Run2_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: 0.003666s
{'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=1.00966870162731, c2=0.025958556376657574 ....................
[CV] c1=1.00966870162731, c2=0.025958556376657574, score=0.656999 - 1.0s
[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
[CV] c1=1.168847855695387, c2=0.054074754440257625, score=0.549071 - 0.9s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.559946 - 0.9s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.840539 - 1.1s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.660012 - 1.2s
[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
[CV] c1=1.00966870162731, c2=0.025958556376657574, score=0.826261 - 0.8s
[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
[CV] c1=0.22656149469246054, c2=0.06475330717049832, score=0.919762 - 1.0s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.761818 - 1.1s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.848001 - 1.2s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.761418 - 1.1s
[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
[CV] c1=1.00966870162731, c2=0.025958556376657574, score=0.716676 - 0.9s
[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
[CV] c1=1.168847855695387, c2=0.054074754440257625, score=0.670684 - 1.1s
[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
[CV] c1=0.7823077481969921, c2=0.03404532137185433, score=0.872399 - 1.1s
[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
[CV] c1=0.6765797517220264, c2=0.007434912899378703, score=0.743125 - 1.1s
[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
[CV] c1=0.20078106949479455, c2=0.023670407350363146, score=0.838429 - 1.0s
[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
[CV] c1=1.00966870162731, c2=0.025958556376657574, score=0.641040 - 0.9s
[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
[CV] c1=1.168847855695387, c2=0.054074754440257625, score=0.704277 - 1.0s
[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
[CV] c1=0.7823077481969921, c2=0.03404532137185433, score=0.694072 - 1.2s
[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
[CV] c1=0.6765797517220264, c2=0.007434912899378703, score=0.694072 - 1.2s
[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
[CV] c1=0.20078106949479455, c2=0.023670407350363146, score=0.679766 - 1.1s
[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
[CV] c1=1.00966870162731, c2=0.025958556376657574, score=0.787287 - 0.8s
[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
[CV] c1=0.22656149469246054, c2=0.06475330717049832, score=0.724007 - 1.1s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.719596 - 1.2s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.919762 - 1.0s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.852821 - 1.2s
[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
[CV] c1=0.37276009448707553, c2=0.08055336693981598, score=0.566523 - 1.1s
[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
[CV] c1=0.6326902790510075, c2=0.060383400796135134, score=0.704866 - 1.2s
[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
[CV] c1=0.7823077481969921, c2=0.03404532137185433, score=0.576589 - 1.0s
[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
[CV] c1=0.6765797517220264, c2=0.007434912899378703, score=0.666440 - 1.0s
[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
[CV] c1=0.20078106949479455, c2=0.023670407350363146, score=0.721334 - 1.3s
[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
[CV] c1=0.6395797105929565, c2=0.0461197515046378, score=0.761818 - 1.0s
[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
[CV] c1=0.22656149469246054, c2=0.06475330717049832, score=0.660510 - 1.2s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.891760 - 1.2s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.607039 - 0.9s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.848001 - 1.3s
[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
[CV] c1=0.6395797105929565, c2=0.0461197515046378, score=0.852821 - 1.1s
[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
[CV] c1=0.22656149469246054, c2=0.06475330717049832, score=0.592237 - 1.0s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.843338 - 1.2s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.718941 - 1.2s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.899703 - 1.3s
[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
[CV] c1=0.37276009448707553, c2=0.08055336693981598, score=0.848001 - 1.0s
[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
[CV] c1=1.168847855695387, c2=0.054074754440257625, score=0.787287 - 1.1s
[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
[CV] c1=0.7823077481969921, c2=0.03404532137185433, score=0.739174 - 1.3s
[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
[CV] c1=0.6765797517220264, c2=0.007434912899378703, score=0.753693 - 1.1s
[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
[CV] c1=0.20078106949479455, c2=0.023670407350363146, score=0.848001 - 1.1s
[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
[CV] c1=0.6395797105929565, c2=0.0461197515046378, score=0.760479 - 1.1s
[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
[CV] c1=1.168847855695387, c2=0.054074754440257625, score=0.606581 - 1.1s
[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
[CV] c1=0.7823077481969921, c2=0.03404532137185433, score=0.661884 - 1.2s
[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
[CV] c1=0.6765797517220264, c2=0.007434912899378703, score=0.855614 - 1.2s
[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
[CV] c1=0.20078106949479455, c2=0.023670407350363146, score=0.876920 - 1.0s
[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
[CV] c1=0.16888346085657382, c2=0.02208269716963201, score=0.740663 - 1.2s
[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
[CV] c1=0.8607518495035315, c2=0.15862627698471804, score=0.797002 - 1.2s
[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
[CV] c1=0.6168211659220036, c2=0.006845272732197598, score=0.883954 - 1.2s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.716266 - 1.3s
[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
[CV] c1=0.37276009448707553, c2=0.08055336693981598, score=0.858883 - 0.7s
[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
[CV] c1=0.22656149469246054, c2=0.06475330717049832, score=0.721334 - 1.2s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.693442 - 1.1s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.720311 - 1.2s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.874700 - 1.2s
[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
[CV] c1=0.37276009448707553, c2=0.08055336693981598, score=0.899703 - 1.5s
[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
[CV] c1=0.6326902790510075, c2=0.060383400796135134, score=0.571166 - 0.9s
[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
[CV] c1=0.016463867524667154, c2=0.009787977090088149, score=0.935386 - 1.2s
[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
[CV] c1=0.2837138419533594, c2=0.009966189901122134, score=0.586182 - 0.9s
[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
[CV] c1=0.20078106949479455, c2=0.023670407350363146, score=0.581925 - 0.9s
[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
[CV] c1=0.6395797105929565, c2=0.0461197515046378, score=0.912680 - 0.9s
[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
[CV] c1=0.22656149469246054, c2=0.06475330717049832, score=0.872249 - 1.2s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.903565 - 1.2s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.906853 - 1.1s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.561061 - 1.1s
[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
[CV] c1=0.6395797105929565, c2=0.0461197515046378, score=0.794740 - 0.9s
[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
[CV] c1=0.22656149469246054, c2=0.06475330717049832, score=0.869740 - 1.3s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.753693 - 1.1s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.766835 - 1.2s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.920970 - 1.1s
[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
[CV] c1=0.16888346085657382, c2=0.02208269716963201, score=0.906853 - 1.4s
[CV] c1=0.7463567881969966, c2=0.010504031522292094 ..................
[CV] c1=0.7463567881969966, c2=0.010504031522292094, score=0.852821 - 1.1s
[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
[CV] c1=0.06766924551335582, c2=0.05664528713448661, score=0.887557 - 1.2s
[CV] c1=0.48395276763378503, c2=0.022365459591399905 .................
[CV] c1=0.48395276763378503, c2=0.022365459591399905, score=0.729308 - 1.1s
[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
[CV] c1=1.00966870162731, c2=0.025958556376657574, score=0.870586 - 1.2s
[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
[CV] c1=0.6326902790510075, c2=0.060383400796135134, score=0.883954 - 1.1s
[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
[CV] c1=0.016463867524667154, c2=0.009787977090088149, score=0.932448 - 1.1s
[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
[CV] c1=0.2837138419533594, c2=0.009966189901122134, score=0.879383 - 1.1s
[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
[CV] c1=0.10973444640225576, c2=0.010828669158530741, score=0.748850 - 0.9s
[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
[CV] c1=0.16888346085657382, c2=0.02208269716963201, score=0.843407 - 1.3s
[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
[CV] c1=0.8607518495035315, c2=0.15862627698471804, score=0.787287 - 1.2s
[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
[CV] c1=0.6168211659220036, c2=0.006845272732197598, score=0.753693 - 1.0s
[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
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[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
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[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
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[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
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[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
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[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
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[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
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[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
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[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
[CV] c1=0.016463867524667154, c2=0.009787977090088149, score=0.906853 - 1.1s
[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
[CV] c1=0.2837138419533594, c2=0.009966189901122134, score=0.674776 - 1.0s
[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
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[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
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[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
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[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
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[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
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[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
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[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
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[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
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[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
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[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
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[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
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[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
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[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
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[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
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[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
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[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
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[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
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[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
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[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
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[CV] c1=0.6765797517220264, c2=0.007434912899378703 ..................
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[CV] c1=0.20078106949479455, c2=0.023670407350363146 .................
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[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
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[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
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[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
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[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=1.00966870162731, c2=0.025958556376657574 ....................
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[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
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[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
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[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
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[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
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[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
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[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
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[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
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[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
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[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
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[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
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[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
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[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
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[CV] c1=0.10973444640225576, c2=0.010828669158530741 .................
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[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
[CV] c1=0.8607518495035315, c2=0.15862627698471804, score=0.624124 - 1.1s
[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
[CV] c1=0.6168211659220036, c2=0.006845272732197598, score=0.857493 - 1.2s
[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
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[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
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[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
[CV] c1=0.6168211659220036, c2=0.006845272732197598, score=0.778347 - 1.2s
[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
[CV] c1=0.9988969075737604, c2=0.006345198146357405, score=0.566256 - 1.0s
[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
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[CV] c1=0.22656149469246054, c2=0.06475330717049832 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
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[CV] c1=0.06766924551335582, c2=0.05664528713448661 ..................
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[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
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[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.37276009448707553, c2=0.08055336693981598 ..................
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[CV] c1=0.6326902790510075, c2=0.060383400796135134 ..................
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[CV] c1=0.016463867524667154, c2=0.009787977090088149 ................
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[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
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[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
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[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
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[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
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[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.6395797105929565, c2=0.0461197515046378 ....................
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[CV] c1=1.168847855695387, c2=0.054074754440257625 ...................
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[CV] c1=0.7823077481969921, c2=0.03404532137185433 ...................
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[CV] c1=0.2837138419533594, c2=0.009966189901122134 ..................
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[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
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[CV] c1=0.16888346085657382, c2=0.02208269716963201 ..................
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[CV] c1=0.8607518495035315, c2=0.15862627698471804 ...................
[CV] c1=0.8607518495035315, c2=0.15862627698471804, score=0.654029 - 1.1s
[CV] c1=0.6168211659220036, c2=0.006845272732197598 ..................
[CV] c1=0.6168211659220036, c2=0.006845272732197598, score=0.761818 - 1.2s
[CV] c1=0.9988969075737604, c2=0.006345198146357405 ..................
[CV] c1=0.9988969075737604, c2=0.006345198146357405, score=0.787287 - 1.3s
[CV] c1=2.243122699972053, c2=0.02408920842785463 ....................
[CV] c1=2.243122699972053, c2=0.02408920842785463, score=0.660504 - 0.9s
Training done in: 7.331329s
Saving training model...
Saving training model done in: 0.014029s
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Prediction done in: 0.024944s