Run4_v1.txt
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-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70_v4.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30_v4.txt
Exclude stop words: False
Levels: True True
Report file: _v9
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 283
Sentences test data: 122
Reading corpus done in: 0.003836s
{'lemma': 'δsoxs', 'postag': 'NN', '+1:lemma': 'pq', '+1:postag': 'NN'}
{'lemma': 'affyexp', 'postag': 'JJ', '+1:lemma': '_', '+1:postag': 'NN'}
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.567237 - 0.9s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.852821 - 1.1s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.654823 - 1.0s
[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.921915 - 1.2s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.899703 - 1.2s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.920970 - 1.4s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.720311 - 1.3s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.675506 - 1.3s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.570419 - 1.0s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.723593 - 0.8s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.710539 - 1.2s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.867500 - 1.1s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.701323 - 1.2s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.858883 - 1.2s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.848230 - 0.7s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.753693 - 1.2s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.766835 - 1.0s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.624832 - 1.2s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.679766 - 1.3s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.802426 - 0.9s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.919762 - 1.1s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.887557 - 1.1s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.640353 - 1.1s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.848001 - 1.2s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.774739 - 0.9s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.656490 - 1.1s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
[CV] c1=0.10252491344185391, c2=0.035456409715521185, score=0.920970 - 1.2s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.691890 - 1.3s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.864316 - 1.2s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.717157 - 0.8s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.761818 - 1.1s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.848001 - 1.2s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.853988 - 1.2s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.920970 - 1.2s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.763058 - 0.9s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
[CV] c1=0.037804502799856664, c2=0.17775310605580735, score=0.643807 - 1.2s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
[CV] c1=0.48021458727568206, c2=0.024520344430852173, score=0.715300 - 1.1s
[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.632407 - 1.0s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.867500 - 1.1s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.852821 - 1.1s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.556973 - 1.0s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.731639 - 1.3s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.557241 - 1.0s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.737308 - 1.3s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.935386 - 1.1s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.852821 - 1.1s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.753693 - 1.1s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.606581 - 1.0s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.887557 - 1.0s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.753693 - 1.2s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
[CV] c1=0.037804502799856664, c2=0.17775310605580735, score=0.848001 - 1.2s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
[CV] c1=0.48021458727568206, c2=0.024520344430852173, score=0.761418 - 1.0s
[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.637423 - 1.0s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.899703 - 1.2s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.834063 - 1.2s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.727061 - 1.1s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
[CV] c1=0.48021458727568206, c2=0.024520344430852173, score=0.899703 - 1.2s
[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.688946 - 1.1s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.775757 - 1.1s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.699610 - 1.4s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
[CV] c1=0.10252491344185391, c2=0.035456409715521185, score=0.720311 - 1.2s
[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.674776 - 1.2s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.679766 - 1.0s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.548511 - 0.8s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.641007 - 1.0s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
[CV] c1=0.10252491344185391, c2=0.035456409715521185, score=0.682397 - 1.0s
[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.721334 - 1.0s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.586573 - 1.1s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.687750 - 0.9s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.899703 - 1.1s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
[CV] c1=0.037804502799856664, c2=0.17775310605580735, score=0.826869 - 1.2s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
[CV] c1=0.48021458727568206, c2=0.024520344430852173, score=0.660012 - 1.1s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.870586 - 1.2s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.654823 - 1.2s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.569039 - 0.7s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.807016 - 1.3s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.906853 - 1.2s
[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.678288 - 1.3s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.766835 - 1.2s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.674776 - 1.0s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.782641 - 1.0s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.656490 - 1.1s
[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.686713 - 1.1s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.896193 - 1.2s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.715320 - 1.4s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.860729 - 1.3s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.573749 - 1.1s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.698982 - 1.1s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.905489 - 0.9s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.599785 - 0.8s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
[CV] c1=0.037804502799856664, c2=0.17775310605580735, score=0.654823 - 1.0s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.875991 - 1.2s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.815463 - 1.0s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.710539 - 1.1s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.553828 - 0.5s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.625815 - 1.1s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
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[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
[CV] c1=0.48021458727568206, c2=0.024520344430852173, score=0.920970 - 1.2s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.659056 - 1.2s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.659253 - 1.1s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.705332 - 1.1s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
[CV] c1=0.037804502799856664, c2=0.17775310605580735, score=0.606859 - 1.0s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
[CV] c1=0.48021458727568206, c2=0.024520344430852173, score=0.793956 - 1.2s
[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.787287 - 1.3s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.906853 - 1.1s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.703150 - 1.1s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.761418 - 1.2s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.905489 - 1.2s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.605840 - 1.1s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
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[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
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[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.660012 - 1.1s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
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[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
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[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.607039 - 1.1s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.919762 - 1.2s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
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[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.761818 - 1.3s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.843581 - 1.2s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.624832 - 0.8s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.664849 - 1.1s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
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[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
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[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.540524 - 0.9s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.724290 - 1.2s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.866790 - 1.2s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.899703 - 1.1s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.883954 - 1.2s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.526041 - 1.0s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.883954 - 1.2s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.761597 - 1.4s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
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[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.577889 - 0.9s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.721334 - 1.4s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.815463 - 0.9s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.661281 - 1.4s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
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[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.906853 - 1.2s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.580556 - 1.0s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.794740 - 1.0s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.928170 - 1.4s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
[CV] c1=0.10252491344185391, c2=0.035456409715521185, score=0.929766 - 1.1s
[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.938387 - 1.2s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.879383 - 1.1s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.670787 - 1.1s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.906853 - 1.3s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
[CV] c1=0.10252491344185391, c2=0.035456409715521185, score=0.603251 - 0.9s
[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.848001 - 1.3s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.740663 - 1.2s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.878327 - 0.9s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.740663 - 1.0s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
[CV] c1=0.037804502799856664, c2=0.17775310605580735, score=0.875991 - 1.2s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.716266 - 1.3s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.578869 - 1.1s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.753693 - 1.1s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.674776 - 0.8s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.729308 - 1.2s
[CV] c1=0.035487685725177805, c2=0.07066796438693485 .................
[CV] c1=0.035487685725177805, c2=0.07066796438693485, score=0.607039 - 0.9s
[CV] c1=0.7754820747377101, c2=0.12099050393613156 ...................
[CV] c1=0.7754820747377101, c2=0.12099050393613156, score=0.787287 - 1.3s
[CV] c1=0.38805051498984994, c2=0.01477620810001598 ..................
[CV] c1=0.38805051498984994, c2=0.01477620810001598, score=0.782641 - 1.4s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.720311 - 1.2s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.919762 - 1.1s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.729308 - 1.2s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.788630 - 1.1s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.852821 - 1.1s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.906853 - 1.2s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.547996 - 1.0s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.855614 - 1.2s
[CV] c1=1.2077186464874288, c2=0.11106721030811739 ...................
[CV] c1=1.2077186464874288, c2=0.11106721030811739, score=0.722890 - 1.1s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.728584 - 1.1s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.812131 - 1.1s
[CV] c1=0.5672718732034153, c2=0.02408083022682672 ...................
[CV] c1=0.5672718732034153, c2=0.02408083022682672, score=0.899703 - 1.3s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
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[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.852672 - 1.2s
[CV] c1=0.725079276744011, c2=0.0025324013059438034 ..................
[CV] c1=0.725079276744011, c2=0.0025324013059438034, score=0.843338 - 1.2s
[CV] c1=0.15761238349200285, c2=0.002525593517619589 .................
[CV] c1=0.15761238349200285, c2=0.002525593517619589, score=0.867217 - 1.5s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
[CV] c1=0.10252491344185391, c2=0.035456409715521185, score=0.866790 - 1.1s
[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.741434 - 1.3s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.920970 - 1.1s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.728987 - 0.9s
[CV] c1=0.08401658210095098, c2=0.01884625069711085 ..................
[CV] c1=0.08401658210095098, c2=0.01884625069711085, score=0.920970 - 1.5s
[CV] c1=0.10252491344185391, c2=0.035456409715521185 .................
[CV] c1=0.10252491344185391, c2=0.035456409715521185, score=0.814619 - 1.2s
[CV] c1=0.1942293390156905, c2=0.0118048238421011 ....................
[CV] c1=0.1942293390156905, c2=0.0118048238421011, score=0.839369 - 1.1s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.838429 - 1.1s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.691890 - 1.1s
[CV] c1=0.489724053657197, c2=0.044922427709806804 ...................
[CV] c1=0.489724053657197, c2=0.044922427709806804, score=0.656490 - 1.2s
[CV] c1=0.037804502799856664, c2=0.17775310605580735 .................
[CV] c1=0.037804502799856664, c2=0.17775310605580735, score=0.707931 - 1.2s
[CV] c1=0.48021458727568206, c2=0.024520344430852173 .................
[CV] c1=0.48021458727568206, c2=0.024520344430852173, score=0.710539 - 1.2s
[CV] c1=1.1913664771508643, c2=0.02636126240604801 ...................
[CV] c1=1.1913664771508643, c2=0.02636126240604801, score=0.677417 - 1.2s
[CV] c1=0.011396903498125098, c2=0.08331303274987872 .................
[CV] c1=0.011396903498125098, c2=0.08331303274987872, score=0.866790 - 1.1s
[CV] c1=0.389627350050321, c2=0.20541641674647737 ....................
[CV] c1=0.389627350050321, c2=0.20541641674647737, score=0.877067 - 1.1s
[CV] c1=0.478213957506215, c2=0.020477014457446593 ...................
[CV] c1=0.478213957506215, c2=0.020477014457446593, score=0.793956 - 1.2s
[CV] c1=0.585686407327112, c2=0.012901559348345326 ...................
[CV] c1=0.585686407327112, c2=0.012901559348345326, score=0.852821 - 1.4s
[CV] c1=0.32462532886586554, c2=0.018288220546846753 .................
[CV] c1=0.32462532886586554, c2=0.018288220546846753, score=0.848001 - 1.3s
[CV] c1=0.7414419018297659, c2=0.12193121091232882 ...................
[CV] c1=0.7414419018297659, c2=0.12193121091232882, score=0.853988 - 1.0s
Training done in: 7.486107s
Saving training model...
Saving training model done in: 0.013334s
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Prediction done in: 0.023981s