Run6_v10.txt
29.4 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
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
-------------------------------- PARAMETERS --------------------------------
Path of training data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with training data set: training-data-set-70.txt
Path of test data set: /home/egaytan/automatic-extraction-growth-conditions/CRF/data-sets
File with test data set: test-data-set-30.txt
Exclude stop words: False
Levels: True False
Report file: _v10
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003691s
-------------------------------- FEATURES --------------------------------
--------------------------Features Training ---------------------------
0 1
0 lemma 2
1 postag CD
2 -1:lemma fructose
3 -1:postag NN
4 hUpper False
5 hLower False
6 hGreek False
7 symb False
8 word[:1] 2
9 -2:lemma Cra
10 -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 hUpper True
7 hLower True
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=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.793425 - 1.4s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.867343 - 1.3s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.690464 - 1.7s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.927296 - 1.5s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.865012 - 1.4s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.929588 - 1.5s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.794911 - 1.3s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.879117 - 1.7s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.778490 - 1.3s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.865854 - 1.4s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.935899 - 1.4s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.867343 - 1.4s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.821783 - 1.5s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.939330 - 1.5s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.853112 - 1.3s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.865456 - 1.4s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.894301 - 1.3s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.865456 - 1.3s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.894474 - 1.4s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.834907 - 1.3s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.858859 - 1.4s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.841065 - 1.3s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.935899 - 1.6s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.828226 - 1.6s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.854635 - 1.3s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.757614 - 1.4s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.812241 - 1.4s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.835814 - 1.6s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.879798 - 1.6s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.700963 - 1.8s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.900542 - 1.2s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.736765 - 1.6s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.798780 - 1.6s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.798780 - 1.8s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.835917 - 1.5s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.783001 - 1.5s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.733105 - 1.6s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.835917 - 1.4s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.922662 - 1.6s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.881053 - 1.5s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.733105 - 1.6s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.827485 - 1.4s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.927296 - 1.6s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.852443 - 1.6s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.800079 - 1.6s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.826682 - 1.3s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.813331 - 1.6s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.946103 - 1.7s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.889591 - 1.6s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.935899 - 1.5s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.932061 - 1.7s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.939262 - 1.6s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.786606 - 1.5s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.841250 - 1.7s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.578499 - 1.4s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.651358 - 1.6s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.862461 - 1.4s
[CV] c1=0.33724815678767384, c2=0.15538629766986978 ..................
[CV] c1=0.33724815678767384, c2=0.15538629766986978, score=0.690464 - 1.9s
[CV] c1=0.2074777767896592, c2=0.02494933488641053 ...................
[CV] c1=0.2074777767896592, c2=0.02494933488641053, score=0.946103 - 1.7s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.865747 - 1.6s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.624531 - 1.6s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.843508 - 1.6s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.876459 - 1.3s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.922539 - 1.4s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.762974 - 1.5s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.847753 - 1.5s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.806351 - 1.3s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.880403 - 1.4s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.763999 - 1.5s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.923088 - 1.5s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.813331 - 1.5s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.922539 - 1.2s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.926416 - 1.4s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.858859 - 1.3s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.857836 - 1.5s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.922388 - 1.4s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.914935 - 1.6s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.807541 - 1.5s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.854088 - 1.5s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.918393 - 1.4s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.711517 - 1.4s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.763999 - 1.5s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.857572 - 1.5s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.861553 - 1.2s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.852644 - 1.4s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.931826 - 1.5s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.843508 - 1.7s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.599896 - 1.5s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.816823 - 1.6s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.879162 - 1.4s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.904019 - 1.4s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.753193 - 1.7s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.922388 - 1.5s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.932061 - 1.5s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.902301 - 1.4s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.813331 - 1.6s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.894301 - 1.5s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.789267 - 1.5s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.894301 - 1.5s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.924447 - 1.4s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.951395 - 1.6s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.858859 - 1.6s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.778490 - 1.2s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.826650 - 1.3s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.656233 - 1.4s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.860761 - 1.5s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.852019 - 1.4s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.826698 - 1.5s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.618972 - 1.4s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.838737 - 1.4s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.922539 - 1.3s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.932061 - 1.6s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.819518 - 1.6s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.845018 - 1.2s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.725655 - 1.6s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.931826 - 1.5s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.862377 - 1.5s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.728502 - 1.5s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.904019 - 1.3s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.824101 - 1.5s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.849255 - 1.5s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.852603 - 1.6s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.807541 - 1.4s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.933427 - 1.2s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.834495 - 1.5s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.834436 - 1.4s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.918102 - 1.5s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.923088 - 1.4s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.813331 - 1.4s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.792801 - 1.4s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.922388 - 1.6s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.871771 - 1.6s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.733105 - 1.6s
[CV] c1=0.15419879816724802, c2=0.012826859604695727 .................
[CV] c1=0.15419879816724802, c2=0.012826859604695727, score=0.951395 - 1.6s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.857594 - 1.5s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.867318 - 1.8s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.846341 - 1.6s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.867343 - 1.4s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.879798 - 1.2s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.898930 - 1.6s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.881616 - 1.4s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.935899 - 1.4s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.901459 - 1.5s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.928279 - 1.3s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.914826 - 1.5s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.793739 - 1.4s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.902301 - 1.3s
[CV] c1=1.2084188241795155, c2=0.05654297208049296 ...................
[CV] c1=1.2084188241795155, c2=0.05654297208049296, score=0.808333 - 1.5s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.744355 - 1.5s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.946103 - 1.6s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.946103 - 1.6s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.853112 - 1.5s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.789267 - 1.3s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.926731 - 1.2s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.864529 - 1.5s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.918393 - 1.3s
[CV] c1=0.09691034944164684, c2=0.004204871857834622 .................
[CV] c1=0.09691034944164684, c2=0.004204871857834622, score=0.917968 - 1.6s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.723972 - 1.5s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.843948 - 1.3s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.914386 - 1.2s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.904019 - 1.3s
[CV] c1=0.1805136966403216, c2=0.07777892802577017 ...................
[CV] c1=0.1805136966403216, c2=0.07777892802577017, score=0.860367 - 1.3s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.877204 - 1.3s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.903885 - 1.3s
[CV] c1=0.7138037380094754, c2=0.09821277598627046 ...................
[CV] c1=0.7138037380094754, c2=0.09821277598627046, score=0.824101 - 1.4s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.725655 - 1.5s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.728502 - 1.7s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.840805 - 1.5s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.922388 - 1.5s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.871305 - 1.1s
[CV] c1=0.7077783869918963, c2=0.018821218321315464 ..................
[CV] c1=0.7077783869918963, c2=0.018821218321315464, score=0.838552 - 1.4s
[CV] c1=0.880769811590579, c2=0.06496317380759915 ....................
[CV] c1=0.880769811590579, c2=0.06496317380759915, score=0.816538 - 1.4s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.951395 - 1.8s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.831561 - 1.6s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.857572 - 1.2s
[CV] c1=0.1226651147490872, c2=0.0059614661118123965 .................
[CV] c1=0.1226651147490872, c2=0.0059614661118123965, score=0.951395 - 1.7s
[CV] c1=0.12921575529399648, c2=0.022522239009519832 .................
[CV] c1=0.12921575529399648, c2=0.022522239009519832, score=0.935899 - 1.6s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.850847 - 1.4s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.921722 - 1.6s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.683730 - 1.4s
[CV] c1=0.16931667210800003, c2=0.01855789911042521 ..................
[CV] c1=0.16931667210800003, c2=0.01855789911042521, score=0.814557 - 1.6s
[CV] c1=0.49390388777624017, c2=0.07495517296178955 ..................
[CV] c1=0.49390388777624017, c2=0.07495517296178955, score=0.857594 - 1.3s
[CV] c1=0.16045199952287093, c2=0.03349544150437709 ..................
[CV] c1=0.16045199952287093, c2=0.03349544150437709, score=0.710879 - 1.5s
[CV] c1=1.102798163509896, c2=0.07441446987912796 ....................
[CV] c1=1.102798163509896, c2=0.07441446987912796, score=0.599896 - 1.5s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.839397 - 1.3s
[CV] c1=2.0772840450026786, c2=0.01612403394563899 ...................
[CV] c1=2.0772840450026786, c2=0.01612403394563899, score=0.825639 - 1.4s
[CV] c1=0.9447446796043686, c2=0.014950641482488432 ..................
[CV] c1=0.9447446796043686, c2=0.014950641482488432, score=0.816538 - 1.5s
[CV] c1=0.22034340464816077, c2=0.023290360446083555 .................
[CV] c1=0.22034340464816077, c2=0.023290360446083555, score=0.911621 - 2.0s
[CV] c1=0.2992471675291976, c2=0.04387206593008659 ...................
[CV] c1=0.2992471675291976, c2=0.04387206593008659, score=0.946103 - 1.7s
[CV] c1=0.10042756262488722, c2=0.2272603272440672 ...................
[CV] c1=0.10042756262488722, c2=0.2272603272440672, score=0.922662 - 1.3s
Training done in: 9.974953s
Saving training model...
Saving training model done in: 0.014405s
*********************************
Prediction done in: 0.041326s