Run7_v1.txt
28.5 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
-------------------------------- 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: False True
Report file: _v9
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 283
Sentences test data: 122
Reading corpus done in: 0.003661s
{'lemma': 'δsoxs', 'postag': 'NN', '+1:lemma': 'pq', '+1:postag': 'NN'}
{'lemma': 'affyexp', 'postag': 'JJ', '+1:lemma': '_', '+1:postag': 'NN'}
Fitting 10 folds for each of 20 candidates, totalling 200 fits
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.568777 - 0.8s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.761418 - 1.3s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.815463 - 1.1s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.761418 - 1.1s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.753693 - 1.1s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.651934 - 1.0s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.789190 - 1.2s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.558164 - 0.9s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.860729 - 1.2s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.794740 - 1.1s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.866790 - 0.8s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.666440 - 1.0s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.691890 - 1.0s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.824341 - 1.2s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.694072 - 1.2s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.761418 - 1.1s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.662630 - 1.3s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.703150 - 1.2s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.659253 - 1.0s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.659121 - 1.0s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.538621 - 1.0s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.712560 - 1.1s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.920970 - 1.1s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.852821 - 1.2s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.652192 - 0.8s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.716266 - 1.2s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.716676 - 1.2s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.867889 - 1.1s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.739174 - 1.2s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.723492 - 1.0s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.857493 - 1.2s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.826261 - 1.3s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.553248 - 1.1s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.561630 - 1.2s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.923613 - 1.2s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.843407 - 1.1s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.656999 - 1.0s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.899703 - 1.1s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.891760 - 1.2s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.844400 - 1.1s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.920970 - 1.2s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.555648 - 0.9s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.588673 - 1.2s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.832206 - 1.1s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.607039 - 0.9s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.843338 - 1.2s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.787287 - 1.2s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.855506 - 1.1s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.708065 - 1.3s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.741434 - 1.1s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.904567 - 1.1s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.870586 - 1.2s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.592492 - 1.0s
[CV] c1=0.7882460794764874, c2=0.008314409656759104 ..................
[CV] c1=0.7882460794764874, c2=0.008314409656759104, score=0.903565 - 1.2s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.843338 - 1.2s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.631269 - 0.9s
[CV] c1=0.8830586244748654, c2=0.08016526354894071 ...................
[CV] c1=0.8830586244748654, c2=0.08016526354894071, score=0.691841 - 1.1s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.775906 - 1.2s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.720311 - 1.2s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.571166 - 0.9s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.906853 - 1.1s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.856715 - 1.1s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.773116 - 1.1s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.654823 - 1.1s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.891760 - 1.1s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.674776 - 1.0s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.787287 - 1.2s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.660064 - 1.1s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.607039 - 1.0s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.747150 - 1.1s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.766379 - 1.1s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.698636 - 1.1s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.596309 - 1.1s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.654694 - 1.1s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.920970 - 1.2s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.721334 - 1.1s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.678696 - 1.2s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.535665 - 1.2s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.881938 - 1.2s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.852821 - 1.1s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.866790 - 1.3s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.556324 - 0.9s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.507480 - 0.9s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.848001 - 1.2s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.712255 - 1.1s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.848230 - 1.1s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.704526 - 1.2s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.757867 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.628354 - 1.0s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.935386 - 1.1s
[CV] c1=0.6043003012819512, c2=0.0016246066449729678 .................
[CV] c1=0.6043003012819512, c2=0.0016246066449729678, score=0.899703 - 1.2s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.716676 - 1.2s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.678203 - 1.1s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.730124 - 1.2s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.739174 - 1.1s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.938387 - 1.2s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.873262 - 1.2s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.778713 - 1.1s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.906853 - 1.1s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.687750 - 1.1s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.679766 - 1.2s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.712560 - 1.1s
[CV] c1=2.2502498485352547, c2=0.014818926001867778 ..................
[CV] c1=2.2502498485352547, c2=0.014818926001867778, score=0.568556 - 1.1s
[CV] c1=0.061316816538251634, c2=0.10728243189441995 .................
[CV] c1=0.061316816538251634, c2=0.10728243189441995, score=0.875991 - 1.2s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.891760 - 1.2s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.906853 - 1.2s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.582068 - 1.1s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.562931 - 1.0s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.758770 - 1.0s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.802426 - 1.2s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.718941 - 1.1s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.861675 - 1.2s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.891760 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.906294 - 1.0s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.743125 - 1.2s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.871210 - 1.3s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.899703 - 1.0s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.694072 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.819818 - 1.1s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.871555 - 1.2s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.607625 - 1.0s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.919762 - 1.1s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.823922 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.841822 - 1.0s
[CV] c1=0.03962800005233316, c2=0.022576612705236622 .................
[CV] c1=0.03962800005233316, c2=0.022576612705236622, score=0.763058 - 1.2s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.848001 - 1.3s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.656490 - 1.1s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.649303 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.704237 - 1.2s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.698636 - 1.1s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.717126 - 1.3s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.753693 - 1.1s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.852821 - 1.2s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.724515 - 0.9s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.912680 - 1.2s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.643620 - 1.1s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.643620 - 1.1s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.654823 - 1.0s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.892456 - 1.0s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.679766 - 1.0s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.741434 - 1.2s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.729308 - 1.1s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.912680 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.674703 - 1.1s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.920970 - 1.1s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.723537 - 1.3s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.682607 - 1.2s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.906853 - 1.1s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.654817 - 0.7s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.710539 - 1.1s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.598446 - 1.0s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.761818 - 1.2s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.718872 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.575917 - 1.0s
[CV] c1=0.8576127193843588, c2=0.011655958946285804 ..................
[CV] c1=0.8576127193843588, c2=0.011655958946285804, score=0.836651 - 1.1s
[CV] c1=0.18334620784152844, c2=0.008065728975440238 .................
[CV] c1=0.18334620784152844, c2=0.008065728975440238, score=0.741434 - 1.2s
[CV] c1=0.9896982442127485, c2=0.029349684897034673 ..................
[CV] c1=0.9896982442127485, c2=0.029349684897034673, score=0.870586 - 1.3s
[CV] c1=0.7431358277276424, c2=0.011105476280036924 ..................
[CV] c1=0.7431358277276424, c2=0.011105476280036924, score=0.753693 - 1.1s
[CV] c1=0.2936978694984962, c2=0.18231632927233646 ...................
[CV] c1=0.2936978694984962, c2=0.18231632927233646, score=0.717219 - 1.1s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.899703 - 1.3s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.517508 - 0.9s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.788076 - 1.2s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.877650 - 1.2s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.935386 - 0.9s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.841313 - 1.2s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.673654 - 1.3s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.518602 - 1.0s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.654694 - 1.2s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.741434 - 0.9s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.863440 - 1.1s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.789900 - 1.2s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.698163 - 1.1s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.730124 - 1.0s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.664655 - 1.0s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.570419 - 0.9s
[CV] c1=0.09824882728525007, c2=0.01967357302620265 ..................
[CV] c1=0.09824882728525007, c2=0.01967357302620265, score=0.920970 - 1.1s
[CV] c1=0.5517747693290754, c2=0.03723059660924028 ...................
[CV] c1=0.5517747693290754, c2=0.03723059660924028, score=0.852821 - 1.2s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.720311 - 1.3s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.923613 - 0.8s
[CV] c1=0.38596509561932013, c2=0.021114690490169043 .................
[CV] c1=0.38596509561932013, c2=0.021114690490169043, score=0.772136 - 1.3s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.843581 - 1.2s
[CV] c1=0.4160233685238722, c2=0.015614531623244441 ..................
[CV] c1=0.4160233685238722, c2=0.015614531623244441, score=0.679766 - 1.0s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.875991 - 1.1s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.707036 - 0.9s
[CV] c1=0.6639775093102331, c2=0.05327533729445978 ...................
[CV] c1=0.6639775093102331, c2=0.05327533729445978, score=0.682045 - 1.2s
[CV] c1=1.6387163642774465, c2=0.006347413830953892 ..................
[CV] c1=1.6387163642774465, c2=0.006347413830953892, score=0.599660 - 1.3s
[CV] c1=1.4731035528519316, c2=0.0985918850323886 ....................
[CV] c1=1.4731035528519316, c2=0.0985918850323886, score=0.605840 - 1.1s
[CV] c1=0.03993462764763037, c2=0.10539193423951572 ..................
[CV] c1=0.03993462764763037, c2=0.10539193423951572, score=0.866790 - 1.2s
[CV] c1=0.011903408156662585, c2=0.0023869256052412744 ...............
[CV] c1=0.011903408156662585, c2=0.0023869256052412744, score=0.927704 - 0.9s
Training done in: 7.249866s
Saving training model...
Saving training model done in: 0.014392s
*********************************
Prediction done in: 0.025039s