Run8_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: 0.003941s
{'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=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.739174 - 1.1s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.867500 - 1.2s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.883871 - 1.2s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.682045 - 1.3s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.592237 - 0.8s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.674776 - 1.0s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.861398 - 1.1s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.592237 - 0.9s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.747150 - 1.4s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.679766 - 0.8s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.713945 - 1.1s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.713945 - 1.2s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.632439 - 1.0s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.721334 - 1.2s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.735607 - 1.0s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.593330 - 1.0s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.848001 - 1.2s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.753693 - 1.1s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.761418 - 1.2s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.724290 - 1.1s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.578486 - 0.9s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.906853 - 1.3s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.737308 - 1.2s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.556324 - 0.9s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.920970 - 1.2s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.704452 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.912680 - 1.1s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.581649 - 1.0s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.715320 - 1.1s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.784950 - 1.0s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.814619 - 1.1s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.854246 - 1.3s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.899703 - 1.2s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.563779 - 1.1s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.740663 - 1.0s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.906853 - 1.1s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.920970 - 1.1s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.819818 - 1.1s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.860755 - 1.3s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.652192 - 1.1s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.669071 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.656490 - 1.0s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.705332 - 1.1s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.920970 - 1.2s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.737308 - 1.0s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.887557 - 1.1s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.865426 - 1.2s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.860755 - 1.3s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.656490 - 1.1s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.906853 - 1.0s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.872399 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.753693 - 1.1s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.814619 - 1.1s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.854423 - 1.0s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.652192 - 1.0s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.794740 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.860755 - 1.1s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.869740 - 1.2s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.723593 - 1.0s
[CV] c1=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.704866 - 1.0s
[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
[CV] c1=0.1827955499307428, c2=0.002673779161901005, score=0.748048 - 1.1s
[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
[CV] c1=0.010916997872083896, c2=0.01703042309947876, score=0.637082 - 1.0s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.758128 - 1.1s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.673541 - 1.1s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.867500 - 1.1s
[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
[CV] c1=0.1827955499307428, c2=0.002673779161901005, score=0.843407 - 1.1s
[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
[CV] c1=0.010916997872083896, c2=0.01703042309947876, score=0.716313 - 1.1s
[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
[CV] c1=0.11923109411090525, c2=0.08712148554319654, score=0.920970 - 1.0s
[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
[CV] c1=1.5310724688252555, c2=0.007849882070317076, score=0.680407 - 0.9s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.721334 - 1.1s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.866790 - 1.2s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.600487 - 0.9s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.810663 - 1.2s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.866790 - 1.5s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.872249 - 1.1s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.740663 - 1.1s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.734847 - 1.3s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.674776 - 1.1s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.899703 - 1.3s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.600487 - 1.1s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.878327 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.561392 - 0.9s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.917838 - 1.1s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.784199 - 1.4s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.866790 - 1.2s
[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
[CV] c1=0.1827955499307428, c2=0.002673779161901005, score=0.641268 - 0.9s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.708833 - 1.2s
[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
[CV] c1=0.11923109411090525, c2=0.08712148554319654, score=0.720311 - 1.3s
[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
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[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.946561 - 1.1s
[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
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[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
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[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
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[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
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[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
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[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
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[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
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[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
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[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
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[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
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[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
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[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
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[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
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[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.899703 - 1.2s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
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[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.654823 - 1.1s
[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
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[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
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[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
[CV] c1=1.5310724688252555, c2=0.007849882070317076, score=0.744499 - 1.0s
[CV] c1=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.659121 - 1.1s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.727470 - 1.1s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
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[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.659121 - 1.0s
[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
[CV] c1=1.5310724688252555, c2=0.007849882070317076, score=0.843581 - 1.0s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
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[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
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[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
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[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
[CV] c1=0.11923109411090525, c2=0.08712148554319654, score=0.608719 - 0.9s
[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
[CV] c1=1.5310724688252555, c2=0.007849882070317076, score=0.643620 - 1.2s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.896193 - 1.1s
[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
[CV] c1=0.1827955499307428, c2=0.002673779161901005, score=0.924594 - 1.2s
[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
[CV] c1=0.010916997872083896, c2=0.01703042309947876, score=0.895411 - 1.1s
[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
[CV] c1=0.11923109411090525, c2=0.08712148554319654, score=0.761019 - 1.1s
[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
[CV] c1=1.5310724688252555, c2=0.007849882070317076, score=0.831084 - 1.0s
[CV] c1=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.852821 - 1.1s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.883871 - 1.1s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.838429 - 1.1s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.739174 - 1.1s
[CV] c1=0.06371903845172723, c2=0.09382386151498534 ..................
[CV] c1=0.06371903845172723, c2=0.09382386151498534, score=0.840539 - 0.9s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.920970 - 1.1s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.725767 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.794740 - 1.1s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.872249 - 1.3s
[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
[CV] c1=1.5310724688252555, c2=0.007849882070317076, score=0.639214 - 1.1s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.764863 - 1.1s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.779725 - 1.1s
[CV] c1=0.2107941425103855, c2=0.07645318409354064 ...................
[CV] c1=0.2107941425103855, c2=0.07645318409354064, score=0.730124 - 1.2s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.721334 - 1.2s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.848001 - 1.3s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.906853 - 1.1s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.912680 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.883954 - 1.1s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.899703 - 1.1s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.919762 - 1.3s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.848001 - 1.2s
[CV] c1=0.1827955499307428, c2=0.002673779161901005 ..................
[CV] c1=0.1827955499307428, c2=0.002673779161901005, score=0.710539 - 1.3s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.679766 - 1.1s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.712255 - 1.1s
[CV] c1=0.06371903845172723, c2=0.09382386151498534 ..................
[CV] c1=0.06371903845172723, c2=0.09382386151498534, score=0.720311 - 0.9s
[CV] c1=0.14547316667964716, c2=0.04275866782811716 ..................
[CV] c1=0.14547316667964716, c2=0.04275866782811716, score=0.838429 - 1.0s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.687750 - 1.3s
[CV] c1=0.010916997872083896, c2=0.01703042309947876 .................
[CV] c1=0.010916997872083896, c2=0.01703042309947876, score=0.935386 - 1.2s
[CV] c1=0.11923109411090525, c2=0.08712148554319654 ..................
[CV] c1=0.11923109411090525, c2=0.08712148554319654, score=0.730124 - 1.1s
[CV] c1=1.5310724688252555, c2=0.007849882070317076 ..................
[CV] c1=1.5310724688252555, c2=0.007849882070317076, score=0.672745 - 1.1s
[CV] c1=0.3610226719997963, c2=0.029611486118589044 ..................
[CV] c1=0.3610226719997963, c2=0.029611486118589044, score=0.841313 - 1.1s
[CV] c1=0.0893601644204355, c2=0.024019081127496116 ..................
[CV] c1=0.0893601644204355, c2=0.024019081127496116, score=0.920970 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.704526 - 1.2s
[CV] c1=0.33894023669353496, c2=0.021885953440521758 .................
[CV] c1=0.33894023669353496, c2=0.021885953440521758, score=0.920970 - 1.1s
[CV] c1=0.48934294075061485, c2=0.059643580535587194 .................
[CV] c1=0.48934294075061485, c2=0.059643580535587194, score=0.852821 - 1.4s
[CV] c1=0.005890787510878062, c2=0.06901405430753309 .................
[CV] c1=0.005890787510878062, c2=0.06901405430753309, score=0.607039 - 0.9s
[CV] c1=0.7907559657386046, c2=0.04221232955070474 ...................
[CV] c1=0.7907559657386046, c2=0.04221232955070474, score=0.737619 - 1.1s
[CV] c1=0.6067183285356851, c2=0.02508677467384688 ...................
[CV] c1=0.6067183285356851, c2=0.02508677467384688, score=0.761818 - 1.1s
[CV] c1=0.43870196113001303, c2=0.10254088863167253 ..................
[CV] c1=0.43870196113001303, c2=0.10254088863167253, score=0.562376 - 0.9s
[CV] c1=0.4124010091584731, c2=0.03226124445670804 ...................
[CV] c1=0.4124010091584731, c2=0.03226124445670804, score=0.784950 - 0.9s
[CV] c1=0.06371903845172723, c2=0.09382386151498534 ..................
[CV] c1=0.06371903845172723, c2=0.09382386151498534, score=0.607039 - 0.7s
[CV] c1=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.747150 - 1.1s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.687454 - 1.1s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.935386 - 1.1s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.852821 - 1.1s
[CV] c1=0.06371903845172723, c2=0.09382386151498534 ..................
[CV] c1=0.06371903845172723, c2=0.09382386151498534, score=0.660510 - 0.9s
[CV] c1=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.912680 - 1.4s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.608985 - 1.0s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.923613 - 1.2s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.878327 - 1.1s
[CV] c1=0.06371903845172723, c2=0.09382386151498534 ..................
[CV] c1=0.06371903845172723, c2=0.09382386151498534, score=0.775757 - 0.9s
[CV] c1=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.578486 - 1.1s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.902145 - 1.2s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.920970 - 1.3s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.578486 - 0.9s
[CV] c1=0.06371903845172723, c2=0.09382386151498534 ..................
[CV] c1=0.06371903845172723, c2=0.09382386151498534, score=0.866790 - 1.0s
[CV] c1=0.6805169695271499, c2=0.059941860636124 .....................
[CV] c1=0.6805169695271499, c2=0.059941860636124, score=0.794740 - 1.1s
[CV] c1=0.002248053678487388, c2=0.022468299598165514 ................
[CV] c1=0.002248053678487388, c2=0.022468299598165514, score=0.935386 - 1.2s
[CV] c1=0.11105424454358216, c2=0.015741660010216145 .................
[CV] c1=0.11105424454358216, c2=0.015741660010216145, score=0.741434 - 1.1s
[CV] c1=0.6648810381927359, c2=0.08001031738332513 ...................
[CV] c1=0.6648810381927359, c2=0.08001031738332513, score=0.794740 - 1.1s
[CV] c1=0.06371903845172723, c2=0.09382386151498534 ..................
[CV] c1=0.06371903845172723, c2=0.09382386151498534, score=0.881938 - 1.0s
Training done in: 7.467291s
Saving training model...
Saving training model done in: 0.015227s
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Prediction done in: 0.026117s