Run8_v10.txt
30.4 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
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
-------------------------------- 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 True
Report file: _v10
Exclude symbols: False
-------------------------------- PROCESSING --------------------------------
Reading corpus...
Sentences training data: 286
Sentences test data: 123
Reading corpus done in: 0.003613s
-------------------------------- 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 word 2
10 isUpper False
11 isLower False
12 isGreek False
13 isNumber True
14 -1:word fructose
15 -2:lemma Cra
16 -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 word delta-arcA
13 isUpper False
14 isLower False
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=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.856131 - 1.3s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.850628 - 1.8s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.855584 - 1.8s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.805243 - 1.9s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.860618 - 1.9s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.817562 - 1.5s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.936699 - 1.8s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.839785 - 1.6s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.940884 - 1.7s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.880183 - 1.6s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.946646 - 1.8s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.904483 - 1.6s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.931991 - 1.8s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.927469 - 1.9s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.831340 - 1.8s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.931991 - 1.8s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.860367 - 1.6s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.931487 - 1.8s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.843262 - 1.9s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.694284 - 1.7s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.684520 - 1.4s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.860618 - 1.7s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.866388 - 2.0s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.792923 - 1.8s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.834495 - 2.0s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.823620 - 1.7s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.862461 - 1.6s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.835917 - 1.8s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.931991 - 1.6s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.866388 - 1.5s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.904483 - 1.5s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.931991 - 1.7s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.834436 - 1.8s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.820947 - 1.7s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.923585 - 2.2s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.819500 - 1.7s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.819500 - 1.7s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.886301 - 1.6s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.932900 - 1.9s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.831561 - 1.8s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.859499 - 1.6s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.950725 - 1.8s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.919606 - 1.8s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.876202 - 1.7s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.922774 - 1.9s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.922774 - 1.7s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.857572 - 1.9s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.854858 - 1.8s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.816251 - 1.9s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.932775 - 1.9s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.873704 - 1.7s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.848780 - 1.9s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.867297 - 1.8s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.852277 - 1.9s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.946646 - 2.0s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.936699 - 1.8s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.889913 - 1.7s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.872798 - 1.8s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.854009 - 1.8s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.849184 - 1.8s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.922774 - 1.7s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.759900 - 1.4s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.834495 - 1.8s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.701018 - 1.8s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.834436 - 1.9s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.857572 - 2.0s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.701018 - 1.7s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.731222 - 2.0s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.881053 - 1.7s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.931991 - 1.8s
[CV] c1=0.4420415052296795, c2=0.07721906671833131 ...................
[CV] c1=0.4420415052296795, c2=0.07721906671833131, score=0.848780 - 1.4s
[CV] c1=0.40509433275603074, c2=0.06406543656353396 ..................
[CV] c1=0.40509433275603074, c2=0.06406543656353396, score=0.693016 - 1.7s
[CV] c1=0.006371899009903469, c2=0.06787470837280492 .................
[CV] c1=0.006371899009903469, c2=0.06787470837280492, score=0.698450 - 1.9s
[CV] c1=0.5360507066860308, c2=0.22373749787706054 ...................
[CV] c1=0.5360507066860308, c2=0.22373749787706054, score=0.677786 - 1.9s
[CV] c1=0.41559189389198053, c2=0.024104836626471112 .................
[CV] c1=0.41559189389198053, c2=0.024104836626471112, score=0.693016 - 1.9s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.857594 - 1.7s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.816747 - 1.5s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.946646 - 1.8s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.935984 - 1.7s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.897012 - 1.7s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.677786 - 1.9s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.848780 - 1.7s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.931991 - 1.9s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.852019 - 1.9s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.863117 - 1.6s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.950725 - 2.0s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.827485 - 1.7s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.857572 - 1.7s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.839785 - 1.7s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.849184 - 1.6s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.834495 - 1.8s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.932900 - 1.8s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.916643 - 1.7s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.864903 - 1.6s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.950876 - 1.6s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.652822 - 1.7s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.940537 - 1.8s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.839443 - 1.6s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.855735 - 1.8s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.849255 - 1.6s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.868123 - 1.8s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.931991 - 1.7s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.886480 - 1.7s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.829534 - 1.9s
[CV] c1=0.012363125351600902, c2=0.1572507114704887 ..................
[CV] c1=0.012363125351600902, c2=0.1572507114704887, score=0.837423 - 1.8s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.819500 - 1.8s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.834781 - 1.8s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.925645 - 1.8s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.872798 - 1.8s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.866388 - 1.6s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.866388 - 1.7s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.747737 - 1.7s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.871771 - 1.5s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.841626 - 1.8s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.863117 - 1.4s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.932900 - 1.8s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.861159 - 1.8s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.931991 - 1.8s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.946646 - 1.7s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.834436 - 1.6s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.827485 - 1.8s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.933245 - 1.7s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.865754 - 1.6s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.899527 - 1.7s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.837423 - 1.5s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.926690 - 1.7s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.812135 - 1.7s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.936699 - 2.0s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.922774 - 1.6s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.809959 - 1.3s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.784847 - 1.9s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.901459 - 1.7s
[CV] c1=0.3472271220144462, c2=0.014176061322889857 ..................
[CV] c1=0.3472271220144462, c2=0.014176061322889857, score=0.831561 - 1.7s
[CV] c1=0.15298119165388915, c2=0.018482656916134235 .................
[CV] c1=0.15298119165388915, c2=0.018482656916134235, score=0.956017 - 2.1s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.698450 - 1.6s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.883693 - 1.8s
[CV] c1=0.2336502013872894, c2=0.09318602763483955 ...................
[CV] c1=0.2336502013872894, c2=0.09318602763483955, score=0.946103 - 1.8s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.792847 - 1.9s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.712400 - 1.9s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.926835 - 1.6s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.827616 - 2.0s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.834495 - 1.9s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.946103 - 2.0s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.817562 - 1.6s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.854858 - 1.4s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.698450 - 1.7s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.825574 - 1.6s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.822834 - 1.8s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.927509 - 1.8s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.939823 - 1.5s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.931991 - 1.7s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.633535 - 1.8s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.844415 - 1.8s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.857594 - 1.8s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.917473 - 1.3s
[CV] c1=0.4217142984283428, c2=0.1679065014088753 ....................
[CV] c1=0.4217142984283428, c2=0.1679065014088753, score=0.936674 - 1.8s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.629526 - 1.8s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.834495 - 1.9s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.831561 - 1.8s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.790503 - 1.5s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.855584 - 1.8s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.834495 - 1.9s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.872206 - 1.7s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.647210 - 1.8s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.821826 - 1.4s
[CV] c1=0.7548748937747425, c2=0.01567613490693052 ...................
[CV] c1=0.7548748937747425, c2=0.01567613490693052, score=0.815186 - 1.7s
[CV] c1=0.8144879781785279, c2=0.024720227111225807 ..................
[CV] c1=0.8144879781785279, c2=0.024720227111225807, score=0.927028 - 1.8s
[CV] c1=0.28682775544038513, c2=0.08729987447030063 ..................
[CV] c1=0.28682775544038513, c2=0.08729987447030063, score=0.709513 - 1.8s
[CV] c1=0.4023568295081368, c2=0.005508317640747278 ..................
[CV] c1=0.4023568295081368, c2=0.005508317640747278, score=0.834495 - 1.8s
[CV] c1=0.011895855801865073, c2=0.13347483267807422 .................
[CV] c1=0.011895855801865073, c2=0.13347483267807422, score=0.931991 - 1.4s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.869204 - 1.7s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.858068 - 1.9s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.965003 - 1.8s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.827485 - 1.8s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.793883 - 1.2s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.929431 - 1.8s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.811937 - 1.8s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.878301 - 1.7s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.932900 - 1.8s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.928279 - 1.2s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.872206 - 1.8s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.917821 - 1.7s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.694284 - 1.8s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.834495 - 2.0s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.851880 - 1.4s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.854858 - 1.7s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.827485 - 1.7s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.931991 - 1.7s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.781928 - 1.8s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.607714 - 1.5s
[CV] c1=0.0006462709537178506, c2=0.04908644406590121 ................
[CV] c1=0.0006462709537178506, c2=0.04908644406590121, score=0.834436 - 1.8s
[CV] c1=0.8064748804871678, c2=0.0566511582931341 ....................
[CV] c1=0.8064748804871678, c2=0.0566511582931341, score=0.932900 - 2.0s
[CV] c1=0.034331838389826896, c2=0.07441350049485611 .................
[CV] c1=0.034331838389826896, c2=0.07441350049485611, score=0.939823 - 1.8s
[CV] c1=0.7303370849262278, c2=0.0338506308830609 ....................
[CV] c1=0.7303370849262278, c2=0.0338506308830609, score=0.819500 - 1.8s
[CV] c1=1.327429294256592, c2=0.014318433897260289 ...................
[CV] c1=1.327429294256592, c2=0.014318433897260289, score=0.799616 - 1.2s
Training done in: 11.832994s
Saving training model...
Saving training model done in: 0.013243s
*********************************
Prediction done in: 0.046246s