Carlos-Francisco Méndez-Cruz / automatic-extraction-growth-conditions

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Run16_v12.txt 65.8 KB
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-------------------------------- PARAMETERS --------------------------------
Path of test and training data sets: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
Path of outputs: /home/egaytan/automatic-extraction-growth-conditions/CRF/
File with training data set: training-data-set-70-NER.txt
File with test data set: test-data-set-30-NER.txt
reportName: Run16
Exclude stop words: False
Levels: S1: TrueS2: TrueS3: TrueS4: True
Run variant: 12
Number of rules on report file: 500
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
   Sentences training data: 286
   Sentences test data: 123
Reading corpus done in: 0.003725s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
             0        1
0        lemma        :
1       postag        :
2     -1:lemma       in
3    -1:postag       IN
4     +1:lemma       m9
5    +1:postag       NN
6       hUpper    False
7       hLower    False
8       hGreek    False
9         symb    False
10    word[:1]        :
11  postag[:1]        :
12        word        :
13     isUpper    False
14     isLower    False
15     isGreek    False
16    isNumber    False
17     -1:word       in
18     +1:word       M9
19    -2:lemma  culture
20   -2:postag      VBN
21    +2:lemma  minimal
22   +2:postag       JJ
23      -1:ner        _
24      +1:ner      MED
25      -2:ner        _
26      +2:ner      MED
--------------------------- 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       False
10    word[:1]           d
11    word[:2]          de
12  postag[:1]           N
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
25      -1:ner           _
26      +1:ner           _
27      -2:ner           _
28      +2:ner        SUPP
Fitting 5 folds for each of 100 candidates, totalling 500 fits
[CV] c1=0.8573111416520891, c2=0.03332557158918708 ...................
[CV]  c1=0.8573111416520891, c2=0.03332557158918708, score=0.838456 -   1.7s
[CV] c1=0.12486633054768549, c2=0.020247643480145495 .................
[CV]  c1=0.12486633054768549, c2=0.020247643480145495, score=0.783647 -   1.5s
[CV] c1=0.34675400327606554, c2=0.0496007698240786 ...................
[CV]  c1=0.34675400327606554, c2=0.0496007698240786, score=0.878036 -   2.0s
[CV] c1=0.002603283872351975, c2=0.025222837206245876 ................
[CV]  c1=0.002603283872351975, c2=0.025222837206245876, score=0.800717 -   1.9s
[CV] c1=0.13003109865596438, c2=0.016991762037143546 .................
[CV]  c1=0.13003109865596438, c2=0.016991762037143546, score=0.885624 -   1.9s
[CV] c1=0.8797741184119439, c2=0.04277219171275081 ...................
[CV]  c1=0.8797741184119439, c2=0.04277219171275081, score=0.710258 -   1.6s
[CV] c1=0.3482734344654556, c2=0.10182268088558233 ...................
[CV]  c1=0.3482734344654556, c2=0.10182268088558233, score=0.756732 -   1.6s
[CV] c1=0.3209211292696093, c2=0.018635182914399587 ..................
[CV]  c1=0.3209211292696093, c2=0.018635182914399587, score=0.755786 -   1.5s
[CV] c1=1.1258449837691988, c2=0.05054416342137652 ...................
[CV]  c1=1.1258449837691988, c2=0.05054416342137652, score=0.660043 -   1.4s
[CV] c1=0.4318150456834849, c2=0.07807671816965212 ...................
[CV]  c1=0.4318150456834849, c2=0.07807671816965212, score=0.754746 -   1.6s
[CV] c1=0.3062891243526067, c2=0.05388728928364015 ...................
[CV]  c1=0.3062891243526067, c2=0.05388728928364015, score=0.767149 -   1.5s
[CV] c1=0.20975711375775957, c2=0.10060795680281127 ..................
[CV]  c1=0.20975711375775957, c2=0.10060795680281127, score=0.807861 -   1.9s
[CV] c1=1.165531304075132, c2=0.03484536079017848 ....................
[CV]  c1=1.165531304075132, c2=0.03484536079017848, score=0.862530 -   1.9s
[CV] c1=3.0720235164918974, c2=0.007742400041516841 ..................
[CV]  c1=3.0720235164918974, c2=0.007742400041516841, score=0.571897 -   1.8s
[CV] c1=1.3078815855488541, c2=0.010394324801136641 ..................
[CV]  c1=1.3078815855488541, c2=0.010394324801136641, score=0.802604 -   1.8s
[CV] c1=0.10897889931461163, c2=0.010750160202335471 .................
[CV]  c1=0.10897889931461163, c2=0.010750160202335471, score=0.851627 -   1.8s
[CV] c1=0.08526788571110812, c2=0.13382531105480874 ..................
[CV]  c1=0.08526788571110812, c2=0.13382531105480874, score=0.799708 -   1.9s
[CV] c1=0.04632998128229683, c2=0.06907412685996904 ..................
[CV]  c1=0.04632998128229683, c2=0.06907412685996904, score=0.880051 -   1.9s
[CV] c1=0.15235847616529405, c2=0.005140820742760215 .................
[CV]  c1=0.15235847616529405, c2=0.005140820742760215, score=0.791837 -   1.9s
[CV] c1=3.6536400451021973, c2=0.0615815143070015 ....................
[CV]  c1=3.6536400451021973, c2=0.0615815143070015, score=0.445226 -   1.8s
[CV] c1=0.34806218030922864, c2=0.03125308462899429 ..................
[CV]  c1=0.34806218030922864, c2=0.03125308462899429, score=0.869687 -   1.8s
[CV] c1=1.0298929909520367, c2=0.03327170617889213 ...................
[CV]  c1=1.0298929909520367, c2=0.03327170617889213, score=0.801996 -   1.7s
[CV] c1=0.20255253328883313, c2=0.04337614719657083 ..................
[CV]  c1=0.20255253328883313, c2=0.04337614719657083, score=0.751268 -   1.5s
[CV] c1=0.3772307005646545, c2=0.034457848007251664 ..................
[CV]  c1=0.3772307005646545, c2=0.034457848007251664, score=0.837619 -   1.9s
[CV] c1=0.6829291892899357, c2=0.00238956595775298 ...................
[CV]  c1=0.6829291892899357, c2=0.00238956595775298, score=0.735695 -   1.5s
[CV] c1=1.1290602496930402, c2=0.10292353664811803 ...................
[CV]  c1=1.1290602496930402, c2=0.10292353664811803, score=0.780991 -   1.7s
[CV] c1=0.8593787367606301, c2=0.03082738341727498 ...................
[CV]  c1=0.8593787367606301, c2=0.03082738341727498, score=0.704550 -   1.9s
[CV] c1=0.08544829519639574, c2=0.1548415335966792 ...................
[CV]  c1=0.08544829519639574, c2=0.1548415335966792, score=0.876044 -   2.0s
[CV] c1=0.021811050212240758, c2=0.06450844323213505 .................
[CV]  c1=0.021811050212240758, c2=0.06450844323213505, score=0.758177 -   1.5s
[CV] c1=0.13003109865596438, c2=0.016991762037143546 .................
[CV]  c1=0.13003109865596438, c2=0.016991762037143546, score=0.881503 -   1.9s
[CV] c1=0.8155542506543331, c2=0.16478687110735463 ...................
[CV]  c1=0.8155542506543331, c2=0.16478687110735463, score=0.677695 -   2.0s
[CV] c1=0.078525676715756, c2=0.11203131301356009 ....................
[CV]  c1=0.078525676715756, c2=0.11203131301356009, score=0.880176 -   1.9s
[CV] c1=0.43125884569175277, c2=0.03408914109225735 ..................
[CV]  c1=0.43125884569175277, c2=0.03408914109225735, score=0.753571 -   2.0s
[CV] c1=0.07255895387310529, c2=0.053696431131930934 .................
[CV]  c1=0.07255895387310529, c2=0.053696431131930934, score=0.887853 -   1.8s
[CV] c1=0.5724415337066926, c2=0.028938468449420985 ..................
[CV]  c1=0.5724415337066926, c2=0.028938468449420985, score=0.751509 -   1.5s
[CV] c1=1.7172114550567856, c2=0.06053114514989168 ...................
[CV]  c1=1.7172114550567856, c2=0.06053114514989168, score=0.619095 -   2.0s
[CV] c1=1.434698574838073, c2=0.08311074306861754 ....................
[CV]  c1=1.434698574838073, c2=0.08311074306861754, score=0.625504 -   2.0s
[CV] c1=0.028717184336666087, c2=0.07464475523861196 .................
[CV]  c1=0.028717184336666087, c2=0.07464475523861196, score=0.861188 -   1.8s
[CV] c1=0.4733314263697012, c2=0.12651017307500673 ...................
[CV]  c1=0.4733314263697012, c2=0.12651017307500673, score=0.729128 -   1.9s
[CV] c1=0.48889236588787044, c2=0.03331411438297624 ..................
[CV]  c1=0.48889236588787044, c2=0.03331411438297624, score=0.855162 -   1.9s
[CV] c1=0.08526788571110812, c2=0.13382531105480874 ..................
[CV]  c1=0.08526788571110812, c2=0.13382531105480874, score=0.861188 -   1.8s
[CV] c1=0.25794287148115197, c2=0.040580206830349755 .................
[CV]  c1=0.25794287148115197, c2=0.040580206830349755, score=0.790487 -   1.9s
[CV] c1=0.166457809567163, c2=0.13889362459375734 ....................
[CV]  c1=0.166457809567163, c2=0.13889362459375734, score=0.834802 -   1.9s
[CV] c1=3.6536400451021973, c2=0.0615815143070015 ....................
[CV]  c1=3.6536400451021973, c2=0.0615815143070015, score=0.551852 -   2.0s
[CV] c1=1.1258449837691988, c2=0.05054416342137652 ...................
[CV]  c1=1.1258449837691988, c2=0.05054416342137652, score=0.863959 -   1.8s
[CV] c1=0.3230775045789648, c2=0.10808522186584256 ...................
[CV]  c1=0.3230775045789648, c2=0.10808522186584256, score=0.764202 -   1.5s
[CV] c1=0.011605599912145288, c2=0.00632063180711085 .................
[CV]  c1=0.011605599912145288, c2=0.00632063180711085, score=0.852275 -   1.8s
[CV] c1=0.09153402991931628, c2=0.009197816826480097 .................
[CV]  c1=0.09153402991931628, c2=0.009197816826480097, score=0.869476 -   1.8s
[CV] c1=0.6829291892899357, c2=0.00238956595775298 ...................
[CV]  c1=0.6829291892899357, c2=0.00238956595775298, score=0.818250 -   1.7s
[CV] c1=0.25976124774631704, c2=0.016125813344577442 .................
[CV]  c1=0.25976124774631704, c2=0.016125813344577442, score=0.773963 -   1.4s
[CV] c1=0.8593787367606301, c2=0.03082738341727498 ...................
[CV]  c1=0.8593787367606301, c2=0.03082738341727498, score=0.874829 -   1.9s
[CV] c1=0.08544829519639574, c2=0.1548415335966792 ...................
[CV]  c1=0.08544829519639574, c2=0.1548415335966792, score=0.807056 -   2.0s
[CV] c1=0.021811050212240758, c2=0.06450844323213505 .................
[CV]  c1=0.021811050212240758, c2=0.06450844323213505, score=0.880176 -   1.9s
[CV] c1=0.06983810409088079, c2=0.039753081826740366 .................
[CV]  c1=0.06983810409088079, c2=0.039753081826740366, score=0.849670 -   1.8s
[CV] c1=0.8797741184119439, c2=0.04277219171275081 ...................
[CV]  c1=0.8797741184119439, c2=0.04277219171275081, score=0.693713 -   1.9s
[CV] c1=0.078525676715756, c2=0.11203131301356009 ....................
[CV]  c1=0.078525676715756, c2=0.11203131301356009, score=0.796024 -   1.9s
[CV] c1=0.6034643080105504, c2=0.09205986702839997 ...................
[CV]  c1=0.6034643080105504, c2=0.09205986702839997, score=0.881456 -   1.9s
[CV] c1=0.07255895387310529, c2=0.053696431131930934 .................
[CV]  c1=0.07255895387310529, c2=0.053696431131930934, score=0.797318 -   1.9s
[CV] c1=0.5724415337066926, c2=0.028938468449420985 ..................
[CV]  c1=0.5724415337066926, c2=0.028938468449420985, score=0.854778 -   2.0s
[CV] c1=0.3772307005646545, c2=0.034457848007251664 ..................
[CV]  c1=0.3772307005646545, c2=0.034457848007251664, score=0.749705 -   1.9s
[CV] c1=0.5126391482560252, c2=0.04065741496927025 ...................
[CV]  c1=0.5126391482560252, c2=0.04065741496927025, score=0.822710 -   1.9s
[CV] c1=0.25976124774631704, c2=0.016125813344577442 .................
[CV]  c1=0.25976124774631704, c2=0.016125813344577442, score=0.920574 -   1.7s
[CV] c1=0.12486633054768549, c2=0.020247643480145495 .................
[CV]  c1=0.12486633054768549, c2=0.020247643480145495, score=0.799708 -   1.9s
[CV] c1=0.1600048120256439, c2=0.06749727157242567 ...................
[CV]  c1=0.1600048120256439, c2=0.06749727157242567, score=0.811445 -   1.9s
[CV] c1=0.48773956152235637, c2=0.2087716155378857 ...................
[CV]  c1=0.48773956152235637, c2=0.2087716155378857, score=0.688022 -   1.5s
[CV] c1=0.06983810409088079, c2=0.039753081826740366 .................
[CV]  c1=0.06983810409088079, c2=0.039753081826740366, score=0.873497 -   1.9s
[CV] c1=0.7392917194575317, c2=0.004261307031590841 ..................
[CV]  c1=0.7392917194575317, c2=0.004261307031590841, score=0.749955 -   1.5s
[CV] c1=0.3482734344654556, c2=0.10182268088558233 ...................
[CV]  c1=0.3482734344654556, c2=0.10182268088558233, score=0.878036 -   2.0s
[CV] c1=0.43125884569175277, c2=0.03408914109225735 ..................
[CV]  c1=0.43125884569175277, c2=0.03408914109225735, score=0.899526 -   1.9s
[CV] c1=0.24729397915104762, c2=0.017615681666529773 .................
[CV]  c1=0.24729397915104762, c2=0.017615681666529773, score=0.782436 -   1.8s
[CV] c1=0.11680398654439843, c2=0.1066663364975167 ...................
[CV]  c1=0.11680398654439843, c2=0.1066663364975167, score=0.849132 -   1.8s
[CV] c1=0.20975711375775957, c2=0.10060795680281127 ..................
[CV]  c1=0.20975711375775957, c2=0.10060795680281127, score=0.854423 -   2.1s
[CV] c1=0.5126391482560252, c2=0.04065741496927025 ...................
[CV]  c1=0.5126391482560252, c2=0.04065741496927025, score=0.902602 -   1.9s
[CV] c1=0.028717184336666087, c2=0.07464475523861196 .................
[CV]  c1=0.028717184336666087, c2=0.07464475523861196, score=0.763961 -   1.5s
[CV] c1=0.12486633054768549, c2=0.020247643480145495 .................
[CV]  c1=0.12486633054768549, c2=0.020247643480145495, score=0.875412 -   1.9s
[CV] c1=0.48547564926572967, c2=0.12399066402119606 ..................
[CV]  c1=0.48547564926572967, c2=0.12399066402119606, score=0.904253 -   1.9s
[CV] c1=0.48773956152235637, c2=0.2087716155378857 ...................
[CV]  c1=0.48773956152235637, c2=0.2087716155378857, score=0.720853 -   2.1s
[CV] c1=0.2821831285504188, c2=0.09370582467361752 ...................
[CV]  c1=0.2821831285504188, c2=0.09370582467361752, score=0.854423 -   1.7s
[CV] c1=0.005639683858693419, c2=0.06244427245549233 .................
[CV]  c1=0.005639683858693419, c2=0.06244427245549233, score=0.818706 -   1.8s
[CV] c1=1.2515631393023146, c2=0.03183816278568514 ...................
[CV]  c1=1.2515631393023146, c2=0.03183816278568514, score=0.785213 -   1.8s
[CV] c1=1.344815889243292, c2=0.15259537559293232 ....................
[CV]  c1=1.344815889243292, c2=0.15259537559293232, score=0.781043 -   1.8s
[CV] c1=0.1781702520377878, c2=0.025004338405887436 ..................
[CV]  c1=0.1781702520377878, c2=0.025004338405887436, score=0.773867 -   1.5s
[CV] c1=0.5724415337066926, c2=0.028938468449420985 ..................
[CV]  c1=0.5724415337066926, c2=0.028938468449420985, score=0.728268 -   1.9s
[CV] c1=0.5559377210253521, c2=0.013392070411862562 ..................
[CV]  c1=0.5559377210253521, c2=0.013392070411862562, score=0.845829 -   1.9s
[CV] c1=1.165531304075132, c2=0.03484536079017848 ....................
[CV]  c1=1.165531304075132, c2=0.03484536079017848, score=0.691332 -   1.9s
[CV] c1=3.0720235164918974, c2=0.007742400041516841 ..................
[CV]  c1=3.0720235164918974, c2=0.007742400041516841, score=0.697111 -   1.8s
[CV] c1=1.3078815855488541, c2=0.010394324801136641 ..................
[CV]  c1=1.3078815855488541, c2=0.010394324801136641, score=0.619809 -   2.0s
[CV] c1=0.20503295269610408, c2=0.009131358726044252 .................
[CV]  c1=0.20503295269610408, c2=0.009131358726044252, score=0.782492 -   1.5s
[CV] c1=0.4031086355715093, c2=0.15245013793199164 ...................
[CV]  c1=0.4031086355715093, c2=0.15245013793199164, score=0.835542 -   1.8s
[CV] c1=0.2821831285504188, c2=0.09370582467361752 ...................
[CV]  c1=0.2821831285504188, c2=0.09370582467361752, score=0.846106 -   1.9s
[CV] c1=0.166457809567163, c2=0.13889362459375734 ....................
[CV]  c1=0.166457809567163, c2=0.13889362459375734, score=0.728567 -   1.5s
[CV] c1=0.564524940150662, c2=0.016009223436458803 ...................
[CV]  c1=0.564524940150662, c2=0.016009223436458803, score=0.882352 -   1.9s
[CV] c1=1.344815889243292, c2=0.15259537559293232 ....................
[CV]  c1=1.344815889243292, c2=0.15259537559293232, score=0.624019 -   2.2s
[CV] c1=1.0298929909520367, c2=0.03327170617889213 ...................
[CV]  c1=1.0298929909520367, c2=0.03327170617889213, score=0.873181 -   1.8s
[CV] c1=0.011605599912145288, c2=0.00632063180711085 .................
[CV]  c1=0.011605599912145288, c2=0.00632063180711085, score=0.852120 -   1.9s
[CV] c1=0.18519774522522023, c2=0.023126645342849184 .................
[CV]  c1=0.18519774522522023, c2=0.023126645342849184, score=0.750011 -   1.5s
[CV] c1=0.6829291892899357, c2=0.00238956595775298 ...................
[CV]  c1=0.6829291892899357, c2=0.00238956595775298, score=0.883199 -   2.0s
[CV] c1=0.028717184336666087, c2=0.07464475523861196 .................
[CV]  c1=0.028717184336666087, c2=0.07464475523861196, score=0.818706 -   1.9s
[CV] c1=1.3078815855488541, c2=0.010394324801136641 ..................
[CV]  c1=1.3078815855488541, c2=0.010394324801136641, score=0.860484 -   1.9s
[CV] c1=0.10897889931461163, c2=0.010750160202335471 .................
[CV]  c1=0.10897889931461163, c2=0.010750160202335471, score=0.805891 -   1.5s
[CV] c1=0.48773956152235637, c2=0.2087716155378857 ...................
[CV]  c1=0.48773956152235637, c2=0.2087716155378857, score=0.831347 -   1.8s
[CV] c1=0.42644807202877966, c2=0.01910944591269954 ..................
[CV]  c1=0.42644807202877966, c2=0.01910944591269954, score=0.851538 -   1.8s
[CV] c1=0.7392917194575317, c2=0.004261307031590841 ..................
[CV]  c1=0.7392917194575317, c2=0.004261307031590841, score=0.782873 -   2.0s
[CV] c1=1.8413017715662978, c2=0.020647440332441275 ..................
[CV]  c1=1.8413017715662978, c2=0.020647440332441275, score=0.838621 -   1.8s
[CV] c1=0.3290750359946001, c2=0.013407782998243004 ..................
[CV]  c1=0.3290750359946001, c2=0.013407782998243004, score=0.741401 -   1.5s
[CV] c1=0.07255895387310529, c2=0.053696431131930934 .................
[CV]  c1=0.07255895387310529, c2=0.053696431131930934, score=0.849132 -   1.8s
[CV] c1=0.5724415337066926, c2=0.028938468449420985 ..................
[CV]  c1=0.5724415337066926, c2=0.028938468449420985, score=0.803789 -   2.0s
[CV] c1=0.3772307005646545, c2=0.034457848007251664 ..................
[CV]  c1=0.3772307005646545, c2=0.034457848007251664, score=0.853407 -   1.8s
[CV] c1=0.5126391482560252, c2=0.04065741496927025 ...................
[CV]  c1=0.5126391482560252, c2=0.04065741496927025, score=0.846613 -   2.0s
[CV] c1=0.10076937624770857, c2=0.08050652589661307 ..................
[CV]  c1=0.10076937624770857, c2=0.08050652589661307, score=0.799708 -   1.9s
[CV] c1=0.8906768251922592, c2=0.020788077802387873 ..................
[CV]  c1=0.8906768251922592, c2=0.020788077802387873, score=0.870116 -   1.8s
[CV] c1=0.5655947129474109, c2=0.02233672766127511 ...................
[CV]  c1=0.5655947129474109, c2=0.02233672766127511, score=0.902238 -   1.8s
[CV] c1=0.2522819643096065, c2=0.06893900236916922 ...................
[CV]  c1=0.2522819643096065, c2=0.06893900236916922, score=0.765405 -   1.5s
[CV] c1=0.25794287148115197, c2=0.040580206830349755 .................
[CV]  c1=0.25794287148115197, c2=0.040580206830349755, score=0.807861 -   1.8s
[CV] c1=0.15235847616529405, c2=0.005140820742760215 .................
[CV]  c1=0.15235847616529405, c2=0.005140820742760215, score=0.887878 -   1.8s
[CV] c1=3.6536400451021973, c2=0.0615815143070015 ....................
[CV]  c1=3.6536400451021973, c2=0.0615815143070015, score=0.475426 -   1.5s
[CV] c1=1.344815889243292, c2=0.15259537559293232 ....................
[CV]  c1=1.344815889243292, c2=0.15259537559293232, score=0.645635 -   1.9s
[CV] c1=0.1781702520377878, c2=0.025004338405887436 ..................
[CV]  c1=0.1781702520377878, c2=0.025004338405887436, score=0.875592 -   1.9s
[CV] c1=0.011605599912145288, c2=0.00632063180711085 .................
[CV]  c1=0.011605599912145288, c2=0.00632063180711085, score=0.810951 -   1.4s
[CV] c1=0.5559377210253521, c2=0.013392070411862562 ..................
[CV]  c1=0.5559377210253521, c2=0.013392070411862562, score=0.821749 -   1.8s
[CV] c1=1.165531304075132, c2=0.03484536079017848 ....................
[CV]  c1=1.165531304075132, c2=0.03484536079017848, score=0.629789 -   1.9s
[CV] c1=0.25976124774631704, c2=0.016125813344577442 .................
[CV]  c1=0.25976124774631704, c2=0.016125813344577442, score=0.798645 -   1.7s
[CV] c1=0.12486633054768549, c2=0.020247643480145495 .................
[CV]  c1=0.12486633054768549, c2=0.020247643480145495, score=0.865375 -   1.8s
[CV] c1=0.1600048120256439, c2=0.06749727157242567 ...................
[CV]  c1=0.1600048120256439, c2=0.06749727157242567, score=0.739291 -   1.5s
[CV] c1=0.002603283872351975, c2=0.025222837206245876 ................
[CV]  c1=0.002603283872351975, c2=0.025222837206245876, score=0.869915 -   1.8s
[CV] c1=0.26310619558082143, c2=0.06477532799827239 ..................
[CV]  c1=0.26310619558082143, c2=0.06477532799827239, score=0.846569 -   1.9s
[CV] c1=0.8155542506543331, c2=0.16478687110735463 ...................
[CV]  c1=0.8155542506543331, c2=0.16478687110735463, score=0.865564 -   1.8s
[CV] c1=1.0945808137327815, c2=0.05352428934585795 ...................
[CV]  c1=1.0945808137327815, c2=0.05352428934585795, score=0.743421 -   2.2s
[CV] c1=0.43125884569175277, c2=0.03408914109225735 ..................
[CV]  c1=0.43125884569175277, c2=0.03408914109225735, score=0.860538 -   1.9s
[CV] c1=0.07255895387310529, c2=0.053696431131930934 .................
[CV]  c1=0.07255895387310529, c2=0.053696431131930934, score=0.740363 -   1.5s
[CV] c1=0.11680398654439843, c2=0.1066663364975167 ...................
[CV]  c1=0.11680398654439843, c2=0.1066663364975167, score=0.885741 -   1.9s
[CV] c1=0.20975711375775957, c2=0.10060795680281127 ..................
[CV]  c1=0.20975711375775957, c2=0.10060795680281127, score=0.787617 -   1.9s
[CV] c1=1.434698574838073, c2=0.08311074306861754 ....................
[CV]  c1=1.434698574838073, c2=0.08311074306861754, score=0.649414 -   2.2s
[CV] c1=3.0720235164918974, c2=0.007742400041516841 ..................
[CV]  c1=3.0720235164918974, c2=0.007742400041516841, score=0.521496 -   1.9s
[CV] c1=0.46783476853418304, c2=0.0944239406963 ......................
[CV]  c1=0.46783476853418304, c2=0.0944239406963, score=0.748677 -   1.5s
[CV] c1=0.10897889931461163, c2=0.010750160202335471 .................
[CV]  c1=0.10897889931461163, c2=0.010750160202335471, score=0.883403 -   1.8s
[CV] c1=0.08526788571110812, c2=0.13382531105480874 ..................
[CV]  c1=0.08526788571110812, c2=0.13382531105480874, score=0.885741 -   1.7s
[CV] c1=0.2821831285504188, c2=0.09370582467361752 ...................
[CV]  c1=0.2821831285504188, c2=0.09370582467361752, score=0.790738 -   1.8s
[CV] c1=0.005639683858693419, c2=0.06244427245549233 .................
[CV]  c1=0.005639683858693419, c2=0.06244427245549233, score=0.858948 -   1.7s
[CV] c1=1.2515631393023146, c2=0.03183816278568514 ...................
[CV]  c1=1.2515631393023146, c2=0.03183816278568514, score=0.865633 -   1.8s
[CV] c1=1.344815889243292, c2=0.15259537559293232 ....................
[CV]  c1=1.344815889243292, c2=0.15259537559293232, score=0.653825 -   1.5s
[CV] c1=0.24729397915104762, c2=0.017615681666529773 .................
[CV]  c1=0.24729397915104762, c2=0.017615681666529773, score=0.885836 -   1.9s
[CV] c1=0.5724415337066926, c2=0.028938468449420985 ..................
[CV]  c1=0.5724415337066926, c2=0.028938468449420985, score=0.900500 -   1.9s
[CV] c1=0.5559377210253521, c2=0.013392070411862562 ..................
[CV]  c1=0.5559377210253521, c2=0.013392070411862562, score=0.738467 -   2.0s
[CV] c1=0.5126391482560252, c2=0.04065741496927025 ...................
[CV]  c1=0.5126391482560252, c2=0.04065741496927025, score=0.739317 -   1.8s
[CV] c1=1.1290602496930402, c2=0.10292353664811803 ...................
[CV]  c1=1.1290602496930402, c2=0.10292353664811803, score=0.738866 -   1.6s
[CV] c1=0.6150671238127792, c2=0.06235479414063233 ...................
[CV]  c1=0.6150671238127792, c2=0.06235479414063233, score=0.854778 -   1.9s
[CV] c1=0.08544829519639574, c2=0.1548415335966792 ...................
[CV]  c1=0.08544829519639574, c2=0.1548415335966792, score=0.861188 -   1.8s
[CV] c1=0.002603283872351975, c2=0.025222837206245876 ................
[CV]  c1=0.002603283872351975, c2=0.025222837206245876, score=0.860729 -   1.8s
[CV] c1=0.13003109865596438, c2=0.016991762037143546 .................
[CV]  c1=0.13003109865596438, c2=0.016991762037143546, score=0.849670 -   1.7s
[CV] c1=0.8155542506543331, c2=0.16478687110735463 ...................
[CV]  c1=0.8155542506543331, c2=0.16478687110735463, score=0.686666 -   1.5s
[CV] c1=0.04952494262178127, c2=0.04418055648722324 ..................
[CV]  c1=0.04952494262178127, c2=0.04418055648722324, score=0.833873 -   1.9s
[CV] c1=0.3209211292696093, c2=0.018635182914399587 ..................
[CV]  c1=0.3209211292696093, c2=0.018635182914399587, score=0.915796 -   2.0s
[CV] c1=0.23903951437947946, c2=0.06268396817365848 ..................
[CV]  c1=0.23903951437947946, c2=0.06268396817365848, score=0.817622 -   2.0s
[CV] c1=0.049864128666242305, c2=0.00937788807955589 .................
[CV]  c1=0.049864128666242305, c2=0.00937788807955589, score=0.867912 -   1.8s
[CV] c1=1.7172114550567856, c2=0.06053114514989168 ...................
[CV]  c1=1.7172114550567856, c2=0.06053114514989168, score=0.736704 -   1.7s
[CV] c1=0.0021148540089996554, c2=0.015924680235763298 ...............
[CV]  c1=0.0021148540089996554, c2=0.015924680235763298, score=0.787501 -   1.5s
[CV] c1=0.5057303443734367, c2=0.02789198464236502 ...................
[CV]  c1=0.5057303443734367, c2=0.02789198464236502, score=0.753249 -   1.4s
[CV] c1=3.0720235164918974, c2=0.007742400041516841 ..................
[CV]  c1=3.0720235164918974, c2=0.007742400041516841, score=0.689010 -   1.8s
[CV] c1=1.3078815855488541, c2=0.010394324801136641 ..................
[CV]  c1=1.3078815855488541, c2=0.010394324801136641, score=0.683416 -   2.0s
[CV] c1=0.20503295269610408, c2=0.009131358726044252 .................
[CV]  c1=0.20503295269610408, c2=0.009131358726044252, score=0.917903 -   1.9s
[CV] c1=0.2522819643096065, c2=0.06893900236916922 ...................
[CV]  c1=0.2522819643096065, c2=0.06893900236916922, score=0.923073 -   1.8s
[CV] c1=1.0199632593178567, c2=0.0005001324194679756 .................
[CV]  c1=1.0199632593178567, c2=0.0005001324194679756, score=0.874736 -   1.9s
[CV] c1=0.04952494262178127, c2=0.04418055648722324 ..................
[CV]  c1=0.04952494262178127, c2=0.04418055648722324, score=0.772468 -   1.4s
[CV] c1=3.6536400451021973, c2=0.0615815143070015 ....................
[CV]  c1=3.6536400451021973, c2=0.0615815143070015, score=0.665184 -   1.9s
[CV] c1=0.34806218030922864, c2=0.03125308462899429 ..................
[CV]  c1=0.34806218030922864, c2=0.03125308462899429, score=0.761947 -   1.7s
[CV] c1=0.4318150456834849, c2=0.07807671816965212 ...................
[CV]  c1=0.4318150456834849, c2=0.07807671816965212, score=0.858256 -   1.7s
[CV] c1=0.011605599912145288, c2=0.00632063180711085 .................
[CV]  c1=0.011605599912145288, c2=0.00632063180711085, score=0.872424 -   1.8s
[CV] c1=0.09153402991931628, c2=0.009197816826480097 .................
[CV]  c1=0.09153402991931628, c2=0.009197816826480097, score=0.762907 -   1.5s
[CV] c1=1.165531304075132, c2=0.03484536079017848 ....................
[CV]  c1=1.165531304075132, c2=0.03484536079017848, score=0.816174 -   1.9s
[CV] c1=0.10076937624770857, c2=0.08050652589661307 ..................
[CV]  c1=0.10076937624770857, c2=0.08050652589661307, score=0.873228 -   1.8s
[CV] c1=0.46783476853418304, c2=0.0944239406963 ......................
[CV]  c1=0.46783476853418304, c2=0.0944239406963, score=0.849754 -   1.9s
[CV] c1=0.5655947129474109, c2=0.02233672766127511 ...................
[CV]  c1=0.5655947129474109, c2=0.02233672766127511, score=0.747610 -   1.6s
[CV] c1=0.4382242721071933, c2=0.11004349156273059 ...................
[CV]  c1=0.4382242721071933, c2=0.11004349156273059, score=0.899870 -   1.9s
[CV] c1=0.04632998128229683, c2=0.06907412685996904 ..................
[CV]  c1=0.04632998128229683, c2=0.06907412685996904, score=0.861188 -   1.8s
[CV] c1=0.15235847616529405, c2=0.005140820742760215 .................
[CV]  c1=0.15235847616529405, c2=0.005140820742760215, score=0.866346 -   1.8s
[CV] c1=3.6536400451021973, c2=0.0615815143070015 ....................
[CV]  c1=3.6536400451021973, c2=0.0615815143070015, score=0.585389 -   1.8s
[CV] c1=0.34806218030922864, c2=0.03125308462899429 ..................
[CV]  c1=0.34806218030922864, c2=0.03125308462899429, score=0.909871 -   1.9s
[CV] c1=1.0298929909520367, c2=0.03327170617889213 ...................
[CV]  c1=1.0298929909520367, c2=0.03327170617889213, score=0.673565 -   2.0s
[CV] c1=0.17296596435454967, c2=0.05822612464424481 ..................
[CV]  c1=0.17296596435454967, c2=0.05822612464424481, score=0.771035 -   1.5s
[CV] c1=0.09153402991931628, c2=0.009197816826480097 .................
[CV]  c1=0.09153402991931628, c2=0.009197816826480097, score=0.911334 -   1.9s
[CV] c1=0.5028927668221623, c2=0.07023907354239299 ...................
[CV]  c1=0.5028927668221623, c2=0.07023907354239299, score=0.745870 -   1.5s
[CV] c1=0.39175621731359517, c2=0.03472523699438633 ..................
[CV]  c1=0.39175621731359517, c2=0.03472523699438633, score=0.742776 -   1.4s
[CV] c1=0.12486633054768549, c2=0.020247643480145495 .................
[CV]  c1=0.12486633054768549, c2=0.020247643480145495, score=0.899088 -   1.9s
[CV] c1=0.1600048120256439, c2=0.06749727157242567 ...................
[CV]  c1=0.1600048120256439, c2=0.06749727157242567, score=0.797318 -   1.9s
[CV] c1=0.021811050212240758, c2=0.06450844323213505 .................
[CV]  c1=0.021811050212240758, c2=0.06450844323213505, score=0.834325 -   1.9s
[CV] c1=0.42644807202877966, c2=0.01910944591269954 ..................
[CV]  c1=0.42644807202877966, c2=0.01910944591269954, score=0.778922 -   1.8s
[CV] c1=0.7392917194575317, c2=0.004261307031590841 ..................
[CV]  c1=0.7392917194575317, c2=0.004261307031590841, score=0.812347 -   1.8s
[CV] c1=0.564524940150662, c2=0.016009223436458803 ...................
[CV]  c1=0.564524940150662, c2=0.016009223436458803, score=0.806286 -   1.9s
[CV] c1=1.344815889243292, c2=0.15259537559293232 ....................
[CV]  c1=1.344815889243292, c2=0.15259537559293232, score=0.852554 -   1.9s
[CV] c1=0.1781702520377878, c2=0.025004338405887436 ..................
[CV]  c1=0.1781702520377878, c2=0.025004338405887436, score=0.799164 -   1.9s
[CV] c1=0.3062891243526067, c2=0.05388728928364015 ...................
[CV]  c1=0.3062891243526067, c2=0.05388728928364015, score=0.878036 -   1.9s
[CV] c1=0.09153402991931628, c2=0.009197816826480097 .................
[CV]  c1=0.09153402991931628, c2=0.009197816826480097, score=0.813218 -   1.9s
[CV] c1=0.6829291892899357, c2=0.00238956595775298 ...................
[CV]  c1=0.6829291892899357, c2=0.00238956595775298, score=0.881338 -   1.7s
[CV] c1=0.7826460218094339, c2=0.029940039961255212 ..................
[CV]  c1=0.7826460218094339, c2=0.029940039961255212, score=0.782406 -   1.5s
[CV] c1=0.6150671238127792, c2=0.06235479414063233 ...................
[CV]  c1=0.6150671238127792, c2=0.06235479414063233, score=0.721758 -   1.9s
[CV] c1=0.34675400327606554, c2=0.0496007698240786 ...................
[CV]  c1=0.34675400327606554, c2=0.0496007698240786, score=0.864900 -   2.0s
[CV] c1=0.002603283872351975, c2=0.025222837206245876 ................
[CV]  c1=0.002603283872351975, c2=0.025222837206245876, score=0.779454 -   1.5s
[CV] c1=0.2522819643096065, c2=0.06893900236916922 ...................
[CV]  c1=0.2522819643096065, c2=0.06893900236916922, score=0.854961 -   1.9s
[CV] c1=1.0199632593178567, c2=0.0005001324194679756 .................
[CV]  c1=1.0199632593178567, c2=0.0005001324194679756, score=0.694659 -   1.9s
[CV] c1=1.0945808137327815, c2=0.05352428934585795 ...................
[CV]  c1=1.0945808137327815, c2=0.05352428934585795, score=0.868694 -   1.9s
[CV] c1=0.3209211292696093, c2=0.018635182914399587 ..................
[CV]  c1=0.3209211292696093, c2=0.018635182914399587, score=0.790487 -   1.8s
[CV] c1=0.23903951437947946, c2=0.06268396817365848 ..................
[CV]  c1=0.23903951437947946, c2=0.06268396817365848, score=0.759450 -   1.5s
[CV] c1=0.3230775045789648, c2=0.10808522186584256 ...................
[CV]  c1=0.3230775045789648, c2=0.10808522186584256, score=0.906879 -   1.8s
[CV] c1=0.17296596435454967, c2=0.05822612464424481 ..................
[CV]  c1=0.17296596435454967, c2=0.05822612464424481, score=0.905038 -   1.9s
[CV] c1=0.5500497172148461, c2=0.06301710200841153 ...................
[CV]  c1=0.5500497172148461, c2=0.06301710200841153, score=0.754746 -   1.5s
[CV] c1=0.5028927668221623, c2=0.07023907354239299 ...................
[CV]  c1=0.5028927668221623, c2=0.07023907354239299, score=0.890643 -   1.7s
[CV] c1=0.7826460218094339, c2=0.029940039961255212 ..................
[CV]  c1=0.7826460218094339, c2=0.029940039961255212, score=0.708356 -   1.4s
[CV] c1=1.1191828131476678, c2=0.07812650695149906 ...................
[CV]  c1=1.1191828131476678, c2=0.07812650695149906, score=0.743421 -   2.0s
[CV] c1=0.34675400327606554, c2=0.0496007698240786 ...................
[CV]  c1=0.34675400327606554, c2=0.0496007698240786, score=0.778196 -   1.8s
[CV] c1=0.3534228872262302, c2=0.06996777944064998 ...................
[CV]  c1=0.3534228872262302, c2=0.06996777944064998, score=0.851070 -   1.8s
[CV] c1=0.26310619558082143, c2=0.06477532799827239 ..................
[CV]  c1=0.26310619558082143, c2=0.06477532799827239, score=0.914145 -   2.3s
[CV] c1=0.8797741184119439, c2=0.04277219171275081 ...................
[CV]  c1=0.8797741184119439, c2=0.04277219171275081, score=0.882092 -   2.0s
[CV] c1=0.078525676715756, c2=0.11203131301356009 ....................
[CV]  c1=0.078525676715756, c2=0.11203131301356009, score=0.843976 -   2.0s
[CV] c1=0.6034643080105504, c2=0.09205986702839997 ...................
[CV]  c1=0.6034643080105504, c2=0.09205986702839997, score=0.725951 -   2.0s
[CV] c1=0.1781702520377878, c2=0.025004338405887436 ..................
[CV]  c1=0.1781702520377878, c2=0.025004338405887436, score=0.887452 -   1.9s
[CV] c1=0.3062891243526067, c2=0.05388728928364015 ...................
[CV]  c1=0.3062891243526067, c2=0.05388728928364015, score=0.778196 -   2.0s
[CV] c1=0.09153402991931628, c2=0.009197816826480097 .................
[CV]  c1=0.09153402991931628, c2=0.009197816826480097, score=0.895693 -   1.9s
[CV] c1=0.6829291892899357, c2=0.00238956595775298 ...................
[CV]  c1=0.6829291892899357, c2=0.00238956595775298, score=0.724074 -   1.9s
[CV] c1=0.25976124774631704, c2=0.016125813344577442 .................
[CV]  c1=0.25976124774631704, c2=0.016125813344577442, score=0.864900 -   1.9s
[CV] c1=0.046363507556721535, c2=0.0477549796812988 ..................
[CV]  c1=0.046363507556721535, c2=0.0477549796812988, score=0.799708 -   1.9s
[CV] c1=0.48889236588787044, c2=0.03331411438297624 ..................
[CV]  c1=0.48889236588787044, c2=0.03331411438297624, score=0.900037 -   1.9s
[CV] c1=0.4031086355715093, c2=0.15245013793199164 ...................
[CV]  c1=0.4031086355715093, c2=0.15245013793199164, score=0.754417 -   2.0s
[CV] c1=0.25794287148115197, c2=0.040580206830349755 .................
[CV]  c1=0.25794287148115197, c2=0.040580206830349755, score=0.925185 -   1.9s
[CV] c1=0.166457809567163, c2=0.13889362459375734 ....................
[CV]  c1=0.166457809567163, c2=0.13889362459375734, score=0.787617 -   1.9s
[CV] c1=1.8413017715662978, c2=0.020647440332441275 ..................
[CV]  c1=1.8413017715662978, c2=0.020647440332441275, score=0.623991 -   2.0s
[CV] c1=0.34806218030922864, c2=0.03125308462899429 ..................
[CV]  c1=0.34806218030922864, c2=0.03125308462899429, score=0.764452 -   1.9s
[CV] c1=1.0298929909520367, c2=0.03327170617889213 ...................
[CV]  c1=1.0298929909520367, c2=0.03327170617889213, score=0.743421 -   2.0s
[CV] c1=0.17296596435454967, c2=0.05822612464424481 ..................
[CV]  c1=0.17296596435454967, c2=0.05822612464424481, score=0.843976 -   1.9s
[CV] c1=0.04876424311423346, c2=0.020718225795039936 .................
[CV]  c1=0.04876424311423346, c2=0.020718225795039936, score=0.786128 -   1.5s
[CV] c1=0.5057303443734367, c2=0.02789198464236502 ...................
[CV]  c1=0.5057303443734367, c2=0.02789198464236502, score=0.897480 -   1.6s
[CV] c1=3.0720235164918974, c2=0.007742400041516841 ..................
[CV]  c1=3.0720235164918974, c2=0.007742400041516841, score=0.559067 -   1.5s
[CV] c1=0.046363507556721535, c2=0.0477549796812988 ..................
[CV]  c1=0.046363507556721535, c2=0.0477549796812988, score=0.749966 -   1.5s
[CV] c1=0.1600048120256439, c2=0.06749727157242567 ...................
[CV]  c1=0.1600048120256439, c2=0.06749727157242567, score=0.905038 -   2.0s
[CV] c1=0.021811050212240758, c2=0.06450844323213505 .................
[CV]  c1=0.021811050212240758, c2=0.06450844323213505, score=0.861188 -   1.7s
[CV] c1=0.06983810409088079, c2=0.039753081826740366 .................
[CV]  c1=0.06983810409088079, c2=0.039753081826740366, score=0.764861 -   1.4s
[CV] c1=0.32313735391716286, c2=0.007886806068654236 .................
[CV]  c1=0.32313735391716286, c2=0.007886806068654236, score=0.853884 -   1.8s
[CV] c1=1.0945808137327815, c2=0.05352428934585795 ...................
[CV]  c1=1.0945808137327815, c2=0.05352428934585795, score=0.684226 -   1.6s
[CV] c1=0.3523222194631296, c2=0.05593400277276437 ...................
[CV]  c1=0.3523222194631296, c2=0.05593400277276437, score=0.862597 -   1.7s
[CV] c1=1.1258449837691988, c2=0.05054416342137652 ...................
[CV]  c1=1.1258449837691988, c2=0.05054416342137652, score=0.774150 -   1.8s
[CV] c1=0.3230775045789648, c2=0.10808522186584256 ...................
[CV]  c1=0.3230775045789648, c2=0.10808522186584256, score=0.848291 -   1.7s
[CV] c1=0.17296596435454967, c2=0.05822612464424481 ..................
[CV]  c1=0.17296596435454967, c2=0.05822612464424481, score=0.791300 -   1.9s
[CV] c1=0.04876424311423346, c2=0.020718225795039936 .................
[CV]  c1=0.04876424311423346, c2=0.020718225795039936, score=0.881945 -   1.9s
[CV] c1=0.20719366225700267, c2=0.01588872416231615 ..................
[CV]  c1=0.20719366225700267, c2=0.01588872416231615, score=0.779857 -   1.3s
[CV] c1=0.25976124774631704, c2=0.016125813344577442 .................
[CV]  c1=0.25976124774631704, c2=0.016125813344577442, score=0.878636 -   1.9s
[CV] c1=0.046363507556721535, c2=0.0477549796812988 ..................
[CV]  c1=0.046363507556721535, c2=0.0477549796812988, score=0.846395 -   1.9s
[CV] c1=0.48889236588787044, c2=0.03331411438297624 ..................
[CV]  c1=0.48889236588787044, c2=0.03331411438297624, score=0.749517 -   1.9s
[CV] c1=0.4031086355715093, c2=0.15245013793199164 ...................
[CV]  c1=0.4031086355715093, c2=0.15245013793199164, score=0.811651 -   1.9s
[CV] c1=0.25794287148115197, c2=0.040580206830349755 .................
[CV]  c1=0.25794287148115197, c2=0.040580206830349755, score=0.744685 -   1.6s
[CV] c1=0.005639683858693419, c2=0.06244427245549233 .................
[CV]  c1=0.005639683858693419, c2=0.06244427245549233, score=0.834325 -   1.9s
[CV] c1=1.8413017715662978, c2=0.020647440332441275 ..................
[CV]  c1=1.8413017715662978, c2=0.020647440332441275, score=0.649831 -   1.5s
[CV] c1=0.6034643080105504, c2=0.09205986702839997 ...................
[CV]  c1=0.6034643080105504, c2=0.09205986702839997, score=0.854778 -   2.0s
[CV] c1=0.1781702520377878, c2=0.025004338405887436 ..................
[CV]  c1=0.1781702520377878, c2=0.025004338405887436, score=0.867678 -   2.2s
[CV] c1=0.20255253328883313, c2=0.04337614719657083 ..................
[CV]  c1=0.20255253328883313, c2=0.04337614719657083, score=0.796775 -   1.9s
[CV] c1=0.18519774522522023, c2=0.023126645342849184 .................
[CV]  c1=0.18519774522522023, c2=0.023126645342849184, score=0.865375 -   1.8s
[CV] c1=0.5028927668221623, c2=0.07023907354239299 ...................
[CV]  c1=0.5028927668221623, c2=0.07023907354239299, score=0.891300 -   1.8s
[CV] c1=0.8573111416520891, c2=0.03332557158918708 ...................
[CV]  c1=0.8573111416520891, c2=0.03332557158918708, score=0.690422 -   1.7s
[CV] c1=0.8593787367606301, c2=0.03082738341727498 ...................
[CV]  c1=0.8593787367606301, c2=0.03082738341727498, score=0.774594 -   2.0s
[CV] c1=0.1600048120256439, c2=0.06749727157242567 ...................
[CV]  c1=0.1600048120256439, c2=0.06749727157242567, score=0.852183 -   1.8s
[CV] c1=0.021811050212240758, c2=0.06450844323213505 .................
[CV]  c1=0.021811050212240758, c2=0.06450844323213505, score=0.809398 -   1.9s
[CV] c1=0.06983810409088079, c2=0.039753081826740366 .................
[CV]  c1=0.06983810409088079, c2=0.039753081826740366, score=0.878011 -   1.9s
[CV] c1=0.7392917194575317, c2=0.004261307031590841 ..................
[CV]  c1=0.7392917194575317, c2=0.004261307031590841, score=0.720268 -   2.0s
[CV] c1=1.2515631393023146, c2=0.03183816278568514 ...................
[CV]  c1=1.2515631393023146, c2=0.03183816278568514, score=0.627627 -   1.9s
[CV] c1=0.3290750359946001, c2=0.013407782998243004 ..................
[CV]  c1=0.3290750359946001, c2=0.013407782998243004, score=0.909998 -   1.9s
[CV] c1=0.4318150456834849, c2=0.07807671816965212 ...................
[CV]  c1=0.4318150456834849, c2=0.07807671816965212, score=0.901937 -   1.9s
[CV] c1=0.011605599912145288, c2=0.00632063180711085 .................
[CV]  c1=0.011605599912145288, c2=0.00632063180711085, score=0.792666 -   2.0s
[CV] c1=0.18519774522522023, c2=0.023126645342849184 .................
[CV]  c1=0.18519774522522023, c2=0.023126645342849184, score=0.910242 -   1.9s
[CV] c1=0.5028927668221623, c2=0.07023907354239299 ...................
[CV]  c1=0.5028927668221623, c2=0.07023907354239299, score=0.728268 -   1.9s
[CV] c1=0.10076937624770857, c2=0.08050652589661307 ..................
[CV]  c1=0.10076937624770857, c2=0.08050652589661307, score=0.887452 -   1.9s
[CV] c1=0.46783476853418304, c2=0.0944239406963 ......................
[CV]  c1=0.46783476853418304, c2=0.0944239406963, score=0.744064 -   1.9s
[CV] c1=0.20503295269610408, c2=0.009131358726044252 .................
[CV]  c1=0.20503295269610408, c2=0.009131358726044252, score=0.790487 -   1.8s
[CV] c1=0.4382242721071933, c2=0.11004349156273059 ...................
[CV]  c1=0.4382242721071933, c2=0.11004349156273059, score=0.762573 -   1.9s
[CV] c1=0.04632998128229683, c2=0.06907412685996904 ..................
[CV]  c1=0.04632998128229683, c2=0.06907412685996904, score=0.846395 -   1.9s
[CV] c1=0.04952494262178127, c2=0.04418055648722324 ..................
[CV]  c1=0.04952494262178127, c2=0.04418055648722324, score=0.887817 -   1.8s
[CV] c1=0.3523222194631296, c2=0.05593400277276437 ...................
[CV]  c1=0.3523222194631296, c2=0.05593400277276437, score=0.908403 -   1.8s
[CV] c1=1.1258449837691988, c2=0.05054416342137652 ...................
[CV]  c1=1.1258449837691988, c2=0.05054416342137652, score=0.643244 -   2.1s
[CV] c1=0.237586485398871, c2=0.0044998736653750265 ..................
[CV]  c1=0.237586485398871, c2=0.0044998736653750265, score=0.754896 -   1.5s
[CV] c1=0.20255253328883313, c2=0.04337614719657083 ..................
[CV]  c1=0.20255253328883313, c2=0.04337614719657083, score=0.842924 -   1.9s
[CV] c1=0.5500497172148461, c2=0.06301710200841153 ...................
[CV]  c1=0.5500497172148461, c2=0.06301710200841153, score=0.724074 -   1.9s
[CV] c1=0.5057303443734367, c2=0.02789198464236502 ...................
[CV]  c1=0.5057303443734367, c2=0.02789198464236502, score=0.854778 -   1.5s
[CV] c1=0.10076937624770857, c2=0.08050652589661307 ..................
[CV]  c1=0.10076937624770857, c2=0.08050652589661307, score=0.849132 -   1.8s
[CV] c1=0.46783476853418304, c2=0.0944239406963 ......................
[CV]  c1=0.46783476853418304, c2=0.0944239406963, score=0.891624 -   1.8s
[CV] c1=0.20503295269610408, c2=0.009131358726044252 .................
[CV]  c1=0.20503295269610408, c2=0.009131358726044252, score=0.910242 -   1.9s
[CV] c1=0.4382242721071933, c2=0.11004349156273059 ...................
[CV]  c1=0.4382242721071933, c2=0.11004349156273059, score=0.760526 -   1.6s
[CV] c1=0.25794287148115197, c2=0.040580206830349755 .................
[CV]  c1=0.25794287148115197, c2=0.040580206830349755, score=0.864900 -   1.9s
[CV] c1=0.15235847616529405, c2=0.005140820742760215 .................
[CV]  c1=0.15235847616529405, c2=0.005140820742760215, score=0.791157 -   1.5s
[CV] c1=1.2515631393023146, c2=0.03183816278568514 ...................
[CV]  c1=1.2515631393023146, c2=0.03183816278568514, score=0.688624 -   1.9s
[CV] c1=0.3290750359946001, c2=0.013407782998243004 ..................
[CV]  c1=0.3290750359946001, c2=0.013407782998243004, score=0.782436 -   1.8s
[CV] c1=0.4318150456834849, c2=0.07807671816965212 ...................
[CV]  c1=0.4318150456834849, c2=0.07807671816965212, score=0.747046 -   2.0s
[CV] c1=0.20255253328883313, c2=0.04337614719657083 ..................
[CV]  c1=0.20255253328883313, c2=0.04337614719657083, score=0.912034 -   1.9s
[CV] c1=0.18519774522522023, c2=0.023126645342849184 .................
[CV]  c1=0.18519774522522023, c2=0.023126645342849184, score=0.796573 -   1.8s
[CV] c1=0.5028927668221623, c2=0.07023907354239299 ...................
[CV]  c1=0.5028927668221623, c2=0.07023907354239299, score=0.825956 -   1.9s
[CV] c1=0.028717184336666087, c2=0.07464475523861196 .................
[CV]  c1=0.028717184336666087, c2=0.07464475523861196, score=0.873004 -   1.8s
[CV] c1=0.4733314263697012, c2=0.12651017307500673 ...................
[CV]  c1=0.4733314263697012, c2=0.12651017307500673, score=0.899526 -   1.8s
[CV] c1=0.48889236588787044, c2=0.03331411438297624 ..................
[CV]  c1=0.48889236588787044, c2=0.03331411438297624, score=0.745870 -   1.5s
[CV] c1=0.48773956152235637, c2=0.2087716155378857 ...................
[CV]  c1=0.48773956152235637, c2=0.2087716155378857, score=0.882366 -   1.8s
[CV] c1=0.42644807202877966, c2=0.01910944591269954 ..................
[CV]  c1=0.42644807202877966, c2=0.01910944591269954, score=0.751943 -   1.6s
[CV] c1=0.8155542506543331, c2=0.16478687110735463 ...................
[CV]  c1=0.8155542506543331, c2=0.16478687110735463, score=0.748276 -   2.0s
[CV] c1=0.564524940150662, c2=0.016009223436458803 ...................
[CV]  c1=0.564524940150662, c2=0.016009223436458803, score=0.898602 -   1.9s
[CV] c1=0.6034643080105504, c2=0.09205986702839997 ...................
[CV]  c1=0.6034643080105504, c2=0.09205986702839997, score=0.758214 -   1.5s
[CV] c1=0.026545657089672978, c2=0.08988520513180341 .................
[CV]  c1=0.026545657089672978, c2=0.08988520513180341, score=0.866392 -   1.9s
[CV] c1=0.11680398654439843, c2=0.1066663364975167 ...................
[CV]  c1=0.11680398654439843, c2=0.1066663364975167, score=0.722783 -   1.5s
[CV] c1=1.7172114550567856, c2=0.06053114514989168 ...................
[CV]  c1=1.7172114550567856, c2=0.06053114514989168, score=0.609251 -   1.5s
[CV] c1=0.5500497172148461, c2=0.06301710200841153 ...................
[CV]  c1=0.5500497172148461, c2=0.06301710200841153, score=0.845862 -   1.8s
[CV] c1=0.5057303443734367, c2=0.02789198464236502 ...................
[CV]  c1=0.5057303443734367, c2=0.02789198464236502, score=0.844103 -   1.6s
[CV] c1=0.028717184336666087, c2=0.07464475523861196 .................
[CV]  c1=0.028717184336666087, c2=0.07464475523861196, score=0.834325 -   1.9s
[CV] c1=1.3078815855488541, c2=0.010394324801136641 ..................
[CV]  c1=1.3078815855488541, c2=0.010394324801136641, score=0.673764 -   1.5s
[CV] c1=0.48547564926572967, c2=0.12399066402119606 ..................
[CV]  c1=0.48547564926572967, c2=0.12399066402119606, score=0.849754 -   1.9s
[CV] c1=0.4031086355715093, c2=0.15245013793199164 ...................
[CV]  c1=0.4031086355715093, c2=0.15245013793199164, score=0.745110 -   1.5s
[CV] c1=0.42644807202877966, c2=0.01910944591269954 ..................
[CV]  c1=0.42644807202877966, c2=0.01910944591269954, score=0.895591 -   1.8s
[CV] c1=0.8797741184119439, c2=0.04277219171275081 ...................
[CV]  c1=0.8797741184119439, c2=0.04277219171275081, score=0.809507 -   1.8s
[CV] c1=0.078525676715756, c2=0.11203131301356009 ....................
[CV]  c1=0.078525676715756, c2=0.11203131301356009, score=0.747614 -   1.5s
[CV] c1=0.3209211292696093, c2=0.018635182914399587 ..................
[CV]  c1=0.3209211292696093, c2=0.018635182914399587, score=0.860688 -   2.0s
[CV] c1=0.026545657089672978, c2=0.08988520513180341 .................
[CV]  c1=0.026545657089672978, c2=0.08988520513180341, score=0.861188 -   1.8s
[CV] c1=0.049864128666242305, c2=0.00937788807955589 .................
[CV]  c1=0.049864128666242305, c2=0.00937788807955589, score=0.814156 -   1.4s
[CV] c1=0.17296596435454967, c2=0.05822612464424481 ..................
[CV]  c1=0.17296596435454967, c2=0.05822612464424481, score=0.867140 -   1.8s
[CV] c1=0.5500497172148461, c2=0.06301710200841153 ...................
[CV]  c1=0.5500497172148461, c2=0.06301710200841153, score=0.845829 -   1.9s
[CV] c1=0.20719366225700267, c2=0.01588872416231615 ..................
[CV]  c1=0.20719366225700267, c2=0.01588872416231615, score=0.865692 -   1.4s
[CV] c1=1.1290602496930402, c2=0.10292353664811803 ...................
[CV]  c1=1.1290602496930402, c2=0.10292353664811803, score=0.863523 -   1.5s
[CV] c1=0.6150671238127792, c2=0.06235479414063233 ...................
[CV]  c1=0.6150671238127792, c2=0.06235479414063233, score=0.720056 -   1.5s
[CV] c1=0.8906768251922592, c2=0.020788077802387873 ..................
[CV]  c1=0.8906768251922592, c2=0.020788077802387873, score=0.693453 -   1.5s
[CV] c1=0.10897889931461163, c2=0.010750160202335471 .................
[CV]  c1=0.10897889931461163, c2=0.010750160202335471, score=0.881018 -   2.0s
[CV] c1=0.4382242721071933, c2=0.11004349156273059 ...................
[CV]  c1=0.4382242721071933, c2=0.11004349156273059, score=0.853496 -   1.8s
[CV] c1=0.04632998128229683, c2=0.06907412685996904 ..................
[CV]  c1=0.04632998128229683, c2=0.06907412685996904, score=0.813172 -   1.9s
[CV] c1=0.15235847616529405, c2=0.005140820742760215 .................
[CV]  c1=0.15235847616529405, c2=0.005140820742760215, score=0.911785 -   2.0s
[CV] c1=0.3523222194631296, c2=0.05593400277276437 ...................
[CV]  c1=0.3523222194631296, c2=0.05593400277276437, score=0.775754 -   1.8s
[CV] c1=0.23903951437947946, c2=0.06268396817365848 ..................
[CV]  c1=0.23903951437947946, c2=0.06268396817365848, score=0.915796 -   2.0s
[CV] c1=0.237586485398871, c2=0.0044998736653750265 ..................
[CV]  c1=0.237586485398871, c2=0.0044998736653750265, score=0.864654 -   1.8s
[CV] c1=0.4191362584742336, c2=0.016125001294342533 ..................
[CV]  c1=0.4191362584742336, c2=0.016125001294342533, score=0.745890 -   1.5s
[CV] c1=0.5500497172148461, c2=0.06301710200841153 ...................
[CV]  c1=0.5500497172148461, c2=0.06301710200841153, score=0.889937 -   1.9s
[CV] c1=0.5057303443734367, c2=0.02789198464236502 ...................
[CV]  c1=0.5057303443734367, c2=0.02789198464236502, score=0.734274 -   1.8s
[CV] c1=0.39175621731359517, c2=0.03472523699438633 ..................
[CV]  c1=0.39175621731359517, c2=0.03472523699438633, score=0.906168 -   1.9s
[CV] c1=0.046363507556721535, c2=0.0477549796812988 ..................
[CV]  c1=0.046363507556721535, c2=0.0477549796812988, score=0.858948 -   1.7s
[CV] c1=0.48547564926572967, c2=0.12399066402119606 ..................
[CV]  c1=0.48547564926572967, c2=0.12399066402119606, score=0.830237 -   1.9s
[CV] c1=0.4031086355715093, c2=0.15245013793199164 ...................
[CV]  c1=0.4031086355715093, c2=0.15245013793199164, score=0.901937 -   1.8s
[CV] c1=0.2821831285504188, c2=0.09370582467361752 ...................
[CV]  c1=0.2821831285504188, c2=0.09370582467361752, score=0.749589 -   1.5s
[CV] c1=0.7392917194575317, c2=0.004261307031590841 ..................
[CV]  c1=0.7392917194575317, c2=0.004261307031590841, score=0.887554 -   1.9s
[CV] c1=0.564524940150662, c2=0.016009223436458803 ...................
[CV]  c1=0.564524940150662, c2=0.016009223436458803, score=0.747102 -   1.5s
[CV] c1=0.9715175264411177, c2=0.09900569873937647 ...................
[CV]  c1=0.9715175264411177, c2=0.09900569873937647, score=0.780105 -   1.8s
[CV] c1=0.026545657089672978, c2=0.08988520513180341 .................
[CV]  c1=0.026545657089672978, c2=0.08988520513180341, score=0.810739 -   1.9s
[CV] c1=0.049864128666242305, c2=0.00937788807955589 .................
[CV]  c1=0.049864128666242305, c2=0.00937788807955589, score=0.851207 -   1.9s
[CV] c1=0.20975711375775957, c2=0.10060795680281127 ..................
[CV]  c1=0.20975711375775957, c2=0.10060795680281127, score=0.912034 -   1.9s
[CV] c1=1.434698574838073, c2=0.08311074306861754 ....................
[CV]  c1=1.434698574838073, c2=0.08311074306861754, score=0.660369 -   1.4s
[CV] c1=0.20719366225700267, c2=0.01588872416231615 ..................
[CV]  c1=0.20719366225700267, c2=0.01588872416231615, score=0.784921 -   1.6s
[CV] c1=0.7826460218094339, c2=0.029940039961255212 ..................
[CV]  c1=0.7826460218094339, c2=0.029940039961255212, score=0.820096 -   1.4s
[CV] c1=1.1191828131476678, c2=0.07812650695149906 ...................
[CV]  c1=1.1191828131476678, c2=0.07812650695149906, score=0.807777 -   1.9s
[CV] c1=0.8906768251922592, c2=0.020788077802387873 ..................
[CV]  c1=0.8906768251922592, c2=0.020788077802387873, score=0.704550 -   2.0s
[CV] c1=0.3534228872262302, c2=0.06996777944064998 ...................
[CV]  c1=0.3534228872262302, c2=0.06996777944064998, score=0.899526 -   2.0s
[CV] c1=0.26310619558082143, c2=0.06477532799827239 ..................
[CV]  c1=0.26310619558082143, c2=0.06477532799827239, score=0.754014 -   1.5s
[CV] c1=1.0199632593178567, c2=0.0005001324194679756 .................
[CV]  c1=1.0199632593178567, c2=0.0005001324194679756, score=0.662386 -   1.5s
[CV] c1=0.166457809567163, c2=0.13889362459375734 ....................
[CV]  c1=0.166457809567163, c2=0.13889362459375734, score=0.854423 -   1.8s
[CV] c1=1.8413017715662978, c2=0.020647440332441275 ..................
[CV]  c1=1.8413017715662978, c2=0.020647440332441275, score=0.718886 -   1.9s
[CV] c1=0.3290750359946001, c2=0.013407782998243004 ..................
[CV]  c1=0.3290750359946001, c2=0.013407782998243004, score=0.854183 -   1.9s
[CV] c1=0.4318150456834849, c2=0.07807671816965212 ...................
[CV]  c1=0.4318150456834849, c2=0.07807671816965212, score=0.860154 -   1.9s
[CV] c1=0.20255253328883313, c2=0.04337614719657083 ..................
[CV]  c1=0.20255253328883313, c2=0.04337614719657083, score=0.846998 -   1.8s
[CV] c1=0.18519774522522023, c2=0.023126645342849184 .................
[CV]  c1=0.18519774522522023, c2=0.023126645342849184, score=0.843195 -   2.0s
[CV] c1=0.20719366225700267, c2=0.01588872416231615 ..................
[CV]  c1=0.20719366225700267, c2=0.01588872416231615, score=0.910242 -   1.6s
[CV] c1=0.8573111416520891, c2=0.03332557158918708 ...................
[CV]  c1=0.8573111416520891, c2=0.03332557158918708, score=0.809494 -   1.6s
[CV] c1=0.8593787367606301, c2=0.03082738341727498 ...................
[CV]  c1=0.8593787367606301, c2=0.03082738341727498, score=0.813595 -   1.8s
[CV] c1=0.08544829519639574, c2=0.1548415335966792 ...................
[CV]  c1=0.08544829519639574, c2=0.1548415335966792, score=0.765249 -   1.5s
[CV] c1=0.5655947129474109, c2=0.02233672766127511 ...................
[CV]  c1=0.5655947129474109, c2=0.02233672766127511, score=0.834417 -   2.1s
[CV] c1=0.13003109865596438, c2=0.016991762037143546 .................
[CV]  c1=0.13003109865596438, c2=0.016991762037143546, score=0.773943 -   1.5s
[CV] c1=1.0199632593178567, c2=0.0005001324194679756 .................
[CV]  c1=1.0199632593178567, c2=0.0005001324194679756, score=0.804897 -   1.7s
[CV] c1=0.04952494262178127, c2=0.04418055648722324 ..................
[CV]  c1=0.04952494262178127, c2=0.04418055648722324, score=0.858948 -   1.7s
[CV] c1=0.3523222194631296, c2=0.05593400277276437 ...................
[CV]  c1=0.3523222194631296, c2=0.05593400277276437, score=0.749741 -   1.6s
[CV] c1=0.34806218030922864, c2=0.03125308462899429 ..................
[CV]  c1=0.34806218030922864, c2=0.03125308462899429, score=0.864900 -   1.9s
[CV] c1=0.3230775045789648, c2=0.10808522186584256 ...................
[CV]  c1=0.3230775045789648, c2=0.10808522186584256, score=0.776754 -   1.9s
[CV] c1=0.4191362584742336, c2=0.016125001294342533 ..................
[CV]  c1=0.4191362584742336, c2=0.016125001294342533, score=0.908279 -   2.0s
[CV] c1=0.04876424311423346, c2=0.020718225795039936 .................
[CV]  c1=0.04876424311423346, c2=0.020718225795039936, score=0.854961 -   1.9s
[CV] c1=0.5947449801198732, c2=0.01932052560615957 ...................
[CV]  c1=0.5947449801198732, c2=0.01932052560615957, score=0.891920 -   1.5s
[CV] c1=1.1290602496930402, c2=0.10292353664811803 ...................
[CV]  c1=1.1290602496930402, c2=0.10292353664811803, score=0.631762 -   1.6s
[CV] c1=0.6150671238127792, c2=0.06235479414063233 ...................
[CV]  c1=0.6150671238127792, c2=0.06235479414063233, score=0.825486 -   1.8s
[CV] c1=0.08544829519639574, c2=0.1548415335966792 ...................
[CV]  c1=0.08544829519639574, c2=0.1548415335966792, score=0.880176 -   1.7s
[CV] c1=0.3534228872262302, c2=0.06996777944064998 ...................
[CV]  c1=0.3534228872262302, c2=0.06996777944064998, score=0.870287 -   2.0s
[CV] c1=0.13003109865596438, c2=0.016991762037143546 .................
[CV]  c1=0.13003109865596438, c2=0.016991762037143546, score=0.799708 -   1.9s
[CV] c1=0.8155542506543331, c2=0.16478687110735463 ...................
[CV]  c1=0.8155542506543331, c2=0.16478687110735463, score=0.783683 -   1.8s
[CV] c1=0.3482734344654556, c2=0.10182268088558233 ...................
[CV]  c1=0.3482734344654556, c2=0.10182268088558233, score=0.846069 -   2.0s
[CV] c1=0.43125884569175277, c2=0.03408914109225735 ..................
[CV]  c1=0.43125884569175277, c2=0.03408914109225735, score=0.762359 -   1.6s
[CV] c1=0.026545657089672978, c2=0.08988520513180341 .................
[CV]  c1=0.026545657089672978, c2=0.08988520513180341, score=0.773444 -   1.5s
[CV] c1=0.237586485398871, c2=0.0044998736653750265 ..................
[CV]  c1=0.237586485398871, c2=0.0044998736653750265, score=0.896361 -   2.0s
[CV] c1=0.4191362584742336, c2=0.016125001294342533 ..................
[CV]  c1=0.4191362584742336, c2=0.016125001294342533, score=0.862707 -   1.7s
[CV] c1=0.04876424311423346, c2=0.020718225795039936 .................
[CV]  c1=0.04876424311423346, c2=0.020718225795039936, score=0.810739 -   1.9s
[CV] c1=0.20719366225700267, c2=0.01588872416231615 ..................
[CV]  c1=0.20719366225700267, c2=0.01588872416231615, score=0.840517 -   1.6s
[CV] c1=0.8573111416520891, c2=0.03332557158918708 ...................
[CV]  c1=0.8573111416520891, c2=0.03332557158918708, score=0.695729 -   1.3s
[CV] c1=0.6150671238127792, c2=0.06235479414063233 ...................
[CV]  c1=0.6150671238127792, c2=0.06235479414063233, score=0.882212 -   1.8s
[CV] c1=0.8906768251922592, c2=0.020788077802387873 ..................
[CV]  c1=0.8906768251922592, c2=0.020788077802387873, score=0.836433 -   1.9s
[CV] c1=0.3534228872262302, c2=0.06996777944064998 ...................
[CV]  c1=0.3534228872262302, c2=0.06996777944064998, score=0.770431 -   1.9s
[CV] c1=0.26310619558082143, c2=0.06477532799827239 ..................
[CV]  c1=0.26310619558082143, c2=0.06477532799827239, score=0.789991 -   1.9s
[CV] c1=0.32313735391716286, c2=0.007886806068654236 .................
[CV]  c1=0.32313735391716286, c2=0.007886806068654236, score=0.871419 -   1.9s
[CV] c1=0.3482734344654556, c2=0.10182268088558233 ...................
[CV]  c1=0.3482734344654556, c2=0.10182268088558233, score=0.762573 -   1.9s
[CV] c1=0.9715175264411177, c2=0.09900569873937647 ...................
[CV]  c1=0.9715175264411177, c2=0.09900569873937647, score=0.647341 -   1.9s
[CV] c1=0.24729397915104762, c2=0.017615681666529773 .................
[CV]  c1=0.24729397915104762, c2=0.017615681666529773, score=0.912741 -   2.0s
[CV] c1=0.11680398654439843, c2=0.1066663364975167 ...................
[CV]  c1=0.11680398654439843, c2=0.1066663364975167, score=0.793635 -   1.9s
[CV] c1=0.5559377210253521, c2=0.013392070411862562 ..................
[CV]  c1=0.5559377210253521, c2=0.013392070411862562, score=0.904048 -   1.9s
[CV] c1=1.165531304075132, c2=0.03484536079017848 ....................
[CV]  c1=1.165531304075132, c2=0.03484536079017848, score=0.691696 -   1.6s
[CV] c1=0.45885612696589256, c2=0.13838286852102 .....................
[CV]  c1=0.45885612696589256, c2=0.13838286852102, score=0.740178 -   1.3s
[CV] c1=0.10076937624770857, c2=0.08050652589661307 ..................
[CV]  c1=0.10076937624770857, c2=0.08050652589661307, score=0.755452 -   1.6s
[CV] c1=0.4733314263697012, c2=0.12651017307500673 ...................
[CV]  c1=0.4733314263697012, c2=0.12651017307500673, score=0.849754 -   1.9s
[CV] c1=0.10897889931461163, c2=0.010750160202335471 .................
[CV]  c1=0.10897889931461163, c2=0.010750160202335471, score=0.799164 -   1.9s
[CV] c1=0.08526788571110812, c2=0.13382531105480874 ..................
[CV]  c1=0.08526788571110812, c2=0.13382531105480874, score=0.843976 -   1.9s
[CV] c1=0.04632998128229683, c2=0.06907412685996904 ..................
[CV]  c1=0.04632998128229683, c2=0.06907412685996904, score=0.762873 -   1.5s
[CV] c1=0.166457809567163, c2=0.13889362459375734 ....................
[CV]  c1=0.166457809567163, c2=0.13889362459375734, score=0.899168 -   1.9s
[CV] c1=1.8413017715662978, c2=0.020647440332441275 ..................
[CV]  c1=1.8413017715662978, c2=0.020647440332441275, score=0.616944 -   1.9s
[CV] c1=0.3290750359946001, c2=0.013407782998243004 ..................
[CV]  c1=0.3290750359946001, c2=0.013407782998243004, score=0.869236 -   1.9s
[CV] c1=1.0298929909520367, c2=0.03327170617889213 ...................
[CV]  c1=1.0298929909520367, c2=0.03327170617889213, score=0.720187 -   1.4s
[CV] c1=0.3062891243526067, c2=0.05388728928364015 ...................
[CV]  c1=0.3062891243526067, c2=0.05388728928364015, score=0.862597 -   1.8s
[CV] c1=0.3772307005646545, c2=0.034457848007251664 ..................
[CV]  c1=0.3772307005646545, c2=0.034457848007251664, score=0.762794 -   1.5s
[CV] c1=1.434698574838073, c2=0.08311074306861754 ....................
[CV]  c1=1.434698574838073, c2=0.08311074306861754, score=0.765848 -   1.8s
[CV] c1=0.45885612696589256, c2=0.13838286852102 .....................
[CV]  c1=0.45885612696589256, c2=0.13838286852102, score=0.819917 -   1.2s
[CV] c1=0.39175621731359517, c2=0.03472523699438633 ..................
[CV]  c1=0.39175621731359517, c2=0.03472523699438633, score=0.849821 -   1.7s
[CV] c1=0.046363507556721535, c2=0.0477549796812988 ..................
[CV]  c1=0.046363507556721535, c2=0.0477549796812988, score=0.887371 -   1.8s
[CV] c1=0.48547564926572967, c2=0.12399066402119606 ..................
[CV]  c1=0.48547564926572967, c2=0.12399066402119606, score=0.726644 -   1.9s
[CV] c1=0.48773956152235637, c2=0.2087716155378857 ...................
[CV]  c1=0.48773956152235637, c2=0.2087716155378857, score=0.817686 -   1.9s
[CV] c1=0.2821831285504188, c2=0.09370582467361752 ...................
[CV]  c1=0.2821831285504188, c2=0.09370582467361752, score=0.892680 -   1.9s
[CV] c1=0.005639683858693419, c2=0.06244427245549233 .................
[CV]  c1=0.005639683858693419, c2=0.06244427245549233, score=0.776954 -   1.5s
[CV] c1=0.078525676715756, c2=0.11203131301356009 ....................
[CV]  c1=0.078525676715756, c2=0.11203131301356009, score=0.855897 -   1.7s
[CV] c1=0.9715175264411177, c2=0.09900569873937647 ...................
[CV]  c1=0.9715175264411177, c2=0.09900569873937647, score=0.777550 -   1.8s
[CV] c1=0.24729397915104762, c2=0.017615681666529773 .................
[CV]  c1=0.24729397915104762, c2=0.017615681666529773, score=0.766653 -   1.5s
[CV] c1=0.237586485398871, c2=0.0044998736653750265 ..................
[CV]  c1=0.237586485398871, c2=0.0044998736653750265, score=0.908780 -   1.9s
[CV] c1=1.7172114550567856, c2=0.06053114514989168 ...................
[CV]  c1=1.7172114550567856, c2=0.06053114514989168, score=0.837512 -   1.9s
[CV] c1=0.0021148540089996554, c2=0.015924680235763298 ...............
[CV]  c1=0.0021148540089996554, c2=0.015924680235763298, score=0.800717 -   1.9s
[CV] c1=0.5947449801198732, c2=0.01932052560615957 ...................
[CV]  c1=0.5947449801198732, c2=0.01932052560615957, score=0.827836 -   1.4s
[CV] c1=0.39175621731359517, c2=0.03472523699438633 ..................
[CV]  c1=0.39175621731359517, c2=0.03472523699438633, score=0.908381 -   2.0s
[CV] c1=0.4733314263697012, c2=0.12651017307500673 ...................
[CV]  c1=0.4733314263697012, c2=0.12651017307500673, score=0.830237 -   1.8s
[CV] c1=0.48889236588787044, c2=0.03331411438297624 ..................
[CV]  c1=0.48889236588787044, c2=0.03331411438297624, score=0.845953 -   1.9s
[CV] c1=0.08526788571110812, c2=0.13382531105480874 ..................
[CV]  c1=0.08526788571110812, c2=0.13382531105480874, score=0.760672 -   1.5s
[CV] c1=0.42644807202877966, c2=0.01910944591269954 ..................
[CV]  c1=0.42644807202877966, c2=0.01910944591269954, score=0.870287 -   1.9s
[CV] c1=0.005639683858693419, c2=0.06244427245549233 .................
[CV]  c1=0.005639683858693419, c2=0.06244427245549233, score=0.880176 -   1.8s
[CV] c1=1.2515631393023146, c2=0.03183816278568514 ...................
[CV]  c1=1.2515631393023146, c2=0.03183816278568514, score=0.689271 -   1.5s
[CV] c1=0.43125884569175277, c2=0.03408914109225735 ..................
[CV]  c1=0.43125884569175277, c2=0.03408914109225735, score=0.855250 -   1.8s
[CV] c1=0.24729397915104762, c2=0.017615681666529773 .................
[CV]  c1=0.24729397915104762, c2=0.017615681666529773, score=0.864900 -   1.9s
[CV] c1=0.11680398654439843, c2=0.1066663364975167 ...................
[CV]  c1=0.11680398654439843, c2=0.1066663364975167, score=0.872459 -   1.9s
[CV] c1=0.5559377210253521, c2=0.013392070411862562 ..................
[CV]  c1=0.5559377210253521, c2=0.013392070411862562, score=0.736068 -   1.5s
[CV] c1=0.0021148540089996554, c2=0.015924680235763298 ...............
[CV]  c1=0.0021148540089996554, c2=0.015924680235763298, score=0.797677 -   1.9s
[CV] c1=0.45885612696589256, c2=0.13838286852102 .....................
[CV]  c1=0.45885612696589256, c2=0.13838286852102, score=0.882446 -   1.4s
Training done in: 26.332006s
     Saving training model...
        Saving training model done in: 0.013709s
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Prediction done in: 0.044960s