Run8_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: True True
Report file: _v11
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003623s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 lemma[:1] 2
9 postag[:1] C
10 postag[:2] CD
11 word 2
12 isUpper False
13 isLower False
14 isGreek False
15 isNumber True
16 -1:word fructose
17 -2:lemma Cra
18 -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 hUpper True
7 hLower True
8 hGreek False
9 symb True
10 lemma[:1] d
11 postag[:1] N
12 lemma[:2] de
13 postag[:2] NN
14 word delta-arcA
15 isUpper False
16 isLower False
17 isGreek False
18 isNumber False
19 -1:word _
20 +1:word _
21 -2:lemma affyexp
22 -2:postag JJ
23 +2:lemma glucose
24 +2:postag NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.886214 - 1.6s
[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
[CV] c1=0.037354859851607435, c2=0.07305354899253944, score=0.877424 - 1.7s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.917614 - 1.9s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.901459 - 1.8s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.917472 - 1.7s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.886214 - 1.7s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.927028 - 2.0s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.897464 - 1.8s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.807866 - 2.0s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.872077 - 1.9s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.864462 - 1.7s
[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
[CV] c1=0.037354859851607435, c2=0.07305354899253944, score=0.927296 - 1.7s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.617405 - 1.9s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
[CV] c1=1.448745475188601, c2=0.026142389740376516, score=0.777170 - 1.3s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.819428 - 1.9s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.826964 - 1.7s
[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.857436 - 1.7s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.759234 - 1.7s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
[CV] c1=1.448745475188601, c2=0.026142389740376516, score=0.789940 - 1.6s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.827435 - 1.8s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.947560 - 1.9s
[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.799499 - 1.7s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.798512 - 1.8s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
[CV] c1=1.448745475188601, c2=0.026142389740376516, score=0.897464 - 1.9s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.923585 - 1.8s
[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
[CV] c1=0.6426016214333032, c2=0.013291072696330009, score=0.813534 - 1.9s
[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.818750 - 2.0s
[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
[CV] c1=0.42695722657704505, c2=0.061285485086823, score=0.877672 - 1.9s
[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.917821 - 1.8s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
[CV] c1=0.46546093853678977, c2=0.10881019404335167, score=0.836208 - 1.5s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.927296 - 1.6s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.815328 - 1.8s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.744355 - 1.9s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.818450 - 2.0s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.727471 - 2.1s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.871337 - 1.6s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.879397 - 2.3s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.814374 - 1.9s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.876526 - 1.9s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.920469 - 2.0s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.710634 - 1.9s
[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
[CV] c1=0.037354859851607435, c2=0.07305354899253944, score=0.867297 - 1.8s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.859655 - 2.0s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
[CV] c1=1.448745475188601, c2=0.026142389740376516, score=0.792588 - 2.0s
[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
[CV] c1=0.068283530973784, c2=0.035968750782347465, score=0.694284 - 1.9s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.696553 - 1.8s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.815781 - 2.0s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.609476 - 2.2s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
[CV] c1=1.448745475188601, c2=0.026142389740376516, score=0.727632 - 2.2s
[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
[CV] c1=0.068283530973784, c2=0.035968750782347465, score=0.927296 - 1.9s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.869321 - 1.8s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.836437 - 1.9s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.741826 - 2.1s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
[CV] c1=1.448745475188601, c2=0.026142389740376516, score=0.767841 - 1.9s
[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
[CV] c1=0.068283530973784, c2=0.035968750782347465, score=0.888272 - 1.8s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.927296 - 1.7s
[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
[CV] c1=0.037354859851607435, c2=0.07305354899253944, score=0.855584 - 1.8s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.767841 - 1.8s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.927296 - 1.6s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.863961 - 2.1s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.832514 - 1.6s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.702779 - 2.0s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.777170 - 1.8s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.852142 - 2.2s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.950725 - 2.0s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.876720 - 1.7s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.950725 - 2.0s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.925424 - 1.9s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.827435 - 2.1s
[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
[CV] c1=0.068283530973784, c2=0.035968750782347465, score=0.857576 - 1.9s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.847957 - 2.0s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.854858 - 1.8s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.932900 - 2.1s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.916688 - 1.9s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.834436 - 1.9s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.920469 - 1.9s
[CV] c1=1.3925811330953486, c2=0.01587323954257908 ...................
[CV] c1=1.3925811330953486, c2=0.01587323954257908, score=0.792588 - 2.0s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.945654 - 2.4s
[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
[CV] c1=0.068283530973784, c2=0.035968750782347465, score=0.950946 - 1.9s
[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
[CV] c1=0.005630188558136274, c2=0.0901354093196231, score=0.854858 - 1.8s
[CV] c1=0.34832253122622947, c2=0.0024260335577202747 ................
[CV] c1=0.34832253122622947, c2=0.0024260335577202747, score=0.932775 - 2.0s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.803472 - 2.0s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
[CV] c1=1.448745475188601, c2=0.026142389740376516, score=0.917614 - 2.2s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
[CV] c1=0.46546093853678977, c2=0.10881019404335167, score=0.848596 - 1.8s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
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[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
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[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
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[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
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[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
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[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
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[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.849027 - 1.8s
[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
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[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.841763 - 1.8s
[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
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[CV] c1=0.005630188558136274, c2=0.0901354093196231 ..................
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[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
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[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
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[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
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[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
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[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
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[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
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[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
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[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.818750 - 2.0s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
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[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
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[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
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[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.833470 - 1.8s
[CV] c1=1.448745475188601, c2=0.026142389740376516 ...................
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[CV] c1=0.068283530973784, c2=0.035968750782347465 ...................
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[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
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[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.801130 - 2.0s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.786527 - 1.7s
[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.950725 - 1.8s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
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[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
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[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.932739 - 1.9s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.809571 - 2.0s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.777170 - 1.8s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
[CV] c1=0.46546093853678977, c2=0.10881019404335167, score=0.824101 - 1.6s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.931991 - 1.8s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.876720 - 1.7s
[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
[CV] c1=0.42695722657704505, c2=0.061285485086823, score=0.888955 - 1.8s
[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.871106 - 1.9s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
[CV] c1=0.46546093853678977, c2=0.10881019404335167, score=0.950725 - 1.8s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.871039 - 1.9s
[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
[CV] c1=0.037354859851607435, c2=0.07305354899253944, score=0.834436 - 1.9s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.912553 - 2.2s
[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.798097 - 2.2s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
[CV] c1=0.46546093853678977, c2=0.10881019404335167, score=0.892309 - 1.7s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.908709 - 2.0s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.694284 - 1.7s
[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
[CV] c1=0.42695722657704505, c2=0.061285485086823, score=0.824101 - 1.8s
[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.877726 - 1.7s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
[CV] c1=0.46546093853678977, c2=0.10881019404335167, score=0.702779 - 1.8s
[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
[CV] c1=0.6426016214333032, c2=0.013291072696330009, score=0.816898 - 1.8s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.855584 - 1.9s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.818750 - 2.0s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.897464 - 1.8s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.875354 - 1.5s
[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
[CV] c1=0.6426016214333032, c2=0.013291072696330009, score=0.818750 - 1.9s
[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.908266 - 1.9s
[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
[CV] c1=0.42695722657704505, c2=0.061285485086823, score=0.798342 - 2.1s
[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.824101 - 2.0s
[CV] c1=0.46546093853678977, c2=0.10881019404335167 ..................
[CV] c1=0.46546093853678977, c2=0.10881019404335167, score=0.933350 - 1.7s
[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
[CV] c1=0.6426016214333032, c2=0.013291072696330009, score=0.946646 - 1.8s
[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.932900 - 2.1s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.632413 - 1.9s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.609476 - 2.0s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.927296 - 1.4s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.708949 - 2.0s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.844415 - 2.0s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.862659 - 2.0s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.912553 - 2.1s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.864462 - 1.3s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.916643 - 1.8s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.950946 - 1.9s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.936486 - 2.0s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.759234 - 1.8s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.909996 - 1.4s
[CV] c1=0.6426016214333032, c2=0.013291072696330009 ..................
[CV] c1=0.6426016214333032, c2=0.013291072696330009, score=0.843153 - 1.6s
[CV] c1=0.037354859851607435, c2=0.07305354899253944 .................
[CV] c1=0.037354859851607435, c2=0.07305354899253944, score=0.694284 - 1.8s
[CV] c1=1.6782438716438826, c2=0.005852028918477585 ..................
[CV] c1=1.6782438716438826, c2=0.005852028918477585, score=0.750445 - 1.6s
[CV] c1=0.23763693406252395, c2=0.15562360351028884 ..................
[CV] c1=0.23763693406252395, c2=0.15562360351028884, score=0.701018 - 1.9s
[CV] c1=0.3528158466716618, c2=0.02622785537868205 ...................
[CV] c1=0.3528158466716618, c2=0.02622785537868205, score=0.813790 - 1.8s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.939823 - 1.3s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.921722 - 1.9s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.945871 - 1.8s
[CV] c1=0.7425928083768661, c2=0.07211893896234671 ...................
[CV] c1=0.7425928083768661, c2=0.07211893896234671, score=0.815896 - 1.9s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.798512 - 1.8s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.888272 - 1.5s
[CV] c1=0.019077332979171517, c2=0.03842571004062146 .................
[CV] c1=0.019077332979171517, c2=0.03842571004062146, score=0.945871 - 1.8s
[CV] c1=0.9295470777582396, c2=0.06136448305133849 ...................
[CV] c1=0.9295470777582396, c2=0.06136448305133849, score=0.744355 - 2.1s
[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
[CV] c1=0.42695722657704505, c2=0.061285485086823, score=0.950725 - 2.0s
[CV] c1=1.5389567508867608, c2=0.0341172934690459 ....................
[CV] c1=1.5389567508867608, c2=0.0341172934690459, score=0.745317 - 2.1s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.832180 - 1.5s
[CV] c1=0.23410168766018233, c2=0.007576332674008764 .................
[CV] c1=0.23410168766018233, c2=0.007576332674008764, score=0.872077 - 1.9s
[CV] c1=0.05139054695837179, c2=0.0988983229417386 ...................
[CV] c1=0.05139054695837179, c2=0.0988983229417386, score=0.927296 - 1.6s
[CV] c1=0.42695722657704505, c2=0.061285485086823 ....................
[CV] c1=0.42695722657704505, c2=0.061285485086823, score=0.923585 - 1.9s
[CV] c1=0.6285063975967342, c2=0.00047708053019435885 ................
[CV] c1=0.6285063975967342, c2=0.00047708053019435885, score=0.923585 - 2.0s
[CV] c1=0.04223966754804299, c2=0.014836666503726496 .................
[CV] c1=0.04223966754804299, c2=0.014836666503726496, score=0.870571 - 1.7s
Training done in: 12.658946s
Saving training model...
Saving training model done in: 0.013450s
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Prediction done in: 0.050529s