Run4_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: True True
Report file: _v2
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 283
Sentences test data: 122
Reading corpus done in: 0.004035s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 1
1 postag CD
2 -1:lemma pq
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 word[:1] 1
9 word 1
10 isUpper False
11 isLower False
12 isGreek False
13 isNumber True
14 -1:word PQ
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-fnr
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 hUpper False
7 hLower False
8 hGreek False
9 symb True
10 word[:1] d
11 word[:2] de
12 word delta-fnr
13 isUpper False
14 isLower True
15 isGreek False
16 isNumber False
17 -1:word _
18 +1:word _
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.719482 - 1.7s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.964829 - 1.8s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.671893 - 1.4s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.860861 - 1.8s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.714313 - 1.7s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.932342 - 1.5s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.893986 - 1.6s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.850267 - 1.6s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.713686 - 1.4s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.728846 - 1.7s
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.715320 - 1.7s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.854753 - 1.6s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.644709 - 1.7s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.868023 - 2.1s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.628257 - 1.6s
[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
[CV] c1=0.4078998263978875, c2=0.03823537952712818, score=0.729114 - 1.5s
[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
[CV] c1=1.0979918753546847, c2=0.002918879102946894, score=0.805804 - 1.7s
[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
[CV] c1=1.9851987092826848, c2=0.05255571087688783, score=0.630354 - 1.3s
[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
[CV] c1=0.7263916143048589, c2=0.031205799626709132, score=0.714493 - 1.6s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.750968 - 1.8s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.696002 - 1.5s
[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
[CV] c1=1.0979918753546847, c2=0.002918879102946894, score=0.664975 - 1.4s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.745162 - 1.7s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.792078 - 1.8s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.947941 - 1.6s
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.628257 - 1.4s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.718319 - 1.8s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.855472 - 1.7s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.757924 - 1.8s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.885770 - 1.9s
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.885770 - 1.8s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.708131 - 1.3s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.709305 - 1.6s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.709789 - 1.9s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.854474 - 1.8s
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.706850 - 1.6s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.778194 - 1.4s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.657958 - 1.7s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.718319 - 2.0s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.879698 - 1.9s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.760487 - 1.3s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.733738 - 1.8s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.666232 - 1.7s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.887504 - 2.0s
[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
[CV] c1=0.19555004078116134, c2=0.013719557943369584, score=0.729277 - 1.6s
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.766835 - 1.6s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.868023 - 1.8s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.682610 - 1.6s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.959209 - 1.8s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.778194 - 1.8s
[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
[CV] c1=0.4078998263978875, c2=0.03823537952712818, score=0.885770 - 1.8s
[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
[CV] c1=0.6094784835218059, c2=0.01690933209411638, score=0.730987 - 1.4s
[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
[CV] c1=0.4346959767707268, c2=0.004694241666253667, score=0.709789 - 1.6s
[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
[CV] c1=0.7263916143048589, c2=0.031205799626709132, score=0.887052 - 1.7s
[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
[CV] c1=0.19555004078116134, c2=0.013719557943369584, score=0.779163 - 1.6s
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.864078 - 1.8s
[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
[CV] c1=0.2858121257516539, c2=0.017143803593821803, score=0.747961 - 1.6s
[CV] c1=1.6285175067140285, c2=0.06773142195214325 ...................
[CV] c1=1.6285175067140285, c2=0.06773142195214325, score=0.883968 - 1.6s
[CV] c1=0.30683200632675367, c2=0.019783947264900577 .................
[CV] c1=0.30683200632675367, c2=0.019783947264900577, score=0.941969 - 1.8s
[CV] c1=0.03158220752670695, c2=0.051210940198560144 .................
[CV] c1=0.03158220752670695, c2=0.051210940198560144, score=0.901159 - 1.9s
[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
[CV] c1=0.4078998263978875, c2=0.03823537952712818, score=0.709789 - 1.7s
[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
[CV] c1=1.0979918753546847, c2=0.002918879102946894, score=0.883806 - 1.6s
[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
[CV] c1=1.9851987092826848, c2=0.05255571087688783, score=0.849709 - 1.7s
[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
[CV] c1=0.7263916143048589, c2=0.031205799626709132, score=0.930418 - 1.7s
[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
[CV] c1=0.19555004078116134, c2=0.013719557943369584, score=0.888519 - 1.7s
[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
[CV] c1=0.4078998263978875, c2=0.03823537952712818, score=0.881641 - 1.8s
[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
[CV] c1=0.6094784835218059, c2=0.01690933209411638, score=0.887052 - 1.8s
[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
[CV] c1=0.4346959767707268, c2=0.004694241666253667, score=0.720815 - 1.5s
[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
[CV] c1=0.48552233382782606, c2=0.16512343963590606, score=0.852225 - 1.8s
[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
[CV] c1=0.4728739554959987, c2=0.22420666837898567, score=0.880778 - 1.4s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.715254 - 1.7s
[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
[CV] c1=1.0979918753546847, c2=0.002918879102946894, score=0.807056 - 1.6s
[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
[CV] c1=1.9851987092826848, c2=0.05255571087688783, score=0.855472 - 1.8s
[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
[CV] c1=0.7263916143048589, c2=0.031205799626709132, score=0.779866 - 1.7s
[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
[CV] c1=0.19555004078116134, c2=0.013719557943369584, score=0.943602 - 1.8s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.847994 - 1.7s
[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
[CV] c1=1.0979918753546847, c2=0.002918879102946894, score=0.919451 - 1.5s
[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
[CV] c1=1.9851987092826848, c2=0.05255571087688783, score=0.657337 - 1.7s
[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
[CV] c1=0.7263916143048589, c2=0.031205799626709132, score=0.876022 - 1.9s
[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
[CV] c1=0.19555004078116134, c2=0.013719557943369584, score=0.943015 - 1.6s
[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
[CV] c1=0.07231471163871557, c2=0.09430964775259432, score=0.941969 - 1.7s
[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
[CV] c1=1.0979918753546847, c2=0.002918879102946894, score=0.704193 - 2.0s
[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
[CV] c1=0.4346959767707268, c2=0.004694241666253667, score=0.729114 - 1.8s
[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
[CV] c1=0.48552233382782606, c2=0.16512343963590606, score=0.696480 - 1.8s
[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
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[CV] c1=0.07231471163871557, c2=0.09430964775259432 ..................
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[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
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[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
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[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
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[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
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[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
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[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
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[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
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[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
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[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
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[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
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[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
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[CV] c1=0.2858121257516539, c2=0.017143803593821803 ..................
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[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
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[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
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[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
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[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
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[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
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[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
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[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
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[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
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[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
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[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
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[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
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[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
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[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
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[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
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[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
[CV] c1=0.6094784835218059, c2=0.01690933209411638, score=0.675603 - 1.6s
[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
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[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
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[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
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[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
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[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
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[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
[CV] c1=1.9851987092826848, c2=0.05255571087688783, score=0.655059 - 1.8s
[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
[CV] c1=0.48552233382782606, c2=0.16512343963590606, score=0.719074 - 1.8s
[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
[CV] c1=0.4728739554959987, c2=0.22420666837898567, score=0.719074 - 1.7s
[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
[CV] c1=0.10648945642165056, c2=0.015449511254995961, score=0.603309 - 1.3s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.787795 - 1.7s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.719482 - 1.6s
[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
[CV] c1=0.48552233382782606, c2=0.16512343963590606, score=0.674297 - 1.6s
[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
[CV] c1=0.4728739554959987, c2=0.22420666837898567, score=0.854753 - 1.7s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.849461 - 1.9s
[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
[CV] c1=0.6094784835218059, c2=0.01690933209411638, score=0.849461 - 1.9s
[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
[CV] c1=0.4346959767707268, c2=0.004694241666253667, score=0.932342 - 1.8s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.692156 - 1.8s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.714313 - 1.4s
[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
[CV] c1=0.4078998263978875, c2=0.03823537952712818, score=0.705001 - 1.6s
[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
[CV] c1=0.6094784835218059, c2=0.01690933209411638, score=0.932342 - 1.9s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.798468 - 1.7s
[CV] c1=0.48552233382782606, c2=0.16512343963590606 ..................
[CV] c1=0.48552233382782606, c2=0.16512343963590606, score=0.887504 - 1.7s
[CV] c1=0.4728739554959987, c2=0.22420666837898567 ...................
[CV] c1=0.4728739554959987, c2=0.22420666837898567, score=0.887504 - 1.5s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.880778 - 1.9s
[CV] c1=1.0979918753546847, c2=0.002918879102946894 ..................
[CV] c1=1.0979918753546847, c2=0.002918879102946894, score=0.699725 - 1.3s
[CV] c1=1.9851987092826848, c2=0.05255571087688783 ...................
[CV] c1=1.9851987092826848, c2=0.05255571087688783, score=0.657958 - 1.8s
[CV] c1=0.7263916143048589, c2=0.031205799626709132 ..................
[CV] c1=0.7263916143048589, c2=0.031205799626709132, score=0.811024 - 1.8s
[CV] c1=0.19555004078116134, c2=0.013719557943369584 .................
[CV] c1=0.19555004078116134, c2=0.013719557943369584, score=0.873401 - 1.7s
[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
[CV] c1=0.10648945642165056, c2=0.015449511254995961, score=0.933701 - 1.6s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.901764 - 1.7s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.651984 - 1.4s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.875476 - 1.8s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.706850 - 1.4s
[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
[CV] c1=0.10648945642165056, c2=0.015449511254995961, score=0.732294 - 1.8s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.876022 - 1.7s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.792078 - 1.9s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.719347 - 1.3s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.728846 - 1.5s
[CV] c1=0.4078998263978875, c2=0.03823537952712818 ...................
[CV] c1=0.4078998263978875, c2=0.03823537952712818, score=0.746445 - 1.7s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.719074 - 1.8s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.938702 - 1.6s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.750923 - 1.7s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.854474 - 1.4s
[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
[CV] c1=0.10648945642165056, c2=0.015449511254995961, score=0.943602 - 1.7s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.705909 - 1.6s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.698041 - 1.7s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.699565 - 1.7s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.778194 - 1.4s
[CV] c1=0.5522760556298829, c2=0.011764289096805257 ..................
[CV] c1=0.5522760556298829, c2=0.011764289096805257, score=0.887504 - 1.8s
[CV] c1=0.6094784835218059, c2=0.01690933209411638 ...................
[CV] c1=0.6094784835218059, c2=0.01690933209411638, score=0.881641 - 1.9s
[CV] c1=0.4346959767707268, c2=0.004694241666253667 ..................
[CV] c1=0.4346959767707268, c2=0.004694241666253667, score=0.882037 - 1.8s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.664975 - 1.9s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.943015 - 1.3s
[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
[CV] c1=0.10648945642165056, c2=0.015449511254995961, score=0.885770 - 1.7s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.843229 - 1.7s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.860861 - 1.7s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.788564 - 1.9s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.624694 - 1.3s
[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
[CV] c1=0.10648945642165056, c2=0.015449511254995961, score=0.888519 - 1.6s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.680329 - 1.3s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.872268 - 1.7s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.684029 - 1.6s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.891699 - 1.5s
[CV] c1=0.10648945642165056, c2=0.015449511254995961 .................
[CV] c1=0.10648945642165056, c2=0.015449511254995961, score=0.792078 - 1.6s
[CV] c1=0.8236049945299427, c2=0.15208965114284034 ...................
[CV] c1=0.8236049945299427, c2=0.15208965114284034, score=0.925608 - 1.7s
[CV] c1=0.046498819434789694, c2=0.007495861195002632 ................
[CV] c1=0.046498819434789694, c2=0.007495861195002632, score=0.870252 - 1.7s
[CV] c1=1.3104946340308028, c2=0.016932301174739674 ..................
[CV] c1=1.3104946340308028, c2=0.016932301174739674, score=0.871212 - 1.7s
[CV] c1=0.021441360234559073, c2=0.04563400559940925 .................
[CV] c1=0.021441360234559073, c2=0.04563400559940925, score=0.855704 - 1.4s
Training done in: 11.278545s
Saving training model...
Saving training model done in: 0.014307s
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Prediction done in: 0.041099s