Run8_v2.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 True
Report file: _v2
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 283
Sentences test data: 122
Reading corpus done in: 0.003745s
-------------------------------- 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 word 1
10 isUpper False
11 isLower False
12 isGreek False
13 isNumber True
14 -1:word PQ
15 -2:lemma δsoxs
16 -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 word delta-fnr
13 isUpper False
14 isLower True
15 isGreek False
16 isNumber False
17 -1:word _
18 +1:word _
19 -2:lemma affyexp
20 -2:postag JJ
21 +2:lemma glucose
22 +2:postag NN
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.08997152792208764, c2=0.004363773952774669 .................
[CV] c1=0.08997152792208764, c2=0.004363773952774669, score=0.860686 - 1.4s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.856606 - 2.1s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
[CV] c1=0.16114579362036052, c2=0.09197634743194505, score=0.860686 - 1.6s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.711685 - 1.9s
[CV] c1=1.1812306284364236, c2=0.008430514440727933 ..................
[CV] c1=1.1812306284364236, c2=0.008430514440727933, score=0.918560 - 2.1s
[CV] c1=0.08369291557347798, c2=0.012233988100281703 .................
[CV] c1=0.08369291557347798, c2=0.012233988100281703, score=0.715283 - 1.5s
[CV] c1=0.3286068152393628, c2=0.10962981701798313 ...................
[CV] c1=0.3286068152393628, c2=0.10962981701798313, score=0.883499 - 1.9s
[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
[CV] c1=0.6822425755498431, c2=0.020713938001918012, score=0.724487 - 1.9s
[CV] c1=0.37575104918065877, c2=0.014068909404949474 .................
[CV] c1=0.37575104918065877, c2=0.014068909404949474, score=0.680522 - 1.8s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.697314 - 1.5s
[CV] c1=0.08369291557347798, c2=0.012233988100281703 .................
[CV] c1=0.08369291557347798, c2=0.012233988100281703, score=0.860686 - 1.5s
[CV] c1=0.3286068152393628, c2=0.10962981701798313 ...................
[CV] c1=0.3286068152393628, c2=0.10962981701798313, score=0.727640 - 2.1s
[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
[CV] c1=0.6822425755498431, c2=0.020713938001918012, score=0.871735 - 1.7s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.722958 - 1.6s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.860776 - 1.9s
[CV] c1=0.05199276558605893, c2=0.0702365499252205 ...................
[CV] c1=0.05199276558605893, c2=0.0702365499252205, score=0.795468 - 1.6s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.759154 - 1.9s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
[CV] c1=0.16114579362036052, c2=0.09197634743194505, score=0.855051 - 1.9s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.863709 - 1.9s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.778562 - 1.8s
[CV] c1=0.08997152792208764, c2=0.004363773952774669 .................
[CV] c1=0.08997152792208764, c2=0.004363773952774669, score=0.708096 - 1.3s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.727640 - 1.9s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
[CV] c1=0.16114579362036052, c2=0.09197634743194505, score=0.673283 - 2.1s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.845435 - 2.0s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.847925 - 2.1s
[CV] c1=0.05199276558605893, c2=0.0702365499252205 ...................
[CV] c1=0.05199276558605893, c2=0.0702365499252205, score=0.621599 - 1.6s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.717756 - 1.7s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
[CV] c1=0.16114579362036052, c2=0.09197634743194505, score=0.795468 - 1.8s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.801799 - 2.1s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.779671 - 1.9s
[CV] c1=0.08997152792208764, c2=0.004363773952774669 .................
[CV] c1=0.08997152792208764, c2=0.004363773952774669, score=0.961600 - 1.8s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.933241 - 2.0s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
[CV] c1=0.16114579362036052, c2=0.09197634743194505, score=0.706732 - 1.8s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.750626 - 1.9s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.759154 - 1.9s
[CV] c1=0.08997152792208764, c2=0.004363773952774669 .................
[CV] c1=0.08997152792208764, c2=0.004363773952774669, score=0.705910 - 1.5s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.802981 - 1.8s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
[CV] c1=0.16114579362036052, c2=0.09197634743194505, score=0.891699 - 2.0s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.848726 - 2.2s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.933241 - 2.0s
[CV] c1=0.1380082549956592, c2=0.015618296578657088 ..................
[CV] c1=0.1380082549956592, c2=0.015618296578657088, score=0.868519 - 1.8s
[CV] c1=0.14146941159261275, c2=0.0623745074286256 ...................
[CV] c1=0.14146941159261275, c2=0.0623745074286256, score=0.855051 - 1.9s
[CV] c1=0.5149952083751863, c2=0.020547420013119894 ..................
[CV] c1=0.5149952083751863, c2=0.020547420013119894, score=0.790731 - 2.2s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.667213 - 1.9s
[CV] c1=0.08997152792208764, c2=0.004363773952774669 .................
[CV] c1=0.08997152792208764, c2=0.004363773952774669, score=0.906414 - 1.4s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.860682 - 2.0s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
[CV] c1=0.16114579362036052, c2=0.09197634743194505, score=0.917580 - 2.1s
[CV] c1=0.9049035713403341, c2=0.021741456177008588 ..................
[CV] c1=0.9049035713403341, c2=0.021741456177008588, score=0.795856 - 1.9s
[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
[CV] c1=0.603209677420507, c2=0.0025056598967555105, score=0.885638 - 2.0s
[CV] c1=0.08369291557347798, c2=0.012233988100281703 .................
[CV] c1=0.08369291557347798, c2=0.012233988100281703, score=0.746316 - 1.8s
[CV] c1=0.3286068152393628, c2=0.10962981701798313 ...................
[CV] c1=0.3286068152393628, c2=0.10962981701798313, score=0.705446 - 1.7s
[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
[CV] c1=0.6822425755498431, c2=0.020713938001918012, score=0.885638 - 1.9s
[CV] c1=0.37575104918065877, c2=0.014068909404949474 .................
[CV] c1=0.37575104918065877, c2=0.014068909404949474, score=0.896573 - 1.9s
[CV] c1=0.5180245113660787, c2=0.03601101440244791 ...................
[CV] c1=0.5180245113660787, c2=0.03601101440244791, score=0.677691 - 1.6s
[CV] c1=0.05199276558605893, c2=0.0702365499252205 ...................
[CV] c1=0.05199276558605893, c2=0.0702365499252205, score=0.732294 - 1.9s
[CV] c1=0.3286068152393628, c2=0.10962981701798313 ...................
[CV] c1=0.3286068152393628, c2=0.10962981701798313, score=0.895764 - 2.1s
[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
[CV] c1=0.6822425755498431, c2=0.020713938001918012, score=0.802130 - 1.8s
[CV] c1=0.37575104918065877, c2=0.014068909404949474 .................
[CV] c1=0.37575104918065877, c2=0.014068909404949474, score=0.784018 - 1.9s
[CV] c1=0.5180245113660787, c2=0.03601101440244791 ...................
[CV] c1=0.5180245113660787, c2=0.03601101440244791, score=0.860350 - 1.8s
[CV] c1=0.08369291557347798, c2=0.012233988100281703 .................
[CV] c1=0.08369291557347798, c2=0.012233988100281703, score=0.691162 - 1.6s
[CV] c1=0.06155533734282551, c2=0.11747794204884306 ..................
[CV] c1=0.06155533734282551, c2=0.11747794204884306, score=0.735598 - 1.9s
[CV] c1=0.32267196716974095, c2=0.030929293399615435 .................
[CV] c1=0.32267196716974095, c2=0.030929293399615435, score=0.705265 - 1.8s
[CV] c1=0.37575104918065877, c2=0.014068909404949474 .................
[CV] c1=0.37575104918065877, c2=0.014068909404949474, score=0.702864 - 1.6s
[CV] c1=0.5180245113660787, c2=0.03601101440244791 ...................
[CV] c1=0.5180245113660787, c2=0.03601101440244791, score=0.730482 - 1.8s
[CV] c1=0.1380082549956592, c2=0.015618296578657088 ..................
[CV] c1=0.1380082549956592, c2=0.015618296578657088, score=0.680522 - 1.6s
[CV] c1=0.06155533734282551, c2=0.11747794204884306 ..................
[CV] c1=0.06155533734282551, c2=0.11747794204884306, score=0.660504 - 1.8s
[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
[CV] c1=0.6822425755498431, c2=0.020713938001918012, score=0.778562 - 1.8s
[CV] c1=0.37575104918065877, c2=0.014068909404949474 .................
[CV] c1=0.37575104918065877, c2=0.014068909404949474, score=0.917580 - 2.0s
[CV] c1=0.5180245113660787, c2=0.03601101440244791 ...................
[CV] c1=0.5180245113660787, c2=0.03601101440244791, score=0.768697 - 1.7s
[CV] c1=0.05199276558605893, c2=0.0702365499252205 ...................
[CV] c1=0.05199276558605893, c2=0.0702365499252205, score=0.906414 - 2.1s
[CV] c1=0.06155533734282551, c2=0.11747794204884306 ..................
[CV] c1=0.06155533734282551, c2=0.11747794204884306, score=0.900313 - 1.9s
[CV] c1=0.32267196716974095, c2=0.030929293399615435 .................
[CV] c1=0.32267196716974095, c2=0.030929293399615435, score=0.730917 - 1.9s
[CV] c1=0.8844076483955583, c2=0.11585472431298503 ...................
[CV] c1=0.8844076483955583, c2=0.11585472431298503, score=0.657484 - 1.9s
[CV] c1=0.5180245113660787, c2=0.03601101440244791 ...................
[CV] c1=0.5180245113660787, c2=0.03601101440244791, score=0.738645 - 1.6s
[CV] c1=0.1380082549956592, c2=0.015618296578657088 ..................
[CV] c1=0.1380082549956592, c2=0.015618296578657088, score=0.865290 - 1.8s
[CV] c1=0.06155533734282551, c2=0.11747794204884306 ..................
[CV] c1=0.06155533734282551, c2=0.11747794204884306, score=0.618706 - 1.6s
[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
[CV] c1=0.6822425755498431, c2=0.020713938001918012, score=0.868519 - 1.9s
[CV] c1=0.37575104918065877, c2=0.014068909404949474 .................
[CV] c1=0.37575104918065877, c2=0.014068909404949474, score=0.933241 - 1.9s
[CV] c1=0.5180245113660787, c2=0.03601101440244791 ...................
[CV] c1=0.5180245113660787, c2=0.03601101440244791, score=0.906753 - 1.8s
[CV] c1=0.08997152792208764, c2=0.004363773952774669 .................
[CV] c1=0.08997152792208764, c2=0.004363773952774669, score=0.818747 - 1.8s
[CV] c1=0.49898154231973574, c2=0.00020584758644216306 ...............
[CV] c1=0.49898154231973574, c2=0.00020584758644216306, score=0.790731 - 2.0s
[CV] c1=0.16114579362036052, c2=0.09197634743194505 ..................
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[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
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[CV] c1=0.8844076483955583, c2=0.11585472431298503 ...................
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[CV] c1=0.14146941159261275, c2=0.0623745074286256 ...................
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[CV] c1=0.5149952083751863, c2=0.020547420013119894 ..................
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[CV] c1=0.603209677420507, c2=0.0025056598967555105 ..................
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[CV] c1=0.8585868277805841, c2=0.018563372539478897 ..................
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[CV] c1=0.6822425755498431, c2=0.020713938001918012 ..................
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[CV] c1=0.37575104918065877, c2=0.014068909404949474 .................
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[CV] c1=0.1380082549956592, c2=0.015618296578657088 ..................
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[CV] c1=0.5149952083751863, c2=0.020547420013119894 ..................
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[CV] c1=0.8585868277805841, c2=0.018563372539478897 ..................
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[CV] c1=0.8585868277805841, c2=0.018563372539478897 ..................
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[CV] c1=0.08369291557347798, c2=0.012233988100281703 .................
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[CV] c1=0.06155533734282551, c2=0.11747794204884306 ..................
[CV] c1=0.06155533734282551, c2=0.11747794204884306, score=0.855051 - 1.9s
[CV] c1=0.32267196716974095, c2=0.030929293399615435 .................
[CV] c1=0.32267196716974095, c2=0.030929293399615435, score=0.925895 - 2.0s
[CV] c1=1.1812306284364236, c2=0.008430514440727933 ..................
[CV] c1=1.1812306284364236, c2=0.008430514440727933, score=0.699424 - 1.9s
[CV] c1=0.8585868277805841, c2=0.018563372539478897 ..................
[CV] c1=0.8585868277805841, c2=0.018563372539478897, score=0.821625 - 1.7s
[CV] c1=0.08369291557347798, c2=0.012233988100281703 .................
[CV] c1=0.08369291557347798, c2=0.012233988100281703, score=0.908780 - 2.0s
[CV] c1=0.14146941159261275, c2=0.0623745074286256 ...................
[CV] c1=0.14146941159261275, c2=0.0623745074286256, score=0.732294 - 2.2s
[CV] c1=0.5149952083751863, c2=0.020547420013119894 ..................
[CV] c1=0.5149952083751863, c2=0.020547420013119894, score=0.791382 - 1.9s
[CV] c1=1.1812306284364236, c2=0.008430514440727933 ..................
[CV] c1=1.1812306284364236, c2=0.008430514440727933, score=0.827582 - 1.9s
[CV] c1=0.8585868277805841, c2=0.018563372539478897 ..................
[CV] c1=0.8585868277805841, c2=0.018563372539478897, score=0.795856 - 1.7s
Training done in: 12.580321s
Saving training model...
Saving training model done in: 0.013719s
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Prediction done in: 0.043038s