Run5_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: False False
Report file: _v11
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003735s
-------------------------------- 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=0.08426040318830852, c2=0.002328265004792895 .................
[CV] c1=0.08426040318830852, c2=0.002328265004792895, score=0.876754 - 1.0s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.870921 - 1.0s
[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
[CV] c1=0.5240513458580968, c2=0.013581892070558639, score=0.911799 - 1.4s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.911799 - 1.1s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.722395 - 1.2s
[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
[CV] c1=0.08426040318830852, c2=0.002328265004792895, score=0.853481 - 1.0s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.679217 - 1.3s
[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
[CV] c1=1.6432543044010746, c2=0.052616499777765384, score=0.870921 - 1.2s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.801130 - 1.0s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.954937 - 1.1s
[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
[CV] c1=0.04963393265100299, c2=0.088551724674726, score=0.903499 - 1.4s
[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
[CV] c1=0.1938501827725464, c2=0.060963666181269166, score=0.874448 - 1.3s
[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
[CV] c1=0.46250133950837036, c2=0.03491945784167068, score=0.816898 - 1.3s
[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
[CV] c1=0.16709072688926693, c2=0.03966093568152965, score=0.942868 - 1.4s
[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
[CV] c1=0.3021941878425496, c2=0.003216589098510098, score=0.866353 - 1.1s
[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
[CV] c1=0.20607603990598763, c2=0.0747627966661754, score=0.854935 - 1.2s
[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
[CV] c1=0.5240513458580968, c2=0.013581892070558639, score=0.787478 - 1.4s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.783151 - 1.2s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.796785 - 1.3s
[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
[CV] c1=0.14521637026904505, c2=0.02160263268998293, score=0.836305 - 1.1s
[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
[CV] c1=0.20607603990598763, c2=0.0747627966661754, score=0.924842 - 1.2s
[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
[CV] c1=0.5240513458580968, c2=0.013581892070558639, score=0.692146 - 1.5s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.820836 - 1.1s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.864680 - 1.2s
[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
[CV] c1=0.04963393265100299, c2=0.088551724674726, score=0.859890 - 1.5s
[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
[CV] c1=0.1938501827725464, c2=0.060963666181269166, score=0.907893 - 1.2s
[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
[CV] c1=0.46250133950837036, c2=0.03491945784167068, score=0.925933 - 1.4s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.839355 - 1.4s
[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
[CV] c1=0.14521637026904505, c2=0.02160263268998293, score=0.924118 - 1.3s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.695802 - 1.1s
[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
[CV] c1=0.5240513458580968, c2=0.013581892070558639, score=0.854874 - 1.3s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.626801 - 1.3s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.854811 - 1.4s
[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
[CV] c1=0.3021941878425496, c2=0.003216589098510098, score=0.931824 - 1.1s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.801531 - 1.4s
[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
[CV] c1=0.04758003297351373, c2=0.10579732691225392, score=0.884047 - 1.1s
[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
[CV] c1=0.4238319563930542, c2=0.08124852735361125, score=0.924842 - 1.1s
[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
[CV] c1=0.22568008528765934, c2=0.025016650518504283, score=0.888803 - 1.1s
[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
[CV] c1=0.14521637026904505, c2=0.02160263268998293, score=0.931814 - 1.1s
[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
[CV] c1=0.20607603990598763, c2=0.0747627966661754, score=0.824358 - 1.4s
[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
[CV] c1=1.6432543044010746, c2=0.052616499777765384, score=0.597112 - 1.3s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.912409 - 1.3s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.931814 - 1.3s
[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
[CV] c1=0.3021941878425496, c2=0.003216589098510098, score=0.831726 - 1.2s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.566809 - 1.3s
[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
[CV] c1=1.6432543044010746, c2=0.052616499777765384, score=0.672936 - 1.3s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.878774 - 1.2s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.843508 - 1.4s
[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
[CV] c1=0.14521637026904505, c2=0.02160263268998293, score=0.888803 - 1.2s
[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
[CV] c1=0.20607603990598763, c2=0.0747627966661754, score=0.779035 - 1.3s
[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
[CV] c1=0.5240513458580968, c2=0.013581892070558639, score=0.931824 - 1.4s
[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
[CV] c1=0.8398646451603109, c2=0.015812206995340566, score=0.863374 - 1.2s
[CV] c1=0.08086735329920966, c2=0.046728936926976494 .................
[CV] c1=0.08086735329920966, c2=0.046728936926976494, score=0.916685 - 1.4s
[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
[CV] c1=0.04963393265100299, c2=0.088551724674726, score=0.722395 - 1.2s
[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
[CV] c1=0.1938501827725464, c2=0.060963666181269166, score=0.897917 - 1.2s
[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
[CV] c1=0.04758003297351373, c2=0.10579732691225392, score=0.854811 - 1.2s
[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
[CV] c1=0.42180099361133494, c2=0.054830905439908206, score=0.857192 - 1.2s
[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
[CV] c1=0.15129291116762528, c2=0.040969962486065804, score=0.934983 - 1.0s
[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
[CV] c1=0.14521637026904505, c2=0.02160263268998293, score=0.722395 - 1.1s
[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
[CV] c1=0.20607603990598763, c2=0.0747627966661754, score=0.717373 - 1.4s
[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
[CV] c1=0.5240513458580968, c2=0.013581892070558639, score=0.883573 - 1.4s
[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
[CV] c1=0.4238319563930542, c2=0.08124852735361125, score=0.843546 - 1.2s
[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
[CV] c1=0.22568008528765934, c2=0.025016650518504283, score=0.722395 - 1.3s
[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
[CV] c1=0.3021941878425496, c2=0.003216589098510098, score=0.896731 - 1.1s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.754955 - 1.3s
[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
[CV] c1=1.6432543044010746, c2=0.052616499777765384, score=0.710551 - 1.3s
[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
[CV] c1=0.4238319563930542, c2=0.08124852735361125, score=0.816898 - 1.1s
[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
[CV] c1=0.22568008528765934, c2=0.025016650518504283, score=0.854935 - 1.2s
[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
[CV] c1=0.08426040318830852, c2=0.002328265004792895, score=0.893442 - 1.1s
[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
[CV] c1=0.02350745992548303, c2=0.05840652032018121, score=0.934983 - 1.2s
[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
[CV] c1=0.04758003297351373, c2=0.10579732691225392, score=0.934983 - 1.1s
[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
[CV] c1=0.4238319563930542, c2=0.08124852735361125, score=0.907893 - 1.0s
[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
[CV] c1=0.22568008528765934, c2=0.025016650518504283, score=0.897917 - 1.2s
[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
[CV] c1=0.3021941878425496, c2=0.003216589098510098, score=0.851449 - 1.2s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.688062 - 1.2s
[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
[CV] c1=1.6432543044010746, c2=0.052616499777765384, score=0.795650 - 1.3s
[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
[CV] c1=0.4238319563930542, c2=0.08124852735361125, score=0.868208 - 1.1s
[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
[CV] c1=0.22568008528765934, c2=0.025016650518504283, score=0.792736 - 1.4s
[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
[CV] c1=0.3021941878425496, c2=0.003216589098510098, score=0.736861 - 1.2s
[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
[CV] c1=1.8566153502825635, c2=0.0595145726559928, score=0.773166 - 1.2s
[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
[CV] c1=1.6432543044010746, c2=0.052616499777765384, score=0.694375 - 1.3s
[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
[CV] c1=0.4238319563930542, c2=0.08124852735361125, score=0.782242 - 1.4s
[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
[CV] c1=0.22568008528765934, c2=0.025016650518504283, score=0.874448 - 1.3s
[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
[CV] c1=0.08426040318830852, c2=0.002328265004792895, score=0.835567 - 1.2s
[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
[CV] c1=0.02350745992548303, c2=0.05840652032018121, score=0.722395 - 1.3s
[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
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[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
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[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
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[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
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[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
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[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
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[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
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[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
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[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
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[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
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[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
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[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
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[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
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[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
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[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
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[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
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[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
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[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
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[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
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[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
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[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
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[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
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[CV] c1=1.8566153502825635, c2=0.0595145726559928 ....................
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[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
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[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
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[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
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[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
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[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
[CV] c1=0.08426040318830852, c2=0.002328265004792895, score=0.716783 - 1.2s
[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
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[CV] c1=0.42180099361133494, c2=0.054830905439908206 .................
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[CV] c1=0.15129291116762528, c2=0.040969962486065804 .................
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[CV] c1=0.3021941878425496, c2=0.003216589098510098 ..................
[CV] c1=0.3021941878425496, c2=0.003216589098510098, score=0.824358 - 1.3s
[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=0.04758003297351373, c2=0.10579732691225392 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
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[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
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[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
[CV] c1=0.14521637026904505, c2=0.02160263268998293, score=0.859890 - 1.2s
[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
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[CV] c1=1.6432543044010746, c2=0.052616499777765384 ..................
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[CV] c1=0.4238319563930542, c2=0.08124852735361125 ...................
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[CV] c1=0.22568008528765934, c2=0.025016650518504283 .................
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[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
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[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
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[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
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[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
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[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
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[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
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[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
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[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
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[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
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[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
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[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
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[CV] c1=0.14521637026904505, c2=0.02160263268998293 ..................
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[CV] c1=0.20607603990598763, c2=0.0747627966661754 ...................
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[CV] c1=0.5240513458580968, c2=0.013581892070558639 ..................
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[CV] c1=0.8398646451603109, c2=0.015812206995340566 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
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[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
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[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
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[CV] c1=0.02350745992548303, c2=0.05840652032018121 ..................
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[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
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[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
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[CV] c1=0.08426040318830852, c2=0.002328265004792895 .................
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[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
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[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
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[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
[CV] c1=0.16709072688926693, c2=0.03966093568152965, score=0.836305 - 1.3s
[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
[CV] c1=0.39517791711719746, c2=0.009650373540785788, score=0.907780 - 0.9s
[CV] c1=0.04963393265100299, c2=0.088551724674726 ....................
[CV] c1=0.04963393265100299, c2=0.088551724674726, score=0.796785 - 1.4s
[CV] c1=0.1938501827725464, c2=0.060963666181269166 ..................
[CV] c1=0.1938501827725464, c2=0.060963666181269166, score=0.722395 - 1.2s
[CV] c1=0.46250133950837036, c2=0.03491945784167068 ..................
[CV] c1=0.46250133950837036, c2=0.03491945784167068, score=0.702493 - 1.4s
[CV] c1=0.16709072688926693, c2=0.03966093568152965 ..................
[CV] c1=0.16709072688926693, c2=0.03966093568152965, score=0.913784 - 1.4s
[CV] c1=0.39517791711719746, c2=0.009650373540785788 .................
[CV] c1=0.39517791711719746, c2=0.009650373540785788, score=0.815919 - 0.9s
Training done in: 8.310973s
Saving training model...
Saving training model done in: 0.013086s
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Prediction done in: 0.030126s