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

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Run15_v13.txt 71.1 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: Run15
Exclude stop words: False
Levels: S1: FalseS2: TrueS3: TrueS4: True
Run variant: 13
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: 0.003621s
-------------------------------- 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        word        :
7     isUpper    False
8     isLower    False
9     isGreek    False
10   isNumber    False
11    -1:word       in
12    +1:word       M9
13   -2:lemma  culture
14  -2:postag      VBN
15   +2:lemma  minimal
16  +2:postag       JJ
17     -1:ner        _
18     +1:ner      MED
19     -2:ner        _
20     +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        word  delta-arcA
7     isUpper       False
8     isLower       False
9     isGreek       False
10   isNumber       False
11    -1:word           _
12    +1:word           _
13   -2:lemma     affyexp
14  -2:postag          JJ
15   +2:lemma     glucose
16  +2:postag          NN
17     -1:ner           _
18     +1:ner           _
19     -2:ner           _
20     +2:ner        SUPP
Fitting 5 folds for each of 100 candidates, totalling 500 fits
[CV] c1=0.752259809938945, c2=0.13632801024729252 ....................
[CV]  c1=0.752259809938945, c2=0.13632801024729252, score=0.865543 -   1.7s
[CV] c1=0.6494400431544749, c2=0.005281131036357565 ..................
[CV]  c1=0.6494400431544749, c2=0.005281131036357565, score=0.880344 -   1.7s
[CV] c1=0.5040427227012549, c2=0.02839758694823832 ...................
[CV]  c1=0.5040427227012549, c2=0.02839758694823832, score=0.838591 -   1.8s
[CV] c1=0.5807884202105709, c2=0.006710199971858181 ..................
[CV]  c1=0.5807884202105709, c2=0.006710199971858181, score=0.808745 -   1.7s
[CV] c1=0.16182204658288055, c2=0.008834994414984188 .................
[CV]  c1=0.16182204658288055, c2=0.008834994414984188, score=0.867224 -   1.7s
[CV] c1=0.05715273529864092, c2=0.01108697182817814 ..................
[CV]  c1=0.05715273529864092, c2=0.01108697182817814, score=0.848843 -   1.8s
[CV] c1=0.1606118237959953, c2=0.07632153902589378 ...................
[CV]  c1=0.1606118237959953, c2=0.07632153902589378, score=0.787752 -   1.7s
[CV] c1=0.06767432930875536, c2=0.03073523875094793 ..................
[CV]  c1=0.06767432930875536, c2=0.03073523875094793, score=0.876140 -   1.6s
[CV] c1=1.463375496714161, c2=0.006639270393834511 ...................
[CV]  c1=1.463375496714161, c2=0.006639270393834511, score=0.866148 -   1.7s
[CV] c1=0.13529584802616074, c2=0.06770891962757322 ..................
[CV]  c1=0.13529584802616074, c2=0.06770891962757322, score=0.706432 -   1.5s
[CV] c1=0.6083910708710164, c2=0.05612149139600581 ...................
[CV]  c1=0.6083910708710164, c2=0.05612149139600581, score=0.809908 -   1.7s
[CV] c1=0.08430929141275526, c2=0.04027289121802749 ..................
[CV]  c1=0.08430929141275526, c2=0.04027289121802749, score=0.731629 -   1.3s
[CV] c1=0.4191218035698548, c2=0.041058834026875324 ..................
[CV]  c1=0.4191218035698548, c2=0.041058834026875324, score=0.766869 -   1.9s
[CV] c1=0.027796709112803287, c2=0.015061268436096412 ................
[CV]  c1=0.027796709112803287, c2=0.015061268436096412, score=0.841204 -   1.8s
[CV] c1=1.2841823134942698, c2=0.10948724760625086 ...................
[CV]  c1=1.2841823134942698, c2=0.10948724760625086, score=0.638136 -   1.7s
[CV] c1=1.306063230715063, c2=0.06086498234798973 ....................
[CV]  c1=1.306063230715063, c2=0.06086498234798973, score=0.638511 -   1.9s
[CV] c1=0.06910443190771647, c2=0.07143385779616433 ..................
[CV]  c1=0.06910443190771647, c2=0.07143385779616433, score=0.793824 -   1.7s
[CV] c1=0.6933879415138604, c2=0.0018363764423556324 .................
[CV]  c1=0.6933879415138604, c2=0.0018363764423556324, score=0.816478 -   1.7s
[CV] c1=0.670620398972846, c2=0.012014533652713934 ...................
[CV]  c1=0.670620398972846, c2=0.012014533652713934, score=0.877082 -   1.7s
[CV] c1=1.1491048647050062, c2=0.03812775605937096 ...................
[CV]  c1=1.1491048647050062, c2=0.03812775605937096, score=0.638989 -   1.8s
[CV] c1=0.41627368349034544, c2=0.010520754335490302 .................
[CV]  c1=0.41627368349034544, c2=0.010520754335490302, score=0.907722 -   1.7s
[CV] c1=0.09034176113387098, c2=0.08180840630438983 ..................
[CV]  c1=0.09034176113387098, c2=0.08180840630438983, score=0.790141 -   1.7s
[CV] c1=0.16618626252817145, c2=0.1576570227041733 ...................
[CV]  c1=0.16618626252817145, c2=0.1576570227041733, score=0.780134 -   1.8s
[CV] c1=0.10113340120103063, c2=0.0033520616552264585 ................
[CV]  c1=0.10113340120103063, c2=0.0033520616552264585, score=0.810089 -   1.6s
[CV] c1=0.40609618174622186, c2=0.034051517470961815 .................
[CV]  c1=0.40609618174622186, c2=0.034051517470961815, score=0.749914 -   1.7s
[CV] c1=0.5040427227012549, c2=0.02839758694823832 ...................
[CV]  c1=0.5040427227012549, c2=0.02839758694823832, score=0.833452 -   1.7s
[CV] c1=0.08228983478481358, c2=0.24460408555795674 ..................
[CV]  c1=0.08228983478481358, c2=0.24460408555795674, score=0.858778 -   1.7s
[CV] c1=0.16182204658288055, c2=0.008834994414984188 .................
[CV]  c1=0.16182204658288055, c2=0.008834994414984188, score=0.877699 -   1.8s
[CV] c1=0.05715273529864092, c2=0.01108697182817814 ..................
[CV]  c1=0.05715273529864092, c2=0.01108697182817814, score=0.761195 -   1.4s
[CV] c1=0.1723700099609017, c2=0.04556413484459568 ...................
[CV]  c1=0.1723700099609017, c2=0.04556413484459568, score=0.788844 -   1.8s
[CV] c1=0.4505689472075339, c2=0.07754136848585219 ...................
[CV]  c1=0.4505689472075339, c2=0.07754136848585219, score=0.894129 -   1.9s
[CV] c1=0.2167587953596191, c2=0.01150803467871346 ...................
[CV]  c1=0.2167587953596191, c2=0.01150803467871346, score=0.841663 -   1.8s
[CV] c1=0.43615330471298264, c2=0.019949515526172468 .................
[CV]  c1=0.43615330471298264, c2=0.019949515526172468, score=0.862248 -   1.7s
[CV] c1=0.028464659974473467, c2=0.0757554188875116 ..................
[CV]  c1=0.028464659974473467, c2=0.0757554188875116, score=0.741372 -   1.4s
[CV] c1=0.10157560677546373, c2=0.016899164498576712 .................
[CV]  c1=0.10157560677546373, c2=0.016899164498576712, score=0.877739 -   1.7s
[CV] c1=1.4997014423095727, c2=0.014257119025691196 ..................
[CV]  c1=1.4997014423095727, c2=0.014257119025691196, score=0.865187 -   1.7s
[CV] c1=0.6284895157294884, c2=0.0048431022606003704 .................
[CV]  c1=0.6284895157294884, c2=0.0048431022606003704, score=0.833464 -   1.7s
[CV] c1=0.04225349817589368, c2=0.18609191707489464 ..................
[CV]  c1=0.04225349817589368, c2=0.18609191707489464, score=0.756402 -   1.3s
[CV] c1=0.32816656152027385, c2=0.001567052815515329 .................
[CV]  c1=0.32816656152027385, c2=0.001567052815515329, score=0.797538 -   1.7s
[CV] c1=0.18314786317894188, c2=0.0014914524009928777 ................
[CV]  c1=0.18314786317894188, c2=0.0014914524009928777, score=0.852742 -   1.6s
[CV] c1=1.106608946955786, c2=0.01240789351575899 ....................
[CV]  c1=1.106608946955786, c2=0.01240789351575899, score=0.633978 -   1.3s
[CV] c1=0.1606118237959953, c2=0.07632153902589378 ...................
[CV]  c1=0.1606118237959953, c2=0.07632153902589378, score=0.880108 -   1.6s
[CV] c1=0.4505689472075339, c2=0.07754136848585219 ...................
[CV]  c1=0.4505689472075339, c2=0.07754136848585219, score=0.809570 -   1.8s
[CV] c1=0.19376951381571378, c2=0.028733720232256274 .................
[CV]  c1=0.19376951381571378, c2=0.028733720232256274, score=0.800252 -   1.6s
[CV] c1=0.43615330471298264, c2=0.019949515526172468 .................
[CV]  c1=0.43615330471298264, c2=0.019949515526172468, score=0.916208 -   1.6s
[CV] c1=0.6083910708710164, c2=0.05612149139600581 ...................
[CV]  c1=0.6083910708710164, c2=0.05612149139600581, score=0.883741 -   1.7s
[CV] c1=0.10157560677546373, c2=0.016899164498576712 .................
[CV]  c1=0.10157560677546373, c2=0.016899164498576712, score=0.805232 -   1.7s
[CV] c1=0.10248380213326022, c2=0.005015198092486652 .................
[CV]  c1=0.10248380213326022, c2=0.005015198092486652, score=0.886404 -   1.4s
[CV] c1=0.4744593260771863, c2=0.035208670242626625 ..................
[CV]  c1=0.4744593260771863, c2=0.035208670242626625, score=0.755626 -   1.8s
[CV] c1=0.13835110827134814, c2=0.03156661041664845 ..................
[CV]  c1=0.13835110827134814, c2=0.03156661041664845, score=0.841800 -   1.7s
[CV] c1=0.19090107526962175, c2=0.0030499185495058 ...................
[CV]  c1=0.19090107526962175, c2=0.0030499185495058, score=0.861556 -   1.7s
[CV] c1=1.4416209867259464, c2=0.022112165647977 .....................
[CV]  c1=1.4416209867259464, c2=0.022112165647977, score=0.732190 -   1.7s
[CV] c1=0.06910443190771647, c2=0.07143385779616433 ..................
[CV]  c1=0.06910443190771647, c2=0.07143385779616433, score=0.838837 -   1.8s
[CV] c1=0.1723700099609017, c2=0.04556413484459568 ...................
[CV]  c1=0.1723700099609017, c2=0.04556413484459568, score=0.871281 -   1.7s
[CV] c1=0.670620398972846, c2=0.012014533652713934 ...................
[CV]  c1=0.670620398972846, c2=0.012014533652713934, score=0.801396 -   1.9s
[CV] c1=0.2167587953596191, c2=0.01150803467871346 ...................
[CV]  c1=0.2167587953596191, c2=0.01150803467871346, score=0.802641 -   1.8s
[CV] c1=0.43615330471298264, c2=0.019949515526172468 .................
[CV]  c1=0.43615330471298264, c2=0.019949515526172468, score=0.857763 -   1.7s
[CV] c1=0.6083910708710164, c2=0.05612149139600581 ...................
[CV]  c1=0.6083910708710164, c2=0.05612149139600581, score=0.803586 -   1.6s
[CV] c1=0.10157560677546373, c2=0.016899164498576712 .................
[CV]  c1=0.10157560677546373, c2=0.016899164498576712, score=0.866839 -   1.6s
[CV] c1=0.752259809938945, c2=0.13632801024729252 ....................
[CV]  c1=0.752259809938945, c2=0.13632801024729252, score=0.822132 -   1.7s
[CV] c1=0.6494400431544749, c2=0.005281131036357565 ..................
[CV]  c1=0.6494400431544749, c2=0.005281131036357565, score=0.810116 -   1.7s
[CV] c1=0.2743058923797177, c2=0.08606005044606713 ...................
[CV]  c1=0.2743058923797177, c2=0.08606005044606713, score=0.699640 -   1.6s
[CV] c1=0.7441623655509021, c2=0.011333927957483298 ..................
[CV]  c1=0.7441623655509021, c2=0.011333927957483298, score=0.872608 -   1.7s
[CV] c1=0.0892644412457624, c2=0.11984207496500779 ...................
[CV]  c1=0.0892644412457624, c2=0.11984207496500779, score=0.789764 -   1.8s
[CV] c1=1.106608946955786, c2=0.01240789351575899 ....................
[CV]  c1=1.106608946955786, c2=0.01240789351575899, score=0.656178 -   1.7s
[CV] c1=0.3946513128189392, c2=0.08751866308612871 ...................
[CV]  c1=0.3946513128189392, c2=0.08751866308612871, score=0.887700 -   1.7s
[CV] c1=0.1803245279864374, c2=0.03168975613151679 ...................
[CV]  c1=0.1803245279864374, c2=0.03168975613151679, score=0.738323 -   1.4s
[CV] c1=0.19376951381571378, c2=0.028733720232256274 .................
[CV]  c1=0.19376951381571378, c2=0.028733720232256274, score=0.820419 -   1.8s
[CV] c1=0.13529584802616074, c2=0.06770891962757322 ..................
[CV]  c1=0.13529584802616074, c2=0.06770891962757322, score=0.863073 -   1.6s
[CV] c1=0.028464659974473467, c2=0.0757554188875116 ..................
[CV]  c1=0.028464659974473467, c2=0.0757554188875116, score=0.834282 -   1.7s
[CV] c1=0.036265040005861664, c2=0.043992737761965564 ................
[CV]  c1=0.036265040005861664, c2=0.043992737761965564, score=0.737756 -   1.3s
[CV] c1=0.4191218035698548, c2=0.041058834026875324 ..................
[CV]  c1=0.4191218035698548, c2=0.041058834026875324, score=0.726714 -   1.4s
[CV] c1=0.4531000401615301, c2=0.028601225889616638 ..................
[CV]  c1=0.4531000401615301, c2=0.028601225889616638, score=0.837696 -   1.8s
[CV] c1=0.004906637093781637, c2=0.03946188551186733 .................
[CV]  c1=0.004906637093781637, c2=0.03946188551186733, score=0.761605 -   1.3s
[CV] c1=0.5807884202105709, c2=0.006710199971858181 ..................
[CV]  c1=0.5807884202105709, c2=0.006710199971858181, score=0.810116 -   1.7s
[CV] c1=0.0892644412457624, c2=0.11984207496500779 ...................
[CV]  c1=0.0892644412457624, c2=0.11984207496500779, score=0.877223 -   1.8s
[CV] c1=1.0091331005467783, c2=0.05727581292164206 ...................
[CV]  c1=1.0091331005467783, c2=0.05727581292164206, score=0.610775 -   1.7s
[CV] c1=0.0018895288405304694, c2=0.05558743836264954 ................
[CV]  c1=0.0018895288405304694, c2=0.05558743836264954, score=0.854115 -   1.7s
[CV] c1=0.1803245279864374, c2=0.03168975613151679 ...................
[CV]  c1=0.1803245279864374, c2=0.03168975613151679, score=0.891526 -   1.7s
[CV] c1=0.3867630214433191, c2=0.02514809582529395 ...................
[CV]  c1=0.3867630214433191, c2=0.02514809582529395, score=0.857763 -   1.5s
[CV] c1=0.03279806251385013, c2=0.04305168157522314 ..................
[CV]  c1=0.03279806251385013, c2=0.04305168157522314, score=0.882680 -   1.6s
[CV] c1=0.20755417109335084, c2=0.036795301788140646 .................
[CV]  c1=0.20755417109335084, c2=0.036795301788140646, score=0.734536 -   1.4s
[CV] c1=0.10157560677546373, c2=0.016899164498576712 .................
[CV]  c1=0.10157560677546373, c2=0.016899164498576712, score=0.835253 -   1.7s
[CV] c1=0.2955907603120557, c2=0.10001501201171051 ...................
[CV]  c1=0.2955907603120557, c2=0.10001501201171051, score=0.803185 -   1.7s
[CV] c1=0.4531000401615301, c2=0.028601225889616638 ..................
[CV]  c1=0.4531000401615301, c2=0.028601225889616638, score=0.824804 -   1.8s
[CV] c1=0.004906637093781637, c2=0.03946188551186733 .................
[CV]  c1=0.004906637093781637, c2=0.03946188551186733, score=0.885850 -   1.6s
[CV] c1=0.32816656152027385, c2=0.001567052815515329 .................
[CV]  c1=0.32816656152027385, c2=0.001567052815515329, score=0.904631 -   1.6s
[CV] c1=0.18314786317894188, c2=0.0014914524009928777 ................
[CV]  c1=0.18314786317894188, c2=0.0014914524009928777, score=0.895589 -   1.7s
[CV] c1=1.106608946955786, c2=0.01240789351575899 ....................
[CV]  c1=1.106608946955786, c2=0.01240789351575899, score=0.864371 -   1.6s
[CV] c1=0.0018895288405304694, c2=0.05558743836264954 ................
[CV]  c1=0.0018895288405304694, c2=0.05558743836264954, score=0.890318 -   1.6s
[CV] c1=0.01679229145190292, c2=0.038693982988578846 .................
[CV]  c1=0.01679229145190292, c2=0.038693982988578846, score=0.823713 -   1.7s
[CV] c1=1.463375496714161, c2=0.006639270393834511 ...................
[CV]  c1=1.463375496714161, c2=0.006639270393834511, score=0.642920 -   1.9s
[CV] c1=0.03279806251385013, c2=0.04305168157522314 ..................
[CV]  c1=0.03279806251385013, c2=0.04305168157522314, score=0.750967 -   1.3s
[CV] c1=0.028464659974473467, c2=0.0757554188875116 ..................
[CV]  c1=0.028464659974473467, c2=0.0757554188875116, score=0.885114 -   1.7s
[CV] c1=0.08430929141275526, c2=0.04027289121802749 ..................
[CV]  c1=0.08430929141275526, c2=0.04027289121802749, score=0.864061 -   1.6s
[CV] c1=0.4191218035698548, c2=0.041058834026875324 ..................
[CV]  c1=0.4191218035698548, c2=0.041058834026875324, score=0.903748 -   1.8s
[CV] c1=0.6284895157294884, c2=0.0048431022606003704 .................
[CV]  c1=0.6284895157294884, c2=0.0048431022606003704, score=0.717471 -   1.5s
[CV] c1=0.004906637093781637, c2=0.03946188551186733 .................
[CV]  c1=0.004906637093781637, c2=0.03946188551186733, score=0.851684 -   1.6s
[CV] c1=0.4076922901008913, c2=0.11516554517820005 ...................
[CV]  c1=0.4076922901008913, c2=0.11516554517820005, score=0.702380 -   1.4s
[CV] c1=0.18314786317894188, c2=0.0014914524009928777 ................
[CV]  c1=0.18314786317894188, c2=0.0014914524009928777, score=0.754111 -   1.4s
[CV] c1=0.05715273529864092, c2=0.01108697182817814 ..................
[CV]  c1=0.05715273529864092, c2=0.01108697182817814, score=0.853487 -   1.6s
[CV] c1=0.5481914056911523, c2=0.0038665614015526277 .................
[CV]  c1=0.5481914056911523, c2=0.0038665614015526277, score=0.797673 -   1.7s
[CV] c1=0.01679229145190292, c2=0.038693982988578846 .................
[CV]  c1=0.01679229145190292, c2=0.038693982988578846, score=0.886297 -   1.7s
[CV] c1=0.19376951381571378, c2=0.028733720232256274 .................
[CV]  c1=0.19376951381571378, c2=0.028733720232256274, score=0.903042 -   1.7s
[CV] c1=0.43615330471298264, c2=0.019949515526172468 .................
[CV]  c1=0.43615330471298264, c2=0.019949515526172468, score=0.751843 -   1.7s
[CV] c1=0.6083910708710164, c2=0.05612149139600581 ...................
[CV]  c1=0.6083910708710164, c2=0.05612149139600581, score=0.724642 -   1.7s
[CV] c1=0.08430929141275526, c2=0.04027289121802749 ..................
[CV]  c1=0.08430929141275526, c2=0.04027289121802749, score=0.882072 -   1.7s
[CV] c1=1.0120756670644797, c2=0.08941812678670334 ...................
[CV]  c1=1.0120756670644797, c2=0.08941812678670334, score=0.874819 -   1.7s
[CV] c1=0.339897270537157, c2=0.024611117849723814 ...................
[CV]  c1=0.339897270537157, c2=0.024611117849723814, score=0.785415 -   1.8s
[CV] c1=0.2589703923527472, c2=0.06512326602475861 ...................
[CV]  c1=0.2589703923527472, c2=0.06512326602475861, score=0.904977 -   1.7s
[CV] c1=0.4076922901008913, c2=0.11516554517820005 ...................
[CV]  c1=0.4076922901008913, c2=0.11516554517820005, score=0.752363 -   1.6s
[CV] c1=0.5801437895304963, c2=0.2762766844117403 ....................
[CV]  c1=0.5801437895304963, c2=0.2762766844117403, score=0.689075 -   1.7s
[CV] c1=0.14270813853934722, c2=0.01224030918183421 ..................
[CV]  c1=0.14270813853934722, c2=0.01224030918183421, score=0.907192 -   1.6s
[CV] c1=0.15936463496541522, c2=0.32593357695530756 ..................
[CV]  c1=0.15936463496541522, c2=0.32593357695530756, score=0.871414 -   1.6s
[CV] c1=0.7644239665454672, c2=0.06978009296869059 ...................
[CV]  c1=0.7644239665454672, c2=0.06978009296869059, score=0.686489 -   1.3s
[CV] c1=0.3867630214433191, c2=0.02514809582529395 ...................
[CV]  c1=0.3867630214433191, c2=0.02514809582529395, score=0.910807 -   1.9s
[CV] c1=0.3118712551144907, c2=0.07204748350860728 ...................
[CV]  c1=0.3118712551144907, c2=0.07204748350860728, score=0.723124 -   1.3s
[CV] c1=0.20755417109335084, c2=0.036795301788140646 .................
[CV]  c1=0.20755417109335084, c2=0.036795301788140646, score=0.894816 -   1.9s
[CV] c1=0.008520992000206005, c2=0.008665153017420494 ................
[CV]  c1=0.008520992000206005, c2=0.008665153017420494, score=0.729854 -   1.3s
[CV] c1=0.2724831847060931, c2=0.0165714232258963 ....................
[CV]  c1=0.2724831847060931, c2=0.0165714232258963, score=0.809492 -   1.9s
[CV] c1=0.6284895157294884, c2=0.0048431022606003704 .................
[CV]  c1=0.6284895157294884, c2=0.0048431022606003704, score=0.885914 -   1.8s
[CV] c1=0.2589703923527472, c2=0.06512326602475861 ...................
[CV]  c1=0.2589703923527472, c2=0.06512326602475861, score=0.868501 -   1.7s
[CV] c1=0.4076922901008913, c2=0.11516554517820005 ...................
[CV]  c1=0.4076922901008913, c2=0.11516554517820005, score=0.850205 -   1.7s
[CV] c1=0.8336301114371835, c2=0.04363901842393647 ...................
[CV]  c1=0.8336301114371835, c2=0.04363901842393647, score=0.672266 -   1.3s
[CV] c1=0.1886496288522549, c2=0.07222491603812985 ...................
[CV]  c1=0.1886496288522549, c2=0.07222491603812985, score=0.900066 -   1.7s
[CV] c1=0.3946513128189392, c2=0.08751866308612871 ...................
[CV]  c1=0.3946513128189392, c2=0.08751866308612871, score=0.843927 -   1.6s
[CV] c1=0.1803245279864374, c2=0.03168975613151679 ...................
[CV]  c1=0.1803245279864374, c2=0.03168975613151679, score=0.861556 -   1.6s
[CV] c1=0.3867630214433191, c2=0.02514809582529395 ...................
[CV]  c1=0.3867630214433191, c2=0.02514809582529395, score=0.718488 -   1.5s
[CV] c1=0.13529584802616074, c2=0.06770891962757322 ..................
[CV]  c1=0.13529584802616074, c2=0.06770891962757322, score=0.787173 -   1.6s
[CV] c1=0.028464659974473467, c2=0.0757554188875116 ..................
[CV]  c1=0.028464659974473467, c2=0.0757554188875116, score=0.823997 -   1.5s
[CV] c1=0.08430929141275526, c2=0.04027289121802749 ..................
[CV]  c1=0.08430929141275526, c2=0.04027289121802749, score=0.799031 -   1.7s
[CV] c1=1.4997014423095727, c2=0.014257119025691196 ..................
[CV]  c1=1.4997014423095727, c2=0.014257119025691196, score=0.583653 -   1.4s
[CV] c1=0.339897270537157, c2=0.024611117849723814 ...................
[CV]  c1=0.339897270537157, c2=0.024611117849723814, score=0.864206 -   1.7s
[CV] c1=0.004906637093781637, c2=0.03946188551186733 .................
[CV]  c1=0.004906637093781637, c2=0.03946188551186733, score=0.782389 -   1.5s
[CV] c1=0.32816656152027385, c2=0.001567052815515329 .................
[CV]  c1=0.32816656152027385, c2=0.001567052815515329, score=0.861556 -   1.6s
[CV] c1=0.18314786317894188, c2=0.0014914524009928777 ................
[CV]  c1=0.18314786317894188, c2=0.0014914524009928777, score=0.802641 -   1.6s
[CV] c1=1.106608946955786, c2=0.01240789351575899 ....................
[CV]  c1=1.106608946955786, c2=0.01240789351575899, score=0.818595 -   1.4s
[CV] c1=0.1606118237959953, c2=0.07632153902589378 ...................
[CV]  c1=0.1606118237959953, c2=0.07632153902589378, score=0.803185 -   1.7s
[CV] c1=0.06767432930875536, c2=0.03073523875094793 ..................
[CV]  c1=0.06767432930875536, c2=0.03073523875094793, score=0.801362 -   1.6s
[CV] c1=1.463375496714161, c2=0.006639270393834511 ...................
[CV]  c1=1.463375496714161, c2=0.006639270393834511, score=0.616450 -   1.8s
[CV] c1=0.03279806251385013, c2=0.04305168157522314 ..................
[CV]  c1=0.03279806251385013, c2=0.04305168157522314, score=0.866301 -   1.6s
[CV] c1=0.20755417109335084, c2=0.036795301788140646 .................
[CV]  c1=0.20755417109335084, c2=0.036795301788140646, score=0.861556 -   1.6s
[CV] c1=0.036265040005861664, c2=0.043992737761965564 ................
[CV]  c1=0.036265040005861664, c2=0.043992737761965564, score=0.806751 -   1.7s
[CV] c1=1.4997014423095727, c2=0.014257119025691196 ..................
[CV]  c1=1.4997014423095727, c2=0.014257119025691196, score=0.612725 -   1.8s
[CV] c1=0.13835110827134814, c2=0.03156661041664845 ..................
[CV]  c1=0.13835110827134814, c2=0.03156661041664845, score=0.891702 -   1.7s
[CV] c1=1.2841823134942698, c2=0.10948724760625086 ...................
[CV]  c1=1.2841823134942698, c2=0.10948724760625086, score=0.596542 -   1.3s
[CV] c1=0.4076922901008913, c2=0.11516554517820005 ...................
[CV]  c1=0.4076922901008913, c2=0.11516554517820005, score=0.857178 -   1.6s
[CV] c1=0.5801437895304963, c2=0.2762766844117403 ....................
[CV]  c1=0.5801437895304963, c2=0.2762766844117403, score=0.777102 -   1.7s
[CV] c1=0.14270813853934722, c2=0.01224030918183421 ..................
[CV]  c1=0.14270813853934722, c2=0.01224030918183421, score=0.812888 -   1.6s
[CV] c1=0.15936463496541522, c2=0.32593357695530756 ..................
[CV]  c1=0.15936463496541522, c2=0.32593357695530756, score=0.759845 -   1.4s
[CV] c1=0.06767432930875536, c2=0.03073523875094793 ..................
[CV]  c1=0.06767432930875536, c2=0.03073523875094793, score=0.792443 -   1.8s
[CV] c1=0.3867630214433191, c2=0.02514809582529395 ...................
[CV]  c1=0.3867630214433191, c2=0.02514809582529395, score=0.766085 -   1.8s
[CV] c1=0.3118712551144907, c2=0.07204748350860728 ...................
[CV]  c1=0.3118712551144907, c2=0.07204748350860728, score=0.907334 -   1.6s
[CV] c1=0.43755961220525863, c2=0.0008143063923806029 ................
[CV]  c1=0.43755961220525863, c2=0.0008143063923806029, score=0.717203 -   1.2s
[CV] c1=0.08430929141275526, c2=0.04027289121802749 ..................
[CV]  c1=0.08430929141275526, c2=0.04027289121802749, score=0.792443 -   1.7s
[CV] c1=1.0120756670644797, c2=0.08941812678670334 ...................
[CV]  c1=1.0120756670644797, c2=0.08941812678670334, score=0.641013 -   1.3s
[CV] c1=0.6494400431544749, c2=0.005281131036357565 ..................
[CV]  c1=0.6494400431544749, c2=0.005281131036357565, score=0.706933 -   1.3s
[CV] c1=2.8542404736651434, c2=0.04205523377805767 ...................
[CV]  c1=2.8542404736651434, c2=0.04205523377805767, score=0.659632 -   1.5s
[CV] c1=0.19090107526962175, c2=0.0030499185495058 ...................
[CV]  c1=0.19090107526962175, c2=0.0030499185495058, score=0.800252 -   1.7s
[CV] c1=1.4416209867259464, c2=0.022112165647977 .....................
[CV]  c1=1.4416209867259464, c2=0.022112165647977, score=0.649234 -   1.6s
[CV] c1=0.02703528386040871, c2=0.13708661231352223 ..................
[CV]  c1=0.02703528386040871, c2=0.13708661231352223, score=0.782389 -   1.6s
[CV] c1=0.6933879415138604, c2=0.0018363764423556324 .................
[CV]  c1=0.6933879415138604, c2=0.0018363764423556324, score=0.881499 -   1.8s
[CV] c1=0.5345492476025216, c2=0.06014302469856182 ...................
[CV]  c1=0.5345492476025216, c2=0.06014302469856182, score=0.731447 -   1.7s
[CV] c1=0.6310038254591727, c2=0.0432316386822676 ....................
[CV]  c1=0.6310038254591727, c2=0.0432316386822676, score=0.786183 -   1.7s
[CV] c1=0.11983742170229553, c2=0.03254559873123556 ..................
[CV]  c1=0.11983742170229553, c2=0.03254559873123556, score=0.744909 -   1.5s
[CV] c1=0.3754253365265449, c2=0.07095169982427979 ...................
[CV]  c1=0.3754253365265449, c2=0.07095169982427979, score=0.750107 -   1.7s
[CV] c1=0.24992293252674896, c2=0.11105643175773623 ..................
[CV]  c1=0.24992293252674896, c2=0.11105643175773623, score=0.888577 -   1.7s
[CV] c1=1.1648856407033545, c2=0.0173811747742124 ....................
[CV]  c1=1.1648856407033545, c2=0.0173811747742124, score=0.641481 -   1.1s
[CV] c1=1.4997014423095727, c2=0.014257119025691196 ..................
[CV]  c1=1.4997014423095727, c2=0.014257119025691196, score=0.749197 -   1.6s
[CV] c1=0.027796709112803287, c2=0.015061268436096412 ................
[CV]  c1=0.027796709112803287, c2=0.015061268436096412, score=0.872678 -   1.6s
[CV] c1=0.2589703923527472, c2=0.06512326602475861 ...................
[CV]  c1=0.2589703923527472, c2=0.06512326602475861, score=0.787173 -   1.7s
[CV] c1=0.043290804951445695, c2=0.12928296711927964 .................
[CV]  c1=0.043290804951445695, c2=0.12928296711927964, score=0.756228 -   1.3s
[CV] c1=0.18314786317894188, c2=0.0014914524009928777 ................
[CV]  c1=0.18314786317894188, c2=0.0014914524009928777, score=0.808565 -   1.7s
[CV] c1=0.1886496288522549, c2=0.07222491603812985 ...................
[CV]  c1=0.1886496288522549, c2=0.07222491603812985, score=0.785161 -   1.7s
[CV] c1=0.3946513128189392, c2=0.08751866308612871 ...................
[CV]  c1=0.3946513128189392, c2=0.08751866308612871, score=0.827567 -   1.7s
[CV] c1=0.7644239665454672, c2=0.06978009296869059 ...................
[CV]  c1=0.7644239665454672, c2=0.06978009296869059, score=0.715011 -   1.7s
[CV] c1=1.5995902072380093, c2=0.08767954933309148 ...................
[CV]  c1=1.5995902072380093, c2=0.08767954933309148, score=0.577109 -   1.8s
[CV] c1=0.10855313077450741, c2=0.010940300167171634 .................
[CV]  c1=0.10855313077450741, c2=0.010940300167171634, score=0.814872 -   1.7s
[CV] c1=0.1695223869153062, c2=0.017898742713093982 ..................
[CV]  c1=0.1695223869153062, c2=0.017898742713093982, score=0.826249 -   1.7s
[CV] c1=0.11617086221832837, c2=0.004762250076597188 .................
[CV]  c1=0.11617086221832837, c2=0.004762250076597188, score=0.900088 -   1.4s
[CV] c1=0.10248380213326022, c2=0.005015198092486652 .................
[CV]  c1=0.10248380213326022, c2=0.005015198092486652, score=0.741281 -   0.9s
[CV] c1=0.4744593260771863, c2=0.035208670242626625 ..................
[CV]  c1=0.4744593260771863, c2=0.035208670242626625, score=0.898740 -   2.0s
[CV] c1=0.13835110827134814, c2=0.03156661041664845 ..................
[CV]  c1=0.13835110827134814, c2=0.03156661041664845, score=0.795282 -   1.8s
[CV] c1=0.19090107526962175, c2=0.0030499185495058 ...................
[CV]  c1=0.19090107526962175, c2=0.0030499185495058, score=0.739846 -   1.4s
[CV] c1=0.043290804951445695, c2=0.12928296711927964 .................
[CV]  c1=0.043290804951445695, c2=0.12928296711927964, score=0.858778 -   1.6s
[CV] c1=0.8336301114371835, c2=0.04363901842393647 ...................
[CV]  c1=0.8336301114371835, c2=0.04363901842393647, score=0.756943 -   1.7s
[CV] c1=0.739921726709296, c2=0.03777828231158368 ....................
[CV]  c1=0.739921726709296, c2=0.03777828231158368, score=0.870401 -   1.7s
[CV] c1=0.22833888674284988, c2=0.1344639101864193 ...................
[CV]  c1=0.22833888674284988, c2=0.1344639101864193, score=0.733315 -   1.4s
[CV] c1=0.7644239665454672, c2=0.06978009296869059 ...................
[CV]  c1=0.7644239665454672, c2=0.06978009296869059, score=0.867791 -   1.8s
[CV] c1=1.5995902072380093, c2=0.08767954933309148 ...................
[CV]  c1=1.5995902072380093, c2=0.08767954933309148, score=0.741438 -   1.6s
[CV] c1=0.3118712551144907, c2=0.07204748350860728 ...................
[CV]  c1=0.3118712551144907, c2=0.07204748350860728, score=0.790551 -   1.8s
[CV] c1=0.1695223869153062, c2=0.017898742713093982 ..................
[CV]  c1=0.1695223869153062, c2=0.017898742713093982, score=0.794035 -   1.6s
[CV] c1=0.07829034045149781, c2=0.0623605001195555 ...................
[CV]  c1=0.07829034045149781, c2=0.0623605001195555, score=0.795837 -   1.5s
[CV] c1=0.10248380213326022, c2=0.005015198092486652 .................
[CV]  c1=0.10248380213326022, c2=0.005015198092486652, score=0.812888 -   1.3s
[CV] c1=0.4744593260771863, c2=0.035208670242626625 ..................
[CV]  c1=0.4744593260771863, c2=0.035208670242626625, score=0.852555 -   1.8s
[CV] c1=0.13835110827134814, c2=0.03156661041664845 ..................
[CV]  c1=0.13835110827134814, c2=0.03156661041664845, score=0.863073 -   1.6s
[CV] c1=1.2841823134942698, c2=0.10948724760625086 ...................
[CV]  c1=1.2841823134942698, c2=0.10948724760625086, score=0.796800 -   1.7s
[CV] c1=1.306063230715063, c2=0.06086498234798973 ....................
[CV]  c1=1.306063230715063, c2=0.06086498234798973, score=0.741718 -   1.5s
[CV] c1=0.02703528386040871, c2=0.13708661231352223 ..................
[CV]  c1=0.02703528386040871, c2=0.13708661231352223, score=0.743926 -   1.2s
[CV] c1=0.1886496288522549, c2=0.07222491603812985 ...................
[CV]  c1=0.1886496288522549, c2=0.07222491603812985, score=0.863073 -   1.6s
[CV] c1=0.3946513128189392, c2=0.08751866308612871 ...................
[CV]  c1=0.3946513128189392, c2=0.08751866308612871, score=0.752363 -   1.8s
[CV] c1=0.1803245279864374, c2=0.03168975613151679 ...................
[CV]  c1=0.1803245279864374, c2=0.03168975613151679, score=0.818615 -   1.6s
[CV] c1=0.3867630214433191, c2=0.02514809582529395 ...................
[CV]  c1=0.3867630214433191, c2=0.02514809582529395, score=0.805908 -   1.8s
[CV] c1=0.3118712551144907, c2=0.07204748350860728 ...................
[CV]  c1=0.3118712551144907, c2=0.07204748350860728, score=0.871305 -   1.6s
[CV] c1=0.43755961220525863, c2=0.0008143063923806029 ................
[CV]  c1=0.43755961220525863, c2=0.0008143063923806029, score=0.774245 -   1.8s
[CV] c1=0.07829034045149781, c2=0.0623605001195555 ...................
[CV]  c1=0.07829034045149781, c2=0.0623605001195555, score=0.720507 -   1.4s
[CV] c1=0.2955907603120557, c2=0.10001501201171051 ...................
[CV]  c1=0.2955907603120557, c2=0.10001501201171051, score=0.869853 -   1.8s
[CV] c1=0.4531000401615301, c2=0.028601225889616638 ..................
[CV]  c1=0.4531000401615301, c2=0.028601225889616638, score=0.726714 -   1.5s
[CV] c1=0.008620246552390872, c2=0.09684287460683788 .................
[CV]  c1=0.008620246552390872, c2=0.09684287460683788, score=0.878531 -   1.7s
[CV] c1=0.5807884202105709, c2=0.006710199971858181 ..................
[CV]  c1=0.5807884202105709, c2=0.006710199971858181, score=0.887722 -   1.7s
[CV] c1=0.16182204658288055, c2=0.008834994414984188 .................
[CV]  c1=0.16182204658288055, c2=0.008834994414984188, score=0.805232 -   1.7s
[CV] c1=1.0091331005467783, c2=0.05727581292164206 ...................
[CV]  c1=1.0091331005467783, c2=0.05727581292164206, score=0.870436 -   1.8s
[CV] c1=0.0018895288405304694, c2=0.05558743836264954 ................
[CV]  c1=0.0018895288405304694, c2=0.05558743836264954, score=0.759787 -   1.3s
[CV] c1=0.4505689472075339, c2=0.07754136848585219 ...................
[CV]  c1=0.4505689472075339, c2=0.07754136848585219, score=0.827469 -   1.7s
[CV] c1=0.2167587953596191, c2=0.01150803467871346 ...................
[CV]  c1=0.2167587953596191, c2=0.01150803467871346, score=0.722142 -   1.3s
[CV] c1=0.11983742170229553, c2=0.03254559873123556 ..................
[CV]  c1=0.11983742170229553, c2=0.03254559873123556, score=0.858778 -   1.5s
[CV] c1=0.08777368415518812, c2=0.0028956716693545512 ................
[CV]  c1=0.08777368415518812, c2=0.0028956716693545512, score=0.739808 -   1.3s
[CV] c1=0.1695223869153062, c2=0.017898742713093982 ..................
[CV]  c1=0.1695223869153062, c2=0.017898742713093982, score=0.865850 -   1.7s
[CV] c1=0.07829034045149781, c2=0.0623605001195555 ...................
[CV]  c1=0.07829034045149781, c2=0.0623605001195555, score=0.824554 -   1.5s
[CV] c1=0.10113340120103063, c2=0.0033520616552264585 ................
[CV]  c1=0.10113340120103063, c2=0.0033520616552264585, score=0.858212 -   1.5s
[CV] c1=1.0311328605766514, c2=0.015093608504736032 ..................
[CV]  c1=1.0311328605766514, c2=0.015093608504736032, score=0.745430 -   1.7s
[CV] c1=0.5040427227012549, c2=0.02839758694823832 ...................
[CV]  c1=0.5040427227012549, c2=0.02839758694823832, score=0.903913 -   1.7s
[CV] c1=0.08228983478481358, c2=0.24460408555795674 ..................
[CV]  c1=0.08228983478481358, c2=0.24460408555795674, score=0.887761 -   1.6s
[CV] c1=1.4416209867259464, c2=0.022112165647977 .....................
[CV]  c1=1.4416209867259464, c2=0.022112165647977, score=0.593603 -   1.9s
[CV] c1=0.38965201765718566, c2=0.017234404134699878 .................
[CV]  c1=0.38965201765718566, c2=0.017234404134699878, score=0.784643 -   1.6s
[CV] c1=0.1723700099609017, c2=0.04556413484459568 ...................
[CV]  c1=0.1723700099609017, c2=0.04556413484459568, score=0.738515 -   1.4s
[CV] c1=0.5345492476025216, c2=0.06014302469856182 ...................
[CV]  c1=0.5345492476025216, c2=0.06014302469856182, score=0.728080 -   1.3s
[CV] c1=1.762346873523434, c2=0.043810090956525105 ...................
[CV]  c1=1.762346873523434, c2=0.043810090956525105, score=0.810020 -   1.7s
[CV] c1=1.312157211435938, c2=0.08603498128982515 ....................
[CV]  c1=1.312157211435938, c2=0.08603498128982515, score=0.598994 -   1.4s
[CV] c1=0.03279806251385013, c2=0.04305168157522314 ..................
[CV]  c1=0.03279806251385013, c2=0.04305168157522314, score=0.809184 -   1.7s
[CV] c1=0.20755417109335084, c2=0.036795301788140646 .................
[CV]  c1=0.20755417109335084, c2=0.036795301788140646, score=0.820249 -   1.8s
[CV] c1=0.008520992000206005, c2=0.008665153017420494 ................
[CV]  c1=0.008520992000206005, c2=0.008665153017420494, score=0.817245 -   1.4s
[CV] c1=0.2955907603120557, c2=0.10001501201171051 ...................
[CV]  c1=0.2955907603120557, c2=0.10001501201171051, score=0.690179 -   1.1s
[CV] c1=1.0311328605766514, c2=0.015093608504736032 ..................
[CV]  c1=1.0311328605766514, c2=0.015093608504736032, score=0.791176 -   1.6s
[CV] c1=2.8542404736651434, c2=0.04205523377805767 ...................
[CV]  c1=2.8542404736651434, c2=0.04205523377805767, score=0.580273 -   1.7s
[CV] c1=0.19090107526962175, c2=0.0030499185495058 ...................
[CV]  c1=0.19090107526962175, c2=0.0030499185495058, score=0.854628 -   1.8s
[CV] c1=0.26743103044967736, c2=0.00894230058234566 ..................
[CV]  c1=0.26743103044967736, c2=0.00894230058234566, score=0.798958 -   2.0s
[CV] c1=1.0091331005467783, c2=0.05727581292164206 ...................
[CV]  c1=1.0091331005467783, c2=0.05727581292164206, score=0.664815 -   1.8s
[CV] c1=0.0018895288405304694, c2=0.05558743836264954 ................
[CV]  c1=0.0018895288405304694, c2=0.05558743836264954, score=0.836181 -   1.7s
[CV] c1=0.06767432930875536, c2=0.03073523875094793 ..................
[CV]  c1=0.06767432930875536, c2=0.03073523875094793, score=0.858770 -   1.6s
[CV] c1=1.463375496714161, c2=0.006639270393834511 ...................
[CV]  c1=1.463375496714161, c2=0.006639270393834511, score=0.745621 -   1.5s
[CV] c1=0.13529584802616074, c2=0.06770891962757322 ..................
[CV]  c1=0.13529584802616074, c2=0.06770891962757322, score=0.874603 -   1.7s
[CV] c1=0.028464659974473467, c2=0.0757554188875116 ..................
[CV]  c1=0.028464659974473467, c2=0.0757554188875116, score=0.817051 -   1.8s
[CV] c1=0.036265040005861664, c2=0.043992737761965564 ................
[CV]  c1=0.036265040005861664, c2=0.043992737761965564, score=0.888524 -   1.7s
[CV] c1=0.10113340120103063, c2=0.0033520616552264585 ................
[CV]  c1=0.10113340120103063, c2=0.0033520616552264585, score=0.752802 -   0.9s
[CV] c1=0.4744593260771863, c2=0.035208670242626625 ..................
[CV]  c1=0.4744593260771863, c2=0.035208670242626625, score=0.732239 -   1.5s
[CV] c1=0.027796709112803287, c2=0.015061268436096412 ................
[CV]  c1=0.027796709112803287, c2=0.015061268436096412, score=0.809184 -   1.8s
[CV] c1=1.2841823134942698, c2=0.10948724760625086 ...................
[CV]  c1=1.2841823134942698, c2=0.10948724760625086, score=0.852882 -   1.9s
[CV] c1=1.306063230715063, c2=0.06086498234798973 ....................
[CV]  c1=1.306063230715063, c2=0.06086498234798973, score=0.586410 -   1.8s
[CV] c1=0.06910443190771647, c2=0.07143385779616433 ..................
[CV]  c1=0.06910443190771647, c2=0.07143385779616433, score=0.730609 -   1.4s
[CV] c1=0.739921726709296, c2=0.03777828231158368 ....................
[CV]  c1=0.739921726709296, c2=0.03777828231158368, score=0.830551 -   1.7s
[CV] c1=0.5345492476025216, c2=0.06014302469856182 ...................
[CV]  c1=0.5345492476025216, c2=0.06014302469856182, score=0.886803 -   1.8s
[CV] c1=0.6310038254591727, c2=0.0432316386822676 ....................
[CV]  c1=0.6310038254591727, c2=0.0432316386822676, score=0.726471 -   1.4s
[CV] c1=1.312157211435938, c2=0.08603498128982515 ....................
[CV]  c1=1.312157211435938, c2=0.08603498128982515, score=0.854250 -   1.7s
[CV] c1=0.10855313077450741, c2=0.010940300167171634 .................
[CV]  c1=0.10855313077450741, c2=0.010940300167171634, score=0.741722 -   1.3s
[CV] c1=0.43755961220525863, c2=0.0008143063923806029 ................
[CV]  c1=0.43755961220525863, c2=0.0008143063923806029, score=0.907722 -   1.7s
[CV] c1=0.008520992000206005, c2=0.008665153017420494 ................
[CV]  c1=0.008520992000206005, c2=0.008665153017420494, score=0.873353 -   1.7s
[CV] c1=0.2724831847060931, c2=0.0165714232258963 ....................
[CV]  c1=0.2724831847060931, c2=0.0165714232258963, score=0.905541 -   1.5s
[CV] c1=0.6494400431544749, c2=0.005281131036357565 ..................
[CV]  c1=0.6494400431544749, c2=0.005281131036357565, score=0.740287 -   1.7s
[CV] c1=0.008620246552390872, c2=0.09684287460683788 .................
[CV]  c1=0.008620246552390872, c2=0.09684287460683788, score=0.855879 -   1.5s
[CV] c1=0.08228983478481358, c2=0.24460408555795674 ..................
[CV]  c1=0.08228983478481358, c2=0.24460408555795674, score=0.785726 -   1.7s
[CV] c1=0.16182204658288055, c2=0.008834994414984188 .................
[CV]  c1=0.16182204658288055, c2=0.008834994414984188, score=0.720229 -   1.4s
[CV] c1=0.38965201765718566, c2=0.017234404134699878 .................
[CV]  c1=0.38965201765718566, c2=0.017234404134699878, score=0.918071 -   1.7s
[CV] c1=0.1723700099609017, c2=0.04556413484459568 ...................
[CV]  c1=0.1723700099609017, c2=0.04556413484459568, score=0.894816 -   1.7s
[CV] c1=0.670620398972846, c2=0.012014533652713934 ...................
[CV]  c1=0.670620398972846, c2=0.012014533652713934, score=0.731996 -   1.8s
[CV] c1=0.2167587953596191, c2=0.01150803467871346 ...................
[CV]  c1=0.2167587953596191, c2=0.01150803467871346, score=0.903042 -   1.7s
[CV] c1=0.41627368349034544, c2=0.010520754335490302 .................
[CV]  c1=0.41627368349034544, c2=0.010520754335490302, score=0.708576 -   1.3s
[CV] c1=0.08777368415518812, c2=0.0028956716693545512 ................
[CV]  c1=0.08777368415518812, c2=0.0028956716693545512, score=0.873368 -   1.7s
[CV] c1=0.24992293252674896, c2=0.11105643175773623 ..................
[CV]  c1=0.24992293252674896, c2=0.11105643175773623, score=0.719021 -   1.4s
[CV] c1=0.11617086221832837, c2=0.004762250076597188 .................
[CV]  c1=0.11617086221832837, c2=0.004762250076597188, score=0.755289 -   1.2s
[CV] c1=0.4191218035698548, c2=0.041058834026875324 ..................
[CV]  c1=0.4191218035698548, c2=0.041058834026875324, score=0.832943 -   1.8s
[CV] c1=0.027796709112803287, c2=0.015061268436096412 ................
[CV]  c1=0.027796709112803287, c2=0.015061268436096412, score=0.844110 -   1.6s
[CV] c1=0.04225349817589368, c2=0.18609191707489464 ..................
[CV]  c1=0.04225349817589368, c2=0.18609191707489464, score=0.803068 -   1.8s
[CV] c1=0.043290804951445695, c2=0.12928296711927964 .................
[CV]  c1=0.043290804951445695, c2=0.12928296711927964, score=0.820007 -   1.7s
[CV] c1=0.02703528386040871, c2=0.13708661231352223 ..................
[CV]  c1=0.02703528386040871, c2=0.13708661231352223, score=0.805501 -   1.7s
[CV] c1=0.739921726709296, c2=0.03777828231158368 ....................
[CV]  c1=0.739921726709296, c2=0.03777828231158368, score=0.703779 -   1.7s
[CV] c1=0.22833888674284988, c2=0.1344639101864193 ...................
[CV]  c1=0.22833888674284988, c2=0.1344639101864193, score=0.863073 -   1.7s
[CV] c1=1.762346873523434, c2=0.043810090956525105 ...................
[CV]  c1=1.762346873523434, c2=0.043810090956525105, score=0.606825 -   1.8s
[CV] c1=0.7178613099550617, c2=0.011307366805118445 ..................
[CV]  c1=0.7178613099550617, c2=0.011307366805118445, score=0.690777 -   1.4s
[CV] c1=0.3118712551144907, c2=0.07204748350860728 ...................
[CV]  c1=0.3118712551144907, c2=0.07204748350860728, score=0.814257 -   2.0s
[CV] c1=0.13383805032682886, c2=2.9380042983142734e-05 ...............
[CV]  c1=0.13383805032682886, c2=2.9380042983142734e-05, score=0.859492 -   1.6s
[CV] c1=0.11617086221832837, c2=0.004762250076597188 .................
[CV]  c1=0.11617086221832837, c2=0.004762250076597188, score=0.866839 -   1.3s
[CV] c1=1.4997014423095727, c2=0.014257119025691196 ..................
[CV]  c1=1.4997014423095727, c2=0.014257119025691196, score=0.639781 -   1.7s
[CV] c1=0.027796709112803287, c2=0.015061268436096412 ................
[CV]  c1=0.027796709112803287, c2=0.015061268436096412, score=0.752237 -   1.3s
[CV] c1=0.004906637093781637, c2=0.03946188551186733 .................
[CV]  c1=0.004906637093781637, c2=0.03946188551186733, score=0.822625 -   1.6s
[CV] c1=0.4076922901008913, c2=0.11516554517820005 ...................
[CV]  c1=0.4076922901008913, c2=0.11516554517820005, score=0.898740 -   1.7s
[CV] c1=0.5801437895304963, c2=0.2762766844117403 ....................
[CV]  c1=0.5801437895304963, c2=0.2762766844117403, score=0.806622 -   1.6s
[CV] c1=0.1886496288522549, c2=0.07222491603812985 ...................
[CV]  c1=0.1886496288522549, c2=0.07222491603812985, score=0.803185 -   1.7s
[CV] c1=0.15936463496541522, c2=0.32593357695530756 ..................
[CV]  c1=0.15936463496541522, c2=0.32593357695530756, score=0.749990 -   1.7s
[CV] c1=0.7644239665454672, c2=0.06978009296869059 ...................
[CV]  c1=0.7644239665454672, c2=0.06978009296869059, score=0.780421 -   1.8s
[CV] c1=1.312157211435938, c2=0.08603498128982515 ....................
[CV]  c1=1.312157211435938, c2=0.08603498128982515, score=0.640260 -   1.7s
[CV] c1=0.10855313077450741, c2=0.010940300167171634 .................
[CV]  c1=0.10855313077450741, c2=0.010940300167171634, score=0.859492 -   1.5s
[CV] c1=0.1695223869153062, c2=0.017898742713093982 ..................
[CV]  c1=0.1695223869153062, c2=0.017898742713093982, score=0.740716 -   1.4s
[CV] c1=0.036265040005861664, c2=0.043992737761965564 ................
[CV]  c1=0.036265040005861664, c2=0.043992737761965564, score=0.829890 -   1.7s
[CV] c1=0.2724831847060931, c2=0.0165714232258963 ....................
[CV]  c1=0.2724831847060931, c2=0.0165714232258963, score=0.802641 -   1.7s
[CV] c1=0.339897270537157, c2=0.024611117849723814 ...................
[CV]  c1=0.339897270537157, c2=0.024611117849723814, score=0.733055 -   1.4s
[CV] c1=0.008620246552390872, c2=0.09684287460683788 .................
[CV]  c1=0.008620246552390872, c2=0.09684287460683788, score=0.810865 -   1.7s
[CV] c1=0.5807884202105709, c2=0.006710199971858181 ..................
[CV]  c1=0.5807884202105709, c2=0.006710199971858181, score=0.728254 -   1.8s
[CV] c1=0.0892644412457624, c2=0.11984207496500779 ...................
[CV]  c1=0.0892644412457624, c2=0.11984207496500779, score=0.742850 -   1.5s
[CV] c1=0.38965201765718566, c2=0.017234404134699878 .................
[CV]  c1=0.38965201765718566, c2=0.017234404134699878, score=0.859866 -   1.6s
[CV] c1=0.1723700099609017, c2=0.04556413484459568 ...................
[CV]  c1=0.1723700099609017, c2=0.04556413484459568, score=0.838837 -   1.7s
[CV] c1=0.4505689472075339, c2=0.07754136848585219 ...................
[CV]  c1=0.4505689472075339, c2=0.07754136848585219, score=0.732272 -   1.3s
[CV] c1=1.1491048647050062, c2=0.03812775605937096 ...................
[CV]  c1=1.1491048647050062, c2=0.03812775605937096, score=0.855001 -   1.6s
[CV] c1=0.11983742170229553, c2=0.03254559873123556 ..................
[CV]  c1=0.11983742170229553, c2=0.03254559873123556, score=0.875895 -   1.7s
[CV] c1=0.08777368415518812, c2=0.0028956716693545512 ................
[CV]  c1=0.08777368415518812, c2=0.0028956716693545512, score=0.803552 -   1.7s
[CV] c1=0.24992293252674896, c2=0.11105643175773623 ..................
[CV]  c1=0.24992293252674896, c2=0.11105643175773623, score=0.820249 -   1.8s
[CV] c1=0.008416599449333097, c2=0.03385932964226816 .................
[CV]  c1=0.008416599449333097, c2=0.03385932964226816, score=0.751791 -   1.1s
[CV] c1=1.0120756670644797, c2=0.08941812678670334 ...................
[CV]  c1=1.0120756670644797, c2=0.08941812678670334, score=0.789357 -   1.5s
[CV] c1=0.339897270537157, c2=0.024611117849723814 ...................
[CV]  c1=0.339897270537157, c2=0.024611117849723814, score=0.907379 -   1.7s
[CV] c1=0.2743058923797177, c2=0.08606005044606713 ...................
[CV]  c1=0.2743058923797177, c2=0.08606005044606713, score=0.835115 -   1.7s
[CV] c1=0.32816656152027385, c2=0.001567052815515329 .................
[CV]  c1=0.32816656152027385, c2=0.001567052815515329, score=0.830181 -   1.6s
[CV] c1=0.5801437895304963, c2=0.2762766844117403 ....................
[CV]  c1=0.5801437895304963, c2=0.2762766844117403, score=0.863299 -   1.6s
[CV] c1=0.1886496288522549, c2=0.07222491603812985 ...................
[CV]  c1=0.1886496288522549, c2=0.07222491603812985, score=0.719931 -   1.3s
[CV] c1=0.1606118237959953, c2=0.07632153902589378 ...................
[CV]  c1=0.1606118237959953, c2=0.07632153902589378, score=0.863073 -   1.6s
[CV] c1=0.01679229145190292, c2=0.038693982988578846 .................
[CV]  c1=0.01679229145190292, c2=0.038693982988578846, score=0.817105 -   1.7s
[CV] c1=0.19376951381571378, c2=0.028733720232256274 .................
[CV]  c1=0.19376951381571378, c2=0.028733720232256274, score=0.861556 -   1.5s
[CV] c1=0.43615330471298264, c2=0.019949515526172468 .................
[CV]  c1=0.43615330471298264, c2=0.019949515526172468, score=0.727404 -   1.3s
[CV] c1=0.09034176113387098, c2=0.08180840630438983 ..................
[CV]  c1=0.09034176113387098, c2=0.08180840630438983, score=0.877352 -   1.7s
[CV] c1=0.16618626252817145, c2=0.1576570227041733 ...................
[CV]  c1=0.16618626252817145, c2=0.1576570227041733, score=0.728560 -   1.4s
[CV] c1=1.1648856407033545, c2=0.0173811747742124 ....................
[CV]  c1=1.1648856407033545, c2=0.0173811747742124, score=0.868316 -   1.3s
[CV] c1=0.2724831847060931, c2=0.0165714232258963 ....................
[CV]  c1=0.2724831847060931, c2=0.0165714232258963, score=0.713569 -   1.4s
[CV] c1=0.40609618174622186, c2=0.034051517470961815 .................
[CV]  c1=0.40609618174622186, c2=0.034051517470961815, score=0.862013 -   1.9s
[CV] c1=0.2743058923797177, c2=0.08606005044606713 ...................
[CV]  c1=0.2743058923797177, c2=0.08606005044606713, score=0.888577 -   1.7s
[CV] c1=0.7441623655509021, c2=0.011333927957483298 ..................
[CV]  c1=0.7441623655509021, c2=0.011333927957483298, score=0.723388 -   1.4s
[CV] c1=0.26743103044967736, c2=0.00894230058234566 ..................
[CV]  c1=0.26743103044967736, c2=0.00894230058234566, score=0.861556 -   1.8s
[CV] c1=0.05715273529864092, c2=0.01108697182817814 ..................
[CV]  c1=0.05715273529864092, c2=0.01108697182817814, score=0.883564 -   1.7s
[CV] c1=0.5481914056911523, c2=0.0038665614015526277 .................
[CV]  c1=0.5481914056911523, c2=0.0038665614015526277, score=0.833965 -   1.6s
[CV] c1=0.4505689472075339, c2=0.07754136848585219 ...................
[CV]  c1=0.4505689472075339, c2=0.07754136848585219, score=0.741647 -   2.0s
[CV] c1=1.463375496714161, c2=0.006639270393834511 ...................
[CV]  c1=1.463375496714161, c2=0.006639270393834511, score=0.600097 -   1.4s
[CV] c1=0.41627368349034544, c2=0.010520754335490302 .................
[CV]  c1=0.41627368349034544, c2=0.010520754335490302, score=0.816074 -   1.7s
[CV] c1=0.6083910708710164, c2=0.05612149139600581 ...................
[CV]  c1=0.6083910708710164, c2=0.05612149139600581, score=0.698972 -   1.3s
[CV] c1=0.16618626252817145, c2=0.1576570227041733 ...................
[CV]  c1=0.16618626252817145, c2=0.1576570227041733, score=0.787752 -   1.7s
[CV] c1=0.008416599449333097, c2=0.03385932964226816 .................
[CV]  c1=0.008416599449333097, c2=0.03385932964226816, score=0.867224 -   1.0s
[CV] c1=0.2955907603120557, c2=0.10001501201171051 ...................
[CV]  c1=0.2955907603120557, c2=0.10001501201171051, score=0.871305 -   1.6s
[CV] c1=0.4531000401615301, c2=0.028601225889616638 ..................
[CV]  c1=0.4531000401615301, c2=0.028601225889616638, score=0.897484 -   1.7s
[CV] c1=0.2743058923797177, c2=0.08606005044606713 ...................
[CV]  c1=0.2743058923797177, c2=0.08606005044606713, score=0.787173 -   1.7s
[CV] c1=0.7441623655509021, c2=0.011333927957483298 ..................
[CV]  c1=0.7441623655509021, c2=0.011333927957483298, score=0.800825 -   1.7s
[CV] c1=0.0892644412457624, c2=0.11984207496500779 ...................
[CV]  c1=0.0892644412457624, c2=0.11984207496500779, score=0.858778 -   1.7s
[CV] c1=1.0091331005467783, c2=0.05727581292164206 ...................
[CV]  c1=1.0091331005467783, c2=0.05727581292164206, score=0.791176 -   1.5s
[CV] c1=0.1606118237959953, c2=0.07632153902589378 ...................
[CV]  c1=0.1606118237959953, c2=0.07632153902589378, score=0.708986 -   1.6s
[CV] c1=0.01679229145190292, c2=0.038693982988578846 .................
[CV]  c1=0.01679229145190292, c2=0.038693982988578846, score=0.746126 -   1.4s
[CV] c1=1.1491048647050062, c2=0.03812775605937096 ...................
[CV]  c1=1.1491048647050062, c2=0.03812775605937096, score=0.607040 -   1.7s
[CV] c1=0.41627368349034544, c2=0.010520754335490302 .................
[CV]  c1=0.41627368349034544, c2=0.010520754335490302, score=0.774382 -   1.7s
[CV] c1=0.09034176113387098, c2=0.08180840630438983 ..................
[CV]  c1=0.09034176113387098, c2=0.08180840630438983, score=0.792486 -   1.7s
[CV] c1=0.10157560677546373, c2=0.016899164498576712 .................
[CV]  c1=0.10157560677546373, c2=0.016899164498576712, score=0.738575 -   1.4s
[CV] c1=0.008416599449333097, c2=0.03385932964226816 .................
[CV]  c1=0.008416599449333097, c2=0.03385932964226816, score=0.875197 -   1.2s
[CV] c1=0.10248380213326022, c2=0.005015198092486652 .................
[CV]  c1=0.10248380213326022, c2=0.005015198092486652, score=0.866839 -   1.5s
[CV] c1=1.0311328605766514, c2=0.015093608504736032 ..................
[CV]  c1=1.0311328605766514, c2=0.015093608504736032, score=0.636098 -   1.4s
[CV] c1=0.13835110827134814, c2=0.03156661041664845 ..................
[CV]  c1=0.13835110827134814, c2=0.03156661041664845, score=0.743292 -   1.4s
[CV] c1=0.2589703923527472, c2=0.06512326602475861 ...................
[CV]  c1=0.2589703923527472, c2=0.06512326602475861, score=0.843587 -   2.0s
[CV] c1=1.306063230715063, c2=0.06086498234798973 ....................
[CV]  c1=1.306063230715063, c2=0.06086498234798973, score=0.863714 -   1.7s
[CV] c1=0.02703528386040871, c2=0.13708661231352223 ..................
[CV]  c1=0.02703528386040871, c2=0.13708661231352223, score=0.857790 -   1.7s
[CV] c1=0.739921726709296, c2=0.03777828231158368 ....................
[CV]  c1=0.739921726709296, c2=0.03777828231158368, score=0.818175 -   1.7s
[CV] c1=0.22833888674284988, c2=0.1344639101864193 ...................
[CV]  c1=0.22833888674284988, c2=0.1344639101864193, score=0.797593 -   1.8s
[CV] c1=0.6310038254591727, c2=0.0432316386822676 ....................
[CV]  c1=0.6310038254591727, c2=0.0432316386822676, score=0.881275 -   1.7s
[CV] c1=0.7178613099550617, c2=0.011307366805118445 ..................
[CV]  c1=0.7178613099550617, c2=0.011307366805118445, score=0.724845 -   1.7s
[CV] c1=0.3754253365265449, c2=0.07095169982427979 ...................
[CV]  c1=0.3754253365265449, c2=0.07095169982427979, score=0.868501 -   1.7s
[CV] c1=0.13383805032682886, c2=2.9380042983142734e-05 ...............
[CV]  c1=0.13383805032682886, c2=2.9380042983142734e-05, score=0.833711 -   1.8s
[CV] c1=1.1648856407033545, c2=0.0173811747742124 ....................
[CV]  c1=1.1648856407033545, c2=0.0173811747742124, score=0.805736 -   1.3s
[CV] c1=0.4191218035698548, c2=0.041058834026875324 ..................
[CV]  c1=0.4191218035698548, c2=0.041058834026875324, score=0.839633 -   1.7s
[CV] c1=0.6284895157294884, c2=0.0048431022606003704 .................
[CV]  c1=0.6284895157294884, c2=0.0048431022606003704, score=0.808955 -   1.7s
[CV] c1=0.04225349817589368, c2=0.18609191707489464 ..................
[CV]  c1=0.04225349817589368, c2=0.18609191707489464, score=0.882653 -   1.6s
[CV] c1=0.043290804951445695, c2=0.12928296711927964 .................
[CV]  c1=0.043290804951445695, c2=0.12928296711927964, score=0.887858 -   1.6s
[CV] c1=0.8336301114371835, c2=0.04363901842393647 ...................
[CV]  c1=0.8336301114371835, c2=0.04363901842393647, score=0.862141 -   1.7s
[CV] c1=0.14270813853934722, c2=0.01224030918183421 ..................
[CV]  c1=0.14270813853934722, c2=0.01224030918183421, score=0.863073 -   1.6s
[CV] c1=0.15936463496541522, c2=0.32593357695530756 ..................
[CV]  c1=0.15936463496541522, c2=0.32593357695530756, score=0.857864 -   1.6s
[CV] c1=0.7644239665454672, c2=0.06978009296869059 ...................
[CV]  c1=0.7644239665454672, c2=0.06978009296869059, score=0.818504 -   1.6s
[CV] c1=1.5995902072380093, c2=0.08767954933309148 ...................
[CV]  c1=1.5995902072380093, c2=0.08767954933309148, score=0.636401 -   1.9s
[CV] c1=0.10855313077450741, c2=0.010940300167171634 .................
[CV]  c1=0.10855313077450741, c2=0.010940300167171634, score=0.809733 -   1.8s
[CV] c1=0.13383805032682886, c2=2.9380042983142734e-05 ...............
[CV]  c1=0.13383805032682886, c2=2.9380042983142734e-05, score=0.733103 -   1.3s
[CV] c1=0.008520992000206005, c2=0.008665153017420494 ................
[CV]  c1=0.008520992000206005, c2=0.008665153017420494, score=0.798843 -   1.5s
[CV] c1=1.0120756670644797, c2=0.08941812678670334 ...................
[CV]  c1=1.0120756670644797, c2=0.08941812678670334, score=0.653894 -   1.7s
[CV] c1=0.339897270537157, c2=0.024611117849723814 ...................
[CV]  c1=0.339897270537157, c2=0.024611117849723814, score=0.824189 -   1.8s
[CV] c1=0.2589703923527472, c2=0.06512326602475861 ...................
[CV]  c1=0.2589703923527472, c2=0.06512326602475861, score=0.723429 -   1.4s
[CV] c1=0.32816656152027385, c2=0.001567052815515329 .................
[CV]  c1=0.32816656152027385, c2=0.001567052815515329, score=0.725833 -   1.4s
[CV] c1=0.16182204658288055, c2=0.008834994414984188 .................
[CV]  c1=0.16182204658288055, c2=0.008834994414984188, score=0.857866 -   1.7s
[CV] c1=1.0091331005467783, c2=0.05727581292164206 ...................
[CV]  c1=1.0091331005467783, c2=0.05727581292164206, score=0.637024 -   1.3s
[CV] c1=0.5481914056911523, c2=0.0038665614015526277 .................
[CV]  c1=0.5481914056911523, c2=0.0038665614015526277, score=0.899649 -   1.6s
[CV] c1=0.670620398972846, c2=0.012014533652713934 ...................
[CV]  c1=0.670620398972846, c2=0.012014533652713934, score=0.820793 -   1.6s
[CV] c1=1.1491048647050062, c2=0.03812775605937096 ...................
[CV]  c1=1.1491048647050062, c2=0.03812775605937096, score=0.648491 -   1.2s
[CV] c1=1.312157211435938, c2=0.08603498128982515 ....................
[CV]  c1=1.312157211435938, c2=0.08603498128982515, score=0.577605 -   1.6s
[CV] c1=0.3754253365265449, c2=0.07095169982427979 ...................
[CV]  c1=0.3754253365265449, c2=0.07095169982427979, score=0.895412 -   1.7s
[CV] c1=0.13383805032682886, c2=2.9380042983142734e-05 ...............
[CV]  c1=0.13383805032682886, c2=2.9380042983142734e-05, score=0.901706 -   1.7s
[CV] c1=0.11617086221832837, c2=0.004762250076597188 .................
[CV]  c1=0.11617086221832837, c2=0.004762250076597188, score=0.796608 -   1.4s
[CV] c1=0.10113340120103063, c2=0.0033520616552264585 ................
[CV]  c1=0.10113340120103063, c2=0.0033520616552264585, score=0.864634 -   1.6s
[CV] c1=0.40609618174622186, c2=0.034051517470961815 .................
[CV]  c1=0.40609618174622186, c2=0.034051517470961815, score=0.906469 -   1.7s
[CV] c1=0.5040427227012549, c2=0.02839758694823832 ...................
[CV]  c1=0.5040427227012549, c2=0.02839758694823832, score=0.720785 -   1.4s
[CV] c1=1.2841823134942698, c2=0.10948724760625086 ...................
[CV]  c1=1.2841823134942698, c2=0.10948724760625086, score=0.586656 -   1.9s
[CV] c1=0.26743103044967736, c2=0.00894230058234566 ..................
[CV]  c1=0.26743103044967736, c2=0.00894230058234566, score=0.900337 -   1.7s
[CV] c1=0.38965201765718566, c2=0.017234404134699878 .................
[CV]  c1=0.38965201765718566, c2=0.017234404134699878, score=0.729296 -   1.4s
[CV] c1=0.6933879415138604, c2=0.0018363764423556324 .................
[CV]  c1=0.6933879415138604, c2=0.0018363764423556324, score=0.725255 -   1.4s
[CV] c1=0.22833888674284988, c2=0.1344639101864193 ...................
[CV]  c1=0.22833888674284988, c2=0.1344639101864193, score=0.789008 -   1.6s
[CV] c1=1.762346873523434, c2=0.043810090956525105 ...................
[CV]  c1=1.762346873523434, c2=0.043810090956525105, score=0.573723 -   1.4s
[CV] c1=1.5995902072380093, c2=0.08767954933309148 ...................
[CV]  c1=1.5995902072380093, c2=0.08767954933309148, score=0.833332 -   1.6s
[CV] c1=0.03279806251385013, c2=0.04305168157522314 ..................
[CV]  c1=0.03279806251385013, c2=0.04305168157522314, score=0.824164 -   1.8s
[CV] c1=0.43755961220525863, c2=0.0008143063923806029 ................
[CV]  c1=0.43755961220525863, c2=0.0008143063923806029, score=0.826996 -   1.8s
[CV] c1=0.07829034045149781, c2=0.0623605001195555 ...................
[CV]  c1=0.07829034045149781, c2=0.0623605001195555, score=0.858778 -   1.5s
[CV] c1=1.0120756670644797, c2=0.08941812678670334 ...................
[CV]  c1=1.0120756670644797, c2=0.08941812678670334, score=0.636557 -   1.8s
[CV] c1=0.6284895157294884, c2=0.0048431022606003704 .................
[CV]  c1=0.6284895157294884, c2=0.0048431022606003704, score=0.736481 -   1.8s
[CV] c1=0.04225349817589368, c2=0.18609191707489464 ..................
[CV]  c1=0.04225349817589368, c2=0.18609191707489464, score=0.857790 -   1.5s
[CV] c1=0.043290804951445695, c2=0.12928296711927964 .................
[CV]  c1=0.043290804951445695, c2=0.12928296711927964, score=0.821375 -   1.7s
[CV] c1=0.8336301114371835, c2=0.04363901842393647 ...................
[CV]  c1=0.8336301114371835, c2=0.04363901842393647, score=0.804527 -   1.6s
[CV] c1=0.14270813853934722, c2=0.01224030918183421 ..................
[CV]  c1=0.14270813853934722, c2=0.01224030918183421, score=0.848164 -   1.7s
[CV] c1=0.22833888674284988, c2=0.1344639101864193 ...................
[CV]  c1=0.22833888674284988, c2=0.1344639101864193, score=0.888577 -   1.8s
[CV] c1=1.762346873523434, c2=0.043810090956525105 ...................
[CV]  c1=1.762346873523434, c2=0.043810090956525105, score=0.564822 -   1.7s
[CV] c1=0.7178613099550617, c2=0.011307366805118445 ..................
[CV]  c1=0.7178613099550617, c2=0.011307366805118445, score=0.893177 -   1.7s
[CV] c1=0.3754253365265449, c2=0.07095169982427979 ...................
[CV]  c1=0.3754253365265449, c2=0.07095169982427979, score=0.726201 -   1.4s
[CV] c1=0.43755961220525863, c2=0.0008143063923806029 ................
[CV]  c1=0.43755961220525863, c2=0.0008143063923806029, score=0.843373 -   1.6s
[CV] c1=0.008520992000206005, c2=0.008665153017420494 ................
[CV]  c1=0.008520992000206005, c2=0.008665153017420494, score=0.866658 -   1.6s
[CV] c1=0.752259809938945, c2=0.13632801024729252 ....................
[CV]  c1=0.752259809938945, c2=0.13632801024729252, score=0.794414 -   1.4s
[CV] c1=0.40609618174622186, c2=0.034051517470961815 .................
[CV]  c1=0.40609618174622186, c2=0.034051517470961815, score=0.726201 -   1.6s
[CV] c1=2.8542404736651434, c2=0.04205523377805767 ...................
[CV]  c1=2.8542404736651434, c2=0.04205523377805767, score=0.512050 -   1.8s
[CV] c1=0.08228983478481358, c2=0.24460408555795674 ..................
[CV]  c1=0.08228983478481358, c2=0.24460408555795674, score=0.790141 -   1.7s
[CV] c1=0.26743103044967736, c2=0.00894230058234566 ..................
[CV]  c1=0.26743103044967736, c2=0.00894230058234566, score=0.849972 -   1.8s
[CV] c1=0.38965201765718566, c2=0.017234404134699878 .................
[CV]  c1=0.38965201765718566, c2=0.017234404134699878, score=0.836527 -   1.6s
[CV] c1=0.5481914056911523, c2=0.0038665614015526277 .................
[CV]  c1=0.5481914056911523, c2=0.0038665614015526277, score=0.718657 -   1.4s
[CV] c1=0.5345492476025216, c2=0.06014302469856182 ...................
[CV]  c1=0.5345492476025216, c2=0.06014302469856182, score=0.797100 -   1.9s
[CV] c1=1.1491048647050062, c2=0.03812775605937096 ...................
[CV]  c1=1.1491048647050062, c2=0.03812775605937096, score=0.785482 -   1.5s
[CV] c1=0.11983742170229553, c2=0.03254559873123556 ..................
[CV]  c1=0.11983742170229553, c2=0.03254559873123556, score=0.806318 -   1.8s
[CV] c1=0.09034176113387098, c2=0.08180840630438983 ..................
[CV]  c1=0.09034176113387098, c2=0.08180840630438983, score=0.715930 -   1.3s
[CV] c1=0.13383805032682886, c2=2.9380042983142734e-05 ...............
[CV]  c1=0.13383805032682886, c2=2.9380042983142734e-05, score=0.802641 -   1.7s
[CV] c1=0.11617086221832837, c2=0.004762250076597188 .................
[CV]  c1=0.11617086221832837, c2=0.004762250076597188, score=0.869660 -   1.4s
[CV] c1=0.752259809938945, c2=0.13632801024729252 ....................
[CV]  c1=0.752259809938945, c2=0.13632801024729252, score=0.653996 -   1.2s
[CV] c1=0.4744593260771863, c2=0.035208670242626625 ..................
[CV]  c1=0.4744593260771863, c2=0.035208670242626625, score=0.824804 -   1.8s
[CV] c1=2.8542404736651434, c2=0.04205523377805767 ...................
[CV]  c1=2.8542404736651434, c2=0.04205523377805767, score=0.512989 -   1.3s
[CV] c1=0.04225349817589368, c2=0.18609191707489464 ..................
[CV]  c1=0.04225349817589368, c2=0.18609191707489464, score=0.795962 -   1.8s
[CV] c1=1.306063230715063, c2=0.06086498234798973 ....................
[CV]  c1=1.306063230715063, c2=0.06086498234798973, score=0.597981 -   1.4s
[CV] c1=0.8336301114371835, c2=0.04363901842393647 ...................
[CV]  c1=0.8336301114371835, c2=0.04363901842393647, score=0.699482 -   1.6s
[CV] c1=0.14270813853934722, c2=0.01224030918183421 ..................
[CV]  c1=0.14270813853934722, c2=0.01224030918183421, score=0.759427 -   1.4s
[CV] c1=0.0018895288405304694, c2=0.05558743836264954 ................
[CV]  c1=0.0018895288405304694, c2=0.05558743836264954, score=0.780183 -   1.8s
[CV] c1=0.1803245279864374, c2=0.03168975613151679 ...................
[CV]  c1=0.1803245279864374, c2=0.03168975613151679, score=0.796382 -   1.8s
[CV] c1=1.5995902072380093, c2=0.08767954933309148 ...................
[CV]  c1=1.5995902072380093, c2=0.08767954933309148, score=0.571026 -   1.4s
[CV] c1=0.13529584802616074, c2=0.06770891962757322 ..................
[CV]  c1=0.13529584802616074, c2=0.06770891962757322, score=0.806769 -   1.7s
[CV] c1=0.20755417109335084, c2=0.036795301788140646 .................
[CV]  c1=0.20755417109335084, c2=0.036795301788140646, score=0.798771 -   1.7s
[CV] c1=0.036265040005861664, c2=0.043992737761965564 ................
[CV]  c1=0.036265040005861664, c2=0.043992737761965564, score=0.866301 -   1.6s
[CV] c1=0.2724831847060931, c2=0.0165714232258963 ....................
[CV]  c1=0.2724831847060931, c2=0.0165714232258963, score=0.861556 -   1.6s
[CV] c1=0.4531000401615301, c2=0.028601225889616638 ..................
[CV]  c1=0.4531000401615301, c2=0.028601225889616638, score=0.747581 -   1.7s
[CV] c1=0.2743058923797177, c2=0.08606005044606713 ...................
[CV]  c1=0.2743058923797177, c2=0.08606005044606713, score=0.868501 -   1.7s
[CV] c1=0.7441623655509021, c2=0.011333927957483298 ..................
[CV]  c1=0.7441623655509021, c2=0.011333927957483298, score=0.830551 -   1.9s
[CV] c1=0.5801437895304963, c2=0.2762766844117403 ....................
[CV]  c1=0.5801437895304963, c2=0.2762766844117403, score=0.655027 -   1.3s
[CV] c1=0.05715273529864092, c2=0.01108697182817814 ..................
[CV]  c1=0.05715273529864092, c2=0.01108697182817814, score=0.801781 -   1.6s
[CV] c1=0.5481914056911523, c2=0.0038665614015526277 .................
[CV]  c1=0.5481914056911523, c2=0.0038665614015526277, score=0.750973 -   1.9s
[CV] c1=0.01679229145190292, c2=0.038693982988578846 .................
[CV]  c1=0.01679229145190292, c2=0.038693982988578846, score=0.856802 -   1.6s
[CV] c1=0.19376951381571378, c2=0.028733720232256274 .................
[CV]  c1=0.19376951381571378, c2=0.028733720232256274, score=0.725119 -   1.1s
[CV] c1=0.11983742170229553, c2=0.03254559873123556 ..................
[CV]  c1=0.11983742170229553, c2=0.03254559873123556, score=0.801362 -   1.7s
[CV] c1=0.08777368415518812, c2=0.0028956716693545512 ................
[CV]  c1=0.08777368415518812, c2=0.0028956716693545512, score=0.819680 -   1.7s
[CV] c1=0.16618626252817145, c2=0.1576570227041733 ...................
[CV]  c1=0.16618626252817145, c2=0.1576570227041733, score=0.877281 -   1.7s
[CV] c1=1.1648856407033545, c2=0.0173811747742124 ....................
[CV]  c1=1.1648856407033545, c2=0.0173811747742124, score=0.655597 -   1.3s
[CV] c1=0.752259809938945, c2=0.13632801024729252 ....................
[CV]  c1=0.752259809938945, c2=0.13632801024729252, score=0.698558 -   1.6s
[CV] c1=0.40609618174622186, c2=0.034051517470961815 .................
[CV]  c1=0.40609618174622186, c2=0.034051517470961815, score=0.808623 -   1.8s
[CV] c1=0.008620246552390872, c2=0.09684287460683788 .................
[CV]  c1=0.008620246552390872, c2=0.09684287460683788, score=0.768327 -   1.4s
[CV] c1=0.08228983478481358, c2=0.24460408555795674 ..................
[CV]  c1=0.08228983478481358, c2=0.24460408555795674, score=0.770358 -   1.4s
[CV] c1=1.4416209867259464, c2=0.022112165647977 .....................
[CV]  c1=1.4416209867259464, c2=0.022112165647977, score=0.865187 -   1.9s
[CV] c1=0.06910443190771647, c2=0.07143385779616433 ..................
[CV]  c1=0.06910443190771647, c2=0.07143385779616433, score=0.858778 -   1.6s
[CV] c1=0.6933879415138604, c2=0.0018363764423556324 .................
[CV]  c1=0.6933879415138604, c2=0.0018363764423556324, score=0.792138 -   1.6s
[CV] c1=0.5345492476025216, c2=0.06014302469856182 ...................
[CV]  c1=0.5345492476025216, c2=0.06014302469856182, score=0.816724 -   1.6s
[CV] c1=0.6310038254591727, c2=0.0432316386822676 ....................
[CV]  c1=0.6310038254591727, c2=0.0432316386822676, score=0.722920 -   1.7s
[CV] c1=0.7178613099550617, c2=0.011307366805118445 ..................
[CV]  c1=0.7178613099550617, c2=0.011307366805118445, score=0.813942 -   1.7s
[CV] c1=0.3754253365265449, c2=0.07095169982427979 ...................
[CV]  c1=0.3754253365265449, c2=0.07095169982427979, score=0.824189 -   1.8s
[CV] c1=0.24992293252674896, c2=0.11105643175773623 ..................
[CV]  c1=0.24992293252674896, c2=0.11105643175773623, score=0.868501 -   1.8s
[CV] c1=0.008416599449333097, c2=0.03385932964226816 .................
[CV]  c1=0.008416599449333097, c2=0.03385932964226816, score=0.811092 -   1.2s
[CV] c1=0.10113340120103063, c2=0.0033520616552264585 ................
[CV]  c1=0.10113340120103063, c2=0.0033520616552264585, score=0.905292 -   1.4s
[CV] c1=1.0311328605766514, c2=0.015093608504736032 ..................
[CV]  c1=1.0311328605766514, c2=0.015093608504736032, score=0.655298 -   1.9s
[CV] c1=0.5040427227012549, c2=0.02839758694823832 ...................
[CV]  c1=0.5040427227012549, c2=0.02839758694823832, score=0.734434 -   1.9s
[CV] c1=0.5807884202105709, c2=0.006710199971858181 ..................
[CV]  c1=0.5807884202105709, c2=0.006710199971858181, score=0.720785 -   1.4s
[CV] c1=0.26743103044967736, c2=0.00894230058234566 ..................
[CV]  c1=0.26743103044967736, c2=0.00894230058234566, score=0.714814 -   1.5s
[CV] c1=0.06910443190771647, c2=0.07143385779616433 ..................
[CV]  c1=0.06910443190771647, c2=0.07143385779616433, score=0.888524 -   1.7s
[CV] c1=0.6933879415138604, c2=0.0018363764423556324 .................
[CV]  c1=0.6933879415138604, c2=0.0018363764423556324, score=0.724792 -   1.8s
[CV] c1=0.670620398972846, c2=0.012014533652713934 ...................
[CV]  c1=0.670620398972846, c2=0.012014533652713934, score=0.722737 -   1.5s
[CV] c1=0.6310038254591727, c2=0.0432316386822676 ....................
[CV]  c1=0.6310038254591727, c2=0.0432316386822676, score=0.803586 -   1.7s
[CV] c1=0.7178613099550617, c2=0.011307366805118445 ..................
[CV]  c1=0.7178613099550617, c2=0.011307366805118445, score=0.833464 -   1.7s
[CV] c1=0.08777368415518812, c2=0.0028956716693545512 ................
[CV]  c1=0.08777368415518812, c2=0.0028956716693545512, score=0.865384 -   1.7s
[CV] c1=0.24992293252674896, c2=0.11105643175773623 ..................
[CV]  c1=0.24992293252674896, c2=0.11105643175773623, score=0.785161 -   1.7s
[CV] c1=1.1648856407033545, c2=0.0173811747742124 ....................
[CV]  c1=1.1648856407033545, c2=0.0173811747742124, score=0.656178 -   1.4s
Training done in: 23.872422s
     Saving training model...
        Saving training model done in: 0.012978s
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Prediction done in: 0.039713s