Run_7.txt 30.2 KB
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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: False True
Report file: _v13
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
   Sentences training data: 286
   Sentences test data: 123
Reading corpus done in: 0.003575s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
            0         1
0       lemma         2
1      postag        CD
2    -1:lemma  fructose
3   -1:postag        NN
4        word         2
5     isUpper     False
6     isLower     False
7     isGreek     False
8    isNumber      True
9     -1:word  fructose
10   -2:lemma       Cra
11  -2:postag       NNP
--------------------------- 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        word  delta-arcA
7     isUpper       False
8     isLower       False
9     isGreek       False
10   isNumber       False
11    -1:word           _
12    +1:word           _
13   -2:lemma     affyexp
14  -2:postag          JJ
15   +2:lemma     glucose
16  +2:postag          NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.778117 -   1.3s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.853767 -   1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.931253 -   1.4s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.593248 -   1.6s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.927267 -   1.4s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.798145 -   0.9s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.885817 -   1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.856059 -   1.4s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.766544 -   1.6s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.897630 -   1.4s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.885973 -   1.0s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.866353 -   1.4s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.938157 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.907533 -   1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.794758 -   1.6s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.853967 -   1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.931991 -   1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.695368 -   1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.793626 -   1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.798753 -   1.5s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.812996 -   1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.836597 -   1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.853767 -   1.5s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.880703 -   1.4s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.707282 -   1.6s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.601824 -   1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.717781 -   1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.814418 -   1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.813706 -   1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.848812 -   1.5s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.818821 -   1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.892921 -   1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.913784 -   1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.800038 -   1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.913784 -   1.5s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.903311 -   1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.765908 -   1.6s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.845227 -   1.4s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.738812 -   1.5s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.868921 -   1.4s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.889602 -   1.1s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.913784 -   1.8s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.818750 -   1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.867753 -   1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.631304 -   1.2s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.764357 -   1.3s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.827578 -   1.5s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.811515 -   1.5s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.866963 -   1.6s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.783556 -   1.5s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.852879 -   1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.913784 -   1.6s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.912193 -   1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.866353 -   1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.900039 -   1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.866353 -   1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.853559 -   1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.900039 -   1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.869996 -   1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.859362 -   1.3s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.863001 -   1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.849838 -   1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.925823 -   1.4s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.913214 -   1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.906331 -   1.4s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.818254 -   1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.686298 -   1.5s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.680687 -   1.6s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.931991 -   1.4s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.867607 -   1.4s
[CV] c1=1.1125641437191895, c2=0.06613233343219797 ...................
[CV]  c1=1.1125641437191895, c2=0.06613233343219797, score=0.902496 -   1.5s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.790902 -   1.6s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.857043 -   1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.809731 -   1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.840372 -   1.3s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.727697 -   1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.917874 -   1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.797760 -   1.6s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.727697 -   1.5s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.819378 -   1.5s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.833325 -   1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.888803 -   1.4s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.851826 -   1.4s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.969518 -   1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.917037 -   1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.832339 -   1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.847604 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.798145 -   1.3s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.884921 -   1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.722395 -   1.2s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.931814 -   1.4s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.939034 -   1.6s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.842339 -   1.4s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.842929 -   1.5s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.804932 -   1.4s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.951585 -   1.5s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.780124 -   1.5s
[CV] c1=0.6198895769639643, c2=0.0028009206253587736 .................
[CV]  c1=0.6198895769639643, c2=0.0028009206253587736, score=0.803867 -   1.5s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.923193 -   1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.866911 -   1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.848812 -   1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.913784 -   1.6s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.849422 -   1.4s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.853767 -   1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.931991 -   1.3s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.931991 -   1.2s
[CV] c1=0.24222541975427525, c2=0.02858668949001732 ..................
[CV]  c1=0.24222541975427525, c2=0.02858668949001732, score=0.927980 -   1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.928742 -   1.6s
[CV] c1=0.03780171336875179, c2=0.012718090480016972 .................
[CV]  c1=0.03780171336875179, c2=0.012718090480016972, score=0.889602 -   1.4s
[CV] c1=0.31697105278313065, c2=0.1627674927353806 ...................
[CV]  c1=0.31697105278313065, c2=0.1627674927353806, score=0.942868 -   1.5s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.928742 -   1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.808180 -   1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.804932 -   1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.808180 -   1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.931814 -   1.1s
[CV] c1=0.1250735526885256, c2=0.03442702231914988 ...................
[CV]  c1=0.1250735526885256, c2=0.03442702231914988, score=0.847604 -   1.3s
[CV] c1=0.41912632470724565, c2=0.1640401199474577 ...................
[CV]  c1=0.41912632470724565, c2=0.1640401199474577, score=0.855349 -   1.4s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.892921 -   1.6s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.902216 -   1.6s
[CV] c1=0.6177967356330287, c2=0.0501823034129141 ....................
[CV]  c1=0.6177967356330287, c2=0.0501823034129141, score=0.795123 -   1.6s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.808180 -   1.6s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.939034 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.795123 -   1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.707282 -   1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.885973 -   1.1s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.778117 -   1.6s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.826198 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.896776 -   1.4s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.884219 -   1.3s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.858948 -   1.1s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.864761 -   1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.848812 -   1.4s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.917433 -   1.4s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.866714 -   1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.854195 -   1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.601824 -   1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.707282 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.812996 -   1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.927267 -   1.3s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.798145 -   1.2s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.696344 -   1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.804491 -   1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.686298 -   1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.931991 -   1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.826012 -   1.4s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.913784 -   1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.884106 -   1.4s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.900039 -   1.6s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.928742 -   1.4s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.838813 -   1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.885714 -   1.6s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.931991 -   1.3s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.790054 -   1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.696344 -   1.5s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.869958 -   1.4s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.818750 -   1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.906003 -   1.4s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.612088 -   1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.830299 -   1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.848792 -   1.1s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.922396 -   1.4s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.712608 -   1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.827116 -   1.6s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.913784 -   1.6s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.778117 -   1.3s
[CV] c1=0.4089586111008682, c2=0.07211995679529591 ...................
[CV]  c1=0.4089586111008682, c2=0.07211995679529591, score=0.827116 -   1.5s
[CV] c1=0.3431081113231949, c2=0.10070913156646599 ...................
[CV]  c1=0.3431081113231949, c2=0.10070913156646599, score=0.785941 -   1.5s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.859362 -   1.5s
[CV] c1=0.35050990293106027, c2=0.062158504077829205 .................
[CV]  c1=0.35050990293106027, c2=0.062158504077829205, score=0.814418 -   1.6s
[CV] c1=0.11098709687950105, c2=0.0012964773754647193 ................
[CV]  c1=0.11098709687950105, c2=0.0012964773754647193, score=0.939803 -   1.4s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.907533 -   1.6s
[CV] c1=0.3531857394293691, c2=0.028403481397008597 ..................
[CV]  c1=0.3531857394293691, c2=0.028403481397008597, score=0.839546 -   1.5s
[CV] c1=1.7692696573575095, c2=0.014769125134101722 ..................
[CV]  c1=1.7692696573575095, c2=0.014769125134101722, score=0.719375 -   1.3s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.849255 -   1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.806478 -   1.2s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.896776 -   1.4s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.884219 -   1.4s
[CV] c1=0.5525328047238595, c2=0.09184172427704333 ...................
[CV]  c1=0.5525328047238595, c2=0.09184172427704333, score=0.910483 -   1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.841204 -   1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.601824 -   1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.806478 -   1.4s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.863344 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.854202 -   1.4s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.856387 -   1.3s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.812996 -   1.3s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.908387 -   1.6s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.869996 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.908387 -   1.5s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.854811 -   1.4s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.902496 -   1.2s
[CV] c1=0.9489299883913463, c2=0.08651523595457483 ...................
[CV]  c1=0.9489299883913463, c2=0.08651523595457483, score=0.792413 -   1.5s
[CV] c1=0.004944498956920931, c2=0.035071672138884735 ................
[CV]  c1=0.004944498956920931, c2=0.035071672138884735, score=0.859339 -   1.5s
[CV] c1=1.064584223532424, c2=0.010140146677527086 ...................
[CV]  c1=1.064584223532424, c2=0.010140146677527086, score=0.818821 -   1.4s
[CV] c1=0.004633722592074594, c2=0.10886882710897013 .................
[CV]  c1=0.004633722592074594, c2=0.10886882710897013, score=0.952892 -   1.5s
[CV] c1=1.138816237017488, c2=0.03695236961293207 ....................
[CV]  c1=1.138816237017488, c2=0.03695236961293207, score=0.792413 -   1.2s
Training done in: 9.689625s
     Saving training model...
        Saving training model done in: 0.014153s
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Prediction done in: 0.041572s