Run2_v11.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.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: True False
Report file: _v11
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003565s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 lemma[:1] 2
9 postag[:1] C
10 postag[:2] CD
--------------------------- FeaturesTest -----------------------------
0 1
0 lemma delta-arca
1 postag NN
2 -1:lemma _
3 -1:postag NN
4 +1:lemma _
5 +1:postag CD
6 hUpper True
7 hLower True
8 hGreek False
9 symb True
10 lemma[:1] d
11 postag[:1] N
12 lemma[:2] de
13 postag[:2] NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
[CV] c1=0.0861167403673638, c2=0.04828247009963213, score=0.896342 - 1.4s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.924267 - 1.2s
[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
[CV] c1=0.6417792255119764, c2=0.055291444870536756, score=0.924608 - 1.4s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.814051 - 1.4s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.867984 - 1.3s
[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
[CV] c1=0.11358491196479957, c2=0.07461322610286401, score=0.768346 - 1.5s
[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
[CV] c1=0.7033458837225772, c2=0.02974788560801502, score=0.885181 - 1.6s
[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
[CV] c1=1.49287494311989, c2=0.05403116080542014, score=0.889263 - 1.5s
[CV] c1=0.6478044566379584, c2=0.002961554846996858 ..................
[CV] c1=0.6478044566379584, c2=0.002961554846996858, score=0.869411 - 1.6s
[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
[CV] c1=0.11358491196479957, c2=0.07461322610286401, score=0.896342 - 1.5s
[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
[CV] c1=0.7033458837225772, c2=0.02974788560801502, score=0.807845 - 1.6s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.726535 - 1.4s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.688144 - 1.6s
[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
[CV] c1=0.7920601040963161, c2=0.07895815842200327, score=0.939372 - 1.5s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.745590 - 1.4s
[CV] c1=0.7398050605125945, c2=0.05046057309258661 ...................
[CV] c1=0.7398050605125945, c2=0.05046057309258661, score=0.859656 - 1.3s
[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
[CV] c1=2.7077934374074655, c2=0.11493498577823619, score=0.668205 - 1.2s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.836822 - 1.2s
[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
[CV] c1=0.0861167403673638, c2=0.04828247009963213, score=0.796207 - 1.4s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.826447 - 1.2s
[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
[CV] c1=0.6417792255119764, c2=0.055291444870536756, score=0.878690 - 1.4s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.800403 - 1.4s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.790879 - 1.4s
[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
[CV] c1=0.0861167403673638, c2=0.04828247009963213, score=0.884837 - 1.4s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.914124 - 1.3s
[CV] c1=0.7398050605125945, c2=0.05046057309258661 ...................
[CV] c1=0.7398050605125945, c2=0.05046057309258661, score=0.751364 - 1.3s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.857689 - 1.5s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.856261 - 1.4s
[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
[CV] c1=0.7920601040963161, c2=0.07895815842200327, score=0.735586 - 1.5s
[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
[CV] c1=0.08407572754540328, c2=0.009478896359475734, score=0.914124 - 1.0s
[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
[CV] c1=0.6417792255119764, c2=0.055291444870536756, score=0.773694 - 1.3s
[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
[CV] c1=1.49287494311989, c2=0.05403116080542014, score=0.761785 - 1.7s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.546879 - 1.7s
[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
[CV] c1=0.0861167403673638, c2=0.04828247009963213, score=0.935664 - 1.4s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.939675 - 1.4s
[CV] c1=0.004178967435122849, c2=0.09079861448733734 .................
[CV] c1=0.004178967435122849, c2=0.09079861448733734, score=0.881870 - 1.5s
[CV] c1=0.020561906935503537, c2=0.058243167770064976 ................
[CV] c1=0.020561906935503537, c2=0.058243167770064976, score=0.826784 - 1.2s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.823347 - 1.3s
[CV] c1=1.3822985394905212, c2=0.018122887822950486 ..................
[CV] c1=1.3822985394905212, c2=0.018122887822950486, score=0.591566 - 1.3s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.845585 - 1.3s
[CV] c1=0.7398050605125945, c2=0.05046057309258661 ...................
[CV] c1=0.7398050605125945, c2=0.05046057309258661, score=0.891072 - 1.4s
[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
[CV] c1=2.7077934374074655, c2=0.11493498577823619, score=0.755838 - 1.3s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.850014 - 1.3s
[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
[CV] c1=0.0861167403673638, c2=0.04828247009963213, score=0.830232 - 1.3s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.847686 - 1.4s
[CV] c1=0.7398050605125945, c2=0.05046057309258661 ...................
[CV] c1=0.7398050605125945, c2=0.05046057309258661, score=0.806456 - 1.5s
[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
[CV] c1=2.7077934374074655, c2=0.11493498577823619, score=0.726728 - 1.4s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.860459 - 1.2s
[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
[CV] c1=0.7920601040963161, c2=0.07895815842200327, score=0.840020 - 1.4s
[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
[CV] c1=0.08407572754540328, c2=0.009478896359475734, score=0.912280 - 1.3s
[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
[CV] c1=0.6417792255119764, c2=0.055291444870536756, score=0.908551 - 1.4s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.900097 - 1.4s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.880185 - 1.6s
[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
[CV] c1=0.7920601040963161, c2=0.07895815842200327, score=0.802723 - 1.4s
[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
[CV] c1=0.08407572754540328, c2=0.009478896359475734, score=0.845585 - 1.3s
[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
[CV] c1=0.6417792255119764, c2=0.055291444870536756, score=0.891072 - 1.5s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.918264 - 1.6s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.914124 - 1.3s
[CV] c1=1.3822985394905212, c2=0.018122887822950486 ..................
[CV] c1=1.3822985394905212, c2=0.018122887822950486, score=0.867984 - 1.3s
[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
[CV] c1=0.3175148951065869, c2=0.037005562427169, score=0.827976 - 1.3s
[CV] c1=0.7398050605125945, c2=0.05046057309258661 ...................
[CV] c1=0.7398050605125945, c2=0.05046057309258661, score=0.939372 - 1.4s
[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
[CV] c1=2.7077934374074655, c2=0.11493498577823619, score=0.853551 - 1.4s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.897553 - 1.3s
[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
[CV] c1=0.7920601040963161, c2=0.07895815842200327, score=0.806456 - 1.4s
[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
[CV] c1=0.08407572754540328, c2=0.009478896359475734, score=0.916493 - 1.4s
[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
[CV] c1=0.6417792255119764, c2=0.055291444870536756, score=0.853411 - 1.4s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.852407 - 1.5s
[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
[CV] c1=1.5847200457248953, c2=0.006014325493850365, score=0.736415 - 1.5s
[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
[CV] c1=0.11358491196479957, c2=0.07461322610286401, score=0.826784 - 1.3s
[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
[CV] c1=0.3175148951065869, c2=0.037005562427169, score=0.831922 - 1.5s
[CV] c1=0.004178967435122849, c2=0.09079861448733734 .................
[CV] c1=0.004178967435122849, c2=0.09079861448733734, score=0.839590 - 1.3s
[CV] c1=0.020561906935503537, c2=0.058243167770064976 ................
[CV] c1=0.020561906935503537, c2=0.058243167770064976, score=0.768346 - 1.3s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.845585 - 1.2s
[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
[CV] c1=0.7920601040963161, c2=0.07895815842200327, score=0.885181 - 1.5s
[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
[CV] c1=0.19109403616449935, c2=0.0010764561143359712, score=0.849959 - 1.4s
[CV] c1=0.7398050605125945, c2=0.05046057309258661 ...................
[CV] c1=0.7398050605125945, c2=0.05046057309258661, score=0.899678 - 1.3s
[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
[CV] c1=2.7077934374074655, c2=0.11493498577823619, score=0.530224 - 1.4s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.741087 - 1.4s
[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
[CV] c1=0.11358491196479957, c2=0.07461322610286401, score=0.890597 - 1.4s
[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
[CV] c1=0.7033458837225772, c2=0.02974788560801502, score=0.728849 - 1.5s
[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
[CV] c1=1.49287494311989, c2=0.05403116080542014, score=0.889041 - 1.0s
[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
[CV] c1=2.7077934374074655, c2=0.11493498577823619, score=0.706265 - 1.4s
[CV] c1=0.1388422147182745, c2=0.019507314290179247 ..................
[CV] c1=0.1388422147182745, c2=0.019507314290179247, score=0.924267 - 1.2s
[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
[CV] c1=0.0861167403673638, c2=0.04828247009963213, score=0.826784 - 1.2s
[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
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[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
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[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
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[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
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[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
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[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
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[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
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[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
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[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
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[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
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[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
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[CV] c1=1.3822985394905212, c2=0.018122887822950486 ..................
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[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
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[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
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[CV] c1=0.09054223875215395, c2=0.0023518182968725273 ................
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[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
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[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
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[CV] c1=2.7077934374074655, c2=0.11493498577823619 ...................
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[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
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[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
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[CV] c1=0.020561906935503537, c2=0.058243167770064976 ................
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[CV] c1=0.09054223875215395, c2=0.0023518182968725273 ................
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[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
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[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
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[CV] c1=0.7398050605125945, c2=0.05046057309258661 ...................
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[CV] c1=0.020561906935503537, c2=0.058243167770064976 ................
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[CV] c1=0.09054223875215395, c2=0.0023518182968725273 ................
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[CV] c1=1.3822985394905212, c2=0.018122887822950486 ..................
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[CV] c1=0.19109403616449935, c2=0.0010764561143359712 ................
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[CV] c1=0.004178967435122849, c2=0.09079861448733734 .................
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[CV] c1=0.020561906935503537, c2=0.058243167770064976 ................
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[CV] c1=0.09054223875215395, c2=0.0023518182968725273 ................
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[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
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[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
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[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
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[CV] c1=0.6478044566379584, c2=0.002961554846996858 ..................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=1.3822985394905212, c2=0.018122887822950486 ..................
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[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
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[CV] c1=0.004178967435122849, c2=0.09079861448733734 .................
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[CV] c1=0.6478044566379584, c2=0.002961554846996858 ..................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
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[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
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[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
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[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
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[CV] c1=1.5847200457248953, c2=0.006014325493850365 ..................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
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[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
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[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
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[CV] c1=0.6478044566379584, c2=0.002961554846996858 ..................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=0.0861167403673638, c2=0.04828247009963213 ...................
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[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
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[CV] c1=0.004178967435122849, c2=0.09079861448733734 .................
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[CV] c1=0.020561906935503537, c2=0.058243167770064976 ................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=1.3822985394905212, c2=0.018122887822950486 ..................
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[CV] c1=0.3175148951065869, c2=0.037005562427169 .....................
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[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
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[CV] c1=0.020561906935503537, c2=0.058243167770064976 ................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
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[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
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[CV] c1=1.49287494311989, c2=0.05403116080542014 .....................
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[CV] c1=0.6478044566379584, c2=0.002961554846996858 ..................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=0.11358491196479957, c2=0.07461322610286401 ..................
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[CV] c1=0.7033458837225772, c2=0.02974788560801502 ...................
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[CV] c1=0.004178967435122849, c2=0.09079861448733734 .................
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[CV] c1=0.6478044566379584, c2=0.002961554846996858 ..................
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[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
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[CV] c1=0.7920601040963161, c2=0.07895815842200327 ...................
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[CV] c1=0.08407572754540328, c2=0.009478896359475734 .................
[CV] c1=0.08407572754540328, c2=0.009478896359475734, score=0.826784 - 1.2s
[CV] c1=0.6417792255119764, c2=0.055291444870536756 ..................
[CV] c1=0.6417792255119764, c2=0.055291444870536756, score=0.735583 - 1.5s
[CV] c1=1.0804138881567058, c2=0.02459855006208165 ...................
[CV] c1=1.0804138881567058, c2=0.02459855006208165, score=0.765646 - 1.3s
[CV] c1=0.6478044566379584, c2=0.002961554846996858 ..................
[CV] c1=0.6478044566379584, c2=0.002961554846996858, score=0.816050 - 1.5s
[CV] c1=0.6322742654390535, c2=0.009349248677093488 ..................
[CV] c1=0.6322742654390535, c2=0.009349248677093488, score=0.869411 - 1.1s
Training done in: 9.362880s
Saving training model...
Saving training model done in: 0.013935s
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Prediction done in: 0.035958s