Run6_v2.txt 30.1 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_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: _v2
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
   Sentences training data: 283
   Sentences test data: 122
Reading corpus done in: 0.003824s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
            0      1
0       lemma      1
1      postag     CD
2    -1:lemma     pq
3   -1:postag     NN
4      hUpper  False
5      hLower  False
6      hGreek  False
7        symb  False
8    word[:1]      1
9    -2:lemma  δsoxs
10  -2:postag     NN
--------------------------- FeaturesTest -----------------------------
            0          1
0       lemma  delta-fnr
1      postag         NN
2    -1:lemma          _
3   -1:postag         NN
4    +1:lemma          _
5   +1:postag         CD
6      hUpper      False
7      hLower      False
8      hGreek      False
9        symb       True
10   word[:1]          d
11   word[:2]         de
12   -2:lemma    affyexp
13  -2:postag         JJ
14   +2:lemma    glucose
15  +2:postag         NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.748989 -   1.5s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.688607 -   1.2s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.705446 -   1.3s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.844579 -   1.6s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.682226 -   1.5s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.701013 -   1.3s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.895566 -   1.8s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.719074 -   1.7s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.724487 -   1.6s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.868519 -   1.1s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.682226 -   1.4s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.947516 -   1.6s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.933155 -   1.6s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.727054 -   1.3s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.917847 -   1.3s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.738970 -   1.3s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.907093 -   1.6s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.868659 -   1.7s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.780640 -   1.5s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.683958 -   1.4s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.705265 -   1.4s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.732294 -   1.6s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.931297 -   1.9s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.878329 -   1.6s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.773191 -   1.4s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.885638 -   1.6s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.891699 -   1.7s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.673861 -   1.6s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.842875 -   1.7s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.868519 -   1.3s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.759154 -   1.4s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.796438 -   1.5s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.880312 -   1.8s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.734892 -   1.6s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.660504 -   1.1s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.748989 -   1.6s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.688077 -   1.4s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.752420 -   1.6s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.754344 -   1.6s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.698897 -   1.1s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.914825 -   1.6s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.911961 -   1.6s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.796825 -   1.6s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.885638 -   1.7s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.704835 -   1.3s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.648856 -   1.5s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.721111 -   1.5s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.786586 -   1.5s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.653316 -   1.5s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.673792 -   1.4s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.784018 -   1.5s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.746614 -   1.7s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.700287 -   1.5s
[CV] c1=0.6399264634452653, c2=0.014870218135147216 ..................
[CV]  c1=0.6399264634452653, c2=0.014870218135147216, score=0.940069 -   1.6s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.891699 -   1.4s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.730917 -   1.6s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.682226 -   1.4s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.759154 -   1.8s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.713594 -   1.2s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.893607 -   1.6s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.923873 -   1.6s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.631616 -   1.4s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.907061 -   1.8s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.859105 -   1.4s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.706154 -   1.5s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.885638 -   1.6s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.928523 -   1.6s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.891699 -   1.7s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.891699 -   1.6s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.786586 -   1.3s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.724487 -   1.5s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.745942 -   1.7s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.891015 -   1.6s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.889925 -   1.6s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.729157 -   1.6s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.779671 -   1.6s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.715316 -   1.6s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.916959 -   1.6s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.774444 -   1.5s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.766425 -   1.5s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.923873 -   1.6s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.889925 -   1.5s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.727640 -   1.9s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.716285 -   1.5s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.926662 -   1.3s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.881840 -   1.8s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.732929 -   1.5s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.880312 -   1.8s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.626853 -   1.1s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.906414 -   1.3s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.868519 -   1.6s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.865839 -   1.6s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.737479 -   1.3s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.735598 -   1.6s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.752420 -   1.5s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.882932 -   1.8s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.932824 -   1.7s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.706813 -   1.7s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.643342 -   1.4s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.705446 -   1.2s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.868659 -   1.7s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.724487 -   1.7s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.662305 -   1.5s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.940602 -   1.5s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.875198 -   1.7s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.891699 -   1.7s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.794216 -   1.6s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.918895 -   1.6s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.859105 -   1.3s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.889925 -   1.6s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.911961 -   1.7s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.889014 -   1.7s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.679797 -   1.3s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.735598 -   1.5s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.874515 -   1.7s
[CV] c1=0.5185417642698361, c2=0.053008807244735806 ..................
[CV]  c1=0.5185417642698361, c2=0.053008807244735806, score=0.734444 -   1.5s
[CV] c1=0.0027865899296892344, c2=0.0322630560189459 .................
[CV]  c1=0.0027865899296892344, c2=0.0322630560189459, score=0.903099 -   1.6s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.790731 -   1.7s
[CV] c1=0.07859831333888312, c2=0.07646449848130295 ..................
[CV]  c1=0.07859831333888312, c2=0.07646449848130295, score=0.906414 -   1.7s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.740102 -   2.1s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.696425 -   1.5s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.689893 -   1.4s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.826329 -   1.7s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.818562 -   1.3s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.891699 -   1.8s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.786586 -   1.5s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.885638 -   1.7s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.787374 -   1.5s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.889925 -   1.5s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.777509 -   1.7s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.780640 -   1.5s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.885638 -   1.6s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.874108 -   1.5s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.724487 -   1.3s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.760430 -   1.5s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.868519 -   1.7s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.923873 -   1.7s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.745942 -   1.6s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.686160 -   1.3s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.860451 -   1.7s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.723196 -   1.3s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.630336 -   1.4s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.729157 -   1.5s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.891699 -   1.5s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.737084 -   1.6s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.790731 -   1.6s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.802981 -   1.5s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.726092 -   1.5s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.885638 -   1.2s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.735598 -   1.9s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.703965 -   1.3s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.870490 -   1.7s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.866025 -   1.7s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.940602 -   1.4s
[CV] c1=0.11430921774270934, c2=0.06174595493921575 ..................
[CV]  c1=0.11430921774270934, c2=0.06174595493921575, score=0.746614 -   1.6s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.933576 -   1.6s
[CV] c1=0.5229213398180802, c2=0.05988470409107292 ...................
[CV]  c1=0.5229213398180802, c2=0.05988470409107292, score=0.759154 -   1.5s
[CV] c1=1.0068963881008774, c2=0.0209795411094058 ....................
[CV]  c1=1.0068963881008774, c2=0.0209795411094058, score=0.752420 -   1.5s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.703865 -   1.5s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.881840 -   1.4s
[CV] c1=0.25383138714597037, c2=0.04263753154943412 ..................
[CV]  c1=0.25383138714597037, c2=0.04263753154943412, score=0.790731 -   1.7s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.724487 -   1.8s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.772487 -   1.5s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.780640 -   1.2s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.796445 -   1.5s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.856715 -   1.6s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.759154 -   1.8s
[CV] c1=0.35338694963813927, c2=0.027153986749367698 .................
[CV]  c1=0.35338694963813927, c2=0.027153986749367698, score=0.696425 -   2.1s
[CV] c1=0.031180803180743573, c2=0.07896645089543503 .................
[CV]  c1=0.031180803180743573, c2=0.07896645089543503, score=0.903099 -   1.5s
[CV] c1=1.3873487379708354, c2=0.05280678047492682 ...................
[CV]  c1=1.3873487379708354, c2=0.05280678047492682, score=0.629121 -   1.3s
[CV] c1=0.4188873236253328, c2=0.0026616054692428534 .................
[CV]  c1=0.4188873236253328, c2=0.0026616054692428534, score=0.727640 -   1.7s
[CV] c1=0.15577693298267048, c2=0.06637448911598333 ..................
[CV]  c1=0.15577693298267048, c2=0.06637448911598333, score=0.688919 -   1.6s
[CV] c1=0.823900513809091, c2=0.0387534873299443 .....................
[CV]  c1=0.823900513809091, c2=0.0387534873299443, score=0.634732 -   1.5s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.714227 -   1.4s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.736407 -   1.2s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.706154 -   1.6s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.873506 -   1.7s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.725229 -   1.8s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.914459 -   1.5s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.705264 -   1.0s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.891699 -   1.8s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.759154 -   1.5s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.881296 -   1.5s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.891699 -   1.6s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.895584 -   1.4s
[CV] c1=0.2615074589465166, c2=0.00276705652339924 ...................
[CV]  c1=0.2615074589465166, c2=0.00276705652339924, score=0.933576 -   1.9s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.727640 -   1.7s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.894300 -   1.7s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.903099 -   1.7s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.759154 -   1.2s
[CV] c1=0.12876611002706792, c2=0.005687634151887815 .................
[CV]  c1=0.12876611002706792, c2=0.005687634151887815, score=0.914459 -   1.6s
[CV] c1=0.4343684628584727, c2=0.035865115766266005 ..................
[CV]  c1=0.4343684628584727, c2=0.035865115766266005, score=0.926812 -   1.5s
[CV] c1=0.4187966865740437, c2=0.19166197167501114 ...................
[CV]  c1=0.4187966865740437, c2=0.19166197167501114, score=0.855051 -   1.6s
[CV] c1=0.010635150805068118, c2=0.013559125772358571 ................
[CV]  c1=0.010635150805068118, c2=0.013559125772358571, score=0.886041 -   1.6s
[CV] c1=0.5348883068759939, c2=0.00832448452340161 ...................
[CV]  c1=0.5348883068759939, c2=0.00832448452340161, score=0.933155 -   1.2s
Training done in: 10.407644s
     Saving training model...
        Saving training model done in: 0.013260s
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Prediction done in: 0.035441s