Run1_v2.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_v4.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30_v4.txt
Exclude stop words: False
Levels: False False
Report file: _v2
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 283
Sentences test data: 122
Reading corpus done in: 0.003629s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 1
1 postag CD
2 -1:lemma pq
3 -1:postag NN
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-fnr
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=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.659121 - 1.0s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.721334 - 1.2s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.656490 - 1.1s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.632439 - 1.1s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.720311 - 1.2s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.573418 - 0.9s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.674776 - 1.1s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.721334 - 1.2s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.715320 - 1.2s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.647203 - 1.2s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.920970 - 1.1s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.647203 - 1.2s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.745362 - 1.1s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.654823 - 1.0s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.919762 - 1.1s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.660510 - 1.1s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.867500 - 1.1s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.699610 - 1.2s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.720311 - 1.2s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.564072 - 1.0s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.607039 - 0.8s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.865590 - 1.1s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.841313 - 1.2s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.919762 - 1.1s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.775757 - 1.2s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.654823 - 1.1s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.935386 - 1.1s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.647062 - 1.0s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.906853 - 1.1s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.568556 - 1.1s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.848001 - 1.2s
[CV] c1=0.8749871337656958, c2=0.10465716037380113 ...................
[CV] c1=0.8749871337656958, c2=0.10465716037380113, score=0.812515 - 1.1s
[CV] c1=0.8748278310570387, c2=0.16014963439323648 ...................
[CV] c1=0.8748278310570387, c2=0.16014963439323648, score=0.787287 - 1.1s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.875991 - 0.9s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.660504 - 1.1s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.656490 - 1.2s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.867500 - 1.1s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.674776 - 1.1s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.919762 - 1.2s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.521206 - 0.9s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.794740 - 1.1s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.920970 - 1.1s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.899703 - 1.3s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.660510 - 1.1s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.596309 - 1.1s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.720311 - 1.2s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.866790 - 1.2s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.642260 - 1.2s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.603251 - 1.0s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.614085 - 1.2s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.548511 - 0.9s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.727470 - 1.1s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.630985 - 1.0s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.860755 - 1.1s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.877650 - 1.2s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.704452 - 1.2s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.593824 - 1.0s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.776926 - 1.2s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.590947 - 1.0s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.866790 - 1.3s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.725767 - 1.1s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.739346 - 1.2s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.557148 - 1.0s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.848001 - 1.3s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.615427 - 1.2s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.877650 - 1.2s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.603356 - 1.0s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.802426 - 1.2s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.864349 - 1.1s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.785069 - 1.1s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.652192 - 0.9s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.848001 - 1.2s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.874700 - 1.2s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.854423 - 1.1s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.840539 - 1.3s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.694072 - 1.0s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.814619 - 1.2s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.852821 - 1.2s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.724007 - 1.1s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.740663 - 1.2s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.906853 - 1.1s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.752792 - 1.2s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.565690 - 1.0s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.881938 - 1.2s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.689296 - 1.1s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.737619 - 1.1s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.740663 - 1.1s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.761418 - 1.2s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.750132 - 1.2s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.643620 - 1.2s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.919762 - 1.3s
[CV] c1=0.8749871337656958, c2=0.10465716037380113 ...................
[CV] c1=0.8749871337656958, c2=0.10465716037380113, score=0.558164 - 1.0s
[CV] c1=0.8748278310570387, c2=0.16014963439323648 ...................
[CV] c1=0.8748278310570387, c2=0.16014963439323648, score=0.609849 - 1.1s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.608719 - 0.9s
[CV] c1=1.8472687447020986, c2=0.04257730516940555 ...................
[CV] c1=1.8472687447020986, c2=0.04257730516940555, score=0.781637 - 1.1s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.878327 - 1.1s
[CV] c1=0.16006119829799537, c2=0.019860752797724687 .................
[CV] c1=0.16006119829799537, c2=0.019860752797724687, score=0.906853 - 1.1s
[CV] c1=0.4473078179611142, c2=0.031890587207333114 ..................
[CV] c1=0.4473078179611142, c2=0.031890587207333114, score=0.919762 - 1.1s
[CV] c1=0.24874618699414613, c2=0.11465004865259165 ..................
[CV] c1=0.24874618699414613, c2=0.11465004865259165, score=0.899703 - 1.1s
[CV] c1=0.08079651514556553, c2=0.07338414365364293 ..................
[CV] c1=0.08079651514556553, c2=0.07338414365364293, score=0.906853 - 1.3s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.905489 - 1.2s
[CV] c1=0.8749871337656958, c2=0.10465716037380113 ...................
[CV] c1=0.8749871337656958, c2=0.10465716037380113, score=0.624832 - 1.0s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.713945 - 1.1s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.654823 - 1.1s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.654823 - 1.1s
[CV] c1=0.07184657725057575, c2=0.06305366522004678 ..................
[CV] c1=0.07184657725057575, c2=0.06305366522004678, score=0.866790 - 1.2s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.906853 - 1.2s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.876920 - 1.1s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.840539 - 1.3s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.607039 - 0.9s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.852044 - 1.3s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.760431 - 1.1s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.875991 - 1.1s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.731639 - 1.3s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.866790 - 1.1s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.720311 - 1.2s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.608985 - 0.9s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.834063 - 1.2s
[CV] c1=0.09369139763074265, c2=0.07537173130694604 ..................
[CV] c1=0.09369139763074265, c2=0.07537173130694604, score=0.848001 - 1.2s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.720311 - 1.1s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.881938 - 1.2s
[CV] c1=0.8749871337656958, c2=0.10465716037380113 ...................
[CV] c1=0.8749871337656958, c2=0.10465716037380113, score=0.815463 - 1.2s
[CV] c1=0.8748278310570387, c2=0.16014963439323648 ...................
[CV] c1=0.8748278310570387, c2=0.16014963439323648, score=0.564654 - 0.9s
[CV] c1=0.23466274005583443, c2=0.14468669456987662 ..................
[CV] c1=0.23466274005583443, c2=0.14468669456987662, score=0.707931 - 1.1s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.906853 - 1.0s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.883954 - 1.2s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.897401 - 1.1s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.920970 - 1.2s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.906853 - 1.1s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.680867 - 1.1s
[CV] c1=0.7577102413636053, c2=0.053324799785666135 ..................
[CV] c1=0.7577102413636053, c2=0.053324799785666135, score=0.912680 - 1.3s
[CV] c1=0.006393182611656157, c2=0.021090760536671197 ................
[CV] c1=0.006393182611656157, c2=0.021090760536671197, score=0.902145 - 1.1s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.868803 - 1.2s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.848001 - 1.2s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.775757 - 1.0s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.779725 - 1.1s
[CV] c1=0.8749871337656958, c2=0.10465716037380113 ...................
[CV] c1=0.8749871337656958, c2=0.10465716037380113, score=0.691841 - 1.2s
[CV] c1=0.8748278310570387, c2=0.16014963439323648 ...................
[CV] c1=0.8748278310570387, c2=0.16014963439323648, score=0.815463 - 1.1s
[CV] c1=0.23466274005583443, c2=0.14468669456987662 ..................
[CV] c1=0.23466274005583443, c2=0.14468669456987662, score=0.724198 - 1.0s
[CV] c1=0.3233518999667819, c2=0.029859516013558064 ..................
[CV] c1=0.3233518999667819, c2=0.029859516013558064, score=0.721334 - 0.9s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.718465 - 1.2s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.741434 - 1.1s
[CV] c1=0.8748278310570387, c2=0.16014963439323648 ...................
[CV] c1=0.8748278310570387, c2=0.16014963439323648, score=0.653248 - 1.2s
[CV] c1=0.23466274005583443, c2=0.14468669456987662 ..................
[CV] c1=0.23466274005583443, c2=0.14468669456987662, score=0.632439 - 1.0s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.887557 - 1.1s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.753693 - 1.1s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.654823 - 1.0s
[CV] c1=0.2962778461664418, c2=0.28403918392921157 ...................
[CV] c1=0.2962778461664418, c2=0.28403918392921157, score=0.717219 - 1.3s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.720311 - 1.2s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.840539 - 1.2s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.660510 - 1.1s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.923613 - 1.1s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.906853 - 1.1s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.775757 - 1.2s
[CV] c1=0.02968662156028001, c2=0.12184278879734725 ..................
[CV] c1=0.02968662156028001, c2=0.12184278879734725, score=0.875991 - 1.0s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.906853 - 1.3s
[CV] c1=0.8749871337656958, c2=0.10465716037380113 ...................
[CV] c1=0.8749871337656958, c2=0.10465716037380113, score=0.852672 - 1.1s
[CV] c1=0.8748278310570387, c2=0.16014963439323648 ...................
[CV] c1=0.8748278310570387, c2=0.16014963439323648, score=0.843581 - 1.0s
[CV] c1=0.23466274005583443, c2=0.14468669456987662 ..................
[CV] c1=0.23466274005583443, c2=0.14468669456987662, score=0.694090 - 1.1s
[CV] c1=0.3233518999667819, c2=0.029859516013558064 ..................
[CV] c1=0.3233518999667819, c2=0.029859516013558064, score=0.679766 - 1.0s
[CV] c1=0.1483614516251027, c2=0.06633729885192889 ...................
[CV] c1=0.1483614516251027, c2=0.06633729885192889, score=0.603251 - 1.0s
[CV] c1=0.8749871337656958, c2=0.10465716037380113 ...................
[CV] c1=0.8749871337656958, c2=0.10465716037380113, score=0.691890 - 1.2s
[CV] c1=0.8748278310570387, c2=0.16014963439323648 ...................
[CV] c1=0.8748278310570387, c2=0.16014963439323648, score=0.624124 - 1.2s
[CV] c1=0.23466274005583443, c2=0.14468669456987662 ..................
[CV] c1=0.23466274005583443, c2=0.14468669456987662, score=0.919762 - 1.4s
[CV] c1=0.3233518999667819, c2=0.029859516013558064 ..................
[CV] c1=0.3233518999667819, c2=0.029859516013558064, score=0.580556 - 0.7s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.852821 - 1.2s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.760431 - 1.1s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.740663 - 1.1s
[CV] c1=0.026281073826085702, c2=0.11845123072490214 .................
[CV] c1=0.026281073826085702, c2=0.11845123072490214, score=0.887557 - 1.3s
[CV] c1=0.3233518999667819, c2=0.029859516013558064 ..................
[CV] c1=0.3233518999667819, c2=0.029859516013558064, score=0.872249 - 0.9s
[CV] c1=0.5898209423957529, c2=0.01037034945739547 ...................
[CV] c1=0.5898209423957529, c2=0.01037034945739547, score=0.708877 - 1.2s
[CV] c1=0.014516456694382724, c2=0.020326963729101803 ................
[CV] c1=0.014516456694382724, c2=0.020326963729101803, score=0.866790 - 1.1s
[CV] c1=0.17342748153476484, c2=0.03315662632542101 ..................
[CV] c1=0.17342748153476484, c2=0.03315662632542101, score=0.783313 - 1.3s
[CV] c1=0.23466274005583443, c2=0.14468669456987662 ..................
[CV] c1=0.23466274005583443, c2=0.14468669456987662, score=0.848001 - 1.2s
[CV] c1=0.3233518999667819, c2=0.029859516013558064 ..................
[CV] c1=0.3233518999667819, c2=0.029859516013558064, score=0.867217 - 1.0s
Training done in: 7.447655s
Saving training model...
Saving training model done in: 0.014152s
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Prediction done in: 0.025248s