ConvGeNBenchmarkResults/data_result/convGAN-proximity-5/folding_flare-F.log

///////////////////////////////////////////
// Running convGAN-proximary-5 on folding_flare-F
///////////////////////////////////////////

Load 'data_input/folding_flare-F'
from pickle file
non empty cut in data_input/folding_flare-F! (23 points)
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 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.9164
35/82 [===========>..................] - ETA: 0s - loss: 0.2039 
70/82 [========================>.....] - ETA: 0s - loss: 0.1780
82/82 [==============================] - 0s 1ms/step - loss: 0.1726
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1154
35/82 [===========>..................] - ETA: 0s - loss: 0.1320
68/82 [=======================>......] - ETA: 0s - loss: 0.1398
82/82 [==============================] - 0s 2ms/step - loss: 0.1452
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1544
39/82 [=============>................] - ETA: 0s - loss: 0.1210
75/82 [==========================>...] - ETA: 0s - loss: 0.1339
82/82 [==============================] - 0s 1ms/step - loss: 0.1315
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3614
36/82 [============>.................] - ETA: 0s - loss: 0.1426
70/82 [========================>.....] - ETA: 0s - loss: 0.1237
82/82 [==============================] - 0s 1ms/step - loss: 0.1220
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0508
36/82 [============>.................] - ETA: 0s - loss: 0.1172
69/82 [========================>.....] - ETA: 0s - loss: 0.1202
82/82 [==============================] - 0s 1ms/step - loss: 0.1178
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1188
36/82 [============>.................] - ETA: 0s - loss: 0.0972
72/82 [=========================>....] - ETA: 0s - loss: 0.1094
82/82 [==============================] - 0s 1ms/step - loss: 0.1110
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0591
33/82 [===========>..................] - ETA: 0s - loss: 0.1028
62/82 [=====================>........] - ETA: 0s - loss: 0.1145
82/82 [==============================] - 0s 2ms/step - loss: 0.1063
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2754
33/82 [===========>..................] - ETA: 0s - loss: 0.1194
67/82 [=======================>......] - ETA: 0s - loss: 0.1085
82/82 [==============================] - 0s 2ms/step - loss: 0.1047
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0650
35/82 [===========>..................] - ETA: 0s - loss: 0.0961
70/82 [========================>.....] - ETA: 0s - loss: 0.0993
82/82 [==============================] - 0s 1ms/step - loss: 0.1019
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0777
31/82 [==========>...................] - ETA: 0s - loss: 0.0901
64/82 [======================>.......] - ETA: 0s - loss: 0.0978
82/82 [==============================] - 0s 2ms/step - loss: 0.0972
-> test with GAN.predict
GAN tn, fp: 191, 14
GAN fn, tp: 5, 4
GAN f1 score: 0.296
GAN cohens kappa score: 0.254

-> test with 'LR'
LR tn, fp: 171, 34
LR fn, tp: 5, 4
LR f1 score: 0.170
LR cohens kappa score: 0.110
LR average precision score: 0.084

-> test with 'RF'
RF tn, fp: 200, 5
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.031

-> test with 'GB'
GB tn, fp: 202, 3
GB fn, tp: 8, 1
GB f1 score: 0.154
GB cohens kappa score: 0.131

-> test with 'KNN'
KNN tn, fp: 174, 31
KNN fn, tp: 4, 5
KNN f1 score: 0.222
KNN cohens kappa score: 0.166


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.8037
39/82 [=============>................] - ETA: 0s - loss: 0.4501 
79/82 [===========================>..] - ETA: 0s - loss: 0.3606
82/82 [==============================] - 0s 1ms/step - loss: 0.3567
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2673
40/82 [=============>................] - ETA: 0s - loss: 0.2585
80/82 [============================>.] - ETA: 0s - loss: 0.2555
82/82 [==============================] - 0s 1ms/step - loss: 0.2541
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1005
40/82 [=============>................] - ETA: 0s - loss: 0.2117
77/82 [===========================>..] - ETA: 0s - loss: 0.2124
82/82 [==============================] - 0s 1ms/step - loss: 0.2229
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1944
38/82 [============>.................] - ETA: 0s - loss: 0.2049
77/82 [===========================>..] - ETA: 0s - loss: 0.2035
82/82 [==============================] - 0s 1ms/step - loss: 0.2022
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1486
41/82 [==============>...............] - ETA: 0s - loss: 0.1908
81/82 [============================>.] - ETA: 0s - loss: 0.1888
82/82 [==============================] - 0s 1ms/step - loss: 0.1903
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.6140
40/82 [=============>................] - ETA: 0s - loss: 0.2026
79/82 [===========================>..] - ETA: 0s - loss: 0.1831
82/82 [==============================] - 0s 1ms/step - loss: 0.1810
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2341
41/82 [==============>...............] - ETA: 0s - loss: 0.1773
76/82 [==========================>...] - ETA: 0s - loss: 0.1666
82/82 [==============================] - 0s 1ms/step - loss: 0.1715
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2542
37/82 [============>.................] - ETA: 0s - loss: 0.1580
72/82 [=========================>....] - ETA: 0s - loss: 0.1645
82/82 [==============================] - 0s 1ms/step - loss: 0.1642
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1617
39/82 [=============>................] - ETA: 0s - loss: 0.1499
76/82 [==========================>...] - ETA: 0s - loss: 0.1595
82/82 [==============================] - 0s 1ms/step - loss: 0.1593
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1160
35/82 [===========>..................] - ETA: 0s - loss: 0.1536
73/82 [=========================>....] - ETA: 0s - loss: 0.1614
82/82 [==============================] - 0s 1ms/step - loss: 0.1570
-> test with GAN.predict
GAN tn, fp: 181, 24
GAN fn, tp: 2, 7
GAN f1 score: 0.350
GAN cohens kappa score: 0.305

-> test with 'LR'
LR tn, fp: 155, 50
LR fn, tp: 1, 8
LR f1 score: 0.239
LR cohens kappa score: 0.179
LR average precision score: 0.406

-> test with 'RF'
RF tn, fp: 201, 4
RF fn, tp: 8, 1
RF f1 score: 0.143
RF cohens kappa score: 0.116

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 8, 1
GB f1 score: 0.167
GB cohens kappa score: 0.149

-> test with 'KNN'
KNN tn, fp: 167, 38
KNN fn, tp: 2, 7
KNN f1 score: 0.259
KNN cohens kappa score: 0.203


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 1.2668
33/82 [===========>..................] - ETA: 0s - loss: 0.3436 
69/82 [========================>.....] - ETA: 0s - loss: 0.3135
82/82 [==============================] - 0s 1ms/step - loss: 0.2979
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0871
37/82 [============>.................] - ETA: 0s - loss: 0.1967
70/82 [========================>.....] - ETA: 0s - loss: 0.2108
82/82 [==============================] - 0s 1ms/step - loss: 0.2130
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1081
35/82 [===========>..................] - ETA: 0s - loss: 0.1758
69/82 [========================>.....] - ETA: 0s - loss: 0.1791
82/82 [==============================] - 0s 1ms/step - loss: 0.1850
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1216
35/82 [===========>..................] - ETA: 0s - loss: 0.1715
68/82 [=======================>......] - ETA: 0s - loss: 0.1714
82/82 [==============================] - 0s 1ms/step - loss: 0.1650
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0526
34/82 [===========>..................] - ETA: 0s - loss: 0.1243
64/82 [======================>.......] - ETA: 0s - loss: 0.1560
82/82 [==============================] - 0s 2ms/step - loss: 0.1534
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.3033
38/82 [============>.................] - ETA: 0s - loss: 0.1390
74/82 [==========================>...] - ETA: 0s - loss: 0.1490
82/82 [==============================] - 0s 1ms/step - loss: 0.1456
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.3979
36/82 [============>.................] - ETA: 0s - loss: 0.1423
74/82 [==========================>...] - ETA: 0s - loss: 0.1445
82/82 [==============================] - 0s 1ms/step - loss: 0.1449
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0550
35/82 [===========>..................] - ETA: 0s - loss: 0.1353
67/82 [=======================>......] - ETA: 0s - loss: 0.1383
82/82 [==============================] - 0s 2ms/step - loss: 0.1341
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1090
38/82 [============>.................] - ETA: 0s - loss: 0.1312
71/82 [========================>.....] - ETA: 0s - loss: 0.1332
82/82 [==============================] - 0s 1ms/step - loss: 0.1299
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0611
36/82 [============>.................] - ETA: 0s - loss: 0.1364
70/82 [========================>.....] - ETA: 0s - loss: 0.1244
82/82 [==============================] - 0s 1ms/step - loss: 0.1263
-> test with GAN.predict
GAN tn, fp: 190, 15
GAN fn, tp: 5, 4
GAN f1 score: 0.286
GAN cohens kappa score: 0.242

-> test with 'LR'
LR tn, fp: 175, 30
LR fn, tp: 3, 6
LR f1 score: 0.267
LR cohens kappa score: 0.214
LR average precision score: 0.327

-> test with 'RF'
RF tn, fp: 203, 2
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.016

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 175, 30
KNN fn, tp: 4, 5
KNN f1 score: 0.227
KNN cohens kappa score: 0.172


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 12s - loss: 0.2789
37/82 [============>.................] - ETA: 0s - loss: 0.3020 
76/82 [==========================>...] - ETA: 0s - loss: 0.2561
82/82 [==============================] - 0s 1ms/step - loss: 0.2495
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0586
36/82 [============>.................] - ETA: 0s - loss: 0.2338
71/82 [========================>.....] - ETA: 0s - loss: 0.2068
82/82 [==============================] - 0s 1ms/step - loss: 0.2028
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2718
40/82 [=============>................] - ETA: 0s - loss: 0.1600
79/82 [===========================>..] - ETA: 0s - loss: 0.1844
82/82 [==============================] - 0s 1ms/step - loss: 0.1853
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1173
40/82 [=============>................] - ETA: 0s - loss: 0.1669
79/82 [===========================>..] - ETA: 0s - loss: 0.1759
82/82 [==============================] - 0s 1ms/step - loss: 0.1761
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0932
36/82 [============>.................] - ETA: 0s - loss: 0.1570
71/82 [========================>.....] - ETA: 0s - loss: 0.1591
82/82 [==============================] - 0s 1ms/step - loss: 0.1661
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1573
41/82 [==============>...............] - ETA: 0s - loss: 0.1403
79/82 [===========================>..] - ETA: 0s - loss: 0.1587
82/82 [==============================] - 0s 1ms/step - loss: 0.1600
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2359
37/82 [============>.................] - ETA: 0s - loss: 0.1562
72/82 [=========================>....] - ETA: 0s - loss: 0.1536
82/82 [==============================] - 0s 1ms/step - loss: 0.1515
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2067
39/82 [=============>................] - ETA: 0s - loss: 0.1456
78/82 [===========================>..] - ETA: 0s - loss: 0.1447
82/82 [==============================] - 0s 1ms/step - loss: 0.1437
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1486
40/82 [=============>................] - ETA: 0s - loss: 0.1300
77/82 [===========================>..] - ETA: 0s - loss: 0.1415
82/82 [==============================] - 0s 1ms/step - loss: 0.1419
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1600
39/82 [=============>................] - ETA: 0s - loss: 0.1351
79/82 [===========================>..] - ETA: 0s - loss: 0.1368
82/82 [==============================] - 0s 1ms/step - loss: 0.1372
-> test with GAN.predict
GAN tn, fp: 199, 6
GAN fn, tp: 5, 4
GAN f1 score: 0.421
GAN cohens kappa score: 0.394

-> test with 'LR'
LR tn, fp: 186, 19
LR fn, tp: 0, 9
LR f1 score: 0.486
LR cohens kappa score: 0.452
LR average precision score: 0.673

-> test with 'RF'
RF tn, fp: 205, 0
RF fn, tp: 7, 2
RF f1 score: 0.364
RF cohens kappa score: 0.354

-> test with 'GB'
GB tn, fp: 204, 1
GB fn, tp: 7, 2
GB f1 score: 0.333
GB cohens kappa score: 0.319

-> test with 'KNN'
KNN tn, fp: 184, 21
KNN fn, tp: 4, 5
KNN f1 score: 0.286
KNN cohens kappa score: 0.238


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 12s - loss: 0.2122
31/82 [==========>...................] - ETA: 0s - loss: 0.2251 
63/82 [======================>.......] - ETA: 0s - loss: 0.2064
82/82 [==============================] - 0s 2ms/step - loss: 0.2081
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0587
40/82 [=============>................] - ETA: 0s - loss: 0.1626
76/82 [==========================>...] - ETA: 0s - loss: 0.1750
82/82 [==============================] - 0s 1ms/step - loss: 0.1686
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2591
36/82 [============>.................] - ETA: 0s - loss: 0.1341
75/82 [==========================>...] - ETA: 0s - loss: 0.1546
82/82 [==============================] - 0s 1ms/step - loss: 0.1555
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0723
37/82 [============>.................] - ETA: 0s - loss: 0.1457
76/82 [==========================>...] - ETA: 0s - loss: 0.1475
82/82 [==============================] - 0s 1ms/step - loss: 0.1464
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1506
33/82 [===========>..................] - ETA: 0s - loss: 0.1330
70/82 [========================>.....] - ETA: 0s - loss: 0.1424
82/82 [==============================] - 0s 2ms/step - loss: 0.1416
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0533
33/82 [===========>..................] - ETA: 0s - loss: 0.1148
64/82 [======================>.......] - ETA: 0s - loss: 0.1301
82/82 [==============================] - 0s 2ms/step - loss: 0.1323
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1078
40/82 [=============>................] - ETA: 0s - loss: 0.1419
80/82 [============================>.] - ETA: 0s - loss: 0.1288
82/82 [==============================] - 0s 1ms/step - loss: 0.1275
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1280
41/82 [==============>...............] - ETA: 0s - loss: 0.1252
77/82 [===========================>..] - ETA: 0s - loss: 0.1266
82/82 [==============================] - 0s 1ms/step - loss: 0.1248
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0214
37/82 [============>.................] - ETA: 0s - loss: 0.1097
73/82 [=========================>....] - ETA: 0s - loss: 0.1185
82/82 [==============================] - 0s 1ms/step - loss: 0.1190
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1028
37/82 [============>.................] - ETA: 0s - loss: 0.1148
75/82 [==========================>...] - ETA: 0s - loss: 0.1120
82/82 [==============================] - 0s 1ms/step - loss: 0.1163
-> test with GAN.predict
GAN tn, fp: 187, 16
GAN fn, tp: 3, 4
GAN f1 score: 0.296
GAN cohens kappa score: 0.260

-> test with 'LR'
LR tn, fp: 170, 33
LR fn, tp: 2, 5
LR f1 score: 0.222
LR cohens kappa score: 0.176
LR average precision score: 0.204

-> test with 'RF'
RF tn, fp: 200, 3
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.020

-> test with 'GB'
GB tn, fp: 200, 3
GB fn, tp: 6, 1
GB f1 score: 0.182
GB cohens kappa score: 0.161

-> test with 'KNN'
KNN tn, fp: 170, 33
KNN fn, tp: 2, 5
KNN f1 score: 0.222
KNN cohens kappa score: 0.176


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

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 0.4221
39/82 [=============>................] - ETA: 0s - loss: 0.2922 
75/82 [==========================>...] - ETA: 0s - loss: 0.2608
82/82 [==============================] - 0s 1ms/step - loss: 0.2508
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.5967
39/82 [=============>................] - ETA: 0s - loss: 0.2161
73/82 [=========================>....] - ETA: 0s - loss: 0.2004
82/82 [==============================] - 0s 1ms/step - loss: 0.2020
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1999
37/82 [============>.................] - ETA: 0s - loss: 0.1643
75/82 [==========================>...] - ETA: 0s - loss: 0.1801
82/82 [==============================] - 0s 1ms/step - loss: 0.1850
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2612
36/82 [============>.................] - ETA: 0s - loss: 0.1929
74/82 [==========================>...] - ETA: 0s - loss: 0.1827
82/82 [==============================] - 0s 1ms/step - loss: 0.1769
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0908
39/82 [=============>................] - ETA: 0s - loss: 0.1674
77/82 [===========================>..] - ETA: 0s - loss: 0.1637
82/82 [==============================] - 0s 1ms/step - loss: 0.1650
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1582
39/82 [=============>................] - ETA: 0s - loss: 0.1450
76/82 [==========================>...] - ETA: 0s - loss: 0.1562
82/82 [==============================] - 0s 1ms/step - loss: 0.1573
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0503
37/82 [============>.................] - ETA: 0s - loss: 0.1456
76/82 [==========================>...] - ETA: 0s - loss: 0.1620
82/82 [==============================] - 0s 1ms/step - loss: 0.1571
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0568
39/82 [=============>................] - ETA: 0s - loss: 0.1333
78/82 [===========================>..] - ETA: 0s - loss: 0.1487
82/82 [==============================] - 0s 1ms/step - loss: 0.1476
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.3695
39/82 [=============>................] - ETA: 0s - loss: 0.1478
73/82 [=========================>....] - ETA: 0s - loss: 0.1428
82/82 [==============================] - 0s 1ms/step - loss: 0.1462
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1205
41/82 [==============>...............] - ETA: 0s - loss: 0.1419
77/82 [===========================>..] - ETA: 0s - loss: 0.1425
82/82 [==============================] - 0s 1ms/step - loss: 0.1421
-> test with GAN.predict
GAN tn, fp: 180, 25
GAN fn, tp: 2, 7
GAN f1 score: 0.341
GAN cohens kappa score: 0.295

-> test with 'LR'
LR tn, fp: 171, 34
LR fn, tp: 2, 7
LR f1 score: 0.280
LR cohens kappa score: 0.227
LR average precision score: 0.395

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 7, 2
RF f1 score: 0.286
RF cohens kappa score: 0.264

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 8, 1
GB f1 score: 0.167
GB cohens kappa score: 0.149

-> test with 'KNN'
KNN tn, fp: 176, 29
KNN fn, tp: 3, 6
KNN f1 score: 0.273
KNN cohens kappa score: 0.221


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 18s - loss: 0.2428
36/82 [============>.................] - ETA: 0s - loss: 0.2299 
68/82 [=======================>......] - ETA: 0s - loss: 0.2145
82/82 [==============================] - 0s 2ms/step - loss: 0.2118
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1335
29/82 [=========>....................] - ETA: 0s - loss: 0.1705
58/82 [====================>.........] - ETA: 0s - loss: 0.1709
82/82 [==============================] - 0s 2ms/step - loss: 0.1689
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1334
36/82 [============>.................] - ETA: 0s - loss: 0.1656
69/82 [========================>.....] - ETA: 0s - loss: 0.1614
82/82 [==============================] - 0s 1ms/step - loss: 0.1540
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0634
35/82 [===========>..................] - ETA: 0s - loss: 0.1241
67/82 [=======================>......] - ETA: 0s - loss: 0.1497
82/82 [==============================] - 0s 2ms/step - loss: 0.1456
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0176
38/82 [============>.................] - ETA: 0s - loss: 0.1358
74/82 [==========================>...] - ETA: 0s - loss: 0.1325
82/82 [==============================] - 0s 1ms/step - loss: 0.1375
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0752
36/82 [============>.................] - ETA: 0s - loss: 0.1301
70/82 [========================>.....] - ETA: 0s - loss: 0.1261
82/82 [==============================] - 0s 1ms/step - loss: 0.1324
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2179
37/82 [============>.................] - ETA: 0s - loss: 0.1183
68/82 [=======================>......] - ETA: 0s - loss: 0.1247
82/82 [==============================] - 0s 1ms/step - loss: 0.1271
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0757
39/82 [=============>................] - ETA: 0s - loss: 0.1199
75/82 [==========================>...] - ETA: 0s - loss: 0.1276
82/82 [==============================] - 0s 1ms/step - loss: 0.1226
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1150
38/82 [============>.................] - ETA: 0s - loss: 0.1059
77/82 [===========================>..] - ETA: 0s - loss: 0.1164
82/82 [==============================] - 0s 1ms/step - loss: 0.1177
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0197
31/82 [==========>...................] - ETA: 0s - loss: 0.1134
66/82 [=======================>......] - ETA: 0s - loss: 0.1132
82/82 [==============================] - 0s 2ms/step - loss: 0.1149
-> test with GAN.predict
GAN tn, fp: 192, 13
GAN fn, tp: 7, 2
GAN f1 score: 0.167
GAN cohens kappa score: 0.120

-> test with 'LR'
LR tn, fp: 167, 38
LR fn, tp: 3, 6
LR f1 score: 0.226
LR cohens kappa score: 0.168
LR average precision score: 0.355

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.021

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

-> test with 'KNN'
KNN tn, fp: 175, 30
KNN fn, tp: 1, 8
KNN f1 score: 0.340
KNN cohens kappa score: 0.292


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.2248
42/82 [==============>...............] - ETA: 0s - loss: 0.2666 
80/82 [============================>.] - ETA: 0s - loss: 0.2221
82/82 [==============================] - 0s 1ms/step - loss: 0.2199
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2000
40/82 [=============>................] - ETA: 0s - loss: 0.1892
78/82 [===========================>..] - ETA: 0s - loss: 0.1697
82/82 [==============================] - 0s 1ms/step - loss: 0.1690
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1787
39/82 [=============>................] - ETA: 0s - loss: 0.1505
74/82 [==========================>...] - ETA: 0s - loss: 0.1514
82/82 [==============================] - 0s 1ms/step - loss: 0.1492
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1248
41/82 [==============>...............] - ETA: 0s - loss: 0.1246
79/82 [===========================>..] - ETA: 0s - loss: 0.1429
82/82 [==============================] - 0s 1ms/step - loss: 0.1402
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1992
40/82 [=============>................] - ETA: 0s - loss: 0.1389
78/82 [===========================>..] - ETA: 0s - loss: 0.1357
82/82 [==============================] - 0s 1ms/step - loss: 0.1317
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1371
36/82 [============>.................] - ETA: 0s - loss: 0.1385
73/82 [=========================>....] - ETA: 0s - loss: 0.1265
82/82 [==============================] - 0s 1ms/step - loss: 0.1267
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1594
38/82 [============>.................] - ETA: 0s - loss: 0.1113
76/82 [==========================>...] - ETA: 0s - loss: 0.1242
82/82 [==============================] - 0s 1ms/step - loss: 0.1239
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2304
37/82 [============>.................] - ETA: 0s - loss: 0.1200
76/82 [==========================>...] - ETA: 0s - loss: 0.1225
82/82 [==============================] - 0s 1ms/step - loss: 0.1221
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0487
42/82 [==============>...............] - ETA: 0s - loss: 0.1219
82/82 [==============================] - 0s 1ms/step - loss: 0.1185
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1941
41/82 [==============>...............] - ETA: 0s - loss: 0.1140
80/82 [============================>.] - ETA: 0s - loss: 0.1167
82/82 [==============================] - 0s 1ms/step - loss: 0.1162
-> test with GAN.predict
GAN tn, fp: 189, 16
GAN fn, tp: 8, 1
GAN f1 score: 0.077
GAN cohens kappa score: 0.023

-> test with 'LR'
LR tn, fp: 176, 29
LR fn, tp: 3, 6
LR f1 score: 0.273
LR cohens kappa score: 0.221
LR average precision score: 0.234

-> test with 'RF'
RF tn, fp: 203, 2
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.016

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 182, 23
KNN fn, tp: 4, 5
KNN f1 score: 0.270
KNN cohens kappa score: 0.221


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 0.1316
33/82 [===========>..................] - ETA: 0s - loss: 0.2077 
63/82 [======================>.......] - ETA: 0s - loss: 0.1889
82/82 [==============================] - 0s 2ms/step - loss: 0.1918
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0765
33/82 [===========>..................] - ETA: 0s - loss: 0.1610
61/82 [=====================>........] - ETA: 0s - loss: 0.1634
82/82 [==============================] - 0s 2ms/step - loss: 0.1529
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0842
34/82 [===========>..................] - ETA: 0s - loss: 0.1661
65/82 [======================>.......] - ETA: 0s - loss: 0.1482
82/82 [==============================] - 0s 2ms/step - loss: 0.1428
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0520
32/82 [==========>...................] - ETA: 0s - loss: 0.1349
65/82 [======================>.......] - ETA: 0s - loss: 0.1327
82/82 [==============================] - 0s 2ms/step - loss: 0.1316
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0642
31/82 [==========>...................] - ETA: 0s - loss: 0.1468
64/82 [======================>.......] - ETA: 0s - loss: 0.1342
82/82 [==============================] - 0s 2ms/step - loss: 0.1279
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0962
34/82 [===========>..................] - ETA: 0s - loss: 0.1240
68/82 [=======================>......] - ETA: 0s - loss: 0.1222
82/82 [==============================] - 0s 2ms/step - loss: 0.1235
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0341
33/82 [===========>..................] - ETA: 0s - loss: 0.1328
63/82 [======================>.......] - ETA: 0s - loss: 0.1176
82/82 [==============================] - 0s 2ms/step - loss: 0.1207
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1453
32/82 [==========>...................] - ETA: 0s - loss: 0.1128
63/82 [======================>.......] - ETA: 0s - loss: 0.1019
82/82 [==============================] - 0s 2ms/step - loss: 0.1138
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1018
32/82 [==========>...................] - ETA: 0s - loss: 0.1145
66/82 [=======================>......] - ETA: 0s - loss: 0.1150
82/82 [==============================] - 0s 2ms/step - loss: 0.1164
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0902
35/82 [===========>..................] - ETA: 0s - loss: 0.1218
65/82 [======================>.......] - ETA: 0s - loss: 0.1255
82/82 [==============================] - 0s 2ms/step - loss: 0.1140
-> test with GAN.predict
GAN tn, fp: 192, 13
GAN fn, tp: 5, 4
GAN f1 score: 0.308
GAN cohens kappa score: 0.267

-> test with 'LR'
LR tn, fp: 183, 22
LR fn, tp: 4, 5
LR f1 score: 0.278
LR cohens kappa score: 0.229
LR average precision score: 0.313

-> test with 'RF'
RF tn, fp: 201, 4
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.027

-> test with 'GB'
GB tn, fp: 204, 1
GB fn, tp: 8, 1
GB f1 score: 0.182
GB cohens kappa score: 0.169

-> test with 'KNN'
KNN tn, fp: 182, 23
KNN fn, tp: 2, 7
KNN f1 score: 0.359
KNN cohens kappa score: 0.315


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 11s - loss: 0.5284
37/82 [============>.................] - ETA: 0s - loss: 0.3910 
76/82 [==========================>...] - ETA: 0s - loss: 0.3179
82/82 [==============================] - 0s 1ms/step - loss: 0.3135
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1856
43/82 [==============>...............] - ETA: 0s - loss: 0.2434
82/82 [==============================] - 0s 1ms/step - loss: 0.2383
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.4566
42/82 [==============>...............] - ETA: 0s - loss: 0.2073
82/82 [==============================] - 0s 1ms/step - loss: 0.2182
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2717
42/82 [==============>...............] - ETA: 0s - loss: 0.2092
82/82 [==============================] - 0s 1ms/step - loss: 0.2045
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1579
42/82 [==============>...............] - ETA: 0s - loss: 0.1888
82/82 [==============================] - ETA: 0s - loss: 0.1916
82/82 [==============================] - 0s 1ms/step - loss: 0.1916
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1652
43/82 [==============>...............] - ETA: 0s - loss: 0.1844
82/82 [==============================] - 0s 1ms/step - loss: 0.1834
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0590
42/82 [==============>...............] - ETA: 0s - loss: 0.1797
82/82 [==============================] - 0s 1ms/step - loss: 0.1764
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2631
43/82 [==============>...............] - ETA: 0s - loss: 0.1672
82/82 [==============================] - ETA: 0s - loss: 0.1726
82/82 [==============================] - 0s 1ms/step - loss: 0.1726
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0860
41/82 [==============>...............] - ETA: 0s - loss: 0.1651
82/82 [==============================] - 0s 1ms/step - loss: 0.1662
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1216
42/82 [==============>...............] - ETA: 0s - loss: 0.1880
82/82 [==============================] - 0s 1ms/step - loss: 0.1650
-> test with GAN.predict
GAN tn, fp: 178, 25
GAN fn, tp: 1, 6
GAN f1 score: 0.316
GAN cohens kappa score: 0.276

-> test with 'LR'
LR tn, fp: 164, 39
LR fn, tp: 0, 7
LR f1 score: 0.264
LR cohens kappa score: 0.219
LR average precision score: 0.408

-> test with 'RF'
RF tn, fp: 202, 1
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 202, 1
GB fn, tp: 6, 1
GB f1 score: 0.222
GB cohens kappa score: 0.211

-> test with 'KNN'
KNN tn, fp: 174, 29
KNN fn, tp: 1, 6
KNN f1 score: 0.286
KNN cohens kappa score: 0.244


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

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 23s - loss: 0.8492
16/82 [====>.........................] - ETA: 0s - loss: 0.5961 
41/82 [==============>...............] - ETA: 0s - loss: 0.4902
67/82 [=======================>......] - ETA: 0s - loss: 0.4329
82/82 [==============================] - 0s 2ms/step - loss: 0.4037
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2750
26/82 [========>.....................] - ETA: 0s - loss: 0.2798
51/82 [=================>............] - ETA: 0s - loss: 0.2725
76/82 [==========================>...] - ETA: 0s - loss: 0.2778
82/82 [==============================] - 0s 2ms/step - loss: 0.2897
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.4645
27/82 [========>.....................] - ETA: 0s - loss: 0.2317
53/82 [==================>...........] - ETA: 0s - loss: 0.2545
78/82 [===========================>..] - ETA: 0s - loss: 0.2671
82/82 [==============================] - 0s 2ms/step - loss: 0.2675
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1276
33/82 [===========>..................] - ETA: 0s - loss: 0.2634
61/82 [=====================>........] - ETA: 0s - loss: 0.2594
82/82 [==============================] - 0s 2ms/step - loss: 0.2513
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1179
35/82 [===========>..................] - ETA: 0s - loss: 0.2473
65/82 [======================>.......] - ETA: 0s - loss: 0.2357
82/82 [==============================] - 0s 2ms/step - loss: 0.2361
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1370
28/82 [=========>....................] - ETA: 0s - loss: 0.2315
56/82 [===================>..........] - ETA: 0s - loss: 0.2325
82/82 [==============================] - ETA: 0s - loss: 0.2260
82/82 [==============================] - 0s 2ms/step - loss: 0.2260
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0959
29/82 [=========>....................] - ETA: 0s - loss: 0.2142
60/82 [====================>.........] - ETA: 0s - loss: 0.2198
82/82 [==============================] - 0s 2ms/step - loss: 0.2162
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0710
30/82 [=========>....................] - ETA: 0s - loss: 0.2082
57/82 [===================>..........] - ETA: 0s - loss: 0.2011
82/82 [==============================] - 0s 2ms/step - loss: 0.2097
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.2192
36/82 [============>.................] - ETA: 0s - loss: 0.1932
68/82 [=======================>......] - ETA: 0s - loss: 0.2038
82/82 [==============================] - 0s 2ms/step - loss: 0.2027
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1560
36/82 [============>.................] - ETA: 0s - loss: 0.1782
69/82 [========================>.....] - ETA: 0s - loss: 0.1836
82/82 [==============================] - 0s 1ms/step - loss: 0.1939
-> test with GAN.predict
GAN tn, fp: 201, 4
GAN fn, tp: 3, 6
GAN f1 score: 0.632
GAN cohens kappa score: 0.615

-> test with 'LR'
LR tn, fp: 186, 19
LR fn, tp: 2, 7
LR f1 score: 0.400
LR cohens kappa score: 0.360
LR average precision score: 0.719

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: 0.000

-> test with 'KNN'
KNN tn, fp: 193, 12
KNN fn, tp: 2, 7
KNN f1 score: 0.500
KNN cohens kappa score: 0.470


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 0.0706
40/82 [=============>................] - ETA: 0s - loss: 0.1976 
80/82 [============================>.] - ETA: 0s - loss: 0.1920
82/82 [==============================] - 0s 1ms/step - loss: 0.1895
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1319
37/82 [============>.................] - ETA: 0s - loss: 0.1662
74/82 [==========================>...] - ETA: 0s - loss: 0.1399
82/82 [==============================] - 0s 1ms/step - loss: 0.1398
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1012
39/82 [=============>................] - ETA: 0s - loss: 0.1401
78/82 [===========================>..] - ETA: 0s - loss: 0.1161
82/82 [==============================] - 0s 1ms/step - loss: 0.1176
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1004
40/82 [=============>................] - ETA: 0s - loss: 0.1027
78/82 [===========================>..] - ETA: 0s - loss: 0.1052
82/82 [==============================] - 0s 1ms/step - loss: 0.1027
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0766
41/82 [==============>...............] - ETA: 0s - loss: 0.1080
81/82 [============================>.] - ETA: 0s - loss: 0.0977
82/82 [==============================] - 0s 1ms/step - loss: 0.0970
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1032
40/82 [=============>................] - ETA: 0s - loss: 0.0929
77/82 [===========================>..] - ETA: 0s - loss: 0.0920
82/82 [==============================] - 0s 1ms/step - loss: 0.0944
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1774
36/82 [============>.................] - ETA: 0s - loss: 0.0792
71/82 [========================>.....] - ETA: 0s - loss: 0.0939
82/82 [==============================] - 0s 1ms/step - loss: 0.0905
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0270
38/82 [============>.................] - ETA: 0s - loss: 0.0872
66/82 [=======================>......] - ETA: 0s - loss: 0.0909
82/82 [==============================] - 0s 2ms/step - loss: 0.0860
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0411
39/82 [=============>................] - ETA: 0s - loss: 0.0750
77/82 [===========================>..] - ETA: 0s - loss: 0.0799
82/82 [==============================] - 0s 1ms/step - loss: 0.0814
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1546
41/82 [==============>...............] - ETA: 0s - loss: 0.0796
80/82 [============================>.] - ETA: 0s - loss: 0.0785
82/82 [==============================] - 0s 1ms/step - loss: 0.0797
-> test with GAN.predict
GAN tn, fp: 189, 16
GAN fn, tp: 4, 5
GAN f1 score: 0.333
GAN cohens kappa score: 0.292

-> test with 'LR'
LR tn, fp: 166, 39
LR fn, tp: 2, 7
LR f1 score: 0.255
LR cohens kappa score: 0.198
LR average precision score: 0.192

-> test with 'RF'
RF tn, fp: 195, 10
RF fn, tp: 8, 1
RF f1 score: 0.100
RF cohens kappa score: 0.056

-> test with 'GB'
GB tn, fp: 191, 14
GB fn, tp: 5, 4
GB f1 score: 0.296
GB cohens kappa score: 0.254

-> test with 'KNN'
KNN tn, fp: 172, 33
KNN fn, tp: 4, 5
KNN f1 score: 0.213
KNN cohens kappa score: 0.155


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 15s - loss: 0.2134
29/82 [=========>....................] - ETA: 0s - loss: 0.3438 
57/82 [===================>..........] - ETA: 0s - loss: 0.3048
82/82 [==============================] - 0s 2ms/step - loss: 0.2746
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2097
32/82 [==========>...................] - ETA: 0s - loss: 0.2203
65/82 [======================>.......] - ETA: 0s - loss: 0.2100
82/82 [==============================] - 0s 2ms/step - loss: 0.2196
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0829
30/82 [=========>....................] - ETA: 0s - loss: 0.2162
61/82 [=====================>........] - ETA: 0s - loss: 0.1987
82/82 [==============================] - 0s 2ms/step - loss: 0.1997
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2071
32/82 [==========>...................] - ETA: 0s - loss: 0.1833
63/82 [======================>.......] - ETA: 0s - loss: 0.1765
82/82 [==============================] - 0s 2ms/step - loss: 0.1895
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2124
34/82 [===========>..................] - ETA: 0s - loss: 0.1882
67/82 [=======================>......] - ETA: 0s - loss: 0.1839
82/82 [==============================] - 0s 2ms/step - loss: 0.1826
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1397
35/82 [===========>..................] - ETA: 0s - loss: 0.1834
67/82 [=======================>......] - ETA: 0s - loss: 0.1823
82/82 [==============================] - 0s 2ms/step - loss: 0.1765
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.4504
38/82 [============>.................] - ETA: 0s - loss: 0.1795
71/82 [========================>.....] - ETA: 0s - loss: 0.1712
82/82 [==============================] - 0s 1ms/step - loss: 0.1721
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0823
34/82 [===========>..................] - ETA: 0s - loss: 0.1570
71/82 [========================>.....] - ETA: 0s - loss: 0.1693
82/82 [==============================] - 0s 1ms/step - loss: 0.1668
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1807
34/82 [===========>..................] - ETA: 0s - loss: 0.1639
68/82 [=======================>......] - ETA: 0s - loss: 0.1668
82/82 [==============================] - 0s 2ms/step - loss: 0.1621
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1836
34/82 [===========>..................] - ETA: 0s - loss: 0.1450
69/82 [========================>.....] - ETA: 0s - loss: 0.1586
82/82 [==============================] - 0s 1ms/step - loss: 0.1579
-> test with GAN.predict
GAN tn, fp: 189, 16
GAN fn, tp: 4, 5
GAN f1 score: 0.333
GAN cohens kappa score: 0.292

-> test with 'LR'
LR tn, fp: 174, 31
LR fn, tp: 2, 7
LR f1 score: 0.298
LR cohens kappa score: 0.247
LR average precision score: 0.355

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 204, 1
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.008

-> test with 'KNN'
KNN tn, fp: 173, 32
KNN fn, tp: 3, 6
KNN f1 score: 0.255
KNN cohens kappa score: 0.201


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 0.2445
40/82 [=============>................] - ETA: 0s - loss: 0.3131 
80/82 [============================>.] - ETA: 0s - loss: 0.2705
82/82 [==============================] - 0s 1ms/step - loss: 0.2753
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0762
40/82 [=============>................] - ETA: 0s - loss: 0.2319
78/82 [===========================>..] - ETA: 0s - loss: 0.2201
82/82 [==============================] - 0s 1ms/step - loss: 0.2183
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2500
40/82 [=============>................] - ETA: 0s - loss: 0.2026
78/82 [===========================>..] - ETA: 0s - loss: 0.2017
82/82 [==============================] - 0s 1ms/step - loss: 0.2037
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0835
41/82 [==============>...............] - ETA: 0s - loss: 0.1898
79/82 [===========================>..] - ETA: 0s - loss: 0.1896
82/82 [==============================] - 0s 1ms/step - loss: 0.1911
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2216
30/82 [=========>....................] - ETA: 0s - loss: 0.1931
70/82 [========================>.....] - ETA: 0s - loss: 0.1838
82/82 [==============================] - 0s 2ms/step - loss: 0.1805
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0434
33/82 [===========>..................] - ETA: 0s - loss: 0.1794
63/82 [======================>.......] - ETA: 0s - loss: 0.1705
82/82 [==============================] - 0s 2ms/step - loss: 0.1766
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1667
40/82 [=============>................] - ETA: 0s - loss: 0.1810
77/82 [===========================>..] - ETA: 0s - loss: 0.1702
82/82 [==============================] - 0s 1ms/step - loss: 0.1719
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1246
39/82 [=============>................] - ETA: 0s - loss: 0.1744
77/82 [===========================>..] - ETA: 0s - loss: 0.1652
82/82 [==============================] - 0s 1ms/step - loss: 0.1654
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0828
39/82 [=============>................] - ETA: 0s - loss: 0.1380
77/82 [===========================>..] - ETA: 0s - loss: 0.1593
82/82 [==============================] - 0s 1ms/step - loss: 0.1611
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1250
40/82 [=============>................] - ETA: 0s - loss: 0.1552
79/82 [===========================>..] - ETA: 0s - loss: 0.1583
82/82 [==============================] - 0s 1ms/step - loss: 0.1576
-> test with GAN.predict
GAN tn, fp: 191, 14
GAN fn, tp: 6, 3
GAN f1 score: 0.231
GAN cohens kappa score: 0.186

-> test with 'LR'
LR tn, fp: 174, 31
LR fn, tp: 4, 5
LR f1 score: 0.222
LR cohens kappa score: 0.166
LR average precision score: 0.345

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: 0.000

-> test with 'KNN'
KNN tn, fp: 182, 23
KNN fn, tp: 4, 5
KNN f1 score: 0.270
KNN cohens kappa score: 0.221


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 17s - loss: 0.3246
32/82 [==========>...................] - ETA: 0s - loss: 0.2244 
65/82 [======================>.......] - ETA: 0s - loss: 0.2058
82/82 [==============================] - 0s 2ms/step - loss: 0.2051
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1608
31/82 [==========>...................] - ETA: 0s - loss: 0.1487
59/82 [====================>.........] - ETA: 0s - loss: 0.1501
82/82 [==============================] - 0s 2ms/step - loss: 0.1497
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0251
31/82 [==========>...................] - ETA: 0s - loss: 0.1194
63/82 [======================>.......] - ETA: 0s - loss: 0.1352
82/82 [==============================] - 0s 2ms/step - loss: 0.1347
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0542
33/82 [===========>..................] - ETA: 0s - loss: 0.1295
67/82 [=======================>......] - ETA: 0s - loss: 0.1265
82/82 [==============================] - 0s 2ms/step - loss: 0.1266
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0402
32/82 [==========>...................] - ETA: 0s - loss: 0.1041
63/82 [======================>.......] - ETA: 0s - loss: 0.1226
82/82 [==============================] - 0s 2ms/step - loss: 0.1222
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0446
36/82 [============>.................] - ETA: 0s - loss: 0.1184
73/82 [=========================>....] - ETA: 0s - loss: 0.1084
82/82 [==============================] - 0s 1ms/step - loss: 0.1161
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0480
36/82 [============>.................] - ETA: 0s - loss: 0.0945
71/82 [========================>.....] - ETA: 0s - loss: 0.1131
82/82 [==============================] - 0s 1ms/step - loss: 0.1129
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0288
31/82 [==========>...................] - ETA: 0s - loss: 0.1381
66/82 [=======================>......] - ETA: 0s - loss: 0.1160
82/82 [==============================] - 0s 2ms/step - loss: 0.1121
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0640
35/82 [===========>..................] - ETA: 0s - loss: 0.1191
72/82 [=========================>....] - ETA: 0s - loss: 0.1081
82/82 [==============================] - 0s 1ms/step - loss: 0.1070
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0546
38/82 [============>.................] - ETA: 0s - loss: 0.0999
73/82 [=========================>....] - ETA: 0s - loss: 0.1084
82/82 [==============================] - 0s 1ms/step - loss: 0.1051
-> test with GAN.predict
GAN tn, fp: 186, 17
GAN fn, tp: 5, 2
GAN f1 score: 0.154
GAN cohens kappa score: 0.111

-> test with 'LR'
LR tn, fp: 161, 42
LR fn, tp: 1, 6
LR f1 score: 0.218
LR cohens kappa score: 0.170
LR average precision score: 0.244

-> test with 'RF'
RF tn, fp: 197, 6
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.032

-> test with 'GB'
GB tn, fp: 199, 4
GB fn, tp: 6, 1
GB f1 score: 0.167
GB cohens kappa score: 0.143

-> test with 'KNN'
KNN tn, fp: 180, 23
KNN fn, tp: 3, 4
KNN f1 score: 0.235
KNN cohens kappa score: 0.193


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

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 16s - loss: 0.7434
35/82 [===========>..................] - ETA: 0s - loss: 0.2439 
74/82 [==========================>...] - ETA: 0s - loss: 0.2324
82/82 [==============================] - 0s 1ms/step - loss: 0.2255
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0615
40/82 [=============>................] - ETA: 0s - loss: 0.1453
79/82 [===========================>..] - ETA: 0s - loss: 0.1735
82/82 [==============================] - 0s 1ms/step - loss: 0.1724
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1299
41/82 [==============>...............] - ETA: 0s - loss: 0.1782
79/82 [===========================>..] - ETA: 0s - loss: 0.1592
82/82 [==============================] - 0s 1ms/step - loss: 0.1568
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2965
36/82 [============>.................] - ETA: 0s - loss: 0.1517
73/82 [=========================>....] - ETA: 0s - loss: 0.1511
82/82 [==============================] - 0s 1ms/step - loss: 0.1484
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1499
39/82 [=============>................] - ETA: 0s - loss: 0.1546
76/82 [==========================>...] - ETA: 0s - loss: 0.1417
82/82 [==============================] - 0s 1ms/step - loss: 0.1413
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2835
39/82 [=============>................] - ETA: 0s - loss: 0.1374
79/82 [===========================>..] - ETA: 0s - loss: 0.1348
82/82 [==============================] - 0s 1ms/step - loss: 0.1318
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.3789
39/82 [=============>................] - ETA: 0s - loss: 0.1318
76/82 [==========================>...] - ETA: 0s - loss: 0.1269
82/82 [==============================] - 0s 1ms/step - loss: 0.1265
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0398
39/82 [=============>................] - ETA: 0s - loss: 0.1313
76/82 [==========================>...] - ETA: 0s - loss: 0.1250
82/82 [==============================] - 0s 1ms/step - loss: 0.1247
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.6100
35/82 [===========>..................] - ETA: 0s - loss: 0.1199
73/82 [=========================>....] - ETA: 0s - loss: 0.1210
82/82 [==============================] - 0s 1ms/step - loss: 0.1180
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1100
38/82 [============>.................] - ETA: 0s - loss: 0.1199
77/82 [===========================>..] - ETA: 0s - loss: 0.1194
82/82 [==============================] - 0s 1ms/step - loss: 0.1157
-> test with GAN.predict
GAN tn, fp: 192, 13
GAN fn, tp: 5, 4
GAN f1 score: 0.308
GAN cohens kappa score: 0.267

-> test with 'LR'
LR tn, fp: 168, 37
LR fn, tp: 1, 8
LR f1 score: 0.296
LR cohens kappa score: 0.243
LR average precision score: 0.221

-> test with 'RF'
RF tn, fp: 199, 6
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.035

-> test with 'GB'
GB tn, fp: 201, 4
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.027

-> test with 'KNN'
KNN tn, fp: 182, 23
KNN fn, tp: 4, 5
KNN f1 score: 0.270
KNN cohens kappa score: 0.221


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.8841
35/82 [===========>..................] - ETA: 0s - loss: 0.2316 
68/82 [=======================>......] - ETA: 0s - loss: 0.1935
82/82 [==============================] - 0s 2ms/step - loss: 0.1845
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1649
34/82 [===========>..................] - ETA: 0s - loss: 0.1268
67/82 [=======================>......] - ETA: 0s - loss: 0.1423
82/82 [==============================] - 0s 2ms/step - loss: 0.1385
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1781
35/82 [===========>..................] - ETA: 0s - loss: 0.1207
69/82 [========================>.....] - ETA: 0s - loss: 0.1189
82/82 [==============================] - 0s 2ms/step - loss: 0.1236
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1463
36/82 [============>.................] - ETA: 0s - loss: 0.1192
71/82 [========================>.....] - ETA: 0s - loss: 0.1139
82/82 [==============================] - 0s 1ms/step - loss: 0.1170
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0961
37/82 [============>.................] - ETA: 0s - loss: 0.1264
70/82 [========================>.....] - ETA: 0s - loss: 0.1138
82/82 [==============================] - 0s 1ms/step - loss: 0.1143
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0303
36/82 [============>.................] - ETA: 0s - loss: 0.0962
65/82 [======================>.......] - ETA: 0s - loss: 0.0991
82/82 [==============================] - 0s 2ms/step - loss: 0.1083
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0966
34/82 [===========>..................] - ETA: 0s - loss: 0.1032
69/82 [========================>.....] - ETA: 0s - loss: 0.1075
82/82 [==============================] - 0s 2ms/step - loss: 0.1054
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2336
35/82 [===========>..................] - ETA: 0s - loss: 0.0980
68/82 [=======================>......] - ETA: 0s - loss: 0.1018
82/82 [==============================] - 0s 2ms/step - loss: 0.1030
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0487
36/82 [============>.................] - ETA: 0s - loss: 0.1025
69/82 [========================>.....] - ETA: 0s - loss: 0.0961
82/82 [==============================] - 0s 1ms/step - loss: 0.0995
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0758
34/82 [===========>..................] - ETA: 0s - loss: 0.0999
67/82 [=======================>......] - ETA: 0s - loss: 0.0992
82/82 [==============================] - 0s 2ms/step - loss: 0.0993
-> test with GAN.predict
GAN tn, fp: 195, 10
GAN fn, tp: 5, 4
GAN f1 score: 0.348
GAN cohens kappa score: 0.313

-> test with 'LR'
LR tn, fp: 180, 25
LR fn, tp: 2, 7
LR f1 score: 0.341
LR cohens kappa score: 0.295
LR average precision score: 0.546

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.021

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 181, 24
KNN fn, tp: 4, 5
KNN f1 score: 0.263
KNN cohens kappa score: 0.213


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 12s - loss: 0.3874
40/82 [=============>................] - ETA: 0s - loss: 0.1897 
79/82 [===========================>..] - ETA: 0s - loss: 0.1859
82/82 [==============================] - 0s 1ms/step - loss: 0.1841
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0424
38/82 [============>.................] - ETA: 0s - loss: 0.1499
76/82 [==========================>...] - ETA: 0s - loss: 0.1530
82/82 [==============================] - 0s 1ms/step - loss: 0.1506
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1468
40/82 [=============>................] - ETA: 0s - loss: 0.1278
77/82 [===========================>..] - ETA: 0s - loss: 0.1277
82/82 [==============================] - 0s 1ms/step - loss: 0.1363
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0986
43/82 [==============>...............] - ETA: 0s - loss: 0.1325
82/82 [==============================] - ETA: 0s - loss: 0.1283
82/82 [==============================] - 0s 1ms/step - loss: 0.1283
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2165
38/82 [============>.................] - ETA: 0s - loss: 0.1210
76/82 [==========================>...] - ETA: 0s - loss: 0.1251
82/82 [==============================] - 0s 1ms/step - loss: 0.1242
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2127
41/82 [==============>...............] - ETA: 0s - loss: 0.1240
78/82 [===========================>..] - ETA: 0s - loss: 0.1185
82/82 [==============================] - 0s 1ms/step - loss: 0.1186
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1159
39/82 [=============>................] - ETA: 0s - loss: 0.1140
78/82 [===========================>..] - ETA: 0s - loss: 0.1146
82/82 [==============================] - 0s 1ms/step - loss: 0.1150
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0355
38/82 [============>.................] - ETA: 0s - loss: 0.0968
76/82 [==========================>...] - ETA: 0s - loss: 0.1096
82/82 [==============================] - 0s 1ms/step - loss: 0.1112
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0478
34/82 [===========>..................] - ETA: 0s - loss: 0.1095
68/82 [=======================>......] - ETA: 0s - loss: 0.1080
82/82 [==============================] - 0s 1ms/step - loss: 0.1096
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0719
32/82 [==========>...................] - ETA: 0s - loss: 0.1100
71/82 [========================>.....] - ETA: 0s - loss: 0.1083
82/82 [==============================] - 0s 1ms/step - loss: 0.1069
-> test with GAN.predict
GAN tn, fp: 187, 18
GAN fn, tp: 4, 5
GAN f1 score: 0.312
GAN cohens kappa score: 0.268

-> test with 'LR'
LR tn, fp: 168, 37
LR fn, tp: 4, 5
LR f1 score: 0.196
LR cohens kappa score: 0.136
LR average precision score: 0.199

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.169

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 178, 27
KNN fn, tp: 4, 5
KNN f1 score: 0.244
KNN cohens kappa score: 0.191


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 15s - loss: 0.1647
35/82 [===========>..................] - ETA: 0s - loss: 0.1708 
73/82 [=========================>....] - ETA: 0s - loss: 0.1627
82/82 [==============================] - 0s 1ms/step - loss: 0.1595
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0806
34/82 [===========>..................] - ETA: 0s - loss: 0.1258
69/82 [========================>.....] - ETA: 0s - loss: 0.1272
82/82 [==============================] - 0s 2ms/step - loss: 0.1298
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0501
32/82 [==========>...................] - ETA: 0s - loss: 0.1185
58/82 [====================>.........] - ETA: 0s - loss: 0.1121
82/82 [==============================] - 0s 2ms/step - loss: 0.1170
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1087
33/82 [===========>..................] - ETA: 0s - loss: 0.1083
69/82 [========================>.....] - ETA: 0s - loss: 0.1044
82/82 [==============================] - 0s 2ms/step - loss: 0.1101
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1069
35/82 [===========>..................] - ETA: 0s - loss: 0.1180
66/82 [=======================>......] - ETA: 0s - loss: 0.1128
82/82 [==============================] - 0s 2ms/step - loss: 0.1079
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0880
36/82 [============>.................] - ETA: 0s - loss: 0.1069
70/82 [========================>.....] - ETA: 0s - loss: 0.1022
82/82 [==============================] - 0s 1ms/step - loss: 0.1043
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1447
36/82 [============>.................] - ETA: 0s - loss: 0.0934
72/82 [=========================>....] - ETA: 0s - loss: 0.1091
82/82 [==============================] - 0s 1ms/step - loss: 0.1025
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0544
34/82 [===========>..................] - ETA: 0s - loss: 0.1117
70/82 [========================>.....] - ETA: 0s - loss: 0.1059
82/82 [==============================] - 0s 1ms/step - loss: 0.1002
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1113
36/82 [============>.................] - ETA: 0s - loss: 0.1094
71/82 [========================>.....] - ETA: 0s - loss: 0.0960
82/82 [==============================] - 0s 1ms/step - loss: 0.0966
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0616
34/82 [===========>..................] - ETA: 0s - loss: 0.0847
68/82 [=======================>......] - ETA: 0s - loss: 0.0917
82/82 [==============================] - 0s 2ms/step - loss: 0.0929
-> test with GAN.predict
GAN tn, fp: 195, 10
GAN fn, tp: 5, 4
GAN f1 score: 0.348
GAN cohens kappa score: 0.313

-> test with 'LR'
LR tn, fp: 175, 30
LR fn, tp: 1, 8
LR f1 score: 0.340
LR cohens kappa score: 0.292
LR average precision score: 0.402

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 8, 1
RF f1 score: 0.154
RF cohens kappa score: 0.131

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 6, 3
GB f1 score: 0.429
GB cohens kappa score: 0.411

-> test with 'KNN'
KNN tn, fp: 183, 22
KNN fn, tp: 2, 7
KNN f1 score: 0.368
KNN cohens kappa score: 0.325


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 11s - loss: 0.2452
42/82 [==============>...............] - ETA: 0s - loss: 0.3296 
81/82 [============================>.] - ETA: 0s - loss: 0.2943
82/82 [==============================] - 0s 1ms/step - loss: 0.2940
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1815
42/82 [==============>...............] - ETA: 0s - loss: 0.2281
82/82 [==============================] - 0s 1ms/step - loss: 0.2232
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0787
41/82 [==============>...............] - ETA: 0s - loss: 0.2016
80/82 [============================>.] - ETA: 0s - loss: 0.1962
82/82 [==============================] - 0s 1ms/step - loss: 0.1965
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1945
41/82 [==============>...............] - ETA: 0s - loss: 0.1842
82/82 [==============================] - 0s 1ms/step - loss: 0.1816
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1092
42/82 [==============>...............] - ETA: 0s - loss: 0.1631
82/82 [==============================] - 0s 1ms/step - loss: 0.1701
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2869
43/82 [==============>...............] - ETA: 0s - loss: 0.1544
82/82 [==============================] - 0s 1ms/step - loss: 0.1632
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1429
40/82 [=============>................] - ETA: 0s - loss: 0.1492
80/82 [============================>.] - ETA: 0s - loss: 0.1590
82/82 [==============================] - 0s 1ms/step - loss: 0.1587
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1473
42/82 [==============>...............] - ETA: 0s - loss: 0.1659
82/82 [==============================] - ETA: 0s - loss: 0.1521
82/82 [==============================] - 0s 1ms/step - loss: 0.1521
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0769
38/82 [============>.................] - ETA: 0s - loss: 0.1460
78/82 [===========================>..] - ETA: 0s - loss: 0.1500
82/82 [==============================] - 0s 1ms/step - loss: 0.1489
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1277
41/82 [==============>...............] - ETA: 0s - loss: 0.1490
76/82 [==========================>...] - ETA: 0s - loss: 0.1397
82/82 [==============================] - 0s 1ms/step - loss: 0.1431
-> test with GAN.predict
GAN tn, fp: 181, 22
GAN fn, tp: 3, 4
GAN f1 score: 0.242
GAN cohens kappa score: 0.200

-> test with 'LR'
LR tn, fp: 168, 35
LR fn, tp: 1, 6
LR f1 score: 0.250
LR cohens kappa score: 0.205
LR average precision score: 0.507

-> test with 'RF'
RF tn, fp: 201, 2
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.015

-> test with 'GB'
GB tn, fp: 200, 3
GB fn, tp: 6, 1
GB f1 score: 0.182
GB cohens kappa score: 0.161

-> test with 'KNN'
KNN tn, fp: 165, 38
KNN fn, tp: 3, 4
KNN f1 score: 0.163
KNN cohens kappa score: 0.113


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

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.5359
33/82 [===========>..................] - ETA: 0s - loss: 0.4556 
68/82 [=======================>......] - ETA: 0s - loss: 0.3653
82/82 [==============================] - 0s 2ms/step - loss: 0.3554
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0604
37/82 [============>.................] - ETA: 0s - loss: 0.2508
70/82 [========================>.....] - ETA: 0s - loss: 0.2433
82/82 [==============================] - 0s 1ms/step - loss: 0.2381
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.6137
33/82 [===========>..................] - ETA: 0s - loss: 0.2349
65/82 [======================>.......] - ETA: 0s - loss: 0.2028
82/82 [==============================] - 0s 2ms/step - loss: 0.2079
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.7613
33/82 [===========>..................] - ETA: 0s - loss: 0.1918
67/82 [=======================>......] - ETA: 0s - loss: 0.1739
82/82 [==============================] - 0s 2ms/step - loss: 0.1888
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.3021
34/82 [===========>..................] - ETA: 0s - loss: 0.1525
68/82 [=======================>......] - ETA: 0s - loss: 0.1727
82/82 [==============================] - 0s 2ms/step - loss: 0.1774
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0732
33/82 [===========>..................] - ETA: 0s - loss: 0.1440
62/82 [=====================>........] - ETA: 0s - loss: 0.1688
82/82 [==============================] - 0s 2ms/step - loss: 0.1677
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0854
35/82 [===========>..................] - ETA: 0s - loss: 0.1677
74/82 [==========================>...] - ETA: 0s - loss: 0.1622
82/82 [==============================] - 0s 1ms/step - loss: 0.1606
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0405
39/82 [=============>................] - ETA: 0s - loss: 0.1403
74/82 [==========================>...] - ETA: 0s - loss: 0.1555
82/82 [==============================] - 0s 1ms/step - loss: 0.1530
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0371
35/82 [===========>..................] - ETA: 0s - loss: 0.1391
69/82 [========================>.....] - ETA: 0s - loss: 0.1469
82/82 [==============================] - 0s 1ms/step - loss: 0.1469
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1315
36/82 [============>.................] - ETA: 0s - loss: 0.1521
69/82 [========================>.....] - ETA: 0s - loss: 0.1403
82/82 [==============================] - 0s 2ms/step - loss: 0.1413
-> test with GAN.predict
GAN tn, fp: 190, 15
GAN fn, tp: 3, 6
GAN f1 score: 0.400
GAN cohens kappa score: 0.362

-> test with 'LR'
LR tn, fp: 179, 26
LR fn, tp: 4, 5
LR f1 score: 0.250
LR cohens kappa score: 0.198
LR average precision score: 0.184

-> test with 'RF'
RF tn, fp: 203, 2
RF fn, tp: 8, 1
RF f1 score: 0.167
RF cohens kappa score: 0.149

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 8, 1
GB f1 score: 0.167
GB cohens kappa score: 0.149

-> test with 'KNN'
KNN tn, fp: 180, 25
KNN fn, tp: 3, 6
KNN f1 score: 0.300
KNN cohens kappa score: 0.251


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 34s - loss: 0.4885
34/82 [===========>..................] - ETA: 0s - loss: 0.3606 
71/82 [========================>.....] - ETA: 0s - loss: 0.3125
82/82 [==============================] - 1s 1ms/step - loss: 0.2963
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2784
41/82 [==============>...............] - ETA: 0s - loss: 0.2063
81/82 [============================>.] - ETA: 0s - loss: 0.2059
82/82 [==============================] - 0s 1ms/step - loss: 0.2068
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.3236
41/82 [==============>...............] - ETA: 0s - loss: 0.1831
78/82 [===========================>..] - ETA: 0s - loss: 0.1858
82/82 [==============================] - 0s 1ms/step - loss: 0.1885
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2994
36/82 [============>.................] - ETA: 0s - loss: 0.1883
73/82 [=========================>....] - ETA: 0s - loss: 0.1853
82/82 [==============================] - 0s 1ms/step - loss: 0.1813
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0963
40/82 [=============>................] - ETA: 0s - loss: 0.1657
79/82 [===========================>..] - ETA: 0s - loss: 0.1705
82/82 [==============================] - 0s 1ms/step - loss: 0.1725
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2592
39/82 [=============>................] - ETA: 0s - loss: 0.1878
78/82 [===========================>..] - ETA: 0s - loss: 0.1670
82/82 [==============================] - 0s 1ms/step - loss: 0.1658
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2523
36/82 [============>.................] - ETA: 0s - loss: 0.1680
75/82 [==========================>...] - ETA: 0s - loss: 0.1647
82/82 [==============================] - 0s 1ms/step - loss: 0.1640
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2313
33/82 [===========>..................] - ETA: 0s - loss: 0.1829
68/82 [=======================>......] - ETA: 0s - loss: 0.1563
82/82 [==============================] - 0s 2ms/step - loss: 0.1568
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1169
40/82 [=============>................] - ETA: 0s - loss: 0.1574
79/82 [===========================>..] - ETA: 0s - loss: 0.1531
82/82 [==============================] - 0s 1ms/step - loss: 0.1548
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2726
41/82 [==============>...............] - ETA: 0s - loss: 0.1406
78/82 [===========================>..] - ETA: 0s - loss: 0.1448
82/82 [==============================] - 0s 1ms/step - loss: 0.1507
-> test with GAN.predict
GAN tn, fp: 186, 19
GAN fn, tp: 3, 6
GAN f1 score: 0.353
GAN cohens kappa score: 0.310

-> test with 'LR'
LR tn, fp: 174, 31
LR fn, tp: 1, 8
LR f1 score: 0.333
LR cohens kappa score: 0.284
LR average precision score: 0.444

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

-> test with 'KNN'
KNN tn, fp: 171, 34
KNN fn, tp: 2, 7
KNN f1 score: 0.280
KNN cohens kappa score: 0.227


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 17s - loss: 0.3535
32/82 [==========>...................] - ETA: 0s - loss: 0.3412 
61/82 [=====================>........] - ETA: 0s - loss: 0.2876
82/82 [==============================] - 0s 2ms/step - loss: 0.2737
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1979
36/82 [============>.................] - ETA: 0s - loss: 0.2275
71/82 [========================>.....] - ETA: 0s - loss: 0.2239
82/82 [==============================] - 0s 1ms/step - loss: 0.2166
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2018
35/82 [===========>..................] - ETA: 0s - loss: 0.1846
70/82 [========================>.....] - ETA: 0s - loss: 0.2013
82/82 [==============================] - 0s 1ms/step - loss: 0.2018
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2348
35/82 [===========>..................] - ETA: 0s - loss: 0.2024
70/82 [========================>.....] - ETA: 0s - loss: 0.1911
82/82 [==============================] - 0s 2ms/step - loss: 0.1917
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1552
28/82 [=========>....................] - ETA: 0s - loss: 0.1732
60/82 [====================>.........] - ETA: 0s - loss: 0.1812
82/82 [==============================] - 0s 2ms/step - loss: 0.1861
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2826
36/82 [============>.................] - ETA: 0s - loss: 0.1935
71/82 [========================>.....] - ETA: 0s - loss: 0.1828
82/82 [==============================] - 0s 1ms/step - loss: 0.1769
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1189
36/82 [============>.................] - ETA: 0s - loss: 0.1621
69/82 [========================>.....] - ETA: 0s - loss: 0.1652
82/82 [==============================] - 0s 2ms/step - loss: 0.1707
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2396
33/82 [===========>..................] - ETA: 0s - loss: 0.1745
69/82 [========================>.....] - ETA: 0s - loss: 0.1716
82/82 [==============================] - 0s 1ms/step - loss: 0.1668
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0626
34/82 [===========>..................] - ETA: 0s - loss: 0.1635
66/82 [=======================>......] - ETA: 0s - loss: 0.1637
82/82 [==============================] - 0s 2ms/step - loss: 0.1614
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2100
35/82 [===========>..................] - ETA: 0s - loss: 0.1602
69/82 [========================>.....] - ETA: 0s - loss: 0.1586
82/82 [==============================] - 0s 1ms/step - loss: 0.1557
-> test with GAN.predict
GAN tn, fp: 193, 12
GAN fn, tp: 5, 4
GAN f1 score: 0.320
GAN cohens kappa score: 0.281

-> test with 'LR'
LR tn, fp: 174, 31
LR fn, tp: 0, 9
LR f1 score: 0.367
LR cohens kappa score: 0.321
LR average precision score: 0.458

-> test with 'RF'
RF tn, fp: 205, 0
RF fn, tp: 8, 1
RF f1 score: 0.200
RF cohens kappa score: 0.193

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 182, 23
KNN fn, tp: 2, 7
KNN f1 score: 0.359
KNN cohens kappa score: 0.315


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 17s - loss: 0.2537
37/82 [============>.................] - ETA: 0s - loss: 0.1882 
68/82 [=======================>......] - ETA: 0s - loss: 0.1974
82/82 [==============================] - 0s 2ms/step - loss: 0.1870
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1932
35/82 [===========>..................] - ETA: 0s - loss: 0.1435
74/82 [==========================>...] - ETA: 0s - loss: 0.1481
82/82 [==============================] - 0s 1ms/step - loss: 0.1452
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0425
38/82 [============>.................] - ETA: 0s - loss: 0.1213
75/82 [==========================>...] - ETA: 0s - loss: 0.1307
82/82 [==============================] - 0s 1ms/step - loss: 0.1317
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1061
40/82 [=============>................] - ETA: 0s - loss: 0.1057
77/82 [===========================>..] - ETA: 0s - loss: 0.1219
82/82 [==============================] - 0s 1ms/step - loss: 0.1229
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0382
40/82 [=============>................] - ETA: 0s - loss: 0.1116
76/82 [==========================>...] - ETA: 0s - loss: 0.1179
82/82 [==============================] - 0s 1ms/step - loss: 0.1181
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0618
36/82 [============>.................] - ETA: 0s - loss: 0.1291
69/82 [========================>.....] - ETA: 0s - loss: 0.1130
82/82 [==============================] - 0s 1ms/step - loss: 0.1136
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1508
40/82 [=============>................] - ETA: 0s - loss: 0.0886
78/82 [===========================>..] - ETA: 0s - loss: 0.1065
82/82 [==============================] - 0s 1ms/step - loss: 0.1096
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1193
38/82 [============>.................] - ETA: 0s - loss: 0.1158
75/82 [==========================>...] - ETA: 0s - loss: 0.1042
82/82 [==============================] - 0s 1ms/step - loss: 0.1055
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0644
40/82 [=============>................] - ETA: 0s - loss: 0.1226
77/82 [===========================>..] - ETA: 0s - loss: 0.1057
82/82 [==============================] - 0s 1ms/step - loss: 0.1027
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0568
38/82 [============>.................] - ETA: 0s - loss: 0.1143
75/82 [==========================>...] - ETA: 0s - loss: 0.1019
82/82 [==============================] - 0s 1ms/step - loss: 0.1019
-> test with GAN.predict
GAN tn, fp: 193, 12
GAN fn, tp: 6, 3
GAN f1 score: 0.250
GAN cohens kappa score: 0.208

-> test with 'LR'
LR tn, fp: 178, 27
LR fn, tp: 4, 5
LR f1 score: 0.244
LR cohens kappa score: 0.191
LR average precision score: 0.188

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.021

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

-> test with 'KNN'
KNN tn, fp: 186, 19
KNN fn, tp: 4, 5
KNN f1 score: 0.303
KNN cohens kappa score: 0.258


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 12s - loss: 0.2007
42/82 [==============>...............] - ETA: 0s - loss: 0.2405 
82/82 [==============================] - 0s 1ms/step - loss: 0.2171
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2413
41/82 [==============>...............] - ETA: 0s - loss: 0.1589
75/82 [==========================>...] - ETA: 0s - loss: 0.1747
82/82 [==============================] - 0s 1ms/step - loss: 0.1742
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0858
43/82 [==============>...............] - ETA: 0s - loss: 0.1423
82/82 [==============================] - 0s 1ms/step - loss: 0.1614
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0629
43/82 [==============>...............] - ETA: 0s - loss: 0.1539
81/82 [============================>.] - ETA: 0s - loss: 0.1530
82/82 [==============================] - 0s 1ms/step - loss: 0.1526
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2881
40/82 [=============>................] - ETA: 0s - loss: 0.1655
79/82 [===========================>..] - ETA: 0s - loss: 0.1481
82/82 [==============================] - 0s 1ms/step - loss: 0.1470
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1233
41/82 [==============>...............] - ETA: 0s - loss: 0.1536
82/82 [==============================] - ETA: 0s - loss: 0.1395
82/82 [==============================] - 0s 1ms/step - loss: 0.1395
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1136
42/82 [==============>...............] - ETA: 0s - loss: 0.1435
80/82 [============================>.] - ETA: 0s - loss: 0.1332
82/82 [==============================] - 0s 1ms/step - loss: 0.1349
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1679
43/82 [==============>...............] - ETA: 0s - loss: 0.1308
82/82 [==============================] - 0s 1ms/step - loss: 0.1307
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1273
43/82 [==============>...............] - ETA: 0s - loss: 0.1196
82/82 [==============================] - 0s 1ms/step - loss: 0.1265
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2184
38/82 [============>.................] - ETA: 0s - loss: 0.1312
75/82 [==========================>...] - ETA: 0s - loss: 0.1277
82/82 [==============================] - 0s 1ms/step - loss: 0.1246
-> test with GAN.predict
GAN tn, fp: 182, 21
GAN fn, tp: 5, 2
GAN f1 score: 0.133
GAN cohens kappa score: 0.087

-> test with 'LR'
LR tn, fp: 163, 40
LR fn, tp: 2, 5
LR f1 score: 0.192
LR cohens kappa score: 0.143
LR average precision score: 0.336

-> test with 'RF'
RF tn, fp: 196, 7
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.034

-> test with 'GB'
GB tn, fp: 202, 1
GB fn, tp: 5, 2
GB f1 score: 0.400
GB cohens kappa score: 0.388

-> test with 'KNN'
KNN tn, fp: 175, 28
KNN fn, tp: 4, 3
KNN f1 score: 0.158
KNN cohens kappa score: 0.109

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 186, 50
LR fn, tp: 5, 9
LR f1 score: 0.486
LR cohens kappa score: 0.452
LR average precision score: 0.719


average:
LR tn, fp: 172.24, 32.36
LR fn, tp: 2.16, 6.44
LR f1 score: 0.276
LR cohens kappa score: 0.226
LR average precision score: 0.350


minimum:
LR tn, fp: 155, 19
LR fn, tp: 0, 4
LR f1 score: 0.170
LR cohens kappa score: 0.110
LR average precision score: 0.084


-----[ RF ]-----
maximum:
RF tn, fp: 205, 10
RF fn, tp: 9, 2
RF f1 score: 0.364
RF cohens kappa score: 0.354


average:
RF tn, fp: 201.64, 2.96
RF fn, tp: 8.2, 0.4
RF f1 score: 0.064
RF cohens kappa score: 0.044


minimum:
RF tn, fp: 195, 0
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.035


-----[ GB ]-----
maximum:
GB tn, fp: 205, 14
GB fn, tp: 9, 4
GB f1 score: 0.429
GB cohens kappa score: 0.411


average:
GB tn, fp: 202.6, 2.0
GB fn, tp: 7.6, 1.0
GB f1 score: 0.162
GB cohens kappa score: 0.147


minimum:
GB tn, fp: 191, 0
GB fn, tp: 5, 0
GB f1 score: 0.000
GB cohens kappa score: -0.027


-----[ KNN ]-----
maximum:
KNN tn, fp: 193, 38
KNN fn, tp: 4, 8
KNN f1 score: 0.500
KNN cohens kappa score: 0.470


average:
KNN tn, fp: 177.68, 26.92
KNN fn, tp: 3.0, 5.6
KNN f1 score: 0.277
KNN cohens kappa score: 0.228


minimum:
KNN tn, fp: 165, 12
KNN fn, tp: 1, 3
KNN f1 score: 0.158
KNN cohens kappa score: 0.109


-----[ GAN ]-----
maximum:
GAN tn, fp: 201, 25
GAN fn, tp: 8, 7
GAN f1 score: 0.632
GAN cohens kappa score: 0.615


average:
GAN tn, fp: 189.16, 15.44
GAN fn, tp: 4.36, 4.24
GAN f1 score: 0.302
GAN cohens kappa score: 0.262


minimum:
GAN tn, fp: 178, 4
GAN fn, tp: 1, 1
GAN f1 score: 0.077
GAN cohens kappa score: 0.023