Run3_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 True
Report file: _v11
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003641s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 word 2
5 isUpper False
6 isLower False
7 isGreek False
8 isNumber True
9 -1:word fructose
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 word delta-arcA
7 isUpper False
8 isLower False
9 isGreek False
10 isNumber False
11 -1:word _
12 +1:word _
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.23106473162087696, c2=0.015694520156649943 .................
[CV] c1=0.23106473162087696, c2=0.015694520156649943, score=0.908106 - 1.6s
[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
[CV] c1=0.11486416926458794, c2=0.02680674100354409, score=0.920093 - 1.3s
[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
[CV] c1=1.1984741556968186, c2=0.05653817320378769, score=0.849130 - 1.6s
[CV] c1=2.593347208872597, c2=0.012299824833226647 ...................
[CV] c1=2.593347208872597, c2=0.012299824833226647, score=0.853878 - 1.5s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.852298 - 1.2s
[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
[CV] c1=0.6378651675797636, c2=0.013941131343344033, score=0.863495 - 1.2s
[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
[CV] c1=0.20126118928313821, c2=0.08056323897622286, score=0.918743 - 1.3s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.935722 - 1.4s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.923212 - 1.3s
[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
[CV] c1=0.30533486314094455, c2=0.0914754586936966, score=0.794216 - 1.3s
[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
[CV] c1=0.6378651675797636, c2=0.013941131343344033, score=0.773435 - 1.2s
[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
[CV] c1=0.5698075862470543, c2=0.010481334464662654, score=0.674636 - 1.4s
[CV] c1=0.12681094579027236, c2=0.0036690595009708006 ................
[CV] c1=0.12681094579027236, c2=0.0036690595009708006, score=0.848937 - 1.3s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.840107 - 1.4s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.869790 - 1.3s
[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
[CV] c1=0.1339240355864409, c2=0.020293819707040375, score=0.853491 - 1.3s
[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
[CV] c1=0.6125085358121363, c2=0.029808644201330697, score=0.926918 - 1.2s
[CV] c1=0.12681094579027236, c2=0.0036690595009708006 ................
[CV] c1=0.12681094579027236, c2=0.0036690595009708006, score=0.862849 - 1.3s
[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
[CV] c1=0.1962647469141778, c2=0.03287380929699173, score=0.839700 - 1.1s
[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
[CV] c1=0.30533486314094455, c2=0.0914754586936966, score=0.846616 - 1.2s
[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
[CV] c1=0.03425956492795125, c2=0.007813038595582533, score=0.930828 - 1.3s
[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
[CV] c1=0.5698075862470543, c2=0.010481334464662654, score=0.725919 - 1.4s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.879946 - 1.3s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.906184 - 1.3s
[CV] c1=0.23106473162087696, c2=0.015694520156649943 .................
[CV] c1=0.23106473162087696, c2=0.015694520156649943, score=0.830873 - 1.1s
[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
[CV] c1=0.1339240355864409, c2=0.020293819707040375, score=0.855715 - 1.2s
[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
[CV] c1=0.5698075862470543, c2=0.010481334464662654, score=0.879946 - 1.3s
[CV] c1=0.12681094579027236, c2=0.0036690595009708006 ................
[CV] c1=0.12681094579027236, c2=0.0036690595009708006, score=0.927937 - 1.3s
[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
[CV] c1=0.1962647469141778, c2=0.03287380929699173, score=0.839942 - 1.2s
[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
[CV] c1=0.2912635826026504, c2=0.02156672100740503, score=0.826386 - 1.0s
[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
[CV] c1=0.03425956492795125, c2=0.007813038595582533, score=0.910672 - 1.4s
[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
[CV] c1=0.11486416926458794, c2=0.02680674100354409, score=0.930828 - 1.5s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.809719 - 1.5s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.814300 - 1.6s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.841339 - 1.1s
[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
[CV] c1=0.03425956492795125, c2=0.007813038595582533, score=0.839499 - 1.3s
[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
[CV] c1=0.20126118928313821, c2=0.08056323897622286, score=0.895946 - 1.3s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.794216 - 1.2s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.852010 - 1.5s
[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
[CV] c1=0.2912635826026504, c2=0.02156672100740503, score=0.794216 - 1.4s
[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
[CV] c1=0.03425956492795125, c2=0.007813038595582533, score=0.869790 - 1.3s
[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
[CV] c1=0.20126118928313821, c2=0.08056323897622286, score=0.794216 - 1.5s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.856620 - 1.5s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.930828 - 1.4s
[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
[CV] c1=0.2912635826026504, c2=0.02156672100740503, score=0.926918 - 1.1s
[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
[CV] c1=0.03425956492795125, c2=0.007813038595582533, score=0.854345 - 1.3s
[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
[CV] c1=0.20126118928313821, c2=0.08056323897622286, score=0.857663 - 1.4s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.759504 - 1.6s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.857803 - 1.4s
[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
[CV] c1=0.2912635826026504, c2=0.02156672100740503, score=0.863576 - 1.3s
[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
[CV] c1=0.03425956492795125, c2=0.007813038595582533, score=0.927937 - 1.2s
[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
[CV] c1=0.20126118928313821, c2=0.08056323897622286, score=0.660059 - 1.5s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.926918 - 1.3s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.694239 - 1.5s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.930828 - 1.2s
[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
[CV] c1=0.1339240355864409, c2=0.020293819707040375, score=0.704991 - 1.4s
[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
[CV] c1=0.6125085358121363, c2=0.029808644201330697, score=0.674636 - 1.4s
[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
[CV] c1=0.4770198491983926, c2=0.011670029650325785, score=0.678668 - 1.3s
[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
[CV] c1=0.1962647469141778, c2=0.03287380929699173, score=0.794216 - 1.2s
[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
[CV] c1=0.2912635826026504, c2=0.02156672100740503, score=0.888761 - 1.2s
[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
[CV] c1=0.03425956492795125, c2=0.007813038595582533, score=0.853754 - 1.3s
[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
[CV] c1=0.20126118928313821, c2=0.08056323897622286, score=0.927937 - 1.3s
[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
[CV] c1=0.3861841949004038, c2=0.03323132379303178, score=0.678668 - 1.5s
[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
[CV] c1=0.017720414748734287, c2=0.14805811330028124, score=0.830776 - 1.6s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.923212 - 1.3s
[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
[CV] c1=0.1339240355864409, c2=0.020293819707040375, score=0.794216 - 1.4s
[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
[CV] c1=0.6125085358121363, c2=0.029808644201330697, score=0.863495 - 1.4s
[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
[CV] c1=0.4770198491983926, c2=0.011670029650325785, score=0.926918 - 1.3s
[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
[CV] c1=0.1962647469141778, c2=0.03287380929699173, score=0.862849 - 1.2s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.694239 - 1.3s
[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
[CV] c1=0.6378651675797636, c2=0.013941131343344033, score=0.928690 - 1.3s
[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
[CV] c1=0.5698075862470543, c2=0.010481334464662654, score=0.928690 - 1.4s
[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
[CV] c1=0.4770198491983926, c2=0.011670029650325785, score=0.809719 - 1.3s
[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
[CV] c1=0.1962647469141778, c2=0.03287380929699173, score=0.927937 - 1.3s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.849711 - 1.3s
[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
[CV] c1=0.1339240355864409, c2=0.020293819707040375, score=0.838382 - 1.4s
[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
[CV] c1=1.1984741556968186, c2=0.05653817320378769, score=0.687196 - 1.4s
[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
[CV] c1=0.4770198491983926, c2=0.011670029650325785, score=0.808847 - 1.2s
[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
[CV] c1=0.1962647469141778, c2=0.03287380929699173, score=0.795085 - 1.2s
[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
[CV] c1=0.022102126823387226, c2=0.06924520730038973, score=0.830776 - 1.3s
[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
[CV] c1=0.1339240355864409, c2=0.020293819707040375, score=0.955586 - 1.4s
[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
[CV] c1=0.6125085358121363, c2=0.029808644201330697, score=0.928690 - 1.4s
[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
[CV] c1=0.4770198491983926, c2=0.011670029650325785, score=0.851982 - 1.4s
[CV] c1=0.4918515596977871, c2=0.0022814573087973607 .................
[CV] c1=0.4918515596977871, c2=0.0022814573087973607, score=0.926918 - 1.1s
[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
[CV] c1=0.30533486314094455, c2=0.0914754586936966, score=0.791788 - 1.5s
[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
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[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
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[CV] c1=0.12681094579027236, c2=0.0036690595009708006 ................
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[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
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[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
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[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
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[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
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[CV] c1=0.23106473162087696, c2=0.015694520156649943 .................
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[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
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[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
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[CV] c1=0.022102126823387226, c2=0.06924520730038973 .................
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[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
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[CV] c1=0.4918515596977871, c2=0.0022814573087973607 .................
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[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
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[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
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[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
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[CV] c1=0.4918515596977871, c2=0.0022814573087973607 .................
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[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
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[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
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[CV] c1=0.12681094579027236, c2=0.0036690595009708006 ................
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[CV] c1=0.4918515596977871, c2=0.0022814573087973607 .................
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[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
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[CV] c1=0.4918515596977871, c2=0.0022814573087973607 .................
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[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
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[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
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[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
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[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
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[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
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[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
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[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
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[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
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[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
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[CV] c1=0.23106473162087696, c2=0.015694520156649943 .................
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[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
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[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
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[CV] c1=2.593347208872597, c2=0.012299824833226647 ...................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
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[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
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[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
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[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
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[CV] c1=0.3861841949004038, c2=0.03323132379303178 ...................
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[CV] c1=0.1962647469141778, c2=0.03287380929699173 ...................
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[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
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[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
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[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
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[CV] c1=0.12681094579027236, c2=0.0036690595009708006 ................
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[CV] c1=0.017720414748734287, c2=0.14805811330028124 .................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
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[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
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[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
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[CV] c1=0.5698075862470543, c2=0.010481334464662654 ..................
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[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
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[CV] c1=0.4918515596977871, c2=0.0022814573087973607 .................
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[CV] c1=0.30533486314094455, c2=0.0914754586936966 ...................
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[CV] c1=0.6378651675797636, c2=0.013941131343344033 ..................
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[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
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[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
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[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
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[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
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[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
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[CV] c1=2.593347208872597, c2=0.012299824833226647 ...................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
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[CV] c1=0.23106473162087696, c2=0.015694520156649943 .................
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[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
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[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
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[CV] c1=2.593347208872597, c2=0.012299824833226647 ...................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
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[CV] c1=0.23106473162087696, c2=0.015694520156649943 .................
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[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
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[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
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[CV] c1=2.593347208872597, c2=0.012299824833226647 ...................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
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[CV] c1=0.2912635826026504, c2=0.02156672100740503 ...................
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[CV] c1=0.03425956492795125, c2=0.007813038595582533 .................
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[CV] c1=0.20126118928313821, c2=0.08056323897622286 ..................
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[CV] c1=0.12681094579027236, c2=0.0036690595009708006 ................
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[CV] c1=0.4918515596977871, c2=0.0022814573087973607 .................
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[CV] c1=0.1339240355864409, c2=0.020293819707040375 ..................
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[CV] c1=0.6125085358121363, c2=0.029808644201330697 ..................
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[CV] c1=0.4770198491983926, c2=0.011670029650325785 ..................
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[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
[CV] c1=1.6065853828524328, c2=0.007959562254287294, score=0.567922 - 1.4s
[CV] c1=0.23106473162087696, c2=0.015694520156649943 .................
[CV] c1=0.23106473162087696, c2=0.015694520156649943, score=0.794216 - 1.4s
[CV] c1=0.11486416926458794, c2=0.02680674100354409 ..................
[CV] c1=0.11486416926458794, c2=0.02680674100354409, score=0.705243 - 1.5s
[CV] c1=1.1984741556968186, c2=0.05653817320378769 ...................
[CV] c1=1.1984741556968186, c2=0.05653817320378769, score=0.839761 - 1.3s
[CV] c1=2.593347208872597, c2=0.012299824833226647 ...................
[CV] c1=2.593347208872597, c2=0.012299824833226647, score=0.617476 - 1.5s
[CV] c1=1.6065853828524328, c2=0.007959562254287294 ..................
[CV] c1=1.6065853828524328, c2=0.007959562254287294, score=0.846283 - 1.3s
Training done in: 8.982838s
Saving training model...
Saving training model done in: 0.013084s
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Prediction done in: 0.033790s