Run6_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 False
Report file: _v9
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 283
Sentences test data: 122
Reading corpus done in: 0.003860s
{'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=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.903565 - 1.2s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.630985 - 1.0s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.559014 - 0.9s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.592492 - 1.1s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.582068 - 1.1s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.743125 - 1.0s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.866790 - 1.2s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.825330 - 1.1s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.596309 - 1.1s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.789900 - 1.2s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.603251 - 1.0s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.920970 - 1.1s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.870586 - 1.1s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.660504 - 1.1s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.605840 - 1.1s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.865533 - 1.2s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.906853 - 1.1s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.647745 - 1.1s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.649654 - 1.0s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.824341 - 1.1s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.701461 - 1.0s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.840539 - 1.2s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.712560 - 1.2s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.718275 - 1.1s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.672745 - 1.1s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.881938 - 1.1s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.703305 - 1.1s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.673633 - 1.0s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.568556 - 1.2s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.518602 - 1.0s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.659253 - 1.0s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.720311 - 1.2s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.677417 - 1.1s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.683547 - 1.2s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.556540 - 1.2s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.753693 - 1.2s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.601571 - 0.9s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.647745 - 0.9s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.582162 - 1.2s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.643620 - 1.2s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.550050 - 0.9s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.654823 - 1.2s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.678288 - 1.1s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.507094 - 1.1s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.614085 - 1.3s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.883954 - 1.2s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.710369 - 1.1s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.686713 - 1.1s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.594837 - 0.9s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.866790 - 1.1s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.740663 - 1.1s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.770846 - 1.1s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.677417 - 1.1s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.848001 - 1.1s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.935386 - 1.0s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.899703 - 1.2s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.608985 - 0.9s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.548196 - 0.9s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.814619 - 1.3s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.603356 - 0.9s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.843338 - 1.1s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.946561 - 1.1s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.698982 - 1.1s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.720311 - 1.1s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.652192 - 1.2s
[CV] c1=0.7431164639270406, c2=0.0027998889877337263 .................
[CV] c1=0.7431164639270406, c2=0.0027998889877337263, score=0.708065 - 1.1s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.766835 - 1.1s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.856715 - 1.1s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.609338 - 1.2s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.723492 - 1.2s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.721334 - 1.3s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.878773 - 1.1s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.568962 - 1.0s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.580569 - 1.0s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.920970 - 1.0s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.814619 - 1.1s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.848001 - 1.1s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.712560 - 1.2s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.920970 - 1.1s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.775757 - 1.0s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.654823 - 1.0s
[CV] c1=0.09511707500453928, c2=0.0519939941697524 ...................
[CV] c1=0.09511707500453928, c2=0.0519939941697524, score=0.779725 - 1.1s
[CV] c1=1.1133560080812872, c2=0.03524217248955633 ...................
[CV] c1=1.1133560080812872, c2=0.03524217248955633, score=0.686713 - 1.2s
[CV] c1=2.2946346184092543, c2=0.026838185424639973 ..................
[CV] c1=2.2946346184092543, c2=0.026838185424639973, score=0.512837 - 1.0s
[CV] c1=1.4864633814895774, c2=0.07443280995437437 ...................
[CV] c1=1.4864633814895774, c2=0.07443280995437437, score=0.698163 - 1.1s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.906853 - 1.1s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.611684 - 1.0s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.810738 - 1.1s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.741434 - 1.0s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.867500 - 1.2s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.920970 - 1.0s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.688789 - 1.2s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.689868 - 1.0s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.881938 - 1.1s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.741434 - 1.1s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.866790 - 1.2s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.867977 - 1.2s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.684366 - 1.0s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.906853 - 1.1s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.672042 - 1.0s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.848001 - 1.4s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.587654 - 0.8s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.588945 - 1.0s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.568556 - 1.0s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.692232 - 1.0s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.734092 - 1.2s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.654823 - 1.1s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.624832 - 1.1s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.643620 - 1.1s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.655168 - 1.0s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.557148 - 0.9s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.855880 - 1.1s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.825330 - 1.2s
[CV] c1=0.1266383951793103, c2=0.0393032467121349 ....................
[CV] c1=0.1266383951793103, c2=0.0393032467121349, score=0.735607 - 1.2s
[CV] c1=0.03116962391669711, c2=0.034902897212510296 .................
[CV] c1=0.03116962391669711, c2=0.034902897212510296, score=0.906853 - 1.1s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.866790 - 1.2s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.902145 - 1.1s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.675506 - 1.1s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.686231 - 1.1s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.697913 - 0.9s
[CV] c1=0.1614939954077374, c2=0.06205814047571822 ...................
[CV] c1=0.1614939954077374, c2=0.06205814047571822, score=0.713945 - 1.2s
[CV] c1=0.020829028765021226, c2=0.330913244342466 ...................
[CV] c1=0.020829028765021226, c2=0.330913244342466, score=0.888112 - 1.1s
[CV] c1=1.1533562821101506, c2=0.019354995709139386 ..................
[CV] c1=1.1533562821101506, c2=0.019354995709139386, score=0.870586 - 1.2s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.660504 - 1.1s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.815463 - 0.9s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.899703 - 1.2s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.906853 - 1.2s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.515324 - 0.9s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.875991 - 1.1s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.654823 - 0.8s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.708833 - 1.1s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.767606 - 1.1s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.804756 - 1.1s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.605600 - 1.1s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.720505 - 1.1s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.660012 - 1.0s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.727470 - 1.2s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.648834 - 1.1s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.779045 - 1.1s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.870586 - 0.9s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.721334 - 1.3s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.920970 - 1.2s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.824341 - 1.1s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.608719 - 0.9s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.552580 - 0.9s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.761418 - 1.1s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.866790 - 1.1s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.621156 - 1.1s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.856015 - 1.2s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.660510 - 0.8s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.854423 - 1.1s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.867500 - 1.1s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.668774 - 1.2s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.596309 - 1.0s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.787287 - 1.1s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.860755 - 1.2s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.674776 - 1.0s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.787287 - 1.2s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.503462 - 1.0s
[CV] c1=1.0354026125353881, c2=0.04748423868234282 ...................
[CV] c1=1.0354026125353881, c2=0.04748423868234282, score=0.830130 - 1.1s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.919762 - 1.1s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.935386 - 1.1s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.815463 - 1.1s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.720311 - 1.2s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.867500 - 0.9s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.679766 - 1.1s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.716313 - 1.1s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.643620 - 1.1s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.652192 - 1.3s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.875991 - 0.9s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.575822 - 0.9s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.713945 - 1.1s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.723537 - 1.1s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.735257 - 1.2s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.906853 - 0.9s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.770586 - 1.1s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.693714 - 1.2s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.667190 - 1.1s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.906853 - 1.1s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.607039 - 0.8s
[CV] c1=0.3213690128955612, c2=0.03898256391447408 ...................
[CV] c1=0.3213690128955612, c2=0.03898256391447408, score=0.867217 - 1.1s
[CV] c1=0.21271540606230951, c2=0.030620357980156894 .................
[CV] c1=0.21271540606230951, c2=0.030620357980156894, score=0.814619 - 1.1s
[CV] c1=1.6722766965579237, c2=0.013291004231457602 ..................
[CV] c1=1.6722766965579237, c2=0.013291004231457602, score=0.607625 - 1.1s
[CV] c1=0.08475757164945485, c2=0.13819696066777126 ..................
[CV] c1=0.08475757164945485, c2=0.13819696066777126, score=0.680867 - 1.1s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.848001 - 1.0s
[CV] c1=0.4084834008911277, c2=0.06619217123115333 ...................
[CV] c1=0.4084834008911277, c2=0.06619217123115333, score=0.673541 - 1.1s
[CV] c1=0.0033333355799007253, c2=0.01971173429048602 ................
[CV] c1=0.0033333355799007253, c2=0.01971173429048602, score=0.866790 - 1.1s
[CV] c1=0.7225500746993299, c2=0.17031685283847245 ...................
[CV] c1=0.7225500746993299, c2=0.17031685283847245, score=0.852672 - 1.1s
[CV] c1=2.0488638507950374, c2=0.05830217300206339 ...................
[CV] c1=2.0488638507950374, c2=0.05830217300206339, score=0.778713 - 1.2s
[CV] c1=0.001922394963124772, c2=0.1166032351837375 ..................
[CV] c1=0.001922394963124772, c2=0.1166032351837375, score=0.724290 - 1.1s
Training done in: 7.322848s
Saving training model...
Saving training model done in: 0.013721s
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Prediction done in: 0.023824s