0s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.913639 - 1.1s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.807845 - 1.1s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.692888 - 0.8s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.710242 - 1.2s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.879947 - 1.0s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.792622 - 1.2s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.683676 - 1.1s
[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
[CV] c1=0.40043615725844317, c2=0.045177502071716565, score=0.708368 - 1.0s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.839343 - 0.9s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.683676 - 1.1s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.794216 - 1.1s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.794216 - 1.1s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.854405 - 0.9s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.634294 - 1.1s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.853754 - 1.1s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.857529 - 1.1s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.872319 - 1.1s
[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
[CV] c1=0.40043615725844317, c2=0.045177502071716565, score=0.868591 - 1.0s
[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
[CV] c1=0.566877090439985, c2=0.11885476879365008, score=0.856415 - 1.0s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.921051 - 1.0s
[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
[CV] c1=1.7051690366028645, c2=0.04119436723956498, score=0.673456 - 0.9s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.879946 - 1.0s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.902301 - 1.1s
[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
[CV] c1=0.566877090439985, c2=0.11885476879365008, score=0.707416 - 1.0s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.844183 - 1.0s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.868591 - 1.0s
[CV] c1=0.25820273038993297, c2=0.1449995527843055 ...................
[CV] c1=0.25820273038993297, c2=0.1449995527843055, score=0.848009 - 1.1s
[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
[CV] c1=0.40043615725844317, c2=0.045177502071716565, score=0.792622 - 1.1s
[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
[CV] c1=0.566877090439985, c2=0.11885476879365008, score=0.619013 - 1.0s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.708368 - 1.1s
[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
[CV] c1=1.7051690366028645, c2=0.04119436723956498, score=0.829117 - 1.0s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.827517 - 0.9s
[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
[CV] c1=0.4716413701252996, c2=0.020707741802851287, score=0.773639 - 1.1s
[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
[CV] c1=0.6408852258158738, c2=0.00974947513922504, score=0.885444 - 0.9s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.820852 - 1.1s
[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
[CV] c1=1.7051690366028645, c2=0.04119436723956498, score=0.785357 - 1.0s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.911899 - 1.0s
[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
[CV] c1=0.40043615725844317, c2=0.045177502071716565, score=0.794216 - 1.1s
[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
[CV] c1=0.566877090439985, c2=0.11885476879365008, score=0.835390 - 0.9s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.924830 - 1.1s
[CV] c1=0.36321959660359887, c2=0.030083524897554965 .................
[CV] c1=0.36321959660359887, c2=0.030083524897554965, score=0.925063 - 1.0s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.755188 - 1.1s
[CV] c1=0.40043615725844317, c2=0.045177502071716565 .................
[CV] c1=0.40043615725844317, c2=0.045177502071716565, score=0.881748 - 1.2s
[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
[CV] c1=0.6408852258158738, c2=0.00974947513922504, score=0.791386 - 0.9s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.903946 - 1.0s
[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
[CV] c1=1.7051690366028645, c2=0.04119436723956498, score=0.692122 - 1.1s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.868591 - 1.0s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.595497 - 1.2s
[CV] c1=0.5538405782197408, c2=0.07960946817558003 ...................
[CV] c1=0.5538405782197408, c2=0.07960946817558003, score=0.927188 - 1.0s
[CV] c1=0.14843910146742284, c2=0.03226312504680252 ..................
[CV] c1=0.14843910146742284, c2=0.03226312504680252, score=0.846394 - 1.1s
[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
[CV] c1=1.7051690366028645, c2=0.04119436723956498, score=0.675699 - 1.1s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.708368 - 1.1s
[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
[CV] c1=0.4716413701252996, c2=0.020707741802851287, score=0.794216 - 1.1s
[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
[CV] c1=0.6408852258158738, c2=0.00974947513922504, score=0.881136 - 1.1s
[CV] c1=0.5013481333641194, c2=0.0038888430334755165 .................
[CV] c1=0.5013481333641194, c2=0.0038888430334755165, score=0.868591 - 1.0s
[CV] c1=0.55474081003644, c2=0.03200599838771336 .....................
[CV] c1=0.55474081003644, c2=0.03200599838771336, score=0.791386 - 0.9s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.794216 - 1.0s
[CV] c1=1.1447553603576668, c2=0.01990190550729197 ...................
[CV] c1=1.1447553603576668, c2=0.01990190550729197, score=0.788431 - 1.1s
[CV] c1=0.566877090439985, c2=0.11885476879365008 ....................
[CV] c1=0.566877090439985, c2=0.11885476879365008, score=0.884863 - 1.0s
[CV] c1=0.2423964251520167, c2=0.029664141745187163 ..................
[CV] c1=0.2423964251520167, c2=0.029664141745187163, score=0.794216 - 1.1s
[CV] c1=1.7051690366028645, c2=0.04119436723956498 ...................
[CV] c1=1.7051690366028645, c2=0.04119436723956498, score=0.548315 - 1.1s
[CV] c1=0.506331063874698, c2=0.006453306084976453 ...................
[CV] c1=0.506331063874698, c2=0.006453306084976453, score=0.857529 - 1.0s
[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
[CV] c1=0.4716413701252996, c2=0.020707741802851287, score=0.708368 - 1.1s
[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=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=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=0.8754300341342343, c2=0.07834116642130053 ...................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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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=0.5013481333641194, 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=0.55474081003644, 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=0.37003802271170205, c2=0.03235596392564057 ..................
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[CV] c1=0.6408852258158738, c2=0.00974947513922504 ...................
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[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
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[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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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=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
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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=0.2423964251520167, 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=0.37003802271170205, c2=0.03235596392564057 ..................
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[CV] c1=1.3109075902903429, c2=0.0987913465628396 ....................
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[CV] c1=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
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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=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
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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=0.55474081003644, 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=0.19892136084009834, c2=0.0215890963028946 ...................
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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=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
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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=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
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[CV] c1=0.37003802271170205, c2=0.03235596392564057 ..................
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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=0.06704945233304155, c2=0.06794151143065376 ..................
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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=0.19892136084009834, c2=0.0215890963028946 ...................
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[CV] c1=0.6236675675631103, c2=0.08801024577462967 ...................
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[CV] c1=0.06704945233304155, c2=0.06794151143065376 ..................
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[CV] c1=0.4716413701252996, c2=0.020707741802851287 ..................
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[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 ...................
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[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
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Prediction done in: 0.029945s