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

///////////////////////////////////////////
// Running convGAN-proximary-full 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: 0.8798
40/82 [=============>................] - ETA: 0s - loss: 0.2957 
79/82 [===========================>..] - ETA: 0s - loss: 0.2522
82/82 [==============================] - 0s 1ms/step - loss: 0.2436
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 4.9647e-05
40/82 [=============>................] - ETA: 0s - loss: 0.1481    
78/82 [===========================>..] - ETA: 0s - loss: 0.1527
82/82 [==============================] - 0s 1ms/step - loss: 0.1458
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0068
39/82 [=============>................] - ETA: 0s - loss: 0.1224
79/82 [===========================>..] - ETA: 0s - loss: 0.1016
82/82 [==============================] - 0s 1ms/step - loss: 0.1060
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0115
41/82 [==============>...............] - ETA: 0s - loss: 0.0767
80/82 [============================>.] - ETA: 0s - loss: 0.0902
82/82 [==============================] - 0s 1ms/step - loss: 0.0916
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0287
37/82 [============>.................] - ETA: 0s - loss: 0.0957
76/82 [==========================>...] - ETA: 0s - loss: 0.0851
82/82 [==============================] - 0s 1ms/step - loss: 0.0856
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0064
39/82 [=============>................] - ETA: 0s - loss: 0.0735
78/82 [===========================>..] - ETA: 0s - loss: 0.0831
82/82 [==============================] - 0s 1ms/step - loss: 0.0823
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2249
41/82 [==============>...............] - ETA: 0s - loss: 0.1028
81/82 [============================>.] - ETA: 0s - loss: 0.0777
82/82 [==============================] - 0s 1ms/step - loss: 0.0798
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1827
40/82 [=============>................] - ETA: 0s - loss: 0.0754
78/82 [===========================>..] - ETA: 0s - loss: 0.0755
82/82 [==============================] - 0s 1ms/step - loss: 0.0775
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0330
41/82 [==============>...............] - ETA: 0s - loss: 0.0794
81/82 [============================>.] - ETA: 0s - loss: 0.0744
82/82 [==============================] - 0s 1ms/step - loss: 0.0753
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0377
41/82 [==============>...............] - ETA: 0s - loss: 0.0740
79/82 [===========================>..] - ETA: 0s - loss: 0.0746
82/82 [==============================] - 0s 1ms/step - loss: 0.0738
-> 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: 179, 26
LR fn, tp: 8, 1
LR f1 score: 0.056
LR cohens kappa score: -0.008
LR average precision score: 0.087

-> test with 'RF'
RF tn, fp: 197, 8
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.041

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

-> test with 'KNN'
KNN tn, fp: 186, 19
KNN fn, tp: 6, 3
KNN f1 score: 0.194
KNN cohens kappa score: 0.142


------ 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: 12s - loss: 0.5783
35/82 [===========>..................] - ETA: 0s - loss: 0.2684 
68/82 [=======================>......] - ETA: 0s - loss: 0.2594
82/82 [==============================] - 0s 1ms/step - loss: 0.2609
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2303
40/82 [=============>................] - ETA: 0s - loss: 0.2064
79/82 [===========================>..] - ETA: 0s - loss: 0.1765
82/82 [==============================] - 0s 1ms/step - loss: 0.1784
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0129
39/82 [=============>................] - ETA: 0s - loss: 0.1420
77/82 [===========================>..] - ETA: 0s - loss: 0.1384
82/82 [==============================] - 0s 1ms/step - loss: 0.1388
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3442
39/82 [=============>................] - ETA: 0s - loss: 0.1601
76/82 [==========================>...] - ETA: 0s - loss: 0.1172
82/82 [==============================] - 0s 1ms/step - loss: 0.1171
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0131
38/82 [============>.................] - ETA: 0s - loss: 0.0852
75/82 [==========================>...] - ETA: 0s - loss: 0.1032
82/82 [==============================] - 0s 1ms/step - loss: 0.1081
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1787
40/82 [=============>................] - ETA: 0s - loss: 0.1274
80/82 [============================>.] - ETA: 0s - loss: 0.1044
82/82 [==============================] - 0s 1ms/step - loss: 0.1025
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.3090
40/82 [=============>................] - ETA: 0s - loss: 0.0863
76/82 [==========================>...] - ETA: 0s - loss: 0.0992
82/82 [==============================] - 0s 1ms/step - loss: 0.0993
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0356
39/82 [=============>................] - ETA: 0s - loss: 0.0904
79/82 [===========================>..] - ETA: 0s - loss: 0.0990
82/82 [==============================] - 0s 1ms/step - loss: 0.0972
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0109
40/82 [=============>................] - ETA: 0s - loss: 0.1141
73/82 [=========================>....] - ETA: 0s - loss: 0.0935
82/82 [==============================] - 0s 1ms/step - loss: 0.0940
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1013
41/82 [==============>...............] - ETA: 0s - loss: 0.0920
82/82 [==============================] - 0s 1ms/step - loss: 0.0920
-> test with GAN.predict
GAN tn, fp: 197, 8
GAN fn, tp: 6, 3
GAN f1 score: 0.300
GAN cohens kappa score: 0.266

-> test with 'LR'
LR tn, fp: 182, 23
LR fn, tp: 2, 7
LR f1 score: 0.359
LR cohens kappa score: 0.315
LR average precision score: 0.398

-> 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: 187, 18
KNN fn, tp: 6, 3
KNN f1 score: 0.200
KNN cohens kappa score: 0.150


------ 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: 0.0119
34/82 [===========>..................] - ETA: 0s - loss: 0.1711 
68/82 [=======================>......] - ETA: 0s - loss: 0.1960
82/82 [==============================] - 0s 2ms/step - loss: 0.1956
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 4.2061e-04
38/82 [============>.................] - ETA: 0s - loss: 0.1381    
77/82 [===========================>..] - ETA: 0s - loss: 0.1296
82/82 [==============================] - 0s 1ms/step - loss: 0.1245
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1599
40/82 [=============>................] - ETA: 0s - loss: 0.0914
79/82 [===========================>..] - ETA: 0s - loss: 0.0985
82/82 [==============================] - 0s 1ms/step - loss: 0.1009
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0308
38/82 [============>.................] - ETA: 0s - loss: 0.0694
74/82 [==========================>...] - ETA: 0s - loss: 0.0810
82/82 [==============================] - 0s 1ms/step - loss: 0.0889
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1868
37/82 [============>.................] - ETA: 0s - loss: 0.0889
72/82 [=========================>....] - ETA: 0s - loss: 0.0835
82/82 [==============================] - 0s 1ms/step - loss: 0.0823
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0684
41/82 [==============>...............] - ETA: 0s - loss: 0.0897
79/82 [===========================>..] - ETA: 0s - loss: 0.0826
82/82 [==============================] - 0s 1ms/step - loss: 0.0812
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0619
39/82 [=============>................] - ETA: 0s - loss: 0.0823
77/82 [===========================>..] - ETA: 0s - loss: 0.0816
82/82 [==============================] - 0s 1ms/step - loss: 0.0785
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0203
38/82 [============>.................] - ETA: 0s - loss: 0.0699
75/82 [==========================>...] - ETA: 0s - loss: 0.0787
82/82 [==============================] - 0s 1ms/step - loss: 0.0794
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0587
39/82 [=============>................] - ETA: 0s - loss: 0.0832
72/82 [=========================>....] - ETA: 0s - loss: 0.0834
82/82 [==============================] - 0s 1ms/step - loss: 0.0775
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0711
39/82 [=============>................] - ETA: 0s - loss: 0.0816
77/82 [===========================>..] - ETA: 0s - loss: 0.0756
82/82 [==============================] - 0s 1ms/step - loss: 0.0754
-> test with GAN.predict
GAN tn, fp: 196, 9
GAN fn, tp: 7, 2
GAN f1 score: 0.200
GAN cohens kappa score: 0.161

-> test with 'LR'
LR tn, fp: 186, 19
LR fn, tp: 3, 6
LR f1 score: 0.353
LR cohens kappa score: 0.310
LR average precision score: 0.510

-> 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: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 192, 13
KNN fn, tp: 4, 5
KNN f1 score: 0.370
KNN cohens kappa score: 0.333


------ 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: 13s - loss: 0.0933
31/82 [==========>...................] - ETA: 0s - loss: 0.2913 
63/82 [======================>.......] - ETA: 0s - loss: 0.2396
82/82 [==============================] - 0s 2ms/step - loss: 0.2553
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1615
40/82 [=============>................] - ETA: 0s - loss: 0.2279
79/82 [===========================>..] - ETA: 0s - loss: 0.2042
82/82 [==============================] - 0s 1ms/step - loss: 0.1973
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.3431
37/82 [============>.................] - ETA: 0s - loss: 0.1188
76/82 [==========================>...] - ETA: 0s - loss: 0.1438
82/82 [==============================] - 0s 1ms/step - loss: 0.1577
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3390
41/82 [==============>...............] - ETA: 0s - loss: 0.1442
80/82 [============================>.] - ETA: 0s - loss: 0.1413
82/82 [==============================] - 0s 1ms/step - loss: 0.1384
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0454
37/82 [============>.................] - ETA: 0s - loss: 0.1249
74/82 [==========================>...] - ETA: 0s - loss: 0.1219
82/82 [==============================] - 0s 1ms/step - loss: 0.1214
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0363
36/82 [============>.................] - ETA: 0s - loss: 0.1024
74/82 [==========================>...] - ETA: 0s - loss: 0.1024
82/82 [==============================] - 0s 1ms/step - loss: 0.1115
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0523
41/82 [==============>...............] - ETA: 0s - loss: 0.1228
79/82 [===========================>..] - ETA: 0s - loss: 0.1083
82/82 [==============================] - 0s 1ms/step - loss: 0.1072
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0562
40/82 [=============>................] - ETA: 0s - loss: 0.1123
77/82 [===========================>..] - ETA: 0s - loss: 0.1050
82/82 [==============================] - 0s 1ms/step - loss: 0.1026
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0938
36/82 [============>.................] - ETA: 0s - loss: 0.1191
75/82 [==========================>...] - ETA: 0s - loss: 0.1074
82/82 [==============================] - 0s 1ms/step - loss: 0.1040
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0921
40/82 [=============>................] - ETA: 0s - loss: 0.1056
82/82 [==============================] - 0s 1ms/step - loss: 0.0998
-> test with GAN.predict
GAN tn, fp: 202, 3
GAN fn, tp: 6, 3
GAN f1 score: 0.400
GAN cohens kappa score: 0.379

-> test with 'LR'
LR tn, fp: 190, 15
LR fn, tp: 0, 9
LR f1 score: 0.545
LR cohens kappa score: 0.516
LR average precision score: 0.763

-> 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: 199, 6
KNN fn, tp: 6, 3
KNN f1 score: 0.333
KNN cohens kappa score: 0.304


------ 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: 11s - loss: 0.0034
42/82 [==============>...............] - ETA: 0s - loss: 0.2925 
82/82 [==============================] - ETA: 0s - loss: 0.2752
82/82 [==============================] - 0s 1ms/step - loss: 0.2752
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0452
41/82 [==============>...............] - ETA: 0s - loss: 0.1962
82/82 [==============================] - ETA: 0s - loss: 0.1845
82/82 [==============================] - 0s 1ms/step - loss: 0.1845
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0337
44/82 [===============>..............] - ETA: 0s - loss: 0.1615
82/82 [==============================] - 0s 1ms/step - loss: 0.1564
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0588
44/82 [===============>..............] - ETA: 0s - loss: 0.1448
82/82 [==============================] - 0s 1ms/step - loss: 0.1348
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2809
43/82 [==============>...............] - ETA: 0s - loss: 0.1590
82/82 [==============================] - ETA: 0s - loss: 0.1258
82/82 [==============================] - 0s 1ms/step - loss: 0.1258
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1156
43/82 [==============>...............] - ETA: 0s - loss: 0.1169
82/82 [==============================] - 0s 1ms/step - loss: 0.1183
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0454
42/82 [==============>...............] - ETA: 0s - loss: 0.1405
81/82 [============================>.] - ETA: 0s - loss: 0.1157
82/82 [==============================] - 0s 1ms/step - loss: 0.1151
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0478
38/82 [============>.................] - ETA: 0s - loss: 0.1130
73/82 [=========================>....] - ETA: 0s - loss: 0.1170
82/82 [==============================] - 0s 1ms/step - loss: 0.1113
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.2005
40/82 [=============>................] - ETA: 0s - loss: 0.1031
82/82 [==============================] - ETA: 0s - loss: 0.1092
82/82 [==============================] - 0s 1ms/step - loss: 0.1092
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.4260
42/82 [==============>...............] - ETA: 0s - loss: 0.1231
82/82 [==============================] - 0s 1ms/step - loss: 0.1071
-> test with GAN.predict
GAN tn, fp: 192, 11
GAN fn, tp: 3, 4
GAN f1 score: 0.364
GAN cohens kappa score: 0.333

-> test with 'LR'
LR tn, fp: 182, 21
LR fn, tp: 3, 4
LR f1 score: 0.250
LR cohens kappa score: 0.209
LR average precision score: 0.219

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

-> test with 'GB'
GB tn, fp: 200, 3
GB fn, tp: 5, 2
GB f1 score: 0.333
GB cohens kappa score: 0.314

-> test with 'KNN'
KNN tn, fp: 185, 18
KNN fn, tp: 2, 5
KNN f1 score: 0.333
KNN cohens kappa score: 0.297


====== 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: 13s - loss: 0.7578
40/82 [=============>................] - ETA: 0s - loss: 0.3164 
80/82 [============================>.] - ETA: 0s - loss: 0.2719
82/82 [==============================] - 0s 1ms/step - loss: 0.2665
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0914
40/82 [=============>................] - ETA: 0s - loss: 0.1791
79/82 [===========================>..] - ETA: 0s - loss: 0.1555
82/82 [==============================] - 0s 1ms/step - loss: 0.1505
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0057
39/82 [=============>................] - ETA: 0s - loss: 0.0876
78/82 [===========================>..] - ETA: 0s - loss: 0.1110
82/82 [==============================] - 0s 1ms/step - loss: 0.1177
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1994
38/82 [============>.................] - ETA: 0s - loss: 0.1209
76/82 [==========================>...] - ETA: 0s - loss: 0.1054
82/82 [==============================] - 0s 1ms/step - loss: 0.1050
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1066
39/82 [=============>................] - ETA: 0s - loss: 0.0813
78/82 [===========================>..] - ETA: 0s - loss: 0.0973
82/82 [==============================] - 0s 1ms/step - loss: 0.0964
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0166
39/82 [=============>................] - ETA: 0s - loss: 0.0816
79/82 [===========================>..] - ETA: 0s - loss: 0.0893
82/82 [==============================] - 0s 1ms/step - loss: 0.0898
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0173
39/82 [=============>................] - ETA: 0s - loss: 0.0742
78/82 [===========================>..] - ETA: 0s - loss: 0.0860
82/82 [==============================] - 0s 1ms/step - loss: 0.0857
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0859
40/82 [=============>................] - ETA: 0s - loss: 0.0780
80/82 [============================>.] - ETA: 0s - loss: 0.0833
82/82 [==============================] - 0s 1ms/step - loss: 0.0821
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0154
40/82 [=============>................] - ETA: 0s - loss: 0.0610
77/82 [===========================>..] - ETA: 0s - loss: 0.0758
82/82 [==============================] - 0s 1ms/step - loss: 0.0784
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0305
39/82 [=============>................] - ETA: 0s - loss: 0.0699
79/82 [===========================>..] - ETA: 0s - loss: 0.0773
82/82 [==============================] - 0s 1ms/step - loss: 0.0751
-> test with GAN.predict
GAN tn, fp: 202, 3
GAN fn, tp: 6, 3
GAN f1 score: 0.400
GAN cohens kappa score: 0.379

-> 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: 0.426

-> 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: 194, 11
KNN fn, tp: 6, 3
KNN f1 score: 0.261
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: 30s - loss: 0.0049
40/82 [=============>................] - ETA: 0s - loss: 0.2738 
80/82 [============================>.] - ETA: 0s - loss: 0.2302
82/82 [==============================] - 0s 1ms/step - loss: 0.2315
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0042
40/82 [=============>................] - ETA: 0s - loss: 0.1475
77/82 [===========================>..] - ETA: 0s - loss: 0.1458
82/82 [==============================] - 0s 1ms/step - loss: 0.1391
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0237
39/82 [=============>................] - ETA: 0s - loss: 0.1130
78/82 [===========================>..] - ETA: 0s - loss: 0.1121
82/82 [==============================] - 0s 1ms/step - loss: 0.1166
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2979
37/82 [============>.................] - ETA: 0s - loss: 0.1216
74/82 [==========================>...] - ETA: 0s - loss: 0.1114
82/82 [==============================] - 0s 1ms/step - loss: 0.1078
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1434
33/82 [===========>..................] - ETA: 0s - loss: 0.1131
67/82 [=======================>......] - ETA: 0s - loss: 0.1056
82/82 [==============================] - 0s 2ms/step - loss: 0.1020
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0775
39/82 [=============>................] - ETA: 0s - loss: 0.0986
77/82 [===========================>..] - ETA: 0s - loss: 0.1004
82/82 [==============================] - 0s 1ms/step - loss: 0.0966
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0352
39/82 [=============>................] - ETA: 0s - loss: 0.0910
78/82 [===========================>..] - ETA: 0s - loss: 0.0930
82/82 [==============================] - 0s 1ms/step - loss: 0.0935
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2081
40/82 [=============>................] - ETA: 0s - loss: 0.1035
74/82 [==========================>...] - ETA: 0s - loss: 0.0950
82/82 [==============================] - 0s 1ms/step - loss: 0.0908
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0151
40/82 [=============>................] - ETA: 0s - loss: 0.0890
79/82 [===========================>..] - ETA: 0s - loss: 0.0894
82/82 [==============================] - 0s 1ms/step - loss: 0.0884
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0187
39/82 [=============>................] - ETA: 0s - loss: 0.0771
75/82 [==========================>...] - ETA: 0s - loss: 0.0840
82/82 [==============================] - 0s 1ms/step - loss: 0.0857
-> test with GAN.predict
GAN tn, fp: 199, 6
GAN fn, tp: 7, 2
GAN f1 score: 0.235
GAN cohens kappa score: 0.204

-> test with 'LR'
LR tn, fp: 176, 29
LR fn, tp: 4, 5
LR f1 score: 0.233
LR cohens kappa score: 0.178
LR average precision score: 0.377

-> 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: 184, 21
KNN fn, tp: 5, 4
KNN f1 score: 0.235
KNN cohens kappa score: 0.185


------ 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: 12s - loss: 0.7617
39/82 [=============>................] - ETA: 0s - loss: 0.2592 
79/82 [===========================>..] - ETA: 0s - loss: 0.2223
82/82 [==============================] - 0s 1ms/step - loss: 0.2203
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0042
40/82 [=============>................] - ETA: 0s - loss: 0.1794
80/82 [============================>.] - ETA: 0s - loss: 0.1715
82/82 [==============================] - 0s 1ms/step - loss: 0.1718
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.5338
39/82 [=============>................] - ETA: 0s - loss: 0.1285
78/82 [===========================>..] - ETA: 0s - loss: 0.1459
82/82 [==============================] - 0s 1ms/step - loss: 0.1452
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0985
39/82 [=============>................] - ETA: 0s - loss: 0.1245
78/82 [===========================>..] - ETA: 0s - loss: 0.1260
82/82 [==============================] - 0s 1ms/step - loss: 0.1274
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1964
39/82 [=============>................] - ETA: 0s - loss: 0.1274
78/82 [===========================>..] - ETA: 0s - loss: 0.1212
82/82 [==============================] - 0s 1ms/step - loss: 0.1183
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.4864
41/82 [==============>...............] - ETA: 0s - loss: 0.1210
79/82 [===========================>..] - ETA: 0s - loss: 0.1056
82/82 [==============================] - 0s 1ms/step - loss: 0.1065
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0288
38/82 [============>.................] - ETA: 0s - loss: 0.1054
77/82 [===========================>..] - ETA: 0s - loss: 0.1052
82/82 [==============================] - 0s 1ms/step - loss: 0.1040
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0255
38/82 [============>.................] - ETA: 0s - loss: 0.1036
73/82 [=========================>....] - ETA: 0s - loss: 0.0952
82/82 [==============================] - 0s 1ms/step - loss: 0.0999
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1315
40/82 [=============>................] - ETA: 0s - loss: 0.1212
79/82 [===========================>..] - ETA: 0s - loss: 0.0983
82/82 [==============================] - 0s 1ms/step - loss: 0.0966
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2200
40/82 [=============>................] - ETA: 0s - loss: 0.0948
79/82 [===========================>..] - ETA: 0s - loss: 0.0946
82/82 [==============================] - 0s 1ms/step - loss: 0.0951
-> test with GAN.predict
GAN tn, fp: 202, 3
GAN fn, tp: 8, 1
GAN f1 score: 0.154
GAN cohens kappa score: 0.131

-> test with 'LR'
LR tn, fp: 179, 26
LR fn, tp: 3, 6
LR f1 score: 0.293
LR cohens kappa score: 0.243
LR average precision score: 0.370

-> 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: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

-> test with 'KNN'
KNN tn, fp: 192, 13
KNN fn, tp: 5, 4
KNN f1 score: 0.308
KNN cohens kappa score: 0.267


------ 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: 0.5561
39/82 [=============>................] - ETA: 0s - loss: 0.2751 
78/82 [===========================>..] - ETA: 0s - loss: 0.2444
82/82 [==============================] - 0s 1ms/step - loss: 0.2332
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.6244
34/82 [===========>..................] - ETA: 0s - loss: 0.1093
68/82 [=======================>......] - ETA: 0s - loss: 0.1226
82/82 [==============================] - 0s 2ms/step - loss: 0.1361
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0014
38/82 [============>.................] - ETA: 0s - loss: 0.0856
67/82 [=======================>......] - ETA: 0s - loss: 0.1010
82/82 [==============================] - 0s 2ms/step - loss: 0.1003
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0040
38/82 [============>.................] - ETA: 0s - loss: 0.0942
76/82 [==========================>...] - ETA: 0s - loss: 0.0853
82/82 [==============================] - 0s 1ms/step - loss: 0.0881
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0424
38/82 [============>.................] - ETA: 0s - loss: 0.0631
73/82 [=========================>....] - ETA: 0s - loss: 0.0778
82/82 [==============================] - 0s 1ms/step - loss: 0.0809
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0949
39/82 [=============>................] - ETA: 0s - loss: 0.0897
77/82 [===========================>..] - ETA: 0s - loss: 0.0801
82/82 [==============================] - 0s 1ms/step - loss: 0.0778
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2618
34/82 [===========>..................] - ETA: 0s - loss: 0.0652
70/82 [========================>.....] - ETA: 0s - loss: 0.0793
82/82 [==============================] - 0s 1ms/step - loss: 0.0756
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0214
38/82 [============>.................] - ETA: 0s - loss: 0.0951
78/82 [===========================>..] - ETA: 0s - loss: 0.0761
82/82 [==============================] - 0s 1ms/step - loss: 0.0736
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1636
40/82 [=============>................] - ETA: 0s - loss: 0.0711
79/82 [===========================>..] - ETA: 0s - loss: 0.0730
82/82 [==============================] - 0s 1ms/step - loss: 0.0713
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0587
38/82 [============>.................] - ETA: 0s - loss: 0.0445
75/82 [==========================>...] - ETA: 0s - loss: 0.0716
82/82 [==============================] - 0s 1ms/step - loss: 0.0708
-> test with GAN.predict
GAN tn, fp: 201, 4
GAN fn, tp: 9, 0
GAN f1 score: 0.000
GAN cohens kappa score: -0.027

-> test with 'LR'
LR tn, fp: 193, 12
LR fn, tp: 6, 3
LR f1 score: 0.250
LR cohens kappa score: 0.208
LR average precision score: 0.290

-> 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: 204, 1
GB fn, tp: 8, 1
GB f1 score: 0.182
GB cohens kappa score: 0.169

-> test with 'KNN'
KNN tn, fp: 198, 7
KNN fn, tp: 5, 4
KNN f1 score: 0.400
KNN cohens kappa score: 0.371


------ 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: 13s - loss: 0.5331
42/82 [==============>...............] - ETA: 0s - loss: 0.2501 
82/82 [==============================] - 0s 1ms/step - loss: 0.2277
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0573
43/82 [==============>...............] - ETA: 0s - loss: 0.1870
82/82 [==============================] - 0s 1ms/step - loss: 0.1667
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.8294
43/82 [==============>...............] - ETA: 0s - loss: 0.1848
82/82 [==============================] - 0s 1ms/step - loss: 0.1363
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0533
42/82 [==============>...............] - ETA: 0s - loss: 0.0971
82/82 [==============================] - 0s 1ms/step - loss: 0.1226
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0148
41/82 [==============>...............] - ETA: 0s - loss: 0.1434
82/82 [==============================] - 0s 1ms/step - loss: 0.1112
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0030
39/82 [=============>................] - ETA: 0s - loss: 0.0982
82/82 [==============================] - ETA: 0s - loss: 0.1032
82/82 [==============================] - 0s 1ms/step - loss: 0.1032
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0606
42/82 [==============>...............] - ETA: 0s - loss: 0.0793
82/82 [==============================] - 0s 1ms/step - loss: 0.0973
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0128
41/82 [==============>...............] - ETA: 0s - loss: 0.0931
82/82 [==============================] - ETA: 0s - loss: 0.0957
82/82 [==============================] - 0s 1ms/step - loss: 0.0957
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0955
38/82 [============>.................] - ETA: 0s - loss: 0.0933
80/82 [============================>.] - ETA: 0s - loss: 0.0934
82/82 [==============================] - 0s 1ms/step - loss: 0.0918
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0150
42/82 [==============>...............] - ETA: 0s - loss: 0.0842
81/82 [============================>.] - ETA: 0s - loss: 0.0897
82/82 [==============================] - 0s 1ms/step - loss: 0.0889
-> test with GAN.predict
GAN tn, fp: 193, 10
GAN fn, tp: 4, 3
GAN f1 score: 0.300
GAN cohens kappa score: 0.268

-> test with 'LR'
LR tn, fp: 185, 18
LR fn, tp: 0, 7
LR f1 score: 0.438
LR cohens kappa score: 0.407
LR average precision score: 0.404

-> test with 'RF'
RF tn, fp: 201, 2
RF fn, tp: 6, 1
RF f1 score: 0.200
RF cohens kappa score: 0.184

-> test with 'GB'
GB tn, fp: 201, 2
GB fn, tp: 6, 1
GB f1 score: 0.200
GB cohens kappa score: 0.184

-> test with 'KNN'
KNN tn, fp: 185, 18
KNN fn, tp: 1, 6
KNN f1 score: 0.387
KNN cohens kappa score: 0.354


====== 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: 13s - loss: 0.9478
40/82 [=============>................] - ETA: 0s - loss: 0.6003 
77/82 [===========================>..] - ETA: 0s - loss: 0.4394
82/82 [==============================] - 0s 1ms/step - loss: 0.4175
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0672
41/82 [==============>...............] - ETA: 0s - loss: 0.2292
79/82 [===========================>..] - ETA: 0s - loss: 0.2299
82/82 [==============================] - 0s 1ms/step - loss: 0.2247
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0948
41/82 [==============>...............] - ETA: 0s - loss: 0.1767
73/82 [=========================>....] - ETA: 0s - loss: 0.1805
82/82 [==============================] - 0s 1ms/step - loss: 0.1727
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2202
40/82 [=============>................] - ETA: 0s - loss: 0.1453
78/82 [===========================>..] - ETA: 0s - loss: 0.1542
82/82 [==============================] - 0s 1ms/step - loss: 0.1503
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1798
41/82 [==============>...............] - ETA: 0s - loss: 0.1359
81/82 [============================>.] - ETA: 0s - loss: 0.1340
82/82 [==============================] - 0s 1ms/step - loss: 0.1343
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1033
41/82 [==============>...............] - ETA: 0s - loss: 0.1166
79/82 [===========================>..] - ETA: 0s - loss: 0.1270
82/82 [==============================] - 0s 1ms/step - loss: 0.1242
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0200
40/82 [=============>................] - ETA: 0s - loss: 0.0949
80/82 [============================>.] - ETA: 0s - loss: 0.1147
82/82 [==============================] - 0s 1ms/step - loss: 0.1161
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0883
38/82 [============>.................] - ETA: 0s - loss: 0.1156
73/82 [=========================>....] - ETA: 0s - loss: 0.1089
82/82 [==============================] - 0s 1ms/step - loss: 0.1108
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1652
38/82 [============>.................] - ETA: 0s - loss: 0.1085
81/82 [============================>.] - ETA: 0s - loss: 0.1070
82/82 [==============================] - 0s 1ms/step - loss: 0.1071
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0295
42/82 [==============>...............] - ETA: 0s - loss: 0.1062
82/82 [==============================] - ETA: 0s - loss: 0.1038
82/82 [==============================] - 0s 1ms/step - loss: 0.1038
-> test with GAN.predict
GAN tn, fp: 199, 6
GAN fn, tp: 6, 3
GAN f1 score: 0.333
GAN cohens kappa score: 0.304

-> test with 'LR'
LR tn, fp: 188, 17
LR fn, tp: 2, 7
LR f1 score: 0.424
LR cohens kappa score: 0.387
LR average precision score: 0.814

-> 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: 9, 0
GB f1 score: 0.000
GB cohens kappa score: 0.000

-> test with 'KNN'
KNN tn, fp: 195, 10
KNN fn, tp: 3, 6
KNN f1 score: 0.480
KNN cohens kappa score: 0.450


------ 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: 16s - loss: 0.0992
38/82 [============>.................] - ETA: 0s - loss: 0.4136 
79/82 [===========================>..] - ETA: 0s - loss: 0.3936
82/82 [==============================] - 0s 1ms/step - loss: 0.4017
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.3312
41/82 [==============>...............] - ETA: 0s - loss: 0.2902
79/82 [===========================>..] - ETA: 0s - loss: 0.2795
82/82 [==============================] - 0s 1ms/step - loss: 0.2808
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0307
40/82 [=============>................] - ETA: 0s - loss: 0.2292
80/82 [============================>.] - ETA: 0s - loss: 0.2214
82/82 [==============================] - 0s 1ms/step - loss: 0.2182
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0931
41/82 [==============>...............] - ETA: 0s - loss: 0.1495
80/82 [============================>.] - ETA: 0s - loss: 0.1769
82/82 [==============================] - 0s 1ms/step - loss: 0.1733
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0577
41/82 [==============>...............] - ETA: 0s - loss: 0.1493
80/82 [============================>.] - ETA: 0s - loss: 0.1475
82/82 [==============================] - 0s 1ms/step - loss: 0.1487
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0192
40/82 [=============>................] - ETA: 0s - loss: 0.1469
78/82 [===========================>..] - ETA: 0s - loss: 0.1373
82/82 [==============================] - 0s 1ms/step - loss: 0.1393
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2999
40/82 [=============>................] - ETA: 0s - loss: 0.1335
76/82 [==========================>...] - ETA: 0s - loss: 0.1291
82/82 [==============================] - 0s 1ms/step - loss: 0.1319
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2752
38/82 [============>.................] - ETA: 0s - loss: 0.1093
75/82 [==========================>...] - ETA: 0s - loss: 0.1246
82/82 [==============================] - 0s 1ms/step - loss: 0.1268
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0966
40/82 [=============>................] - ETA: 0s - loss: 0.1248
79/82 [===========================>..] - ETA: 0s - loss: 0.1243
82/82 [==============================] - 0s 1ms/step - loss: 0.1235
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0701
40/82 [=============>................] - ETA: 0s - loss: 0.0964
79/82 [===========================>..] - ETA: 0s - loss: 0.1189
82/82 [==============================] - 0s 1ms/step - loss: 0.1187
-> test with GAN.predict
GAN tn, fp: 179, 26
GAN fn, tp: 5, 4
GAN f1 score: 0.205
GAN cohens kappa score: 0.150

-> 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: 0.251

-> test with 'RF'
RF tn, fp: 198, 7
RF fn, tp: 7, 2
RF f1 score: 0.222
RF cohens kappa score: 0.188

-> test with 'GB'
GB tn, fp: 194, 11
GB fn, tp: 5, 4
GB f1 score: 0.333
GB cohens kappa score: 0.296

-> test with 'KNN'
KNN tn, fp: 178, 27
KNN fn, tp: 3, 6
KNN f1 score: 0.286
KNN cohens kappa score: 0.235


------ 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: 13s - loss: 0.0012
37/82 [============>.................] - ETA: 0s - loss: 0.3218 
74/82 [==========================>...] - ETA: 0s - loss: 0.3243
82/82 [==============================] - 0s 1ms/step - loss: 0.3122
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0035
37/82 [============>.................] - ETA: 0s - loss: 0.2362
74/82 [==========================>...] - ETA: 0s - loss: 0.2380
82/82 [==============================] - 0s 1ms/step - loss: 0.2274
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.5262
35/82 [===========>..................] - ETA: 0s - loss: 0.1782
70/82 [========================>.....] - ETA: 0s - loss: 0.1724
82/82 [==============================] - 0s 1ms/step - loss: 0.1673
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0801
39/82 [=============>................] - ETA: 0s - loss: 0.1526
78/82 [===========================>..] - ETA: 0s - loss: 0.1413
82/82 [==============================] - 0s 1ms/step - loss: 0.1440
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0192
40/82 [=============>................] - ETA: 0s - loss: 0.1310
77/82 [===========================>..] - ETA: 0s - loss: 0.1333
82/82 [==============================] - 0s 1ms/step - loss: 0.1322
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1222
40/82 [=============>................] - ETA: 0s - loss: 0.1132
79/82 [===========================>..] - ETA: 0s - loss: 0.1284
82/82 [==============================] - 0s 1ms/step - loss: 0.1264
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0877
40/82 [=============>................] - ETA: 0s - loss: 0.1373
79/82 [===========================>..] - ETA: 0s - loss: 0.1263
82/82 [==============================] - 0s 1ms/step - loss: 0.1248
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0846
38/82 [============>.................] - ETA: 0s - loss: 0.0985
77/82 [===========================>..] - ETA: 0s - loss: 0.1151
82/82 [==============================] - 0s 1ms/step - loss: 0.1209
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0090
38/82 [============>.................] - ETA: 0s - loss: 0.1217
76/82 [==========================>...] - ETA: 0s - loss: 0.1140
82/82 [==============================] - 0s 1ms/step - loss: 0.1181
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1486
36/82 [============>.................] - ETA: 0s - loss: 0.1353
73/82 [=========================>....] - ETA: 0s - loss: 0.1203
82/82 [==============================] - 0s 1ms/step - loss: 0.1158
-> test with GAN.predict
GAN tn, fp: 197, 8
GAN fn, tp: 5, 4
GAN f1 score: 0.381
GAN cohens kappa score: 0.350

-> test with 'LR'
LR tn, fp: 186, 19
LR fn, tp: 3, 6
LR f1 score: 0.353
LR cohens kappa score: 0.310
LR average precision score: 0.370

-> 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: 189, 16
KNN fn, tp: 2, 7
KNN f1 score: 0.438
KNN cohens kappa score: 0.401


------ 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: 12s - loss: 8.8505e-05
40/82 [=============>................] - ETA: 0s - loss: 0.2358     
78/82 [===========================>..] - ETA: 0s - loss: 0.2117
82/82 [==============================] - 0s 1ms/step - loss: 0.2186
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 1.5797
40/82 [=============>................] - ETA: 0s - loss: 0.1782
78/82 [===========================>..] - ETA: 0s - loss: 0.1625
82/82 [==============================] - 0s 1ms/step - loss: 0.1583
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0308
42/82 [==============>...............] - ETA: 0s - loss: 0.1310
81/82 [============================>.] - ETA: 0s - loss: 0.1256
82/82 [==============================] - 0s 1ms/step - loss: 0.1246
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1497
41/82 [==============>...............] - ETA: 0s - loss: 0.0998
81/82 [============================>.] - ETA: 0s - loss: 0.1083
82/82 [==============================] - 0s 1ms/step - loss: 0.1073
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0722
41/82 [==============>...............] - ETA: 0s - loss: 0.1259
79/82 [===========================>..] - ETA: 0s - loss: 0.0953
82/82 [==============================] - 0s 1ms/step - loss: 0.0986
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0046
39/82 [=============>................] - ETA: 0s - loss: 0.0876
73/82 [=========================>....] - ETA: 0s - loss: 0.1003
82/82 [==============================] - 0s 1ms/step - loss: 0.0934
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0632
23/82 [=======>......................] - ETA: 0s - loss: 0.1051
51/82 [=================>............] - ETA: 0s - loss: 0.0881
74/82 [==========================>...] - ETA: 0s - loss: 0.0826
82/82 [==============================] - 0s 2ms/step - loss: 0.0880
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0115
29/82 [=========>....................] - ETA: 0s - loss: 0.0641
51/82 [=================>............] - ETA: 0s - loss: 0.0661
79/82 [===========================>..] - ETA: 0s - loss: 0.0853
82/82 [==============================] - 0s 2ms/step - loss: 0.0856
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0114
30/82 [=========>....................] - ETA: 0s - loss: 0.0880
57/82 [===================>..........] - ETA: 0s - loss: 0.0854
82/82 [==============================] - 0s 2ms/step - loss: 0.0822
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1231
31/82 [==========>...................] - ETA: 0s - loss: 0.0753
56/82 [===================>..........] - ETA: 0s - loss: 0.0830
82/82 [==============================] - 0s 2ms/step - loss: 0.0818
-> test with GAN.predict
GAN tn, fp: 200, 5
GAN fn, tp: 5, 4
GAN f1 score: 0.444
GAN cohens kappa score: 0.420

-> test with 'LR'
LR tn, fp: 189, 16
LR fn, tp: 5, 4
LR f1 score: 0.276
LR cohens kappa score: 0.231
LR average precision score: 0.217

-> 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: 198, 7
KNN fn, tp: 4, 5
KNN f1 score: 0.476
KNN cohens kappa score: 0.450


------ 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: 13s - loss: 0.3184
33/82 [===========>..................] - ETA: 0s - loss: 0.1930 
68/82 [=======================>......] - ETA: 0s - loss: 0.1987
82/82 [==============================] - 0s 1ms/step - loss: 0.1858
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 4.9903e-04
34/82 [===========>..................] - ETA: 0s - loss: 0.1544    
67/82 [=======================>......] - ETA: 0s - loss: 0.1496
82/82 [==============================] - 0s 1ms/step - loss: 0.1394
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0095
33/82 [===========>..................] - ETA: 0s - loss: 0.1175
62/82 [=====================>........] - ETA: 0s - loss: 0.1131
82/82 [==============================] - 0s 2ms/step - loss: 0.1150
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0549
33/82 [===========>..................] - ETA: 0s - loss: 0.1395
64/82 [======================>.......] - ETA: 0s - loss: 0.1066
82/82 [==============================] - 0s 2ms/step - loss: 0.1069
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0100
36/82 [============>.................] - ETA: 0s - loss: 0.1109
70/82 [========================>.....] - ETA: 0s - loss: 0.1026
82/82 [==============================] - 0s 1ms/step - loss: 0.0985
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0074
33/82 [===========>..................] - ETA: 0s - loss: 0.0874
66/82 [=======================>......] - ETA: 0s - loss: 0.0963
82/82 [==============================] - 0s 2ms/step - loss: 0.0947
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0941
38/82 [============>.................] - ETA: 0s - loss: 0.0730
72/82 [=========================>....] - ETA: 0s - loss: 0.0804
82/82 [==============================] - 0s 1ms/step - loss: 0.0921
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0105
36/82 [============>.................] - ETA: 0s - loss: 0.0897
71/82 [========================>.....] - ETA: 0s - loss: 0.0921
82/82 [==============================] - 0s 1ms/step - loss: 0.0913
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0173
35/82 [===========>..................] - ETA: 0s - loss: 0.0738
70/82 [========================>.....] - ETA: 0s - loss: 0.0917
82/82 [==============================] - 0s 2ms/step - loss: 0.0887
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0163
37/82 [============>.................] - ETA: 0s - loss: 0.0840
72/82 [=========================>....] - ETA: 0s - loss: 0.0918
82/82 [==============================] - 0s 1ms/step - loss: 0.0873
-> test with GAN.predict
GAN tn, fp: 195, 8
GAN fn, tp: 5, 2
GAN f1 score: 0.235
GAN cohens kappa score: 0.204

-> test with 'LR'
LR tn, fp: 178, 25
LR fn, tp: 1, 6
LR f1 score: 0.316
LR cohens kappa score: 0.276
LR average precision score: 0.284

-> test with 'RF'
RF tn, fp: 195, 8
RF fn, tp: 5, 2
RF f1 score: 0.235
RF cohens kappa score: 0.204

-> test with 'GB'
GB tn, fp: 198, 5
GB fn, tp: 6, 1
GB f1 score: 0.154
GB cohens kappa score: 0.127

-> test with 'KNN'
KNN tn, fp: 194, 9
KNN fn, tp: 6, 1
KNN f1 score: 0.118
KNN cohens kappa score: 0.082


====== 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: 17s - loss: 0.4707
31/82 [==========>...................] - ETA: 0s - loss: 0.1913 
54/82 [==================>...........] - ETA: 0s - loss: 0.2430
82/82 [==============================] - ETA: 0s - loss: 0.2363
82/82 [==============================] - 0s 2ms/step - loss: 0.2363
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 7.9992e-05
30/82 [=========>....................] - ETA: 0s - loss: 0.0986    
61/82 [=====================>........] - ETA: 0s - loss: 0.1208
82/82 [==============================] - 0s 2ms/step - loss: 0.1622
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0188
28/82 [=========>....................] - ETA: 0s - loss: 0.1314
58/82 [====================>.........] - ETA: 0s - loss: 0.1364
82/82 [==============================] - 0s 2ms/step - loss: 0.1289
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0029
27/82 [========>.....................] - ETA: 0s - loss: 0.1207
54/82 [==================>...........] - ETA: 0s - loss: 0.1251
82/82 [==============================] - 0s 2ms/step - loss: 0.1098
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0106
31/82 [==========>...................] - ETA: 0s - loss: 0.0952
58/82 [====================>.........] - ETA: 0s - loss: 0.0919
82/82 [==============================] - ETA: 0s - loss: 0.0992
82/82 [==============================] - 0s 2ms/step - loss: 0.0992
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0982
31/82 [==========>...................] - ETA: 0s - loss: 0.1026
67/82 [=======================>......] - ETA: 0s - loss: 0.0987
82/82 [==============================] - 0s 2ms/step - loss: 0.0915
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0108
29/82 [=========>....................] - ETA: 0s - loss: 0.1061
60/82 [====================>.........] - ETA: 0s - loss: 0.0812
82/82 [==============================] - 0s 2ms/step - loss: 0.0870
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0432
29/82 [=========>....................] - ETA: 0s - loss: 0.0584
58/82 [====================>.........] - ETA: 0s - loss: 0.0828
82/82 [==============================] - 0s 2ms/step - loss: 0.0838
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0192
29/82 [=========>....................] - ETA: 0s - loss: 0.0852
58/82 [====================>.........] - ETA: 0s - loss: 0.0842
82/82 [==============================] - 0s 2ms/step - loss: 0.0797
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0045
26/82 [========>.....................] - ETA: 0s - loss: 0.0502
53/82 [==================>...........] - ETA: 0s - loss: 0.0829
80/82 [============================>.] - ETA: 0s - loss: 0.0786
82/82 [==============================] - 0s 2ms/step - loss: 0.0787
-> test with GAN.predict
GAN tn, fp: 198, 7
GAN fn, tp: 8, 1
GAN f1 score: 0.118
GAN cohens kappa score: 0.081

-> test with 'LR'
LR tn, fp: 194, 11
LR fn, tp: 7, 2
LR f1 score: 0.182
LR cohens kappa score: 0.139
LR average precision score: 0.187

-> test with 'RF'
RF tn, fp: 198, 7
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.038

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

-> test with 'KNN'
KNN tn, fp: 192, 13
KNN fn, tp: 6, 3
KNN f1 score: 0.240
KNN cohens kappa score: 0.197


------ 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: 14s - loss: 0.6299
32/82 [==========>...................] - ETA: 0s - loss: 0.3510 
66/82 [=======================>......] - ETA: 0s - loss: 0.2784
82/82 [==============================] - 0s 2ms/step - loss: 0.2598
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0273
31/82 [==========>...................] - ETA: 0s - loss: 0.2459
65/82 [======================>.......] - ETA: 0s - loss: 0.2143
82/82 [==============================] - 0s 2ms/step - loss: 0.2031
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.4449
32/82 [==========>...................] - ETA: 0s - loss: 0.1693
64/82 [======================>.......] - ETA: 0s - loss: 0.1821
82/82 [==============================] - 0s 2ms/step - loss: 0.1704
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.4782
32/82 [==========>...................] - ETA: 0s - loss: 0.1548
63/82 [======================>.......] - ETA: 0s - loss: 0.1579
82/82 [==============================] - 0s 2ms/step - loss: 0.1519
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0085
32/82 [==========>...................] - ETA: 0s - loss: 0.1279
59/82 [====================>.........] - ETA: 0s - loss: 0.1338
82/82 [==============================] - 0s 2ms/step - loss: 0.1398
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0044
31/82 [==========>...................] - ETA: 0s - loss: 0.1499
59/82 [====================>.........] - ETA: 0s - loss: 0.1399
82/82 [==============================] - 0s 2ms/step - loss: 0.1322
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1253
29/82 [=========>....................] - ETA: 0s - loss: 0.1059
59/82 [====================>.........] - ETA: 0s - loss: 0.1073
82/82 [==============================] - 0s 2ms/step - loss: 0.1243
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.3059
35/82 [===========>..................] - ETA: 0s - loss: 0.1075
66/82 [=======================>......] - ETA: 0s - loss: 0.1170
82/82 [==============================] - 0s 2ms/step - loss: 0.1199
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0545
34/82 [===========>..................] - ETA: 0s - loss: 0.1185
68/82 [=======================>......] - ETA: 0s - loss: 0.1169
82/82 [==============================] - 0s 2ms/step - loss: 0.1173
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1072
35/82 [===========>..................] - ETA: 0s - loss: 0.1180
68/82 [=======================>......] - ETA: 0s - loss: 0.1233
82/82 [==============================] - 0s 2ms/step - loss: 0.1164
-> test with GAN.predict
GAN tn, fp: 199, 6
GAN fn, tp: 7, 2
GAN f1 score: 0.235
GAN cohens kappa score: 0.204

-> test with 'LR'
LR tn, fp: 189, 16
LR fn, tp: 4, 5
LR f1 score: 0.333
LR cohens kappa score: 0.292
LR average precision score: 0.588

-> 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: 7, 2
GB f1 score: 0.308
GB cohens kappa score: 0.289

-> test with 'KNN'
KNN tn, fp: 191, 14
KNN fn, tp: 6, 3
KNN f1 score: 0.231
KNN cohens kappa score: 0.186


------ 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: 19s - loss: 0.1456
32/82 [==========>...................] - ETA: 0s - loss: 0.2835 
62/82 [=====================>........] - ETA: 0s - loss: 0.2705
82/82 [==============================] - 0s 2ms/step - loss: 0.2541
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0014
34/82 [===========>..................] - ETA: 0s - loss: 0.1782
64/82 [======================>.......] - ETA: 0s - loss: 0.1755
82/82 [==============================] - 0s 2ms/step - loss: 0.1732
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0015
32/82 [==========>...................] - ETA: 0s - loss: 0.1084
61/82 [=====================>........] - ETA: 0s - loss: 0.1503
82/82 [==============================] - 0s 2ms/step - loss: 0.1361
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0291
32/82 [==========>...................] - ETA: 0s - loss: 0.1129
66/82 [=======================>......] - ETA: 0s - loss: 0.1088
82/82 [==============================] - 0s 2ms/step - loss: 0.1144
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0291
32/82 [==========>...................] - ETA: 0s - loss: 0.1222
62/82 [=====================>........] - ETA: 0s - loss: 0.1106
82/82 [==============================] - 0s 2ms/step - loss: 0.1049
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0094
33/82 [===========>..................] - ETA: 0s - loss: 0.1248
64/82 [======================>.......] - ETA: 0s - loss: 0.0950
82/82 [==============================] - 0s 2ms/step - loss: 0.0990
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1042
34/82 [===========>..................] - ETA: 0s - loss: 0.0930
65/82 [======================>.......] - ETA: 0s - loss: 0.0886
82/82 [==============================] - 0s 2ms/step - loss: 0.0946
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1935
36/82 [============>.................] - ETA: 0s - loss: 0.0774
68/82 [=======================>......] - ETA: 0s - loss: 0.0849
82/82 [==============================] - 0s 2ms/step - loss: 0.0915
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1179
32/82 [==========>...................] - ETA: 0s - loss: 0.0822
64/82 [======================>.......] - ETA: 0s - loss: 0.0980
82/82 [==============================] - 0s 2ms/step - loss: 0.0888
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2158
31/82 [==========>...................] - ETA: 0s - loss: 0.0515
63/82 [======================>.......] - ETA: 0s - loss: 0.0828
82/82 [==============================] - 0s 2ms/step - loss: 0.0862
-> test with GAN.predict
GAN tn, fp: 201, 4
GAN fn, tp: 5, 4
GAN f1 score: 0.471
GAN cohens kappa score: 0.449

-> test with 'LR'
LR tn, fp: 184, 21
LR fn, tp: 4, 5
LR f1 score: 0.286
LR cohens kappa score: 0.238
LR average precision score: 0.271

-> 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: 202, 3
GB fn, tp: 7, 2
GB f1 score: 0.286
GB cohens kappa score: 0.264

-> test with 'KNN'
KNN tn, fp: 186, 19
KNN fn, tp: 5, 4
KNN f1 score: 0.250
KNN cohens kappa score: 0.202


------ 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: 20s - loss: 0.1172
34/82 [===========>..................] - ETA: 0s - loss: 0.1601 
65/82 [======================>.......] - ETA: 0s - loss: 0.1881
82/82 [==============================] - 0s 2ms/step - loss: 0.1985
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0330
30/82 [=========>....................] - ETA: 0s - loss: 0.1487
61/82 [=====================>........] - ETA: 0s - loss: 0.1530
82/82 [==============================] - 0s 2ms/step - loss: 0.1467
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.4059
34/82 [===========>..................] - ETA: 0s - loss: 0.1178
67/82 [=======================>......] - ETA: 0s - loss: 0.1281
82/82 [==============================] - 0s 2ms/step - loss: 0.1186
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2646
35/82 [===========>..................] - ETA: 0s - loss: 0.1283
67/82 [=======================>......] - ETA: 0s - loss: 0.1088
82/82 [==============================] - 0s 2ms/step - loss: 0.1041
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1129
33/82 [===========>..................] - ETA: 0s - loss: 0.0864
65/82 [======================>.......] - ETA: 0s - loss: 0.0826
82/82 [==============================] - 0s 2ms/step - loss: 0.0929
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1031
33/82 [===========>..................] - ETA: 0s - loss: 0.0871
66/82 [=======================>......] - ETA: 0s - loss: 0.1052
82/82 [==============================] - 0s 2ms/step - loss: 0.0917
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1565
34/82 [===========>..................] - ETA: 0s - loss: 0.0769
67/82 [=======================>......] - ETA: 0s - loss: 0.0845
82/82 [==============================] - 0s 2ms/step - loss: 0.0857
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0936
32/82 [==========>...................] - ETA: 0s - loss: 0.0773
65/82 [======================>.......] - ETA: 0s - loss: 0.0879
82/82 [==============================] - 0s 2ms/step - loss: 0.0843
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0231
33/82 [===========>..................] - ETA: 0s - loss: 0.0711
66/82 [=======================>......] - ETA: 0s - loss: 0.0853
82/82 [==============================] - 0s 2ms/step - loss: 0.0819
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0274
32/82 [==========>...................] - ETA: 0s - loss: 0.0869
65/82 [======================>.......] - ETA: 0s - loss: 0.0803
82/82 [==============================] - 0s 2ms/step - loss: 0.0807
-> test with GAN.predict
GAN tn, fp: 195, 10
GAN fn, tp: 7, 2
GAN f1 score: 0.190
GAN cohens kappa score: 0.150

-> 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: 0.399

-> test with 'RF'
RF tn, fp: 200, 5
RF fn, tp: 7, 2
RF f1 score: 0.250
RF cohens kappa score: 0.221

-> test with 'GB'
GB tn, fp: 201, 4
GB fn, tp: 7, 2
GB f1 score: 0.267
GB cohens kappa score: 0.241

-> test with 'KNN'
KNN tn, fp: 194, 11
KNN fn, tp: 6, 3
KNN f1 score: 0.261
KNN cohens kappa score: 0.221


------ 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: 13s - loss: 0.0558
36/82 [============>.................] - ETA: 0s - loss: 0.2535 
72/82 [=========================>....] - ETA: 0s - loss: 0.2295
82/82 [==============================] - 0s 1ms/step - loss: 0.2227
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1519
35/82 [===========>..................] - ETA: 0s - loss: 0.1566
68/82 [=======================>......] - ETA: 0s - loss: 0.1513
82/82 [==============================] - 0s 2ms/step - loss: 0.1508
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0932
35/82 [===========>..................] - ETA: 0s - loss: 0.1304
73/82 [=========================>....] - ETA: 0s - loss: 0.1192
82/82 [==============================] - 0s 1ms/step - loss: 0.1252
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0200
33/82 [===========>..................] - ETA: 0s - loss: 0.1300
69/82 [========================>.....] - ETA: 0s - loss: 0.1126
82/82 [==============================] - 0s 2ms/step - loss: 0.1083
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0907
36/82 [============>.................] - ETA: 0s - loss: 0.0826
71/82 [========================>.....] - ETA: 0s - loss: 0.1048
82/82 [==============================] - 0s 1ms/step - loss: 0.1032
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0664
35/82 [===========>..................] - ETA: 0s - loss: 0.1171
70/82 [========================>.....] - ETA: 0s - loss: 0.0997
82/82 [==============================] - 0s 1ms/step - loss: 0.0976
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0561
31/82 [==========>...................] - ETA: 0s - loss: 0.0804
67/82 [=======================>......] - ETA: 0s - loss: 0.1020
82/82 [==============================] - 0s 2ms/step - loss: 0.0961
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0753
34/82 [===========>..................] - ETA: 0s - loss: 0.0949
68/82 [=======================>......] - ETA: 0s - loss: 0.0959
82/82 [==============================] - 0s 1ms/step - loss: 0.0919
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0081
34/82 [===========>..................] - ETA: 0s - loss: 0.1011
69/82 [========================>.....] - ETA: 0s - loss: 0.0935
82/82 [==============================] - 0s 1ms/step - loss: 0.0912
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0065
34/82 [===========>..................] - ETA: 0s - loss: 0.1021
69/82 [========================>.....] - ETA: 0s - loss: 0.0913
82/82 [==============================] - 0s 1ms/step - loss: 0.0899
-> test with GAN.predict
GAN tn, fp: 192, 11
GAN fn, tp: 5, 2
GAN f1 score: 0.200
GAN cohens kappa score: 0.164

-> test with 'LR'
LR tn, fp: 183, 20
LR fn, tp: 1, 6
LR f1 score: 0.364
LR cohens kappa score: 0.328
LR average precision score: 0.490

-> 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: 202, 1
GB fn, tp: 6, 1
GB f1 score: 0.222
GB cohens kappa score: 0.211

-> test with 'KNN'
KNN tn, fp: 189, 14
KNN fn, tp: 4, 3
KNN f1 score: 0.250
KNN cohens kappa score: 0.213


====== 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: 16s - loss: 0.4576
34/82 [===========>..................] - ETA: 0s - loss: 0.3326 
65/82 [======================>.......] - ETA: 0s - loss: 0.3058
82/82 [==============================] - 0s 2ms/step - loss: 0.3181
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 6.3855e-04
36/82 [============>.................] - ETA: 0s - loss: 0.3073    
65/82 [======================>.......] - ETA: 0s - loss: 0.2430
82/82 [==============================] - 0s 2ms/step - loss: 0.2228
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 6.2808e-04
32/82 [==========>...................] - ETA: 0s - loss: 0.2119    
62/82 [=====================>........] - ETA: 0s - loss: 0.1757
82/82 [==============================] - 0s 2ms/step - loss: 0.1668
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2507
33/82 [===========>..................] - ETA: 0s - loss: 0.1358
64/82 [======================>.......] - ETA: 0s - loss: 0.1515
82/82 [==============================] - 0s 2ms/step - loss: 0.1418
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1642
35/82 [===========>..................] - ETA: 0s - loss: 0.1282
67/82 [=======================>......] - ETA: 0s - loss: 0.1303
82/82 [==============================] - 0s 2ms/step - loss: 0.1259
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0194
36/82 [============>.................] - ETA: 0s - loss: 0.1015
68/82 [=======================>......] - ETA: 0s - loss: 0.1049
82/82 [==============================] - 0s 2ms/step - loss: 0.1190
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0368
37/82 [============>.................] - ETA: 0s - loss: 0.1103
68/82 [=======================>......] - ETA: 0s - loss: 0.1124
82/82 [==============================] - 0s 2ms/step - loss: 0.1133
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0308
35/82 [===========>..................] - ETA: 0s - loss: 0.1045
66/82 [=======================>......] - ETA: 0s - loss: 0.1117
82/82 [==============================] - 0s 2ms/step - loss: 0.1091
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0355
35/82 [===========>..................] - ETA: 0s - loss: 0.1078
69/82 [========================>.....] - ETA: 0s - loss: 0.1013
82/82 [==============================] - 0s 2ms/step - loss: 0.1056
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1094
34/82 [===========>..................] - ETA: 0s - loss: 0.0963
63/82 [======================>.......] - ETA: 0s - loss: 0.1030
82/82 [==============================] - 0s 2ms/step - loss: 0.1024
-> test with GAN.predict
GAN tn, fp: 193, 12
GAN fn, tp: 3, 6
GAN f1 score: 0.444
GAN cohens kappa score: 0.411

-> test with 'LR'
LR tn, fp: 186, 19
LR fn, tp: 5, 4
LR f1 score: 0.250
LR cohens kappa score: 0.202
LR average precision score: 0.254

-> 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: 202, 3
GB fn, tp: 8, 1
GB f1 score: 0.154
GB cohens kappa score: 0.131

-> test with 'KNN'
KNN tn, fp: 189, 16
KNN fn, tp: 3, 6
KNN f1 score: 0.387
KNN cohens kappa score: 0.348


------ 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: 13s - loss: 0.2755
43/82 [==============>...............] - ETA: 0s - loss: 0.3481 
82/82 [==============================] - 0s 1ms/step - loss: 0.3212
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0015
43/82 [==============>...............] - ETA: 0s - loss: 0.2749
82/82 [==============================] - 0s 1ms/step - loss: 0.2163
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2248
46/82 [===============>..............] - ETA: 0s - loss: 0.1890
82/82 [==============================] - 0s 1ms/step - loss: 0.1709
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3087
45/82 [===============>..............] - ETA: 0s - loss: 0.1583
82/82 [==============================] - 0s 1ms/step - loss: 0.1447
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1365
44/82 [===============>..............] - ETA: 0s - loss: 0.1282
82/82 [==============================] - 0s 1ms/step - loss: 0.1313
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2203
45/82 [===============>..............] - ETA: 0s - loss: 0.1165
82/82 [==============================] - 0s 1ms/step - loss: 0.1186
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0490
42/82 [==============>...............] - ETA: 0s - loss: 0.1092
82/82 [==============================] - 0s 1ms/step - loss: 0.1128
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1652
36/82 [============>.................] - ETA: 0s - loss: 0.0981
73/82 [=========================>....] - ETA: 0s - loss: 0.1045
82/82 [==============================] - 0s 1ms/step - loss: 0.1054
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.2151
42/82 [==============>...............] - ETA: 0s - loss: 0.1125
82/82 [==============================] - ETA: 0s - loss: 0.1033
82/82 [==============================] - 0s 1ms/step - loss: 0.1033
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1197
43/82 [==============>...............] - ETA: 0s - loss: 0.0848
82/82 [==============================] - 0s 1ms/step - loss: 0.0982
-> test with GAN.predict
GAN tn, fp: 198, 7
GAN fn, tp: 8, 1
GAN f1 score: 0.118
GAN cohens kappa score: 0.081

-> test with 'LR'
LR tn, fp: 183, 22
LR fn, tp: 3, 6
LR f1 score: 0.324
LR cohens kappa score: 0.278
LR average precision score: 0.344

-> 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: 191, 14
KNN fn, tp: 5, 4
KNN f1 score: 0.296
KNN cohens kappa score: 0.254


------ 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: 0.1097
34/82 [===========>..................] - ETA: 0s - loss: 0.2790 
66/82 [=======================>......] - ETA: 0s - loss: 0.3018
82/82 [==============================] - 0s 2ms/step - loss: 0.2788
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0011
29/82 [=========>....................] - ETA: 0s - loss: 0.1732
56/82 [===================>..........] - ETA: 0s - loss: 0.1545
82/82 [==============================] - 0s 2ms/step - loss: 0.1756
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0023
33/82 [===========>..................] - ETA: 0s - loss: 0.1526
65/82 [======================>.......] - ETA: 0s - loss: 0.1210
82/82 [==============================] - 0s 2ms/step - loss: 0.1299
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2292
34/82 [===========>..................] - ETA: 0s - loss: 0.1034
66/82 [=======================>......] - ETA: 0s - loss: 0.1084
82/82 [==============================] - 0s 2ms/step - loss: 0.1077
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0320
34/82 [===========>..................] - ETA: 0s - loss: 0.0904
64/82 [======================>.......] - ETA: 0s - loss: 0.0975
82/82 [==============================] - 0s 2ms/step - loss: 0.0996
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1421
32/82 [==========>...................] - ETA: 0s - loss: 0.0982
61/82 [=====================>........] - ETA: 0s - loss: 0.0902
82/82 [==============================] - 0s 2ms/step - loss: 0.0949
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1317
33/82 [===========>..................] - ETA: 0s - loss: 0.0820
63/82 [======================>.......] - ETA: 0s - loss: 0.0959
82/82 [==============================] - 0s 2ms/step - loss: 0.0917
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0169
34/82 [===========>..................] - ETA: 0s - loss: 0.0837
66/82 [=======================>......] - ETA: 0s - loss: 0.0931
82/82 [==============================] - 0s 2ms/step - loss: 0.0880
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0209
35/82 [===========>..................] - ETA: 0s - loss: 0.1004
68/82 [=======================>......] - ETA: 0s - loss: 0.0850
82/82 [==============================] - 0s 2ms/step - loss: 0.0860
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1197
32/82 [==========>...................] - ETA: 0s - loss: 0.0769
66/82 [=======================>......] - ETA: 0s - loss: 0.0778
82/82 [==============================] - 0s 2ms/step - loss: 0.0841
-> 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: 178, 27
LR fn, tp: 0, 9
LR f1 score: 0.400
LR cohens kappa score: 0.357
LR average precision score: 0.508

-> 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: 204, 1
GB fn, tp: 8, 1
GB f1 score: 0.182
GB cohens kappa score: 0.169

-> test with 'KNN'
KNN tn, fp: 185, 20
KNN fn, tp: 4, 5
KNN f1 score: 0.294
KNN cohens kappa score: 0.248


------ 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: 19s - loss: 0.7224
29/82 [=========>....................] - ETA: 0s - loss: 0.1721 
62/82 [=====================>........] - ETA: 0s - loss: 0.2070
82/82 [==============================] - 0s 2ms/step - loss: 0.1798
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2824
29/82 [=========>....................] - ETA: 0s - loss: 0.0856
59/82 [====================>.........] - ETA: 0s - loss: 0.1185
82/82 [==============================] - 0s 2ms/step - loss: 0.1252
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0896
30/82 [=========>....................] - ETA: 0s - loss: 0.1233
58/82 [====================>.........] - ETA: 0s - loss: 0.1082
82/82 [==============================] - 0s 2ms/step - loss: 0.1016
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0110
32/82 [==========>...................] - ETA: 0s - loss: 0.0860
62/82 [=====================>........] - ETA: 0s - loss: 0.0972
82/82 [==============================] - 0s 2ms/step - loss: 0.0894
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1891
31/82 [==========>...................] - ETA: 0s - loss: 0.1045
62/82 [=====================>........] - ETA: 0s - loss: 0.0828
82/82 [==============================] - 0s 2ms/step - loss: 0.0794
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0964
31/82 [==========>...................] - ETA: 0s - loss: 0.0658
53/82 [==================>...........] - ETA: 0s - loss: 0.0885
77/82 [===========================>..] - ETA: 0s - loss: 0.0850
82/82 [==============================] - 0s 2ms/step - loss: 0.0808
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.3222
30/82 [=========>....................] - ETA: 0s - loss: 0.0865
57/82 [===================>..........] - ETA: 0s - loss: 0.0817
82/82 [==============================] - 0s 2ms/step - loss: 0.0746
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1452
32/82 [==========>...................] - ETA: 0s - loss: 0.0704
60/82 [====================>.........] - ETA: 0s - loss: 0.0756
82/82 [==============================] - 0s 2ms/step - loss: 0.0702
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0563
29/82 [=========>....................] - ETA: 0s - loss: 0.0818
59/82 [====================>.........] - ETA: 0s - loss: 0.0604
82/82 [==============================] - 0s 2ms/step - loss: 0.0687
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0448
30/82 [=========>....................] - ETA: 0s - loss: 0.0537
58/82 [====================>.........] - ETA: 0s - loss: 0.0550
82/82 [==============================] - 0s 2ms/step - loss: 0.0662
-> test with GAN.predict
GAN tn, fp: 200, 5
GAN fn, tp: 6, 3
GAN f1 score: 0.353
GAN cohens kappa score: 0.326

-> test with 'LR'
LR tn, fp: 195, 10
LR fn, tp: 5, 4
LR f1 score: 0.348
LR cohens kappa score: 0.313
LR average precision score: 0.220

-> 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: 202, 3
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.021

-> test with 'KNN'
KNN tn, fp: 199, 6
KNN fn, tp: 6, 3
KNN f1 score: 0.333
KNN cohens kappa score: 0.304


------ 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: 15s - loss: 0.6204
36/82 [============>.................] - ETA: 0s - loss: 0.3565 
71/82 [========================>.....] - ETA: 0s - loss: 0.3242
82/82 [==============================] - 0s 2ms/step - loss: 0.3138
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0510
37/82 [============>.................] - ETA: 0s - loss: 0.2811
64/82 [======================>.......] - ETA: 0s - loss: 0.2376
82/82 [==============================] - 0s 2ms/step - loss: 0.2180
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0197
35/82 [===========>..................] - ETA: 0s - loss: 0.1765
69/82 [========================>.....] - ETA: 0s - loss: 0.1452
82/82 [==============================] - 0s 2ms/step - loss: 0.1557
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2434
35/82 [===========>..................] - ETA: 0s - loss: 0.1355
71/82 [========================>.....] - ETA: 0s - loss: 0.1431
82/82 [==============================] - 0s 1ms/step - loss: 0.1319
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0055
33/82 [===========>..................] - ETA: 0s - loss: 0.1246
66/82 [=======================>......] - ETA: 0s - loss: 0.1222
82/82 [==============================] - 0s 2ms/step - loss: 0.1147
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1027
33/82 [===========>..................] - ETA: 0s - loss: 0.0966
66/82 [=======================>......] - ETA: 0s - loss: 0.1067
82/82 [==============================] - 0s 1ms/step - loss: 0.1062
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2198
34/82 [===========>..................] - ETA: 0s - loss: 0.0773
67/82 [=======================>......] - ETA: 0s - loss: 0.0972
82/82 [==============================] - 0s 1ms/step - loss: 0.0996
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1656
34/82 [===========>..................] - ETA: 0s - loss: 0.0988
67/82 [=======================>......] - ETA: 0s - loss: 0.0926
82/82 [==============================] - 0s 2ms/step - loss: 0.0936
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0077
34/82 [===========>..................] - ETA: 0s - loss: 0.0812
67/82 [=======================>......] - ETA: 0s - loss: 0.0792
82/82 [==============================] - 0s 2ms/step - loss: 0.0900
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0604
36/82 [============>.................] - ETA: 0s - loss: 0.0853
67/82 [=======================>......] - ETA: 0s - loss: 0.0817
82/82 [==============================] - 0s 2ms/step - loss: 0.0862
-> test with GAN.predict
GAN tn, fp: 192, 11
GAN fn, tp: 5, 2
GAN f1 score: 0.200
GAN cohens kappa score: 0.164

-> test with 'LR'
LR tn, fp: 177, 26
LR fn, tp: 2, 5
LR f1 score: 0.263
LR cohens kappa score: 0.221
LR average precision score: 0.450

-> test with 'RF'
RF tn, fp: 196, 7
RF fn, tp: 6, 1
RF f1 score: 0.133
RF cohens kappa score: 0.101

-> test with 'GB'
GB tn, fp: 197, 6
GB fn, tp: 5, 2
GB f1 score: 0.267
GB cohens kappa score: 0.240

-> test with 'KNN'
KNN tn, fp: 190, 13
KNN fn, tp: 5, 2
KNN f1 score: 0.182
KNN cohens kappa score: 0.143

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 195, 31
LR fn, tp: 8, 9
LR f1 score: 0.545
LR cohens kappa score: 0.516
LR average precision score: 0.814


average:
LR tn, fp: 184.08, 20.52
LR fn, tp: 3.08, 5.52
LR f1 score: 0.317
LR cohens kappa score: 0.274
LR average precision score: 0.380


minimum:
LR tn, fp: 174, 10
LR fn, tp: 0, 1
LR f1 score: 0.056
LR cohens kappa score: -0.008
LR average precision score: 0.087


-----[ RF ]-----
maximum:
RF tn, fp: 205, 8
RF fn, tp: 9, 2
RF f1 score: 0.364
RF cohens kappa score: 0.354


average:
RF tn, fp: 201.36, 3.24
RF fn, tp: 7.72, 0.88
RF f1 score: 0.133
RF cohens kappa score: 0.113


minimum:
RF tn, fp: 195, 0
RF fn, tp: 5, 0
RF f1 score: 0.000
RF cohens kappa score: -0.041


-----[ GB ]-----
maximum:
GB tn, fp: 205, 11
GB fn, tp: 9, 4
GB f1 score: 0.333
GB cohens kappa score: 0.319


average:
GB tn, fp: 201.92, 2.68
GB fn, tp: 7.56, 1.04
GB f1 score: 0.156
GB cohens kappa score: 0.138


minimum:
GB tn, fp: 194, 0
GB fn, tp: 5, 0
GB f1 score: 0.000
GB cohens kappa score: -0.035


-----[ KNN ]-----
maximum:
KNN tn, fp: 199, 27
KNN fn, tp: 6, 7
KNN f1 score: 0.480
KNN cohens kappa score: 0.450


average:
KNN tn, fp: 190.48, 14.12
KNN fn, tp: 4.56, 4.04
KNN f1 score: 0.302
KNN cohens kappa score: 0.262


minimum:
KNN tn, fp: 178, 6
KNN fn, tp: 1, 1
KNN f1 score: 0.118
KNN cohens kappa score: 0.082


-----[ GAN ]-----
maximum:
GAN tn, fp: 202, 26
GAN fn, tp: 9, 6
GAN f1 score: 0.471
GAN cohens kappa score: 0.449


average:
GAN tn, fp: 196.2, 8.4
GAN fn, tp: 5.96, 2.64
GAN f1 score: 0.267
GAN cohens kappa score: 0.234


minimum:
GAN tn, fp: 179, 3
GAN fn, tp: 3, 0
GAN f1 score: 0.000
GAN cohens kappa score: -0.027