-
Notifications
You must be signed in to change notification settings - Fork 3
/
Copy pathResults.txt
354 lines (348 loc) · 16.2 KB
/
Results.txt
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
Results SISL kernel:knn
Class1
F= 0.415
F = [0.7499999999999999, 0.37499999999999994, 0.37499999999999994, 0.5, 0.37499999999999994, 0.25, 0.25, 0.5, 0.37499999999999994, 0.4]
AUC =0.53
AUC =[0.8, 0.5, 0.5, 0.6000000000000001, 0.5, 0.4, 0.4, 0.6000000000000001, 0.5, 0.5]
Results SISL kernel:knn
Class2
F= 0.0
F = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
AUC =0.5
AUC =[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
Results SISL kernel:knn
Class2
F= 0.0
F = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
AUC =0.5
AUC =[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
Results SISL kernel:knn
Class3
F= 0.0927272727273
F = [0.18181818181818182, 0.18181818181818182, 0, 0.18181818181818182, 0, 0, 0, 0.18181818181818182, 0, 0.19999999999999998]
AUC =0.500555555556
AUC =[0.55, 0.55, 0.45, 0.55, 0.45, 0.45, 0.45, 0.55, 0.45, 0.5555555555555556]
Results SISL kernel:knn
Class4
F= 0.446405228758
F = [0.888888888888889, 0.4444444444444445, 0.4444444444444445, 0.4444444444444445, 0.5555555555555556, 0.4444444444444445, 0.11111111111111112, 0.5555555555555556, 0.22222222222222224, 0.35294117647058826]
AUC =0.498888888889
AUC =[0.9, 0.5, 0.5, 0.5, 0.6, 0.5, 0.20000000000000004, 0.6, 0.30000000000000004, 0.3888888888888889
Results SISL kernel:knn
Class5
F= 0.0
F = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
AUC =0.5
AUC =[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
——————————————————————————————————
———————————————————
#Segunda Vez SISL. knn
Results SISL kernel:knn
Class4
F= 0.520743034056
F = [0.9473684210526316, 0.631578947368421, 0.3157894736842105, 0.5263157894736842, 0.4210526315789474, 0.7368421052631577, 0.3157894736842105, 0.5263157894736842, 0.3157894736842105, 0.47058823529411764]
AUC =0.545
AUC =[0.95, 0.65, 0.35, 0.55, 0.45000000000000007, 0.7499999999999999, 0.35, 0.55, 0.35, 0.5]
Results SISL kernel:knn
Class2
F= 0.0
F = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
AUC =0.5
AUC =[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
Results SISL kernel:knn
Class1
F= 0.29358974359
F = [0.4615384615384615, 0.15384615384615383, 0.4615384615384615, 0.30769230769230765, 0.30769230769230765, 0.15384615384615383, 0.15384615384615383, 0.30769230769230765, 0.4615384615384615, 0.16666666666666666]
AUC =0.539444444444
AUC =[0.6499999999999999, 0.45000000000000007, 0.6499999999999999, 0.55, 0.55, 0.45000000000000007, 0.45000000000000007, 0.55, 0.6499999999999999, 0.4444444444444444]
Results SISL kernel:knn
Class5
F= 0.453571428571
F = [0.7499999999999999, 0.37499999999999994, 0.5, 0.5, 0.37499999999999994, 0.37499999999999994, 0.37499999999999994, 0.5, 0.5, 0.2857142857142857]
AUC =0.564444444444
AUC =[0.8, 0.5, 0.6000000000000001, 0.6000000000000001, 0.5, 0.5, 0.5, 0.6000000000000001, 0.6000000000000001, 0.44444444444444453]
Results SISL kernel:knn
Class3
F= 0.0
F = [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]
AUC =0.5
AUC =[0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5]
————————————————————————————————————————————————————————————————————————————
Results SISL kernel:rbf
Class1
F= 0.565555555556
F = [1.0, 0.6, 0.4000000000000001, 0.4000000000000001, 0.6, 0.6, 0.6, 0.4000000000000001, 0.5, 0.5555555555555556]
AUC =0.565555555556
AUC =[1.0, 0.6, 0.4, 0.4, 0.6, 0.6, 0.6, 0.4, 0.5, 0.5555555555555556]
Results SISL kernel:rbf
Class2
F= 0.482631578947
F = [1.0, 0.5, 0.6, 0.3, 0.3, 0.4000000000000001, 0.4000000000000001, 0.3, 0.5, 0.5263157894736842]
AUC =0.48
AUC =[1.0, 0.5, 0.6, 0.30000000000000004, 0.30000000000000004, 0.4, 0.4, 0.30000000000000004, 0.5, 0.5]
Results SISL kernel:rbf
Class3
F= 0.542631578947
F = [1.0, 0.5, 0.4000000000000001, 0.6, 0.4000000000000001, 0.5, 0.4000000000000001, 0.6, 0.5, 0.5263157894736842]
AUC =0.54
AUC =[1.0, 0.5, 0.4, 0.6, 0.4, 0.5, 0.4, 0.6, 0.5, 0.5]
Results SISL kernel:rbf
Class4
F= 0.563157894737
F = [1.0, 0.5, 0.4000000000000001, 0.4000000000000001, 0.3, 0.6, 0.6, 0.7, 0.5, 0.631578947368421]
AUC =0.561111111111
AUC =[1.0, 0.5, 0.4, 0.4, 0.30000000000000004, 0.6, 0.6, 0.7, 0.5, 0.611111111111111]
Results SISL kernel:rbf
Class5
F= 0.544444444444
F = [1.0, 0.5, 0.5, 0.4000000000000001, 0.7, 0.4000000000000001, 0.5, 0.4000000000000001, 0.6, 0.4444444444444444]
AUC =0.544444444444
AUC =[1.0, 0.5, 0.5, 0.4, 0.7, 0.4, 0.5, 0.4, 0.6, 0.4444444444444444]
Results SIML kernel:linear
Class1
F= 0.495555555556
F = [1.0, 0.5, 0.5, 0.5, 0.4000000000000001, 0.4000000000000001, 0.4000000000000001, 0.3, 0.4000000000000001, 0.5555555555555556]
AUC =0.495555555556
AUC = [1.0, 0.5, 0.5, 0.5, 0.4, 0.4, 0.4, 0.30000000000000004, 0.4, 0.5555555555555556]
Results SIML kernel:linear
Class2
F= 0.515555555556
F = [1.0, 0.6, 0.4000000000000001, 0.5, 0.5, 0.4000000000000001, 0.5, 0.4000000000000001, 0.3, 0.5555555555555556]
AUC =0.515555555556
AUC = [1.0, 0.6, 0.4, 0.5, 0.5, 0.4, 0.5, 0.4, 0.30000000000000004, 0.5555555555555556]
Results SIML kernel:linear
Class3
F= 0.555555555556
F = [1.0, 0.7, 0.5, 0.6, 0.3, 0.4000000000000001, 0.4000000000000001, 0.6, 0.5, 0.5555555555555556]
AUC =0.555555555556
AUC = [1.0, 0.7, 0.5, 0.6, 0.30000000000000004, 0.4, 0.4, 0.6, 0.5, 0.5555555555555556]
Results SIML kernel:linear
Class4
F= 0.565555555556
F = [1.0, 0.3, 0.6, 0.6, 0.4000000000000001, 0.5, 0.5, 0.6, 0.6, 0.5555555555555556]
AUC =0.565555555556
AUC = [1.0, 0.30000000000000004, 0.6, 0.6, 0.4, 0.5, 0.5, 0.6, 0.6, 0.5555555555555556]
Results SIML kernel:linear
Class5
F= 0.545555555556
F = [1.0, 0.6, 0.4000000000000001, 0.4000000000000001, 0.3, 0.6, 0.6, 0.5, 0.5, 0.5555555555555556]
AUC =0.545555555556
AUC = [1.0, 0.6, 0.4, 0.4, 0.30000000000000004, 0.6, 0.6, 0.5, 0.5, 0.5555555555555556]
Results SIML kernel:rbf
Class1
F= 0.563157894737
F = [1.0, 0.5, 0.5, 0.3, 0.4000000000000001, 0.5, 0.5, 0.6, 0.7, 0.631578947368421]
AUC =0.561111111111
AUC = [1.0, 0.5, 0.5, 0.30000000000000004, 0.4, 0.5, 0.5, 0.6, 0.7, 0.611111111111111]
Results SIML kernel:rbf
Class2
F= 0.473333333333
F = [1.0, 0.4000000000000001, 0.4000000000000001, 0.3, 0.5, 0.3, 0.5, 0.5, 0.5, 0.3333333333333333]
AUC =0.473333333333
AUC = [1.0, 0.4, 0.4, 0.30000000000000004, 0.5, 0.30000000000000004, 0.5, 0.5, 0.5, 0.33333333333333337]
Results SIML kernel:rbf
Class3
F= 0.533333333333
F = [1.0, 0.6, 0.3, 0.4000000000000001, 0.4000000000000001, 0.4000000000000001, 0.5, 0.8000000000000002, 0.6, 0.3333333333333333]
AUC =0.533333333333
AUC = [1.0, 0.6, 0.30000000000000004, 0.4, 0.4, 0.4, 0.5, 0.8000000000000002, 0.6, 0.33333333333333337]
Results SIML kernel:rbf
Class4
F= 0.545555555556
F = [1.0, 0.6, 0.4000000000000001, 0.4000000000000001, 0.6, 0.3, 0.5, 0.5, 0.6, 0.5555555555555556]
AUC =0.545555555556
AUC = [1.0, 0.6, 0.4, 0.4, 0.6, 0.30000000000000004, 0.5, 0.5, 0.6, 0.5555555555555556]
Results SIML kernel:rbf
Class5
F= 0.547058823529
F = [1.0, 0.4000000000000001, 0.4000000000000001, 0.6, 0.5, 0.7, 0.3, 0.6, 0.5, 0.47058823529411764]
AUC =0.55
AUC = [1.0, 0.4, 0.4, 0.6, 0.5, 0.7, 0.30000000000000004, 0.6, 0.5, 0.5]
Results MISL
Class1 Algo:<MILpy.Algorithms.EMDD.EMDD object at 0x118091d10>
F mean= 0.602748046587
F = [0.8235294117647058, 0, 0.9473684210526316, 0.5714285714285715, 0, 0.6666666666666666, 0.8235294117647058, 0.5714285714285715, 0.8235294117647058, 0.8]
AUC mean =0.748333333333
AUC = [0.85, 0.5, 0.95, 0.7, 0.5, 0.75, 0.85, 0.7, 0.85, 0.8333333333333333]
Results MISL
Class2 Algo:<MILpy.Algorithms.EMDD.EMDD object at 0x117f88cd0>
F mean= 0.436616161616
F = [0.888888888888889, 0.18181818181818182, 0.33333333333333337, 0.6666666666666666, 0.7499999999999999, 0.33333333333333337, 0.33333333333333337, 0.33333333333333337, 0.18181818181818182, 0.3636363636363636]
AUC mean =0.656111111111
AUC = [0.9, 0.55, 0.6000000000000001, 0.75, 0.8, 0.6000000000000001, 0.6000000000000001, 0.6000000000000001, 0.55, 0.6111111111111112]
Results MISL
Class3 Algo:<MILpy.Algorithms.EMDD.EMDD object at 0x1149ebb10>
F mean= 0.300649350649
F = [0.33333333333333337, 0.33333333333333337, 0.18181818181818182, 0, 0.5714285714285715, 0.33333333333333337, 0.18181818181818182, 0.5714285714285715, 0, 0.5]
AUC mean =0.596666666667
AUC = [0.6000000000000001, 0.6000000000000001, 0.55, 0.5, 0.7, 0.6000000000000001, 0.55, 0.7, 0.5, 0.6666666666666667]
Results MISL
Class4 Algo:<MILpy.Algorithms.EMDD.EMDD object at 0x114af8050>
F mean= 0.261138861139
F = [0.5714285714285715, 0, 0.18181818181818182, 0, 0.18181818181818182, 0.18181818181818182, 0.4615384615384615, 0.4615384615384615, 0.5714285714285715, 0]
AUC mean =0.585
AUC = [0.7, 0.5, 0.55, 0.5, 0.55, 0.55, 0.6499999999999999, 0.6499999999999999, 0.7, 0.5]
Results MISL
Class5 Algo:<MILpy.Algorithms.EMDD.EMDD object at 0x1149f8050>
F mean= 0.405835830836
F = [0.18181818181818182, 0.5714285714285715, 0.18181818181818182, 0.18181818181818182, 0.4615384615384615, 0.4615384615384615, 0.5714285714285715, 0.33333333333333337, 0.7499999999999999, 0.3636363636363636]
AUC mean =0.636111111111
AUC = [0.55, 0.7, 0.55, 0.55, 0.6499999999999999, 0.6499999999999999, 0.7, 0.6000000000000001, 0.8, 0.6111111111111112]
Results MISL
Class1 Algo:<MILpy.Algorithms.BOW.BOW object at 0x117f6fd10>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class2 Algo:<MILpy.Algorithms.BOW.BOW object at 0x11807ecd0>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class3 Algo:<MILpy.Algorithms.BOW.BOW object at 0x117773d90>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class4 Algo:<MILpy.Algorithms.BOW.BOW object at 0x117f7bd90>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class5 Algo:<MILpy.Algorithms.BOW.BOW object at 0x117f7ad90>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
————
SIMPLE MIL - min
Results MISL
Class1 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117cd9790>
F mean= 0.804983660131
F = [0.7499999999999999, 0.8235294117647058, 0.7499999999999999, 0.7499999999999999, 0.888888888888889, 0.7499999999999999, 0.8235294117647058, 0.888888888888889, 0.7499999999999999, 0.8750000000000001]
AUC mean =0.838888888889
AUC = [0.8, 0.85, 0.8, 0.8, 0.9, 0.8, 0.85, 0.9, 0.8, 0.8888888888888888]
Results MISL
Class2 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x1149f8150>
F mean= 0.491716616717
F = [0.33333333333333337, 0.5714285714285715, 0.5714285714285715, 0.4615384615384615, 0.6666666666666666, 0.33333333333333337, 0.33333333333333337, 0.7499999999999999, 0.18181818181818182, 0.7142857142857143]
AUC mean =0.672777777778
AUC = [0.6000000000000001, 0.7, 0.7, 0.6499999999999999, 0.75, 0.6000000000000001, 0.6000000000000001, 0.8, 0.55, 0.7777777777777778]
Results MISL
Class3 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x1151f2a90>
F mean= 0.760184586655
F = [0.8235294117647058, 0.8235294117647058, 0.5714285714285715, 0.8235294117647058, 0.888888888888889, 0.888888888888889, 0.7499999999999999, 0.7499999999999999, 0.6666666666666666, 0.6153846153846153]
AUC mean =0.812222222222
AUC = [0.85, 0.85, 0.7, 0.85, 0.9, 0.9, 0.8, 0.8, 0.75, 0.7222222222222222]
Results MISL
Class4 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x11786ad10>
F mean= 0.402430902431
F = [0.6666666666666666, 0.18181818181818182, 0.5714285714285715, 0.33333333333333337, 0.5714285714285715, 0.33333333333333337, 0.33333333333333337, 0.4615384615384615, 0.5714285714285715, 0]
AUC mean =0.635
AUC = [0.75, 0.55, 0.7, 0.6000000000000001, 0.7, 0.6000000000000001, 0.6000000000000001, 0.6499999999999999, 0.7, 0.5]
Results MISL
Class5 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x115317050>
F mean= 0.565714024538
F = [0.6666666666666666, 0.18181818181818182, 0.8235294117647058, 0.4615384615384615, 0.4615384615384615, 0.6666666666666666, 0.5714285714285715, 0.5714285714285715, 0.888888888888889, 0.3636363636363636]
AUC mean =0.711111111111
AUC = [0.75, 0.55, 0.85, 0.6499999999999999, 0.6499999999999999, 0.75, 0.7, 0.7, 0.9, 0.6111111111111112]
————
SIMPLE MIL - average
Results MISL
Class1 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117bee650>
F mean= 0.839426384589
F = [0.7499999999999999, 0.7499999999999999, 0.8235294117647058, 0.8235294117647058, 0.888888888888889, 0.888888888888889, 0.8235294117647058, 0.9473684210526316, 0.8235294117647058, 0.8750000000000001]
AUC mean =0.863888888889
AUC = [0.8, 0.8, 0.85, 0.85, 0.9, 0.9, 0.85, 0.95, 0.85, 0.8888888888888888]
Results MISL
Class2 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117774d10>
F mean= 0.97306501548
F = [1.0, 0.9473684210526316, 0.9473684210526316, 1.0, 1.0, 0.9473684210526316, 0.9473684210526316, 1.0, 1.0, 0.9411764705882353]
AUC mean =0.974444444444
AUC = [1.0, 0.95, 0.95, 1.0, 1.0, 0.95, 0.95, 1.0, 1.0, 0.9444444444444444]
Results MISL
Class3 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117873d10>
F mean= 0.973099415205
F = [0.9473684210526316, 1.0, 1.0, 1.0, 0.9473684210526316, 1.0, 0.888888888888889, 0.9473684210526316, 1.0, 1.0]
AUC mean =0.975
AUC = [0.95, 1.0, 1.0, 1.0, 0.95, 1.0, 0.9, 0.95, 1.0, 1.0]
Results MISL
Class4 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117e5ecd0>
F mean= 0.963157894737
F = [0.9473684210526316, 1.0, 0.9473684210526316, 1.0, 0.9473684210526316, 0.9473684210526316, 0.9473684210526316, 0.9473684210526316, 0.9473684210526316, 1.0]
AUC mean =0.965
AUC = [0.95, 1.0, 0.95, 1.0, 0.95, 0.95, 0.95, 0.95, 0.95, 1.0]
Results MISL
Class5 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x1149f8090>
F mean= 0.97306501548
F = [1.0, 1.0, 1.0, 0.9473684210526316, 0.9473684210526316, 0.9473684210526316, 0.9473684210526316, 1.0, 1.0, 0.9411764705882353]
AUC mean =0.974444444444
AUC = [1.0, 1.0, 1.0, 0.95, 0.95, 0.95, 0.95, 1.0, 1.0, 0.9444444444444444]
————
SIMPLE MIL - extreme
Results MISL
Class1 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117071d10>
F mean= 0.994117647059
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.9411764705882353]
AUC mean =0.994444444444
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.9444444444444444]
Results MISL
Class2 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117f7cd10>
F mean= 0.994736842105
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.9473684210526316, 1.0]
AUC mean =0.995
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.95, 1.0]
Results MISL
Class3 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117863d10>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class4 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x114af80d0>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class5 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117884d50>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
————
SIMPLE MIL - max
Results MISL
Class1 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x114af2a90>
F mean= 0.994736842105
F = [1.0, 1.0, 0.9473684210526316, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =0.995
AUC = [1.0, 1.0, 0.95, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class2 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117667d10>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class3 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x1149eba90>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class4 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x117770d10>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
Results MISL
Class5 Algo:<MILpy.Algorithms.simpleMIL.simpleMIL object at 0x1149ec090>
F mean= 1.0
F = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]
AUC mean =1.0
AUC = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0]