Run1_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: False False
Report file: _v9
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 283
Sentences test data: 122
Reading corpus done in: 0.003760s
{'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=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.905489 - 1.1s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.577889 - 0.9s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.679766 - 1.1s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.767569 - 1.1s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.838429 - 1.2s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.857493 - 1.0s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.938387 - 1.1s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.848001 - 1.0s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.660012 - 1.0s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.721334 - 1.2s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.669962 - 0.8s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.703150 - 1.2s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.724515 - 1.2s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.708877 - 1.2s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.679766 - 1.2s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.597458 - 1.0s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.720311 - 1.2s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.661884 - 1.0s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.761418 - 1.2s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.586182 - 0.9s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.848001 - 1.2s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.596949 - 1.0s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.586182 - 1.1s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.905489 - 1.1s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.920970 - 1.0s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.866790 - 1.1s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.756561 - 1.2s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.741434 - 1.1s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.857493 - 1.1s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.687300 - 1.1s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.628354 - 1.1s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.921915 - 1.2s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.906853 - 1.2s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.674776 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.609849 - 1.0s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.547996 - 0.9s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.848001 - 1.2s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.773430 - 1.2s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.538621 - 0.9s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.848001 - 1.3s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.679766 - 0.9s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.906853 - 1.1s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.921915 - 1.1s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.776203 - 1.1s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.872249 - 1.2s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.784628 - 1.2s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.741434 - 1.1s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.687750 - 1.1s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.710539 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.627348 - 1.0s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.761418 - 1.0s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.740663 - 1.4s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.730083 - 1.2s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.583681 - 0.9s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.899703 - 1.2s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.781163 - 0.9s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.871555 - 1.2s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.881356 - 1.3s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.855614 - 1.1s
[CV] c1=0.24819385946875622, c2=0.052655886800089084 .................
[CV] c1=0.24819385946875622, c2=0.052655886800089084, score=0.740663 - 1.2s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.908205 - 1.2s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.710539 - 1.1s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.903565 - 1.0s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.928170 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.624124 - 1.1s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.710369 - 1.1s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.735607 - 1.2s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.632439 - 1.0s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.920970 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.698982 - 1.0s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.841822 - 1.1s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.848001 - 1.2s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.741527 - 1.0s
[CV] c1=0.5713116669674538, c2=0.01054418037901807 ...................
[CV] c1=0.5713116669674538, c2=0.01054418037901807, score=0.883954 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.659056 - 1.1s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.704237 - 1.1s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.838429 - 1.2s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.697912 - 1.1s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.741434 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.788630 - 1.1s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.694090 - 1.2s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.761818 - 1.0s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.818617 - 1.2s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.899703 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.526041 - 1.0s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.592237 - 0.9s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.870763 - 1.1s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.816469 - 1.2s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.866790 - 1.2s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.843581 - 1.1s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.838429 - 1.5s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.899703 - 1.1s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.570419 - 0.9s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.530341 - 0.9s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.674776 - 1.0s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.721334 - 1.2s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.753693 - 1.1s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.860755 - 1.2s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.852672 - 1.1s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.589307 - 0.8s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.716266 - 0.9s
[CV] c1=0.22716579831507944, c2=0.007171535474090697 .................
[CV] c1=0.22716579831507944, c2=0.007171535474090697, score=0.674776 - 1.3s
[CV] c1=0.09651425305864975, c2=0.0039926239609599816 ................
[CV] c1=0.09651425305864975, c2=0.0039926239609599816, score=0.924594 - 1.4s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.847745 - 1.1s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.722890 - 1.2s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.848001 - 1.2s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.817004 - 1.3s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.710539 - 1.1s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.606581 - 1.0s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.920970 - 0.9s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.713945 - 1.2s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.710539 - 1.1s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.578904 - 1.0s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.639214 - 1.2s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.935924 - 1.0s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.899703 - 1.1s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.674776 - 1.3s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.784628 - 1.2s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.761165 - 1.1s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.796488 - 0.9s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.740663 - 1.2s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.917838 - 1.1s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.673541 - 1.2s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.605840 - 1.1s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.838429 - 1.1s
[CV] c1=0.5461072593339137, c2=0.002561125547217938 ..................
[CV] c1=0.5461072593339137, c2=0.002561125547217938, score=0.728584 - 1.2s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.920970 - 1.3s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.720535 - 1.2s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.639214 - 1.1s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.648261 - 0.9s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.906853 - 1.2s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.555809 - 1.0s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.899703 - 1.1s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.530341 - 0.9s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.639214 - 0.9s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.608719 - 1.0s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.866790 - 1.1s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.883034 - 1.1s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.648261 - 1.4s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.541373 - 0.7s
[CV] c1=0.20181412872449603, c2=0.1831099538162916 ...................
[CV] c1=0.20181412872449603, c2=0.1831099538162916, score=0.906294 - 1.1s
[CV] c1=0.12349654401855631, c2=0.02271624803463124 ..................
[CV] c1=0.12349654401855631, c2=0.02271624803463124, score=0.906853 - 1.1s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.566256 - 1.0s
[CV] c1=0.1550751527481274, c2=0.0018910637535844298 .................
[CV] c1=0.1550751527481274, c2=0.0018910637535844298, score=0.803761 - 1.2s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.727700 - 1.1s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.874934 - 1.1s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.656490 - 1.1s
[CV] c1=0.9058341641460185, c2=0.007378307188927494 ..................
[CV] c1=0.9058341641460185, c2=0.007378307188927494, score=0.891760 - 1.1s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.616903 - 0.9s
[CV] c1=1.0380596275637475, c2=0.18279171536318017 ...................
[CV] c1=1.0380596275637475, c2=0.18279171536318017, score=0.685536 - 1.1s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.753176 - 1.1s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.710303 - 1.2s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.899703 - 1.2s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.614746 - 1.1s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.616903 - 0.9s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.848001 - 1.2s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.852821 - 1.0s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.919762 - 1.1s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.680407 - 1.1s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.888529 - 1.1s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.680867 - 1.1s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.660012 - 1.0s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.848001 - 1.1s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.800487 - 1.1s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.740663 - 1.1s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.867013 - 1.2s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.784199 - 1.1s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.679766 - 1.1s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.689868 - 1.1s
[CV] c1=0.17443878436909793, c2=0.025545309300829405 .................
[CV] c1=0.17443878436909793, c2=0.025545309300829405, score=0.906853 - 1.0s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.899703 - 1.3s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.919762 - 1.1s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.919762 - 1.1s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.689868 - 1.1s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.689868 - 0.8s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.775757 - 1.1s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.798294 - 1.1s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.879383 - 1.2s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.573741 - 1.1s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.680407 - 0.8s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.845912 - 1.1s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.556324 - 0.9s
[CV] c1=0.33745249047104287, c2=0.12028799387317968 ..................
[CV] c1=0.33745249047104287, c2=0.12028799387317968, score=0.715320 - 1.0s
[CV] c1=1.395645503093999, c2=0.03913303306397459 ....................
[CV] c1=1.395645503093999, c2=0.03913303306397459, score=0.648261 - 1.4s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.816730 - 1.0s
[CV] c1=0.1126557712627844, c2=0.10045738310383956 ...................
[CV] c1=0.1126557712627844, c2=0.10045738310383956, score=0.919762 - 1.1s
[CV] c1=0.5000947711428705, c2=0.016584093219888196 ..................
[CV] c1=0.5000947711428705, c2=0.016584093219888196, score=0.768203 - 1.1s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.866790 - 1.1s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.748264 - 1.1s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.624124 - 1.0s
[CV] c1=0.27752606848750366, c2=0.036947033112907056 .................
[CV] c1=0.27752606848750366, c2=0.036947033112907056, score=0.920970 - 1.2s
[CV] c1=0.5994878159065081, c2=0.04116230984146705 ...................
[CV] c1=0.5994878159065081, c2=0.04116230984146705, score=0.883954 - 1.2s
[CV] c1=0.38390254403775603, c2=0.019141773881786436 .................
[CV] c1=0.38390254403775603, c2=0.019141773881786436, score=0.761418 - 1.1s
[CV] c1=1.348060881200924, c2=0.05731692872510329 ....................
[CV] c1=1.348060881200924, c2=0.05731692872510329, score=0.800487 - 1.1s
[CV] c1=1.24594687727841, c2=0.044969845912413944 ....................
[CV] c1=1.24594687727841, c2=0.044969845912413944, score=0.776399 - 1.0s
Training done in: 7.289575s
Saving training model...
Saving training model done in: 0.015155s
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Prediction done in: 0.026515s