ConvGeNBenchmarkResults/data_result/convGAN-proximity-full/folding_yeast6.log

///////////////////////////////////////////
// Running convGAN-proximary-full on folding_yeast6
///////////////////////////////////////////

Load 'data_input/folding_yeast6'
from pickle file
Data loaded.
-> Shuffling data
### Start exercise for synthetic point generator

====== Step 1/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 1/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.2957
 42/116 [=========>....................] - ETA: 0s - loss: 0.0826 
 82/116 [====================>.........] - ETA: 0s - loss: 0.0870
116/116 [==============================] - 0s 1ms/step - loss: 0.0975
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1553
 42/116 [=========>....................] - ETA: 0s - loss: 0.0701
 83/116 [====================>.........] - ETA: 0s - loss: 0.0771
116/116 [==============================] - 0s 1ms/step - loss: 0.0915
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0255
 42/116 [=========>....................] - ETA: 0s - loss: 0.0933
 82/116 [====================>.........] - ETA: 0s - loss: 0.0942
116/116 [==============================] - 0s 1ms/step - loss: 0.0895
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2713
 40/116 [=========>....................] - ETA: 0s - loss: 0.1028
 80/116 [===================>..........] - ETA: 0s - loss: 0.0946
116/116 [==============================] - 0s 1ms/step - loss: 0.0872
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0058
 42/116 [=========>....................] - ETA: 0s - loss: 0.0809
 83/116 [====================>.........] - ETA: 0s - loss: 0.0900
116/116 [==============================] - 0s 1ms/step - loss: 0.0862
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0254
 34/116 [=======>......................] - ETA: 0s - loss: 0.1050
 66/116 [================>.............] - ETA: 0s - loss: 0.0912
105/116 [==========================>...] - ETA: 0s - loss: 0.0835
116/116 [==============================] - 0s 1ms/step - loss: 0.0833
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0511
 41/116 [=========>....................] - ETA: 0s - loss: 0.0950
 83/116 [====================>.........] - ETA: 0s - loss: 0.0868
116/116 [==============================] - 0s 1ms/step - loss: 0.0819
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1233
 40/116 [=========>....................] - ETA: 0s - loss: 0.0878
 78/116 [===================>..........] - ETA: 0s - loss: 0.0906
116/116 [==============================] - 0s 1ms/step - loss: 0.0792
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0137
 43/116 [==========>...................] - ETA: 0s - loss: 0.0710
 79/116 [===================>..........] - ETA: 0s - loss: 0.0744
114/116 [============================>.] - ETA: 0s - loss: 0.0791
116/116 [==============================] - 0s 1ms/step - loss: 0.0797
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0213
 34/116 [=======>......................] - ETA: 0s - loss: 0.0738
 72/116 [=================>............] - ETA: 0s - loss: 0.0735
113/116 [============================>.] - ETA: 0s - loss: 0.0783
116/116 [==============================] - 0s 1ms/step - loss: 0.0771
-> test with GAN.predict
GAN tn, fp: 279, 11
GAN fn, tp: 1, 6
GAN f1 score: 0.500
GAN cohens kappa score: 0.483

-> test with 'LR'
LR tn, fp: 271, 19
LR fn, tp: 1, 6
LR f1 score: 0.375
LR cohens kappa score: 0.351
LR average precision score: 0.699

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 4, 3
RF f1 score: 0.500
RF cohens kappa score: 0.490

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 4, 3
GB f1 score: 0.462
GB cohens kappa score: 0.450

-> test with 'KNN'
KNN tn, fp: 277, 13
KNN fn, tp: 1, 6
KNN f1 score: 0.462
KNN cohens kappa score: 0.442


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0451
 40/116 [=========>....................] - ETA: 0s - loss: 0.1817 
 80/116 [===================>..........] - ETA: 0s - loss: 0.1935
116/116 [==============================] - 0s 1ms/step - loss: 0.1879
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2108
 40/116 [=========>....................] - ETA: 0s - loss: 0.1967
 80/116 [===================>..........] - ETA: 0s - loss: 0.1619
116/116 [==============================] - 0s 1ms/step - loss: 0.1664
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0913
 41/116 [=========>....................] - ETA: 0s - loss: 0.1927
 81/116 [===================>..........] - ETA: 0s - loss: 0.1677
116/116 [==============================] - 0s 1ms/step - loss: 0.1559
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2274
 41/116 [=========>....................] - ETA: 0s - loss: 0.1641
 81/116 [===================>..........] - ETA: 0s - loss: 0.1561
116/116 [==============================] - 0s 1ms/step - loss: 0.1478
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.5400
 40/116 [=========>....................] - ETA: 0s - loss: 0.1668
 80/116 [===================>..........] - ETA: 0s - loss: 0.1523
116/116 [==============================] - 0s 1ms/step - loss: 0.1429
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0459
 41/116 [=========>....................] - ETA: 0s - loss: 0.1328
 82/116 [====================>.........] - ETA: 0s - loss: 0.1383
116/116 [==============================] - 0s 1ms/step - loss: 0.1367
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0510
 40/116 [=========>....................] - ETA: 0s - loss: 0.1131
 79/116 [===================>..........] - ETA: 0s - loss: 0.1283
114/116 [============================>.] - ETA: 0s - loss: 0.1330
116/116 [==============================] - 0s 1ms/step - loss: 0.1356
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1984
 38/116 [========>.....................] - ETA: 0s - loss: 0.1291
 78/116 [===================>..........] - ETA: 0s - loss: 0.1377
116/116 [==============================] - 0s 1ms/step - loss: 0.1347
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0416
 41/116 [=========>....................] - ETA: 0s - loss: 0.1405
 82/116 [====================>.........] - ETA: 0s - loss: 0.1219
116/116 [==============================] - 0s 1ms/step - loss: 0.1296
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.2945
 41/116 [=========>....................] - ETA: 0s - loss: 0.1498
 80/116 [===================>..........] - ETA: 0s - loss: 0.1245
116/116 [==============================] - 0s 1ms/step - loss: 0.1272
-> test with GAN.predict
GAN tn, fp: 273, 17
GAN fn, tp: 3, 4
GAN f1 score: 0.286
GAN cohens kappa score: 0.260

-> test with 'LR'
LR tn, fp: 265, 25
LR fn, tp: 2, 5
LR f1 score: 0.270
LR cohens kappa score: 0.241
LR average precision score: 0.427

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 5, 2
RF f1 score: 0.333
RF cohens kappa score: 0.320

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 3, 4
GB f1 score: 0.533
GB cohens kappa score: 0.521

-> test with 'KNN'
KNN tn, fp: 273, 17
KNN fn, tp: 3, 4
KNN f1 score: 0.286
KNN cohens kappa score: 0.260


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.1592
 42/116 [=========>....................] - ETA: 0s - loss: 0.1669 
 82/116 [====================>.........] - ETA: 0s - loss: 0.1676
116/116 [==============================] - 0s 1ms/step - loss: 0.1636
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1153
 41/116 [=========>....................] - ETA: 0s - loss: 0.1407
 79/116 [===================>..........] - ETA: 0s - loss: 0.1472
114/116 [============================>.] - ETA: 0s - loss: 0.1457
116/116 [==============================] - 0s 1ms/step - loss: 0.1470
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1232
 36/116 [========>.....................] - ETA: 0s - loss: 0.1703
 70/116 [=================>............] - ETA: 0s - loss: 0.1617
108/116 [==========================>...] - ETA: 0s - loss: 0.1473
116/116 [==============================] - 0s 1ms/step - loss: 0.1470
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0573
 41/116 [=========>....................] - ETA: 0s - loss: 0.1350
 82/116 [====================>.........] - ETA: 0s - loss: 0.1368
116/116 [==============================] - 0s 1ms/step - loss: 0.1389
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.2281
 43/116 [==========>...................] - ETA: 0s - loss: 0.1196
 83/116 [====================>.........] - ETA: 0s - loss: 0.1306
116/116 [==============================] - 0s 1ms/step - loss: 0.1360
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.3991
 41/116 [=========>....................] - ETA: 0s - loss: 0.1331
 79/116 [===================>..........] - ETA: 0s - loss: 0.1344
116/116 [==============================] - 0s 1ms/step - loss: 0.1308
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1784
 42/116 [=========>....................] - ETA: 0s - loss: 0.1321
 82/116 [====================>.........] - ETA: 0s - loss: 0.1298
116/116 [==============================] - 0s 1ms/step - loss: 0.1307
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0736
 40/116 [=========>....................] - ETA: 0s - loss: 0.1343
 79/116 [===================>..........] - ETA: 0s - loss: 0.1337
116/116 [==============================] - 0s 1ms/step - loss: 0.1280
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.2588
 42/116 [=========>....................] - ETA: 0s - loss: 0.1201
 81/116 [===================>..........] - ETA: 0s - loss: 0.1265
116/116 [==============================] - 0s 1ms/step - loss: 0.1249
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0385
 42/116 [=========>....................] - ETA: 0s - loss: 0.1346
 81/116 [===================>..........] - ETA: 0s - loss: 0.1290
116/116 [==============================] - 0s 1ms/step - loss: 0.1246
-> test with GAN.predict
GAN tn, fp: 268, 22
GAN fn, tp: 1, 6
GAN f1 score: 0.343
GAN cohens kappa score: 0.317

-> test with 'LR'
LR tn, fp: 261, 29
LR fn, tp: 1, 6
LR f1 score: 0.286
LR cohens kappa score: 0.257
LR average precision score: 0.297

-> test with 'RF'
RF tn, fp: 290, 0
RF fn, tp: 3, 4
RF f1 score: 0.727
RF cohens kappa score: 0.723

-> test with 'GB'
GB tn, fp: 290, 0
GB fn, tp: 3, 4
GB f1 score: 0.727
GB cohens kappa score: 0.723

-> test with 'KNN'
KNN tn, fp: 274, 16
KNN fn, tp: 1, 6
KNN f1 score: 0.414
KNN cohens kappa score: 0.392


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.2895
 38/116 [========>.....................] - ETA: 0s - loss: 0.2063 
 75/116 [==================>...........] - ETA: 0s - loss: 0.1902
116/116 [==============================] - ETA: 0s - loss: 0.1864
116/116 [==============================] - 0s 1ms/step - loss: 0.1864
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0656
 38/116 [========>.....................] - ETA: 0s - loss: 0.1409
 78/116 [===================>..........] - ETA: 0s - loss: 0.1496
116/116 [==============================] - 0s 1ms/step - loss: 0.1557
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1260
 40/116 [=========>....................] - ETA: 0s - loss: 0.1268
 80/116 [===================>..........] - ETA: 0s - loss: 0.1376
116/116 [==============================] - 0s 1ms/step - loss: 0.1406
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0746
 43/116 [==========>...................] - ETA: 0s - loss: 0.1391
 84/116 [====================>.........] - ETA: 0s - loss: 0.1397
116/116 [==============================] - 0s 1ms/step - loss: 0.1337
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0709
 42/116 [=========>....................] - ETA: 0s - loss: 0.1151
 81/116 [===================>..........] - ETA: 0s - loss: 0.1301
116/116 [==============================] - 0s 1ms/step - loss: 0.1291
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.2247
 39/116 [=========>....................] - ETA: 0s - loss: 0.1255
 79/116 [===================>..........] - ETA: 0s - loss: 0.1282
116/116 [==============================] - 0s 1ms/step - loss: 0.1282
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1370
 41/116 [=========>....................] - ETA: 0s - loss: 0.1300
 82/116 [====================>.........] - ETA: 0s - loss: 0.1256
116/116 [==============================] - 0s 1ms/step - loss: 0.1240
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0395
 42/116 [=========>....................] - ETA: 0s - loss: 0.1367
 83/116 [====================>.........] - ETA: 0s - loss: 0.1262
116/116 [==============================] - 0s 1ms/step - loss: 0.1232
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1509
 34/116 [=======>......................] - ETA: 0s - loss: 0.1254
 69/116 [================>.............] - ETA: 0s - loss: 0.1164
106/116 [==========================>...] - ETA: 0s - loss: 0.1167
116/116 [==============================] - 0s 1ms/step - loss: 0.1199
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1721
 41/116 [=========>....................] - ETA: 0s - loss: 0.1283
 77/116 [==================>...........] - ETA: 0s - loss: 0.1278
116/116 [==============================] - 0s 1ms/step - loss: 0.1202
-> test with GAN.predict
GAN tn, fp: 274, 16
GAN fn, tp: 1, 6
GAN f1 score: 0.414
GAN cohens kappa score: 0.392

-> test with 'LR'
LR tn, fp: 270, 20
LR fn, tp: 1, 6
LR f1 score: 0.364
LR cohens kappa score: 0.339
LR average precision score: 0.600

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 5, 2
RF f1 score: 0.364
RF cohens kappa score: 0.353

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 4, 3
GB f1 score: 0.429
GB cohens kappa score: 0.415

-> test with 'KNN'
KNN tn, fp: 276, 14
KNN fn, tp: 1, 6
KNN f1 score: 0.444
KNN cohens kappa score: 0.424


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 15s - loss: 0.1071
 43/116 [==========>...................] - ETA: 0s - loss: 0.1561 
 84/116 [====================>.........] - ETA: 0s - loss: 0.1583
116/116 [==============================] - 0s 1ms/step - loss: 0.1644
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2072
 43/116 [==========>...................] - ETA: 0s - loss: 0.1679
 84/116 [====================>.........] - ETA: 0s - loss: 0.1444
116/116 [==============================] - 0s 1ms/step - loss: 0.1490
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0503
 45/116 [==========>...................] - ETA: 0s - loss: 0.1444
 88/116 [=====================>........] - ETA: 0s - loss: 0.1393
116/116 [==============================] - 0s 1ms/step - loss: 0.1410
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.3456
 44/116 [==========>...................] - ETA: 0s - loss: 0.1398
 87/116 [=====================>........] - ETA: 0s - loss: 0.1429
116/116 [==============================] - 0s 1ms/step - loss: 0.1360
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.3433
 38/116 [========>.....................] - ETA: 0s - loss: 0.1395
 80/116 [===================>..........] - ETA: 0s - loss: 0.1321
116/116 [==============================] - 0s 1ms/step - loss: 0.1369
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0456
 42/116 [=========>....................] - ETA: 0s - loss: 0.1481
 84/116 [====================>.........] - ETA: 0s - loss: 0.1426
116/116 [==============================] - 0s 1ms/step - loss: 0.1359
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1746
 44/116 [==========>...................] - ETA: 0s - loss: 0.1302
 87/116 [=====================>........] - ETA: 0s - loss: 0.1346
116/116 [==============================] - 0s 1ms/step - loss: 0.1329
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0592
 43/116 [==========>...................] - ETA: 0s - loss: 0.1247
 86/116 [=====================>........] - ETA: 0s - loss: 0.1268
116/116 [==============================] - 0s 1ms/step - loss: 0.1298
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0526
 43/116 [==========>...................] - ETA: 0s - loss: 0.1471
 87/116 [=====================>........] - ETA: 0s - loss: 0.1357
116/116 [==============================] - 0s 1ms/step - loss: 0.1318
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1364
 43/116 [==========>...................] - ETA: 0s - loss: 0.1157
 84/116 [====================>.........] - ETA: 0s - loss: 0.1179
116/116 [==============================] - 0s 1ms/step - loss: 0.1303
-> test with GAN.predict
GAN tn, fp: 271, 18
GAN fn, tp: 1, 6
GAN f1 score: 0.387
GAN cohens kappa score: 0.364

-> test with 'LR'
LR tn, fp: 253, 36
LR fn, tp: 0, 7
LR f1 score: 0.280
LR cohens kappa score: 0.249
LR average precision score: 0.585

-> test with 'RF'
RF tn, fp: 287, 2
RF fn, tp: 2, 5
RF f1 score: 0.714
RF cohens kappa score: 0.707

-> test with 'GB'
GB tn, fp: 285, 4
GB fn, tp: 1, 6
GB f1 score: 0.706
GB cohens kappa score: 0.697

-> test with 'KNN'
KNN tn, fp: 267, 22
KNN fn, tp: 0, 7
KNN f1 score: 0.389
KNN cohens kappa score: 0.365


====== Step 2/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 21s - loss: 0.1792
 40/116 [=========>....................] - ETA: 0s - loss: 0.1497 
 79/116 [===================>..........] - ETA: 0s - loss: 0.1440
116/116 [==============================] - 0s 1ms/step - loss: 0.1434
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2197
 36/116 [========>.....................] - ETA: 0s - loss: 0.1358
 69/116 [================>.............] - ETA: 0s - loss: 0.1339
108/116 [==========================>...] - ETA: 0s - loss: 0.1294
116/116 [==============================] - 0s 1ms/step - loss: 0.1278
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0809
 42/116 [=========>....................] - ETA: 0s - loss: 0.1331
 83/116 [====================>.........] - ETA: 0s - loss: 0.1239
116/116 [==============================] - 0s 1ms/step - loss: 0.1179
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0405
 40/116 [=========>....................] - ETA: 0s - loss: 0.1179
 78/116 [===================>..........] - ETA: 0s - loss: 0.1139
116/116 [==============================] - 0s 1ms/step - loss: 0.1146
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0493
 41/116 [=========>....................] - ETA: 0s - loss: 0.1113
 78/116 [===================>..........] - ETA: 0s - loss: 0.1235
116/116 [==============================] - ETA: 0s - loss: 0.1115
116/116 [==============================] - 0s 1ms/step - loss: 0.1115
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0678
 42/116 [=========>....................] - ETA: 0s - loss: 0.0986
 82/116 [====================>.........] - ETA: 0s - loss: 0.1064
116/116 [==============================] - 0s 1ms/step - loss: 0.1092
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1571
 39/116 [=========>....................] - ETA: 0s - loss: 0.0971
 79/116 [===================>..........] - ETA: 0s - loss: 0.1113
116/116 [==============================] - 0s 1ms/step - loss: 0.1085
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0236
 41/116 [=========>....................] - ETA: 0s - loss: 0.1039
 82/116 [====================>.........] - ETA: 0s - loss: 0.1035
116/116 [==============================] - 0s 1ms/step - loss: 0.1058
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0109
 40/116 [=========>....................] - ETA: 0s - loss: 0.1113
 79/116 [===================>..........] - ETA: 0s - loss: 0.1023
116/116 [==============================] - 0s 1ms/step - loss: 0.1069
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0096
 41/116 [=========>....................] - ETA: 0s - loss: 0.0925
 81/116 [===================>..........] - ETA: 0s - loss: 0.1099
116/116 [==============================] - 0s 1ms/step - loss: 0.1044
-> test with GAN.predict
GAN tn, fp: 276, 14
GAN fn, tp: 1, 6
GAN f1 score: 0.444
GAN cohens kappa score: 0.424

-> test with 'LR'
LR tn, fp: 272, 18
LR fn, tp: 1, 6
LR f1 score: 0.387
LR cohens kappa score: 0.364
LR average precision score: 0.668

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 3, 4
RF f1 score: 0.571
RF cohens kappa score: 0.561

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 3, 4
GB f1 score: 0.571
GB cohens kappa score: 0.561

-> test with 'KNN'
KNN tn, fp: 274, 16
KNN fn, tp: 1, 6
KNN f1 score: 0.414
KNN cohens kappa score: 0.392


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0609
 37/116 [========>.....................] - ETA: 0s - loss: 0.1247 
 67/116 [================>.............] - ETA: 0s - loss: 0.1340
 96/116 [=======================>......] - ETA: 0s - loss: 0.1277
116/116 [==============================] - 0s 2ms/step - loss: 0.1309
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0089
 40/116 [=========>....................] - ETA: 0s - loss: 0.1188
 79/116 [===================>..........] - ETA: 0s - loss: 0.1177
116/116 [==============================] - 0s 1ms/step - loss: 0.1191
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.2476
 40/116 [=========>....................] - ETA: 0s - loss: 0.0959
 79/116 [===================>..........] - ETA: 0s - loss: 0.1071
116/116 [==============================] - 0s 1ms/step - loss: 0.1115
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2014
 39/116 [=========>....................] - ETA: 0s - loss: 0.0966
 79/116 [===================>..........] - ETA: 0s - loss: 0.1020
116/116 [==============================] - 0s 1ms/step - loss: 0.1088
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1438
 41/116 [=========>....................] - ETA: 0s - loss: 0.0807
 80/116 [===================>..........] - ETA: 0s - loss: 0.1056
116/116 [==============================] - 0s 1ms/step - loss: 0.1071
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0268
 40/116 [=========>....................] - ETA: 0s - loss: 0.1038
 80/116 [===================>..........] - ETA: 0s - loss: 0.0990
116/116 [==============================] - 0s 1ms/step - loss: 0.1029
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0779
 39/116 [=========>....................] - ETA: 0s - loss: 0.1078
 79/116 [===================>..........] - ETA: 0s - loss: 0.0927
116/116 [==============================] - 0s 1ms/step - loss: 0.1007
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0448
 41/116 [=========>....................] - ETA: 0s - loss: 0.0993
 81/116 [===================>..........] - ETA: 0s - loss: 0.1007
116/116 [==============================] - 0s 1ms/step - loss: 0.0987
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0794
 39/116 [=========>....................] - ETA: 0s - loss: 0.0998
 80/116 [===================>..........] - ETA: 0s - loss: 0.0959
116/116 [==============================] - 0s 1ms/step - loss: 0.0978
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1047
 42/116 [=========>....................] - ETA: 0s - loss: 0.1019
 83/116 [====================>.........] - ETA: 0s - loss: 0.0955
116/116 [==============================] - 0s 1ms/step - loss: 0.0994
-> test with GAN.predict
GAN tn, fp: 263, 27
GAN fn, tp: 1, 6
GAN f1 score: 0.300
GAN cohens kappa score: 0.272

-> test with 'LR'
LR tn, fp: 263, 27
LR fn, tp: 0, 7
LR f1 score: 0.341
LR cohens kappa score: 0.315
LR average precision score: 0.291

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 3, 4
RF f1 score: 0.571
RF cohens kappa score: 0.561

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 0, 7
GB f1 score: 0.778
GB cohens kappa score: 0.771

-> test with 'KNN'
KNN tn, fp: 276, 14
KNN fn, tp: 0, 7
KNN f1 score: 0.500
KNN cohens kappa score: 0.482


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.0070
 41/116 [=========>....................] - ETA: 0s - loss: 0.1289 
 81/116 [===================>..........] - ETA: 0s - loss: 0.1437
116/116 [==============================] - 0s 1ms/step - loss: 0.1348
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0159
 41/116 [=========>....................] - ETA: 0s - loss: 0.1472
 79/116 [===================>..........] - ETA: 0s - loss: 0.1290
114/116 [============================>.] - ETA: 0s - loss: 0.1244
116/116 [==============================] - 0s 1ms/step - loss: 0.1230
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1720
 40/116 [=========>....................] - ETA: 0s - loss: 0.0803
 80/116 [===================>..........] - ETA: 0s - loss: 0.0925
116/116 [==============================] - 0s 1ms/step - loss: 0.1111
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1218
 41/116 [=========>....................] - ETA: 0s - loss: 0.1070
 82/116 [====================>.........] - ETA: 0s - loss: 0.1064
116/116 [==============================] - 0s 1ms/step - loss: 0.1043
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0270
 39/116 [=========>....................] - ETA: 0s - loss: 0.1000
 78/116 [===================>..........] - ETA: 0s - loss: 0.0970
116/116 [==============================] - 0s 1ms/step - loss: 0.1014
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0912
 41/116 [=========>....................] - ETA: 0s - loss: 0.1124
 81/116 [===================>..........] - ETA: 0s - loss: 0.1043
116/116 [==============================] - 0s 1ms/step - loss: 0.0994
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1788
 41/116 [=========>....................] - ETA: 0s - loss: 0.1048
 80/116 [===================>..........] - ETA: 0s - loss: 0.0959
116/116 [==============================] - 0s 1ms/step - loss: 0.0993
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0133
 41/116 [=========>....................] - ETA: 0s - loss: 0.0917
 79/116 [===================>..........] - ETA: 0s - loss: 0.0981
116/116 [==============================] - 0s 1ms/step - loss: 0.0954
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0861
 41/116 [=========>....................] - ETA: 0s - loss: 0.0879
 81/116 [===================>..........] - ETA: 0s - loss: 0.0949
116/116 [==============================] - 0s 1ms/step - loss: 0.0951
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1786
 38/116 [========>.....................] - ETA: 0s - loss: 0.1069
 77/116 [==================>...........] - ETA: 0s - loss: 0.0920
115/116 [============================>.] - ETA: 0s - loss: 0.0946
116/116 [==============================] - 0s 1ms/step - loss: 0.0947
-> test with GAN.predict
GAN tn, fp: 277, 13
GAN fn, tp: 2, 5
GAN f1 score: 0.400
GAN cohens kappa score: 0.379

-> test with 'LR'
LR tn, fp: 263, 27
LR fn, tp: 1, 6
LR f1 score: 0.300
LR cohens kappa score: 0.272
LR average precision score: 0.510

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 3, 4
RF f1 score: 0.615
RF cohens kappa score: 0.607

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 3, 4
GB f1 score: 0.571
GB cohens kappa score: 0.561

-> test with 'KNN'
KNN tn, fp: 265, 25
KNN fn, tp: 1, 6
KNN f1 score: 0.316
KNN cohens kappa score: 0.288


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0782
 42/116 [=========>....................] - ETA: 0s - loss: 0.1696 
 82/116 [====================>.........] - ETA: 0s - loss: 0.1557
116/116 [==============================] - 0s 1ms/step - loss: 0.1407
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0306
 38/116 [========>.....................] - ETA: 0s - loss: 0.1247
 78/116 [===================>..........] - ETA: 0s - loss: 0.1234
116/116 [==============================] - 0s 1ms/step - loss: 0.1203
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.2236
 41/116 [=========>....................] - ETA: 0s - loss: 0.1282
 79/116 [===================>..........] - ETA: 0s - loss: 0.1191
116/116 [==============================] - 0s 1ms/step - loss: 0.1148
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0221
 39/116 [=========>....................] - ETA: 0s - loss: 0.1153
 79/116 [===================>..........] - ETA: 0s - loss: 0.1133
116/116 [==============================] - 0s 1ms/step - loss: 0.1098
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.2293
 39/116 [=========>....................] - ETA: 0s - loss: 0.1133
 82/116 [====================>.........] - ETA: 0s - loss: 0.1001
116/116 [==============================] - 0s 1ms/step - loss: 0.1091
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0692
 41/116 [=========>....................] - ETA: 0s - loss: 0.1049
 81/116 [===================>..........] - ETA: 0s - loss: 0.1040
116/116 [==============================] - 0s 1ms/step - loss: 0.1062
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0720
 40/116 [=========>....................] - ETA: 0s - loss: 0.1033
 77/116 [==================>...........] - ETA: 0s - loss: 0.1115
115/116 [============================>.] - ETA: 0s - loss: 0.1047
116/116 [==============================] - 0s 1ms/step - loss: 0.1046
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0689
 42/116 [=========>....................] - ETA: 0s - loss: 0.1190
 82/116 [====================>.........] - ETA: 0s - loss: 0.1068
116/116 [==============================] - 0s 1ms/step - loss: 0.1012
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0463
 41/116 [=========>....................] - ETA: 0s - loss: 0.0916
 81/116 [===================>..........] - ETA: 0s - loss: 0.0957
116/116 [==============================] - 0s 1ms/step - loss: 0.0996
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0524
 40/116 [=========>....................] - ETA: 0s - loss: 0.0924
 80/116 [===================>..........] - ETA: 0s - loss: 0.0897
116/116 [==============================] - 0s 1ms/step - loss: 0.0986
-> test with GAN.predict
GAN tn, fp: 279, 11
GAN fn, tp: 2, 5
GAN f1 score: 0.435
GAN cohens kappa score: 0.416

-> test with 'LR'
LR tn, fp: 262, 28
LR fn, tp: 2, 5
LR f1 score: 0.250
LR cohens kappa score: 0.220
LR average precision score: 0.557

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 5, 2
RF f1 score: 0.333
RF cohens kappa score: 0.320

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 5, 2
GB f1 score: 0.333
GB cohens kappa score: 0.320

-> test with 'KNN'
KNN tn, fp: 271, 19
KNN fn, tp: 2, 5
KNN f1 score: 0.323
KNN cohens kappa score: 0.297


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.1684
 42/116 [=========>....................] - ETA: 0s - loss: 0.1867 
 83/116 [====================>.........] - ETA: 0s - loss: 0.1660
116/116 [==============================] - 0s 1ms/step - loss: 0.1585
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0283
 44/116 [==========>...................] - ETA: 0s - loss: 0.1532
 87/116 [=====================>........] - ETA: 0s - loss: 0.1425
116/116 [==============================] - 0s 1ms/step - loss: 0.1393
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0584
 41/116 [=========>....................] - ETA: 0s - loss: 0.1214
 84/116 [====================>.........] - ETA: 0s - loss: 0.1261
116/116 [==============================] - 0s 1ms/step - loss: 0.1307
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0047
 44/116 [==========>...................] - ETA: 0s - loss: 0.1246
 87/116 [=====================>........] - ETA: 0s - loss: 0.1282
116/116 [==============================] - 0s 1ms/step - loss: 0.1282
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0164
 34/116 [=======>......................] - ETA: 0s - loss: 0.1332
 70/116 [=================>............] - ETA: 0s - loss: 0.1191
112/116 [===========================>..] - ETA: 0s - loss: 0.1244
116/116 [==============================] - 0s 1ms/step - loss: 0.1225
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1530
 40/116 [=========>....................] - ETA: 0s - loss: 0.1164
 82/116 [====================>.........] - ETA: 0s - loss: 0.1169
116/116 [==============================] - 0s 1ms/step - loss: 0.1176
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1344
 43/116 [==========>...................] - ETA: 0s - loss: 0.1116
 86/116 [=====================>........] - ETA: 0s - loss: 0.1193
116/116 [==============================] - 0s 1ms/step - loss: 0.1164
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0112
 37/116 [========>.....................] - ETA: 0s - loss: 0.1209
 79/116 [===================>..........] - ETA: 0s - loss: 0.1222
116/116 [==============================] - 0s 1ms/step - loss: 0.1138
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1132
 43/116 [==========>...................] - ETA: 0s - loss: 0.1189
 85/116 [====================>.........] - ETA: 0s - loss: 0.1124
116/116 [==============================] - 0s 1ms/step - loss: 0.1113
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1277
 43/116 [==========>...................] - ETA: 0s - loss: 0.0986
 82/116 [====================>.........] - ETA: 0s - loss: 0.1109
116/116 [==============================] - 0s 1ms/step - loss: 0.1110
-> test with GAN.predict
GAN tn, fp: 279, 10
GAN fn, tp: 2, 5
GAN f1 score: 0.455
GAN cohens kappa score: 0.436

-> test with 'LR'
LR tn, fp: 272, 17
LR fn, tp: 1, 6
LR f1 score: 0.400
LR cohens kappa score: 0.377
LR average precision score: 0.530

-> test with 'RF'
RF tn, fp: 289, 0
RF fn, tp: 5, 2
RF f1 score: 0.444
RF cohens kappa score: 0.439

-> test with 'GB'
GB tn, fp: 289, 0
GB fn, tp: 6, 1
GB f1 score: 0.250
GB cohens kappa score: 0.246

-> test with 'KNN'
KNN tn, fp: 275, 14
KNN fn, tp: 2, 5
KNN f1 score: 0.385
KNN cohens kappa score: 0.363


====== Step 3/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.3119
 42/116 [=========>....................] - ETA: 0s - loss: 0.2817 
 83/116 [====================>.........] - ETA: 0s - loss: 0.2615
116/116 [==============================] - 0s 1ms/step - loss: 0.2507
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0014
 41/116 [=========>....................] - ETA: 0s - loss: 0.2044
 81/116 [===================>..........] - ETA: 0s - loss: 0.2124
116/116 [==============================] - 0s 1ms/step - loss: 0.2022
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0292
 42/116 [=========>....................] - ETA: 0s - loss: 0.1617
 82/116 [====================>.........] - ETA: 0s - loss: 0.1743
116/116 [==============================] - 0s 1ms/step - loss: 0.1772
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.4640
 41/116 [=========>....................] - ETA: 0s - loss: 0.1685
 81/116 [===================>..........] - ETA: 0s - loss: 0.1778
116/116 [==============================] - 0s 1ms/step - loss: 0.1655
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.2000
 42/116 [=========>....................] - ETA: 0s - loss: 0.1560
 82/116 [====================>.........] - ETA: 0s - loss: 0.1722
116/116 [==============================] - 0s 1ms/step - loss: 0.1611
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1820
 41/116 [=========>....................] - ETA: 0s - loss: 0.1574
 81/116 [===================>..........] - ETA: 0s - loss: 0.1564
116/116 [==============================] - 0s 1ms/step - loss: 0.1527
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0354
 41/116 [=========>....................] - ETA: 0s - loss: 0.1292
 81/116 [===================>..........] - ETA: 0s - loss: 0.1342
116/116 [==============================] - 0s 1ms/step - loss: 0.1472
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.2782
 40/116 [=========>....................] - ETA: 0s - loss: 0.1627
 78/116 [===================>..........] - ETA: 0s - loss: 0.1459
116/116 [==============================] - 0s 1ms/step - loss: 0.1438
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.4791
 40/116 [=========>....................] - ETA: 0s - loss: 0.1515
 76/116 [==================>...........] - ETA: 0s - loss: 0.1487
112/116 [===========================>..] - ETA: 0s - loss: 0.1434
116/116 [==============================] - 0s 1ms/step - loss: 0.1436
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0877
 38/116 [========>.....................] - ETA: 0s - loss: 0.1542
 70/116 [=================>............] - ETA: 0s - loss: 0.1468
100/116 [========================>.....] - ETA: 0s - loss: 0.1419
116/116 [==============================] - 0s 2ms/step - loss: 0.1417
-> test with GAN.predict
GAN tn, fp: 269, 21
GAN fn, tp: 1, 6
GAN f1 score: 0.353
GAN cohens kappa score: 0.328

-> test with 'LR'
LR tn, fp: 262, 28
LR fn, tp: 1, 6
LR f1 score: 0.293
LR cohens kappa score: 0.264
LR average precision score: 0.633

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 4, 3
RF f1 score: 0.545
RF cohens kappa score: 0.538

-> test with 'GB'
GB tn, fp: 289, 1
GB fn, tp: 4, 3
GB f1 score: 0.545
GB cohens kappa score: 0.538

-> test with 'KNN'
KNN tn, fp: 268, 22
KNN fn, tp: 1, 6
KNN f1 score: 0.343
KNN cohens kappa score: 0.317


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0013
 42/116 [=========>....................] - ETA: 0s - loss: 0.2808 
 82/116 [====================>.........] - ETA: 0s - loss: 0.2459
116/116 [==============================] - 0s 1ms/step - loss: 0.2330
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1633
 41/116 [=========>....................] - ETA: 0s - loss: 0.2272
 82/116 [====================>.........] - ETA: 0s - loss: 0.2041
116/116 [==============================] - 0s 1ms/step - loss: 0.1931
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0183
 42/116 [=========>....................] - ETA: 0s - loss: 0.2017
 83/116 [====================>.........] - ETA: 0s - loss: 0.1877
116/116 [==============================] - 0s 1ms/step - loss: 0.1749
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2477
 43/116 [==========>...................] - ETA: 0s - loss: 0.1687
 83/116 [====================>.........] - ETA: 0s - loss: 0.1668
116/116 [==============================] - 0s 1ms/step - loss: 0.1737
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1015
 39/116 [=========>....................] - ETA: 0s - loss: 0.1678
 81/116 [===================>..........] - ETA: 0s - loss: 0.1624
116/116 [==============================] - 0s 1ms/step - loss: 0.1651
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.2256
 42/116 [=========>....................] - ETA: 0s - loss: 0.1406
 83/116 [====================>.........] - ETA: 0s - loss: 0.1544
116/116 [==============================] - 0s 1ms/step - loss: 0.1565
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.3604
 42/116 [=========>....................] - ETA: 0s - loss: 0.1706
 82/116 [====================>.........] - ETA: 0s - loss: 0.1500
116/116 [==============================] - 0s 1ms/step - loss: 0.1579
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0749
 41/116 [=========>....................] - ETA: 0s - loss: 0.1367
 81/116 [===================>..........] - ETA: 0s - loss: 0.1498
116/116 [==============================] - 0s 1ms/step - loss: 0.1541
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0564
 36/116 [========>.....................] - ETA: 0s - loss: 0.1357
 69/116 [================>.............] - ETA: 0s - loss: 0.1368
102/116 [=========================>....] - ETA: 0s - loss: 0.1494
116/116 [==============================] - 0s 2ms/step - loss: 0.1523
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0808
 35/116 [========>.....................] - ETA: 0s - loss: 0.1486
 76/116 [==================>...........] - ETA: 0s - loss: 0.1469
114/116 [============================>.] - ETA: 0s - loss: 0.1451
116/116 [==============================] - 0s 1ms/step - loss: 0.1511
-> test with GAN.predict
GAN tn, fp: 267, 23
GAN fn, tp: 0, 7
GAN f1 score: 0.378
GAN cohens kappa score: 0.354

-> test with 'LR'
LR tn, fp: 255, 35
LR fn, tp: 0, 7
LR f1 score: 0.286
LR cohens kappa score: 0.256
LR average precision score: 0.746

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 3, 4
RF f1 score: 0.571
RF cohens kappa score: 0.561

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 2, 5
GB f1 score: 0.625
GB cohens kappa score: 0.615

-> test with 'KNN'
KNN tn, fp: 259, 31
KNN fn, tp: 0, 7
KNN f1 score: 0.311
KNN cohens kappa score: 0.283


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.2032
 41/116 [=========>....................] - ETA: 0s - loss: 0.1768 
 82/116 [====================>.........] - ETA: 0s - loss: 0.1658
116/116 [==============================] - 0s 1ms/step - loss: 0.1653
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1805
 41/116 [=========>....................] - ETA: 0s - loss: 0.1595
 81/116 [===================>..........] - ETA: 0s - loss: 0.1603
116/116 [==============================] - 0s 1ms/step - loss: 0.1522
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1415
 41/116 [=========>....................] - ETA: 0s - loss: 0.1523
 81/116 [===================>..........] - ETA: 0s - loss: 0.1535
116/116 [==============================] - 0s 1ms/step - loss: 0.1465
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0405
 40/116 [=========>....................] - ETA: 0s - loss: 0.1355
 81/116 [===================>..........] - ETA: 0s - loss: 0.1449
116/116 [==============================] - 0s 1ms/step - loss: 0.1415
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0360
 41/116 [=========>....................] - ETA: 0s - loss: 0.1289
 82/116 [====================>.........] - ETA: 0s - loss: 0.1410
116/116 [==============================] - 0s 1ms/step - loss: 0.1405
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1497
 42/116 [=========>....................] - ETA: 0s - loss: 0.1312
 82/116 [====================>.........] - ETA: 0s - loss: 0.1446
116/116 [==============================] - 0s 1ms/step - loss: 0.1406
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.2624
 37/116 [========>.....................] - ETA: 0s - loss: 0.1369
 72/116 [=================>............] - ETA: 0s - loss: 0.1391
106/116 [==========================>...] - ETA: 0s - loss: 0.1391
116/116 [==============================] - 0s 1ms/step - loss: 0.1370
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.3044
 42/116 [=========>....................] - ETA: 0s - loss: 0.1506
 84/116 [====================>.........] - ETA: 0s - loss: 0.1478
116/116 [==============================] - 0s 1ms/step - loss: 0.1392
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0619
 36/116 [========>.....................] - ETA: 0s - loss: 0.1514
 75/116 [==================>...........] - ETA: 0s - loss: 0.1411
115/116 [============================>.] - ETA: 0s - loss: 0.1353
116/116 [==============================] - 0s 1ms/step - loss: 0.1343
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0430
 42/116 [=========>....................] - ETA: 0s - loss: 0.1255
 82/116 [====================>.........] - ETA: 0s - loss: 0.1243
116/116 [==============================] - 0s 1ms/step - loss: 0.1325
-> test with GAN.predict
GAN tn, fp: 268, 22
GAN fn, tp: 3, 4
GAN f1 score: 0.242
GAN cohens kappa score: 0.213

-> test with 'LR'
LR tn, fp: 265, 25
LR fn, tp: 2, 5
LR f1 score: 0.270
LR cohens kappa score: 0.241
LR average precision score: 0.382

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 6, 1
RF f1 score: 0.200
RF cohens kappa score: 0.189

-> test with 'GB'
GB tn, fp: 288, 2
GB fn, tp: 5, 2
GB f1 score: 0.364
GB cohens kappa score: 0.353

-> test with 'KNN'
KNN tn, fp: 276, 14
KNN fn, tp: 2, 5
KNN f1 score: 0.385
KNN cohens kappa score: 0.363


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0490
 36/116 [========>.....................] - ETA: 0s - loss: 0.1699 
 72/116 [=================>............] - ETA: 0s - loss: 0.1642
111/116 [===========================>..] - ETA: 0s - loss: 0.1509
116/116 [==============================] - 0s 1ms/step - loss: 0.1510
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1900
 42/116 [=========>....................] - ETA: 0s - loss: 0.1183
 83/116 [====================>.........] - ETA: 0s - loss: 0.1362
116/116 [==============================] - 0s 1ms/step - loss: 0.1309
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0516
 40/116 [=========>....................] - ETA: 0s - loss: 0.1372
 81/116 [===================>..........] - ETA: 0s - loss: 0.1317
116/116 [==============================] - 0s 1ms/step - loss: 0.1282
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0476
 42/116 [=========>....................] - ETA: 0s - loss: 0.1128
 83/116 [====================>.........] - ETA: 0s - loss: 0.1238
116/116 [==============================] - 0s 1ms/step - loss: 0.1251
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.2836
 40/116 [=========>....................] - ETA: 0s - loss: 0.1189
 80/116 [===================>..........] - ETA: 0s - loss: 0.1195
116/116 [==============================] - 0s 1ms/step - loss: 0.1235
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0225
 42/116 [=========>....................] - ETA: 0s - loss: 0.1012
 82/116 [====================>.........] - ETA: 0s - loss: 0.1282
116/116 [==============================] - 0s 1ms/step - loss: 0.1220
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0272
 38/116 [========>.....................] - ETA: 0s - loss: 0.1079
 77/116 [==================>...........] - ETA: 0s - loss: 0.1127
114/116 [============================>.] - ETA: 0s - loss: 0.1217
116/116 [==============================] - 0s 1ms/step - loss: 0.1221
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0082
 41/116 [=========>....................] - ETA: 0s - loss: 0.1374
 81/116 [===================>..........] - ETA: 0s - loss: 0.1266
114/116 [============================>.] - ETA: 0s - loss: 0.1244
116/116 [==============================] - 0s 1ms/step - loss: 0.1226
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0696
 41/116 [=========>....................] - ETA: 0s - loss: 0.1297
 82/116 [====================>.........] - ETA: 0s - loss: 0.1140
116/116 [==============================] - 0s 1ms/step - loss: 0.1205
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0128
 41/116 [=========>....................] - ETA: 0s - loss: 0.0967
 81/116 [===================>..........] - ETA: 0s - loss: 0.1143
116/116 [==============================] - 0s 1ms/step - loss: 0.1221
-> test with GAN.predict
GAN tn, fp: 276, 14
GAN fn, tp: 2, 5
GAN f1 score: 0.385
GAN cohens kappa score: 0.363

-> test with 'LR'
LR tn, fp: 263, 27
LR fn, tp: 1, 6
LR f1 score: 0.300
LR cohens kappa score: 0.272
LR average precision score: 0.410

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 3, 4
RF f1 score: 0.571
RF cohens kappa score: 0.561

-> test with 'GB'
GB tn, fp: 281, 9
GB fn, tp: 3, 4
GB f1 score: 0.400
GB cohens kappa score: 0.381

-> test with 'KNN'
KNN tn, fp: 268, 22
KNN fn, tp: 1, 6
KNN f1 score: 0.343
KNN cohens kappa score: 0.317


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 15s - loss: 0.0440
 44/116 [==========>...................] - ETA: 0s - loss: 0.1650 
 87/116 [=====================>........] - ETA: 0s - loss: 0.1573
116/116 [==============================] - 0s 1ms/step - loss: 0.1748
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0625
 41/116 [=========>....................] - ETA: 0s - loss: 0.1617
 82/116 [====================>.........] - ETA: 0s - loss: 0.1641
116/116 [==============================] - 0s 1ms/step - loss: 0.1600
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0205
 44/116 [==========>...................] - ETA: 0s - loss: 0.1550
 87/116 [=====================>........] - ETA: 0s - loss: 0.1508
116/116 [==============================] - 0s 1ms/step - loss: 0.1487
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1963
 42/116 [=========>....................] - ETA: 0s - loss: 0.1306
 86/116 [=====================>........] - ETA: 0s - loss: 0.1524
116/116 [==============================] - 0s 1ms/step - loss: 0.1480
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0733
 44/116 [==========>...................] - ETA: 0s - loss: 0.1360
 87/116 [=====================>........] - ETA: 0s - loss: 0.1386
116/116 [==============================] - 0s 1ms/step - loss: 0.1396
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0346
 43/116 [==========>...................] - ETA: 0s - loss: 0.1505
 86/116 [=====================>........] - ETA: 0s - loss: 0.1360
116/116 [==============================] - 0s 1ms/step - loss: 0.1351
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0557
 44/116 [==========>...................] - ETA: 0s - loss: 0.1425
 87/116 [=====================>........] - ETA: 0s - loss: 0.1385
116/116 [==============================] - 0s 1ms/step - loss: 0.1337
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0258
 43/116 [==========>...................] - ETA: 0s - loss: 0.1334
 86/116 [=====================>........] - ETA: 0s - loss: 0.1306
116/116 [==============================] - 0s 1ms/step - loss: 0.1315
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.2260
 45/116 [==========>...................] - ETA: 0s - loss: 0.1416
 88/116 [=====================>........] - ETA: 0s - loss: 0.1300
116/116 [==============================] - 0s 1ms/step - loss: 0.1330
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0290
 45/116 [==========>...................] - ETA: 0s - loss: 0.1406
 89/116 [======================>.......] - ETA: 0s - loss: 0.1335
116/116 [==============================] - 0s 1ms/step - loss: 0.1301
-> test with GAN.predict
GAN tn, fp: 274, 15
GAN fn, tp: 2, 5
GAN f1 score: 0.370
GAN cohens kappa score: 0.348

-> test with 'LR'
LR tn, fp: 269, 20
LR fn, tp: 1, 6
LR f1 score: 0.364
LR cohens kappa score: 0.339
LR average precision score: 0.409

-> test with 'RF'
RF tn, fp: 289, 0
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: 0.000

-> test with 'GB'
GB tn, fp: 288, 1
GB fn, tp: 7, 0
GB f1 score: 0.000
GB cohens kappa score: -0.006

-> test with 'KNN'
KNN tn, fp: 278, 11
KNN fn, tp: 1, 6
KNN f1 score: 0.500
KNN cohens kappa score: 0.483


====== Step 4/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 21s - loss: 0.3112
 42/116 [=========>....................] - ETA: 0s - loss: 0.2133 
 81/116 [===================>..........] - ETA: 0s - loss: 0.1953
116/116 [==============================] - 0s 1ms/step - loss: 0.1916
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2523
 42/116 [=========>....................] - ETA: 0s - loss: 0.1741
 82/116 [====================>.........] - ETA: 0s - loss: 0.1812
116/116 [==============================] - 0s 1ms/step - loss: 0.1770
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1135
 42/116 [=========>....................] - ETA: 0s - loss: 0.1841
 82/116 [====================>.........] - ETA: 0s - loss: 0.1757
116/116 [==============================] - 0s 1ms/step - loss: 0.1714
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2480
 42/116 [=========>....................] - ETA: 0s - loss: 0.1602
 78/116 [===================>..........] - ETA: 0s - loss: 0.1654
116/116 [==============================] - 0s 1ms/step - loss: 0.1686
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1390
 41/116 [=========>....................] - ETA: 0s - loss: 0.1851
 81/116 [===================>..........] - ETA: 0s - loss: 0.1698
116/116 [==============================] - 0s 1ms/step - loss: 0.1673
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1251
 41/116 [=========>....................] - ETA: 0s - loss: 0.1703
 80/116 [===================>..........] - ETA: 0s - loss: 0.1572
116/116 [==============================] - 0s 1ms/step - loss: 0.1643
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0489
 40/116 [=========>....................] - ETA: 0s - loss: 0.1739
 81/116 [===================>..........] - ETA: 0s - loss: 0.1649
116/116 [==============================] - 0s 1ms/step - loss: 0.1636
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.2643
 41/116 [=========>....................] - ETA: 0s - loss: 0.1528
 81/116 [===================>..........] - ETA: 0s - loss: 0.1614
116/116 [==============================] - 0s 1ms/step - loss: 0.1628
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.2024
 40/116 [=========>....................] - ETA: 0s - loss: 0.1596
 78/116 [===================>..........] - ETA: 0s - loss: 0.1655
116/116 [==============================] - 0s 1ms/step - loss: 0.1621
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.2515
 41/116 [=========>....................] - ETA: 0s - loss: 0.1337
 77/116 [==================>...........] - ETA: 0s - loss: 0.1537
112/116 [===========================>..] - ETA: 0s - loss: 0.1562
116/116 [==============================] - 0s 1ms/step - loss: 0.1587
-> test with GAN.predict
GAN tn, fp: 281, 9
GAN fn, tp: 2, 5
GAN f1 score: 0.476
GAN cohens kappa score: 0.459

-> test with 'LR'
LR tn, fp: 270, 20
LR fn, tp: 1, 6
LR f1 score: 0.364
LR cohens kappa score: 0.339
LR average precision score: 0.631

-> test with 'RF'
RF tn, fp: 290, 0
RF fn, tp: 3, 4
RF f1 score: 0.727
RF cohens kappa score: 0.723

-> test with 'GB'
GB tn, fp: 288, 2
GB fn, tp: 1, 6
GB f1 score: 0.800
GB cohens kappa score: 0.795

-> test with 'KNN'
KNN tn, fp: 271, 19
KNN fn, tp: 1, 6
KNN f1 score: 0.375
KNN cohens kappa score: 0.351


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 30s - loss: 0.1600
 26/116 [=====>........................] - ETA: 0s - loss: 0.1633 
 55/116 [=============>................] - ETA: 0s - loss: 0.1360
 81/116 [===================>..........] - ETA: 0s - loss: 0.1194
103/116 [=========================>....] - ETA: 0s - loss: 0.1180
116/116 [==============================] - 0s 2ms/step - loss: 0.1200
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0616
 23/116 [====>.........................] - ETA: 0s - loss: 0.1204
 46/116 [==========>...................] - ETA: 0s - loss: 0.1104
 68/116 [================>.............] - ETA: 0s - loss: 0.1128
100/116 [========================>.....] - ETA: 0s - loss: 0.1167
116/116 [==============================] - 0s 2ms/step - loss: 0.1101
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1012
 28/116 [======>.......................] - ETA: 0s - loss: 0.0836
 53/116 [============>.................] - ETA: 0s - loss: 0.1135
 83/116 [====================>.........] - ETA: 0s - loss: 0.1057
107/116 [==========================>...] - ETA: 0s - loss: 0.1020
116/116 [==============================] - 0s 2ms/step - loss: 0.1060
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1102
 26/116 [=====>........................] - ETA: 0s - loss: 0.1224
 47/116 [===========>..................] - ETA: 0s - loss: 0.1098
 72/116 [=================>............] - ETA: 0s - loss: 0.1086
 97/116 [========================>.....] - ETA: 0s - loss: 0.0975
116/116 [==============================] - 0s 2ms/step - loss: 0.1036
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1823
 24/116 [=====>........................] - ETA: 0s - loss: 0.1306
 42/116 [=========>....................] - ETA: 0s - loss: 0.1153
 51/116 [============>.................] - ETA: 0s - loss: 0.1100
 61/116 [==============>...............] - ETA: 0s - loss: 0.1124
 73/116 [=================>............] - ETA: 0s - loss: 0.1106
 94/116 [=======================>......] - ETA: 0s - loss: 0.1041
108/116 [==========================>...] - ETA: 0s - loss: 0.1064
116/116 [==============================] - 0s 3ms/step - loss: 0.1014
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1082
 16/116 [===>..........................] - ETA: 0s - loss: 0.0819
 27/116 [=====>........................] - ETA: 0s - loss: 0.1024
 44/116 [==========>...................] - ETA: 0s - loss: 0.0960
 64/116 [===============>..............] - ETA: 0s - loss: 0.0984
 86/116 [=====================>........] - ETA: 0s - loss: 0.0955
105/116 [==========================>...] - ETA: 0s - loss: 0.0999
116/116 [==============================] - 0s 3ms/step - loss: 0.1005
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.3103
 20/116 [====>.........................] - ETA: 0s - loss: 0.1127
 44/116 [==========>...................] - ETA: 0s - loss: 0.1130
 58/116 [==============>...............] - ETA: 0s - loss: 0.1144
 74/116 [==================>...........] - ETA: 0s - loss: 0.1066
 95/116 [=======================>......] - ETA: 0s - loss: 0.0987
116/116 [==============================] - 0s 3ms/step - loss: 0.0992
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0071
 24/116 [=====>........................] - ETA: 0s - loss: 0.0939
 47/116 [===========>..................] - ETA: 0s - loss: 0.0883
 65/116 [===============>..............] - ETA: 0s - loss: 0.0967
 87/116 [=====================>........] - ETA: 0s - loss: 0.1000
111/116 [===========================>..] - ETA: 0s - loss: 0.0987
116/116 [==============================] - 0s 2ms/step - loss: 0.1011
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0482
 23/116 [====>.........................] - ETA: 0s - loss: 0.0962
 46/116 [==========>...................] - ETA: 0s - loss: 0.0921
 65/116 [===============>..............] - ETA: 0s - loss: 0.0904
 80/116 [===================>..........] - ETA: 0s - loss: 0.0936
100/116 [========================>.....] - ETA: 0s - loss: 0.0945
116/116 [==============================] - 0s 3ms/step - loss: 0.0972
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.2095
 17/116 [===>..........................] - ETA: 0s - loss: 0.0819
 38/116 [========>.....................] - ETA: 0s - loss: 0.0824
 62/116 [===============>..............] - ETA: 0s - loss: 0.0891
 83/116 [====================>.........] - ETA: 0s - loss: 0.0975
 99/116 [========================>.....] - ETA: 0s - loss: 0.0948
115/116 [============================>.] - ETA: 0s - loss: 0.0965
116/116 [==============================] - 0s 3ms/step - loss: 0.0979
-> test with GAN.predict
GAN tn, fp: 279, 11
GAN fn, tp: 1, 6
GAN f1 score: 0.500
GAN cohens kappa score: 0.483

-> test with 'LR'
LR tn, fp: 266, 24
LR fn, tp: 0, 7
LR f1 score: 0.368
LR cohens kappa score: 0.343
LR average precision score: 0.303

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 5, 2
RF f1 score: 0.333
RF cohens kappa score: 0.320

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 4, 3
GB f1 score: 0.429
GB cohens kappa score: 0.415

-> test with 'KNN'
KNN tn, fp: 273, 17
KNN fn, tp: 1, 6
KNN f1 score: 0.400
KNN cohens kappa score: 0.378


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.1128
 42/116 [=========>....................] - ETA: 0s - loss: 0.1272 
 83/116 [====================>.........] - ETA: 0s - loss: 0.1420
116/116 [==============================] - 0s 1ms/step - loss: 0.1367
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1040
 41/116 [=========>....................] - ETA: 0s - loss: 0.1126
 80/116 [===================>..........] - ETA: 0s - loss: 0.1235
116/116 [==============================] - 0s 1ms/step - loss: 0.1318
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1292
 42/116 [=========>....................] - ETA: 0s - loss: 0.1291
 83/116 [====================>.........] - ETA: 0s - loss: 0.1361
116/116 [==============================] - 0s 1ms/step - loss: 0.1304
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2499
 41/116 [=========>....................] - ETA: 0s - loss: 0.1406
 81/116 [===================>..........] - ETA: 0s - loss: 0.1205
116/116 [==============================] - 0s 1ms/step - loss: 0.1255
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0328
 40/116 [=========>....................] - ETA: 0s - loss: 0.1308
 81/116 [===================>..........] - ETA: 0s - loss: 0.1212
116/116 [==============================] - 0s 1ms/step - loss: 0.1251
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0819
 42/116 [=========>....................] - ETA: 0s - loss: 0.1313
 83/116 [====================>.........] - ETA: 0s - loss: 0.1202
116/116 [==============================] - 0s 1ms/step - loss: 0.1227
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1839
 40/116 [=========>....................] - ETA: 0s - loss: 0.1215
 79/116 [===================>..........] - ETA: 0s - loss: 0.1210
116/116 [==============================] - 0s 1ms/step - loss: 0.1228
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1975
 41/116 [=========>....................] - ETA: 0s - loss: 0.1208
 80/116 [===================>..........] - ETA: 0s - loss: 0.1198
116/116 [==============================] - 0s 1ms/step - loss: 0.1203
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0825
 42/116 [=========>....................] - ETA: 0s - loss: 0.1478
 82/116 [====================>.........] - ETA: 0s - loss: 0.1112
116/116 [==============================] - 0s 1ms/step - loss: 0.1178
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.2397
 42/116 [=========>....................] - ETA: 0s - loss: 0.1081
 82/116 [====================>.........] - ETA: 0s - loss: 0.1210
116/116 [==============================] - 0s 1ms/step - loss: 0.1171
-> test with GAN.predict
GAN tn, fp: 270, 20
GAN fn, tp: 1, 6
GAN f1 score: 0.364
GAN cohens kappa score: 0.339

-> test with 'LR'
LR tn, fp: 257, 33
LR fn, tp: 1, 6
LR f1 score: 0.261
LR cohens kappa score: 0.230
LR average precision score: 0.634

-> test with 'RF'
RF tn, fp: 286, 4
RF fn, tp: 2, 5
RF f1 score: 0.625
RF cohens kappa score: 0.615

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 1, 6
GB f1 score: 0.706
GB cohens kappa score: 0.697

-> test with 'KNN'
KNN tn, fp: 262, 28
KNN fn, tp: 0, 7
KNN f1 score: 0.333
KNN cohens kappa score: 0.306


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 23s - loss: 0.0428
 35/116 [========>.....................] - ETA: 0s - loss: 0.1659 
 73/116 [=================>............] - ETA: 0s - loss: 0.1580
112/116 [===========================>..] - ETA: 0s - loss: 0.1560
116/116 [==============================] - 0s 1ms/step - loss: 0.1557
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1764
 43/116 [==========>...................] - ETA: 0s - loss: 0.1502
 82/116 [====================>.........] - ETA: 0s - loss: 0.1534
116/116 [==============================] - 0s 1ms/step - loss: 0.1508
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1980
 42/116 [=========>....................] - ETA: 0s - loss: 0.1355
 81/116 [===================>..........] - ETA: 0s - loss: 0.1447
116/116 [==============================] - 0s 1ms/step - loss: 0.1449
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0284
 39/116 [=========>....................] - ETA: 0s - loss: 0.1564
 71/116 [=================>............] - ETA: 0s - loss: 0.1445
110/116 [===========================>..] - ETA: 0s - loss: 0.1469
116/116 [==============================] - 0s 1ms/step - loss: 0.1425
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0970
 40/116 [=========>....................] - ETA: 0s - loss: 0.1555
 80/116 [===================>..........] - ETA: 0s - loss: 0.1487
116/116 [==============================] - 0s 1ms/step - loss: 0.1401
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1246
 40/116 [=========>....................] - ETA: 0s - loss: 0.1550
 80/116 [===================>..........] - ETA: 0s - loss: 0.1332
116/116 [==============================] - 0s 1ms/step - loss: 0.1368
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0770
 39/116 [=========>....................] - ETA: 0s - loss: 0.1387
 80/116 [===================>..........] - ETA: 0s - loss: 0.1301
116/116 [==============================] - 0s 1ms/step - loss: 0.1343
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1725
 41/116 [=========>....................] - ETA: 0s - loss: 0.1336
 79/116 [===================>..........] - ETA: 0s - loss: 0.1329
116/116 [==============================] - 0s 1ms/step - loss: 0.1339
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1424
 41/116 [=========>....................] - ETA: 0s - loss: 0.1370
 80/116 [===================>..........] - ETA: 0s - loss: 0.1392
116/116 [==============================] - 0s 1ms/step - loss: 0.1331
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1734
 41/116 [=========>....................] - ETA: 0s - loss: 0.1387
 81/116 [===================>..........] - ETA: 0s - loss: 0.1311
116/116 [==============================] - 0s 1ms/step - loss: 0.1292
-> test with GAN.predict
GAN tn, fp: 273, 17
GAN fn, tp: 2, 5
GAN f1 score: 0.345
GAN cohens kappa score: 0.321

-> test with 'LR'
LR tn, fp: 262, 28
LR fn, tp: 1, 6
LR f1 score: 0.293
LR cohens kappa score: 0.264
LR average precision score: 0.653

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 4, 3
RF f1 score: 0.545
RF cohens kappa score: 0.538

-> test with 'GB'
GB tn, fp: 289, 1
GB fn, tp: 4, 3
GB f1 score: 0.545
GB cohens kappa score: 0.538

-> test with 'KNN'
KNN tn, fp: 274, 16
KNN fn, tp: 1, 6
KNN f1 score: 0.414
KNN cohens kappa score: 0.392


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 16s - loss: 0.1605
 44/116 [==========>...................] - ETA: 0s - loss: 0.1422 
 87/116 [=====================>........] - ETA: 0s - loss: 0.1406
116/116 [==============================] - 0s 1ms/step - loss: 0.1370
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0135
 45/116 [==========>...................] - ETA: 0s - loss: 0.1366
 89/116 [======================>.......] - ETA: 0s - loss: 0.1313
116/116 [==============================] - 0s 1ms/step - loss: 0.1233
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1735
 44/116 [==========>...................] - ETA: 0s - loss: 0.1240
 87/116 [=====================>........] - ETA: 0s - loss: 0.1230
116/116 [==============================] - 0s 1ms/step - loss: 0.1176
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1072
 44/116 [==========>...................] - ETA: 0s - loss: 0.1018
 87/116 [=====================>........] - ETA: 0s - loss: 0.1078
116/116 [==============================] - 0s 1ms/step - loss: 0.1115
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1275
 45/116 [==========>...................] - ETA: 0s - loss: 0.1129
 86/116 [=====================>........] - ETA: 0s - loss: 0.1166
116/116 [==============================] - 0s 1ms/step - loss: 0.1093
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0587
 44/116 [==========>...................] - ETA: 0s - loss: 0.1153
 87/116 [=====================>........] - ETA: 0s - loss: 0.1176
116/116 [==============================] - 0s 1ms/step - loss: 0.1083
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0499
 42/116 [=========>....................] - ETA: 0s - loss: 0.1234
 85/116 [====================>.........] - ETA: 0s - loss: 0.1075
116/116 [==============================] - 0s 1ms/step - loss: 0.1076
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0469
 45/116 [==========>...................] - ETA: 0s - loss: 0.1100
 86/116 [=====================>........] - ETA: 0s - loss: 0.0964
116/116 [==============================] - 0s 1ms/step - loss: 0.1037
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1585
 44/116 [==========>...................] - ETA: 0s - loss: 0.0907
 87/116 [=====================>........] - ETA: 0s - loss: 0.1047
116/116 [==============================] - 0s 1ms/step - loss: 0.1038
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1129
 44/116 [==========>...................] - ETA: 0s - loss: 0.0998
 87/116 [=====================>........] - ETA: 0s - loss: 0.0960
116/116 [==============================] - 0s 1ms/step - loss: 0.1005
-> test with GAN.predict
GAN tn, fp: 276, 13
GAN fn, tp: 2, 5
GAN f1 score: 0.400
GAN cohens kappa score: 0.379

-> test with 'LR'
LR tn, fp: 267, 22
LR fn, tp: 2, 5
LR f1 score: 0.294
LR cohens kappa score: 0.267
LR average precision score: 0.672

-> test with 'RF'
RF tn, fp: 288, 1
RF fn, tp: 4, 3
RF f1 score: 0.545
RF cohens kappa score: 0.537

-> test with 'GB'
GB tn, fp: 288, 1
GB fn, tp: 4, 3
GB f1 score: 0.545
GB cohens kappa score: 0.537

-> test with 'KNN'
KNN tn, fp: 277, 12
KNN fn, tp: 2, 5
KNN f1 score: 0.417
KNN cohens kappa score: 0.396


====== Step 5/5 =======
-> Shuffling data
-> Spliting data to slices

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0042
 41/116 [=========>....................] - ETA: 0s - loss: 0.1682 
 82/116 [====================>.........] - ETA: 0s - loss: 0.1598
116/116 [==============================] - 0s 1ms/step - loss: 0.1608
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2251
 40/116 [=========>....................] - ETA: 0s - loss: 0.1772
 79/116 [===================>..........] - ETA: 0s - loss: 0.1708
116/116 [==============================] - 0s 1ms/step - loss: 0.1588
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.2664
 40/116 [=========>....................] - ETA: 0s - loss: 0.1475
 80/116 [===================>..........] - ETA: 0s - loss: 0.1483
115/116 [============================>.] - ETA: 0s - loss: 0.1465
116/116 [==============================] - 0s 1ms/step - loss: 0.1458
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1695
 35/116 [========>.....................] - ETA: 0s - loss: 0.1174
 70/116 [=================>............] - ETA: 0s - loss: 0.1282
111/116 [===========================>..] - ETA: 0s - loss: 0.1392
116/116 [==============================] - 0s 1ms/step - loss: 0.1425
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0563
 41/116 [=========>....................] - ETA: 0s - loss: 0.1378
 81/116 [===================>..........] - ETA: 0s - loss: 0.1418
116/116 [==============================] - 0s 1ms/step - loss: 0.1388
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0431
 41/116 [=========>....................] - ETA: 0s - loss: 0.1235
 81/116 [===================>..........] - ETA: 0s - loss: 0.1344
116/116 [==============================] - 0s 1ms/step - loss: 0.1404
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0790
 40/116 [=========>....................] - ETA: 0s - loss: 0.1292
 81/116 [===================>..........] - ETA: 0s - loss: 0.1312
116/116 [==============================] - 0s 1ms/step - loss: 0.1386
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1650
 40/116 [=========>....................] - ETA: 0s - loss: 0.1307
 76/116 [==================>...........] - ETA: 0s - loss: 0.1248
116/116 [==============================] - ETA: 0s - loss: 0.1316
116/116 [==============================] - 0s 1ms/step - loss: 0.1316
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0423
 41/116 [=========>....................] - ETA: 0s - loss: 0.1295
 82/116 [====================>.........] - ETA: 0s - loss: 0.1305
116/116 [==============================] - 0s 1ms/step - loss: 0.1307
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.4222
 41/116 [=========>....................] - ETA: 0s - loss: 0.1276
 82/116 [====================>.........] - ETA: 0s - loss: 0.1331
116/116 [==============================] - 0s 1ms/step - loss: 0.1317
-> test with GAN.predict
GAN tn, fp: 265, 25
GAN fn, tp: 1, 6
GAN f1 score: 0.316
GAN cohens kappa score: 0.288

-> test with 'LR'
LR tn, fp: 259, 31
LR fn, tp: 0, 7
LR f1 score: 0.311
LR cohens kappa score: 0.283
LR average precision score: 0.503

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 3, 4
RF f1 score: 0.667
RF cohens kappa score: 0.660

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 3, 4
GB f1 score: 0.571
GB cohens kappa score: 0.561

-> test with 'KNN'
KNN tn, fp: 268, 22
KNN fn, tp: 1, 6
KNN f1 score: 0.343
KNN cohens kappa score: 0.317


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0216
 37/116 [========>.....................] - ETA: 0s - loss: 0.0721 
 71/116 [=================>............] - ETA: 0s - loss: 0.0743
108/116 [==========================>...] - ETA: 0s - loss: 0.0756
116/116 [==============================] - 0s 1ms/step - loss: 0.0805
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0577
 38/116 [========>.....................] - ETA: 0s - loss: 0.0601
 72/116 [=================>............] - ETA: 0s - loss: 0.0663
108/116 [==========================>...] - ETA: 0s - loss: 0.0690
116/116 [==============================] - 0s 1ms/step - loss: 0.0689
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.2663
 36/116 [========>.....................] - ETA: 0s - loss: 0.0681
 69/116 [================>.............] - ETA: 0s - loss: 0.0721
104/116 [=========================>....] - ETA: 0s - loss: 0.0684
116/116 [==============================] - 0s 1ms/step - loss: 0.0638
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1261
 36/116 [========>.....................] - ETA: 0s - loss: 0.0466
 71/116 [=================>............] - ETA: 0s - loss: 0.0425
106/116 [==========================>...] - ETA: 0s - loss: 0.0482
116/116 [==============================] - 0s 1ms/step - loss: 0.0585
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1395
 32/116 [=======>......................] - ETA: 0s - loss: 0.0723
 63/116 [===============>..............] - ETA: 0s - loss: 0.0589
 97/116 [========================>.....] - ETA: 0s - loss: 0.0585
116/116 [==============================] - 0s 2ms/step - loss: 0.0590
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0030
 40/116 [=========>....................] - ETA: 0s - loss: 0.0606
 79/116 [===================>..........] - ETA: 0s - loss: 0.0641
110/116 [===========================>..] - ETA: 0s - loss: 0.0578
116/116 [==============================] - 0s 1ms/step - loss: 0.0580
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0757
 35/116 [========>.....................] - ETA: 0s - loss: 0.0580
 62/116 [===============>..............] - ETA: 0s - loss: 0.0653
 93/116 [=======================>......] - ETA: 0s - loss: 0.0590
116/116 [==============================] - 0s 2ms/step - loss: 0.0560
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0528
 36/116 [========>.....................] - ETA: 0s - loss: 0.0484
 72/116 [=================>............] - ETA: 0s - loss: 0.0493
108/116 [==========================>...] - ETA: 0s - loss: 0.0575
116/116 [==============================] - 0s 1ms/step - loss: 0.0554
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1425
 33/116 [=======>......................] - ETA: 0s - loss: 0.0778
 71/116 [=================>............] - ETA: 0s - loss: 0.0592
109/116 [===========================>..] - ETA: 0s - loss: 0.0528
116/116 [==============================] - 0s 1ms/step - loss: 0.0545
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0086
 37/116 [========>.....................] - ETA: 0s - loss: 0.0367
 68/116 [================>.............] - ETA: 0s - loss: 0.0517
102/116 [=========================>....] - ETA: 0s - loss: 0.0534
116/116 [==============================] - 0s 1ms/step - loss: 0.0549
-> test with GAN.predict
GAN tn, fp: 284, 6
GAN fn, tp: 3, 4
GAN f1 score: 0.471
GAN cohens kappa score: 0.455

-> test with 'LR'
LR tn, fp: 274, 16
LR fn, tp: 3, 4
LR f1 score: 0.296
LR cohens kappa score: 0.271
LR average precision score: 0.222

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 3, 4
RF f1 score: 0.667
RF cohens kappa score: 0.660

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 3, 4
GB f1 score: 0.571
GB cohens kappa score: 0.561

-> test with 'KNN'
KNN tn, fp: 284, 6
KNN fn, tp: 3, 4
KNN f1 score: 0.471
KNN cohens kappa score: 0.455


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.5072
 41/116 [=========>....................] - ETA: 0s - loss: 0.1911 
 82/116 [====================>.........] - ETA: 0s - loss: 0.1917
116/116 [==============================] - 0s 1ms/step - loss: 0.2063
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2567
 41/116 [=========>....................] - ETA: 0s - loss: 0.1957
 81/116 [===================>..........] - ETA: 0s - loss: 0.2007
116/116 [==============================] - 0s 1ms/step - loss: 0.1866
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1290
 40/116 [=========>....................] - ETA: 0s - loss: 0.2091
 80/116 [===================>..........] - ETA: 0s - loss: 0.1828
114/116 [============================>.] - ETA: 0s - loss: 0.1777
116/116 [==============================] - 0s 1ms/step - loss: 0.1781
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0311
 38/116 [========>.....................] - ETA: 0s - loss: 0.1637
 73/116 [=================>............] - ETA: 0s - loss: 0.1729
112/116 [===========================>..] - ETA: 0s - loss: 0.1720
116/116 [==============================] - 0s 1ms/step - loss: 0.1736
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0930
 38/116 [========>.....................] - ETA: 0s - loss: 0.1898
 79/116 [===================>..........] - ETA: 0s - loss: 0.1688
116/116 [==============================] - 0s 1ms/step - loss: 0.1674
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.2449
 40/116 [=========>....................] - ETA: 0s - loss: 0.1651
 79/116 [===================>..........] - ETA: 0s - loss: 0.1648
116/116 [==============================] - 0s 1ms/step - loss: 0.1670
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0724
 42/116 [=========>....................] - ETA: 0s - loss: 0.1734
 78/116 [===================>..........] - ETA: 0s - loss: 0.1716
115/116 [============================>.] - ETA: 0s - loss: 0.1636
116/116 [==============================] - 0s 1ms/step - loss: 0.1633
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.2415
 40/116 [=========>....................] - ETA: 0s - loss: 0.1590
 81/116 [===================>..........] - ETA: 0s - loss: 0.1668
116/116 [==============================] - 0s 1ms/step - loss: 0.1653
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.2866
 41/116 [=========>....................] - ETA: 0s - loss: 0.1590
 80/116 [===================>..........] - ETA: 0s - loss: 0.1732
116/116 [==============================] - 0s 1ms/step - loss: 0.1676
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1148
 40/116 [=========>....................] - ETA: 0s - loss: 0.1453
 81/116 [===================>..........] - ETA: 0s - loss: 0.1499
116/116 [==============================] - 0s 1ms/step - loss: 0.1591
-> test with GAN.predict
GAN tn, fp: 266, 24
GAN fn, tp: 0, 7
GAN f1 score: 0.368
GAN cohens kappa score: 0.343

-> test with 'LR'
LR tn, fp: 259, 31
LR fn, tp: 0, 7
LR f1 score: 0.311
LR cohens kappa score: 0.283
LR average precision score: 0.720

-> test with 'RF'
RF tn, fp: 285, 5
RF fn, tp: 1, 6
RF f1 score: 0.667
RF cohens kappa score: 0.657

-> test with 'GB'
GB tn, fp: 285, 5
GB fn, tp: 0, 7
GB f1 score: 0.737
GB cohens kappa score: 0.729

-> test with 'KNN'
KNN tn, fp: 273, 17
KNN fn, tp: 0, 7
KNN f1 score: 0.452
KNN cohens kappa score: 0.431


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 49s - loss: 0.1183
 42/116 [=========>....................] - ETA: 0s - loss: 0.1624 
 83/116 [====================>.........] - ETA: 0s - loss: 0.1627
116/116 [==============================] - 1s 1ms/step - loss: 0.1681
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2805
 41/116 [=========>....................] - ETA: 0s - loss: 0.1486
 82/116 [====================>.........] - ETA: 0s - loss: 0.1588
116/116 [==============================] - 0s 1ms/step - loss: 0.1548
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0235
 42/116 [=========>....................] - ETA: 0s - loss: 0.1062
 82/116 [====================>.........] - ETA: 0s - loss: 0.1361
116/116 [==============================] - 0s 1ms/step - loss: 0.1455
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.3295
 41/116 [=========>....................] - ETA: 0s - loss: 0.1444
 82/116 [====================>.........] - ETA: 0s - loss: 0.1329
116/116 [==============================] - 0s 1ms/step - loss: 0.1454
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0205
 41/116 [=========>....................] - ETA: 0s - loss: 0.1218
 82/116 [====================>.........] - ETA: 0s - loss: 0.1449
116/116 [==============================] - 0s 1ms/step - loss: 0.1398
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.2333
 41/116 [=========>....................] - ETA: 0s - loss: 0.1468
 80/116 [===================>..........] - ETA: 0s - loss: 0.1323
116/116 [==============================] - 0s 1ms/step - loss: 0.1378
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0970
 42/116 [=========>....................] - ETA: 0s - loss: 0.1211
 81/116 [===================>..........] - ETA: 0s - loss: 0.1427
116/116 [==============================] - 0s 1ms/step - loss: 0.1355
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0464
 41/116 [=========>....................] - ETA: 0s - loss: 0.1344
 76/116 [==================>...........] - ETA: 0s - loss: 0.1297
110/116 [===========================>..] - ETA: 0s - loss: 0.1349
116/116 [==============================] - 0s 1ms/step - loss: 0.1360
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0965
 35/116 [========>.....................] - ETA: 0s - loss: 0.1337
 74/116 [==================>...........] - ETA: 0s - loss: 0.1275
113/116 [============================>.] - ETA: 0s - loss: 0.1335
116/116 [==============================] - 0s 1ms/step - loss: 0.1330
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0340
 40/116 [=========>....................] - ETA: 0s - loss: 0.1294
 80/116 [===================>..........] - ETA: 0s - loss: 0.1300
116/116 [==============================] - 0s 1ms/step - loss: 0.1320
-> test with GAN.predict
GAN tn, fp: 273, 17
GAN fn, tp: 3, 4
GAN f1 score: 0.286
GAN cohens kappa score: 0.260

-> test with 'LR'
LR tn, fp: 259, 31
LR fn, tp: 0, 7
LR f1 score: 0.311
LR cohens kappa score: 0.283
LR average precision score: 0.439

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 5, 2
RF f1 score: 0.400
RF cohens kappa score: 0.391

-> test with 'GB'
GB tn, fp: 289, 1
GB fn, tp: 5, 2
GB f1 score: 0.400
GB cohens kappa score: 0.391

-> test with 'KNN'
KNN tn, fp: 275, 15
KNN fn, tp: 1, 6
KNN f1 score: 0.429
KNN cohens kappa score: 0.408


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 16s - loss: 0.1445
 51/116 [============>.................] - ETA: 0s - loss: 0.1981 
101/116 [=========================>....] - ETA: 0s - loss: 0.2016
116/116 [==============================] - 0s 1ms/step - loss: 0.1933
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.3912
 51/116 [============>.................] - ETA: 0s - loss: 0.1831
102/116 [=========================>....] - ETA: 0s - loss: 0.1798
116/116 [==============================] - 0s 1ms/step - loss: 0.1774
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.4066
 51/116 [============>.................] - ETA: 0s - loss: 0.1535
100/116 [========================>.....] - ETA: 0s - loss: 0.1676
116/116 [==============================] - 0s 1ms/step - loss: 0.1641
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0619
 52/116 [============>.................] - ETA: 0s - loss: 0.1676
103/116 [=========================>....] - ETA: 0s - loss: 0.1642
116/116 [==============================] - 0s 995us/step - loss: 0.1591
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1903
 51/116 [============>.................] - ETA: 0s - loss: 0.1571
100/116 [========================>.....] - ETA: 0s - loss: 0.1537
116/116 [==============================] - 0s 1ms/step - loss: 0.1543
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0047
 49/116 [===========>..................] - ETA: 0s - loss: 0.1451
 96/116 [=======================>......] - ETA: 0s - loss: 0.1543
116/116 [==============================] - 0s 1ms/step - loss: 0.1517
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.4658
 51/116 [============>.................] - ETA: 0s - loss: 0.1713
102/116 [=========================>....] - ETA: 0s - loss: 0.1463
116/116 [==============================] - 0s 1ms/step - loss: 0.1462
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0147
 51/116 [============>.................] - ETA: 0s - loss: 0.1340
102/116 [=========================>....] - ETA: 0s - loss: 0.1440
116/116 [==============================] - 0s 1ms/step - loss: 0.1429
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.2071
 52/116 [============>.................] - ETA: 0s - loss: 0.1433
103/116 [=========================>....] - ETA: 0s - loss: 0.1443
116/116 [==============================] - 0s 998us/step - loss: 0.1418
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0283
 52/116 [============>.................] - ETA: 0s - loss: 0.1293
103/116 [=========================>....] - ETA: 0s - loss: 0.1375
116/116 [==============================] - 0s 995us/step - loss: 0.1367
-> test with GAN.predict
GAN tn, fp: 271, 18
GAN fn, tp: 2, 5
GAN f1 score: 0.333
GAN cohens kappa score: 0.308

-> test with 'LR'
LR tn, fp: 270, 19
LR fn, tp: 2, 5
LR f1 score: 0.323
LR cohens kappa score: 0.297
LR average precision score: 0.432

-> test with 'RF'
RF tn, fp: 287, 2
RF fn, tp: 4, 3
RF f1 score: 0.500
RF cohens kappa score: 0.490

-> test with 'GB'
GB tn, fp: 284, 5
GB fn, tp: 4, 3
GB f1 score: 0.400
GB cohens kappa score: 0.384

-> test with 'KNN'
KNN tn, fp: 268, 21
KNN fn, tp: 2, 5
KNN f1 score: 0.303
KNN cohens kappa score: 0.276

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 274, 36
LR fn, tp: 3, 7
LR f1 score: 0.400
LR cohens kappa score: 0.377
LR average precision score: 0.746


average:
LR tn, fp: 264.36, 25.44
LR fn, tp: 1.0, 6.0
LR f1 score: 0.316
LR cohens kappa score: 0.289
LR average precision score: 0.518


minimum:
LR tn, fp: 253, 16
LR fn, tp: 0, 4
LR f1 score: 0.250
LR cohens kappa score: 0.220
LR average precision score: 0.222


-----[ RF ]-----
maximum:
RF tn, fp: 290, 5
RF fn, tp: 7, 6
RF f1 score: 0.727
RF cohens kappa score: 0.723


average:
RF tn, fp: 287.88, 1.92
RF fn, tp: 3.8, 3.2
RF f1 score: 0.510
RF cohens kappa score: 0.501


minimum:
RF tn, fp: 285, 0
RF fn, tp: 1, 0
RF f1 score: 0.000
RF cohens kappa score: 0.000


-----[ GB ]-----
maximum:
GB tn, fp: 290, 9
GB fn, tp: 7, 7
GB f1 score: 0.800
GB cohens kappa score: 0.795


average:
GB tn, fp: 286.84, 2.96
GB fn, tp: 3.28, 3.72
GB f1 score: 0.520
GB cohens kappa score: 0.510


minimum:
GB tn, fp: 281, 0
GB fn, tp: 0, 0
GB f1 score: 0.000
GB cohens kappa score: -0.006


-----[ KNN ]-----
maximum:
KNN tn, fp: 284, 31
KNN fn, tp: 3, 7
KNN f1 score: 0.500
KNN cohens kappa score: 0.483


average:
KNN tn, fp: 272.08, 17.72
KNN fn, tp: 1.16, 5.84
KNN f1 score: 0.390
KNN cohens kappa score: 0.367


minimum:
KNN tn, fp: 259, 6
KNN fn, tp: 0, 4
KNN f1 score: 0.286
KNN cohens kappa score: 0.260


-----[ GAN ]-----
maximum:
GAN tn, fp: 284, 27
GAN fn, tp: 3, 7
GAN f1 score: 0.500
GAN cohens kappa score: 0.483


average:
GAN tn, fp: 273.24, 16.56
GAN fn, tp: 1.6, 5.4
GAN f1 score: 0.382
GAN cohens kappa score: 0.359


minimum:
GAN tn, fp: 263, 6
GAN fn, tp: 0, 4
GAN f1 score: 0.242
GAN cohens kappa score: 0.213