ConvGeNBenchmarkResults/data_result/ConvGeN-proximity-full/folding_abalone9-18.log

///////////////////////////////////////////
// Running convGAN-proximary-full on folding_abalone9-18
///////////////////////////////////////////

Load 'data_input/folding_abalone9-18'
from pickle file
Data loaded.
-> Shuffling data
### Start exercise for synthetic point generator

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

------ Step 1/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 7s - loss: 0.1357
50/56 [=========================>....] - ETA: 0s - loss: 0.1623
56/56 [==============================] - 0s 1ms/step - loss: 0.1670
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.3035
51/56 [==========================>...] - ETA: 0s - loss: 0.1524
56/56 [==============================] - 0s 1ms/step - loss: 0.1527
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3603
51/56 [==========================>...] - ETA: 0s - loss: 0.1455
56/56 [==============================] - 0s 1ms/step - loss: 0.1501
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0259
43/56 [======================>.......] - ETA: 0s - loss: 0.1546
56/56 [==============================] - 0s 1ms/step - loss: 0.1493
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1956
44/56 [======================>.......] - ETA: 0s - loss: 0.1412
56/56 [==============================] - 0s 1ms/step - loss: 0.1443
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0925
49/56 [=========================>....] - ETA: 0s - loss: 0.1529
56/56 [==============================] - 0s 1ms/step - loss: 0.1437
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.3724
49/56 [=========================>....] - ETA: 0s - loss: 0.1454
56/56 [==============================] - 0s 1ms/step - loss: 0.1451
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0483
51/56 [==========================>...] - ETA: 0s - loss: 0.1408
56/56 [==============================] - 0s 1ms/step - loss: 0.1388
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0474
48/56 [========================>.....] - ETA: 0s - loss: 0.1431
56/56 [==============================] - 0s 1ms/step - loss: 0.1436
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0903
50/56 [=========================>....] - ETA: 0s - loss: 0.1395
56/56 [==============================] - 0s 1ms/step - loss: 0.1398
-> test with GAN.predict
GAN tn, fp: 133, 5
GAN fn, tp: 1, 8
GAN f1 score: 0.727
GAN cohens kappa score: 0.706

-> test with 'LR'
LR tn, fp: 123, 15
LR fn, tp: 0, 9
LR f1 score: 0.545
LR cohens kappa score: 0.501
LR average precision score: 0.918

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.163

-> test with 'GB'
GB tn, fp: 135, 3
GB fn, tp: 7, 2
GB f1 score: 0.286
GB cohens kappa score: 0.253

-> test with 'KNN'
KNN tn, fp: 136, 2
KNN fn, tp: 6, 3
KNN f1 score: 0.429
KNN cohens kappa score: 0.402


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 7s - loss: 0.2272
48/56 [========================>.....] - ETA: 0s - loss: 0.1426
56/56 [==============================] - 0s 1ms/step - loss: 0.1330
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0479
50/56 [=========================>....] - ETA: 0s - loss: 0.0872
56/56 [==============================] - 0s 1ms/step - loss: 0.0950
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0029
50/56 [=========================>....] - ETA: 0s - loss: 0.0920
56/56 [==============================] - 0s 1ms/step - loss: 0.0926
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 6.8266e-04
50/56 [=========================>....] - ETA: 0s - loss: 0.0846    
56/56 [==============================] - 0s 1ms/step - loss: 0.0862
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1586
50/56 [=========================>....] - ETA: 0s - loss: 0.0930
56/56 [==============================] - 0s 1ms/step - loss: 0.0909
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0350
50/56 [=========================>....] - ETA: 0s - loss: 0.0844
56/56 [==============================] - 0s 1ms/step - loss: 0.0790
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0136
50/56 [=========================>....] - ETA: 0s - loss: 0.0792
56/56 [==============================] - 0s 1ms/step - loss: 0.0762
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0387
50/56 [=========================>....] - ETA: 0s - loss: 0.0725
56/56 [==============================] - 0s 1ms/step - loss: 0.0739
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0482
50/56 [=========================>....] - ETA: 0s - loss: 0.0678
56/56 [==============================] - 0s 1ms/step - loss: 0.0756
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0550
50/56 [=========================>....] - ETA: 0s - loss: 0.0610
56/56 [==============================] - 0s 1ms/step - loss: 0.0716
-> test with GAN.predict
GAN tn, fp: 134, 4
GAN fn, tp: 6, 3
GAN f1 score: 0.375
GAN cohens kappa score: 0.340

-> test with 'LR'
LR tn, fp: 133, 5
LR fn, tp: 4, 5
LR f1 score: 0.526
LR cohens kappa score: 0.494
LR average precision score: 0.551

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.163

-> test with 'GB'
GB tn, fp: 133, 5
GB fn, tp: 8, 1
GB f1 score: 0.133
GB cohens kappa score: 0.089

-> test with 'KNN'
KNN tn, fp: 135, 3
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.032


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 7s - loss: 8.9830e-04
44/56 [======================>.......] - ETA: 0s - loss: 0.1184    
56/56 [==============================] - 0s 1ms/step - loss: 0.1184
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0150
46/56 [=======================>......] - ETA: 0s - loss: 0.1023
56/56 [==============================] - 0s 1ms/step - loss: 0.1004
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0478
50/56 [=========================>....] - ETA: 0s - loss: 0.0993
56/56 [==============================] - 0s 1ms/step - loss: 0.1054
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0735
50/56 [=========================>....] - ETA: 0s - loss: 0.0847
56/56 [==============================] - 0s 1ms/step - loss: 0.0969
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2879
50/56 [=========================>....] - ETA: 0s - loss: 0.0871
56/56 [==============================] - 0s 1ms/step - loss: 0.0897
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0549
50/56 [=========================>....] - ETA: 0s - loss: 0.0890
56/56 [==============================] - 0s 1ms/step - loss: 0.0879
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0465
50/56 [=========================>....] - ETA: 0s - loss: 0.0894
56/56 [==============================] - 0s 1ms/step - loss: 0.0874
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1090
50/56 [=========================>....] - ETA: 0s - loss: 0.0944
56/56 [==============================] - 0s 1ms/step - loss: 0.0882
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0159
49/56 [=========================>....] - ETA: 0s - loss: 0.0884
56/56 [==============================] - 0s 1ms/step - loss: 0.0895
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0175
49/56 [=========================>....] - ETA: 0s - loss: 0.0883
56/56 [==============================] - 0s 1ms/step - loss: 0.0858
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 2, 7
GAN f1 score: 0.778
GAN cohens kappa score: 0.763

-> test with 'LR'
LR tn, fp: 132, 6
LR fn, tp: 2, 7
LR f1 score: 0.636
LR cohens kappa score: 0.608
LR average precision score: 0.797

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 6, 3
RF f1 score: 0.429
RF cohens kappa score: 0.402

-> test with 'GB'
GB tn, fp: 137, 1
GB fn, tp: 8, 1
GB f1 score: 0.182
GB cohens kappa score: 0.163

-> test with 'KNN'
KNN tn, fp: 138, 0
KNN fn, tp: 8, 1
KNN f1 score: 0.200
KNN cohens kappa score: 0.190


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.0529
45/56 [=======================>......] - ETA: 0s - loss: 0.1188
56/56 [==============================] - 0s 1ms/step - loss: 0.1220
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0490
44/56 [======================>.......] - ETA: 0s - loss: 0.1029
56/56 [==============================] - 0s 1ms/step - loss: 0.1087
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0697
45/56 [=======================>......] - ETA: 0s - loss: 0.1175
56/56 [==============================] - 0s 1ms/step - loss: 0.1169
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0102
45/56 [=======================>......] - ETA: 0s - loss: 0.1018
56/56 [==============================] - 0s 1ms/step - loss: 0.1023
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1969
45/56 [=======================>......] - ETA: 0s - loss: 0.0852
56/56 [==============================] - 0s 1ms/step - loss: 0.1058
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0093
43/56 [======================>.......] - ETA: 0s - loss: 0.1114
56/56 [==============================] - 0s 1ms/step - loss: 0.0996
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1215
45/56 [=======================>......] - ETA: 0s - loss: 0.0900
56/56 [==============================] - 0s 1ms/step - loss: 0.0923
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1337
45/56 [=======================>......] - ETA: 0s - loss: 0.0991
56/56 [==============================] - 0s 1ms/step - loss: 0.0927
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0169
43/56 [======================>.......] - ETA: 0s - loss: 0.0969
56/56 [==============================] - 0s 1ms/step - loss: 0.0933
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0014
44/56 [======================>.......] - ETA: 0s - loss: 0.0916
56/56 [==============================] - 0s 1ms/step - loss: 0.0931
-> test with GAN.predict
GAN tn, fp: 134, 4
GAN fn, tp: 6, 3
GAN f1 score: 0.375
GAN cohens kappa score: 0.340

-> test with 'LR'
LR tn, fp: 133, 5
LR fn, tp: 4, 5
LR f1 score: 0.526
LR cohens kappa score: 0.494
LR average precision score: 0.631

-> test with 'RF'
RF tn, fp: 138, 0
RF fn, tp: 6, 3
RF f1 score: 0.500
RF cohens kappa score: 0.484

-> test with 'GB'
GB tn, fp: 137, 1
GB fn, tp: 7, 2
GB f1 score: 0.333
GB cohens kappa score: 0.312

-> test with 'KNN'
KNN tn, fp: 138, 0
KNN fn, tp: 8, 1
KNN f1 score: 0.200
KNN cohens kappa score: 0.190


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 516 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.7218
42/56 [=====================>........] - ETA: 0s - loss: 0.1689
56/56 [==============================] - 0s 1ms/step - loss: 0.1843
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0034
43/56 [======================>.......] - ETA: 0s - loss: 0.1682
56/56 [==============================] - 0s 1ms/step - loss: 0.1560
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3309
42/56 [=====================>........] - ETA: 0s - loss: 0.1601
56/56 [==============================] - 0s 1ms/step - loss: 0.1355
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3636
42/56 [=====================>........] - ETA: 0s - loss: 0.1124
56/56 [==============================] - 0s 1ms/step - loss: 0.1096
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2224
43/56 [======================>.......] - ETA: 0s - loss: 0.0894
56/56 [==============================] - 0s 1ms/step - loss: 0.1044
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0064
42/56 [=====================>........] - ETA: 0s - loss: 0.0907
56/56 [==============================] - 0s 1ms/step - loss: 0.0992
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0107
42/56 [=====================>........] - ETA: 0s - loss: 0.1091
56/56 [==============================] - 0s 1ms/step - loss: 0.1021
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0049
43/56 [======================>.......] - ETA: 0s - loss: 0.0955
56/56 [==============================] - 0s 1ms/step - loss: 0.0923
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0726
41/56 [====================>.........] - ETA: 0s - loss: 0.0752
56/56 [==============================] - 0s 1ms/step - loss: 0.0904
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0051
42/56 [=====================>........] - ETA: 0s - loss: 0.0702
56/56 [==============================] - 0s 1ms/step - loss: 0.0875
-> test with GAN.predict
GAN tn, fp: 136, 1
GAN fn, tp: 4, 2
GAN f1 score: 0.444
GAN cohens kappa score: 0.428

-> test with 'LR'
LR tn, fp: 134, 3
LR fn, tp: 2, 4
LR f1 score: 0.615
LR cohens kappa score: 0.597
LR average precision score: 0.447

-> test with 'RF'
RF tn, fp: 137, 0
RF fn, tp: 4, 2
RF f1 score: 0.500
RF cohens kappa score: 0.489

-> test with 'GB'
GB tn, fp: 137, 0
GB fn, tp: 4, 2
GB f1 score: 0.500
GB cohens kappa score: 0.489

-> test with 'KNN'
KNN tn, fp: 137, 0
KNN fn, tp: 5, 1
KNN f1 score: 0.286
KNN cohens kappa score: 0.277


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

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 9s - loss: 0.0047
37/56 [==================>...........] - ETA: 0s - loss: 0.1173
56/56 [==============================] - 0s 1ms/step - loss: 0.1089
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0146
40/56 [====================>.........] - ETA: 0s - loss: 0.1052
56/56 [==============================] - 0s 1ms/step - loss: 0.0916
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0040
39/56 [===================>..........] - ETA: 0s - loss: 0.0878
56/56 [==============================] - 0s 1ms/step - loss: 0.0885
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.6756
40/56 [====================>.........] - ETA: 0s - loss: 0.0883
56/56 [==============================] - 0s 1ms/step - loss: 0.0796
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0185
37/56 [==================>...........] - ETA: 0s - loss: 0.0620
56/56 [==============================] - 0s 1ms/step - loss: 0.0799
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0035
38/56 [===================>..........] - ETA: 0s - loss: 0.0786
56/56 [==============================] - 0s 2ms/step - loss: 0.0730
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0044
36/56 [==================>...........] - ETA: 0s - loss: 0.0559
56/56 [==============================] - 0s 1ms/step - loss: 0.0696
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0408
34/56 [=================>............] - ETA: 0s - loss: 0.0935
56/56 [==============================] - 0s 2ms/step - loss: 0.0716
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0777
33/56 [================>.............] - ETA: 0s - loss: 0.0665
56/56 [==============================] - 0s 2ms/step - loss: 0.0708
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0992
38/56 [===================>..........] - ETA: 0s - loss: 0.1122
56/56 [==============================] - 0s 1ms/step - loss: 0.0967
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 6, 3
GAN f1 score: 0.429
GAN cohens kappa score: 0.402

-> test with 'LR'
LR tn, fp: 131, 7
LR fn, tp: 2, 7
LR f1 score: 0.609
LR cohens kappa score: 0.577
LR average precision score: 0.626

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 7, 2
RF f1 score: 0.333
RF cohens kappa score: 0.312

-> test with 'GB'
GB tn, fp: 135, 3
GB fn, tp: 6, 3
GB f1 score: 0.400
GB cohens kappa score: 0.369

-> test with 'KNN'
KNN tn, fp: 136, 2
KNN fn, tp: 8, 1
KNN f1 score: 0.167
KNN cohens kappa score: 0.140


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.0089
34/56 [=================>............] - ETA: 0s - loss: 0.1064
56/56 [==============================] - 0s 1ms/step - loss: 0.1267
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0246
41/56 [====================>.........] - ETA: 0s - loss: 0.1282
56/56 [==============================] - 0s 1ms/step - loss: 0.1353
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0305
42/56 [=====================>........] - ETA: 0s - loss: 0.1166
56/56 [==============================] - 0s 1ms/step - loss: 0.1064
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0970
41/56 [====================>.........] - ETA: 0s - loss: 0.1002
56/56 [==============================] - 0s 1ms/step - loss: 0.1011
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2697
40/56 [====================>.........] - ETA: 0s - loss: 0.1071
56/56 [==============================] - 0s 1ms/step - loss: 0.0971
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0362
43/56 [======================>.......] - ETA: 0s - loss: 0.1029
56/56 [==============================] - 0s 1ms/step - loss: 0.0910
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1631
37/56 [==================>...........] - ETA: 0s - loss: 0.0763
56/56 [==============================] - 0s 1ms/step - loss: 0.0877
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0329
40/56 [====================>.........] - ETA: 0s - loss: 0.0836
56/56 [==============================] - 0s 1ms/step - loss: 0.0843
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0154
42/56 [=====================>........] - ETA: 0s - loss: 0.0934
56/56 [==============================] - 0s 1ms/step - loss: 0.0829
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0310
45/56 [=======================>......] - ETA: 0s - loss: 0.0774
56/56 [==============================] - 0s 1ms/step - loss: 0.0813
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 3, 6
GAN f1 score: 0.706
GAN cohens kappa score: 0.688

-> test with 'LR'
LR tn, fp: 132, 6
LR fn, tp: 2, 7
LR f1 score: 0.636
LR cohens kappa score: 0.608
LR average precision score: 0.751

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 6, 3
RF f1 score: 0.462
RF cohens kappa score: 0.440

-> test with 'GB'
GB tn, fp: 136, 2
GB fn, tp: 6, 3
GB f1 score: 0.429
GB cohens kappa score: 0.402

-> test with 'KNN'
KNN tn, fp: 137, 1
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.012


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 10s - loss: 5.0524e-04
41/56 [====================>.........] - ETA: 0s - loss: 0.1657     
56/56 [==============================] - 0s 1ms/step - loss: 0.1588
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2426
42/56 [=====================>........] - ETA: 0s - loss: 0.1364
56/56 [==============================] - 0s 1ms/step - loss: 0.1355
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.7550
43/56 [======================>.......] - ETA: 0s - loss: 0.1029
56/56 [==============================] - 0s 1ms/step - loss: 0.1058
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0024
43/56 [======================>.......] - ETA: 0s - loss: 0.1124
56/56 [==============================] - 0s 1ms/step - loss: 0.1005
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0350
42/56 [=====================>........] - ETA: 0s - loss: 0.1121
56/56 [==============================] - 0s 1ms/step - loss: 0.0969
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0303
41/56 [====================>.........] - ETA: 0s - loss: 0.1006
56/56 [==============================] - 0s 1ms/step - loss: 0.0967
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0424
42/56 [=====================>........] - ETA: 0s - loss: 0.0994
56/56 [==============================] - 0s 1ms/step - loss: 0.0934
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0348
42/56 [=====================>........] - ETA: 0s - loss: 0.0939
56/56 [==============================] - 0s 1ms/step - loss: 0.0906
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0272
43/56 [======================>.......] - ETA: 0s - loss: 0.0968
56/56 [==============================] - 0s 1ms/step - loss: 0.0862
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0159
40/56 [====================>.........] - ETA: 0s - loss: 0.0922
56/56 [==============================] - 0s 1ms/step - loss: 0.0875
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 4, 5
GAN f1 score: 0.625
GAN cohens kappa score: 0.604

-> test with 'LR'
LR tn, fp: 134, 4
LR fn, tp: 2, 7
LR f1 score: 0.700
LR cohens kappa score: 0.678
LR average precision score: 0.729

-> test with 'RF'
RF tn, fp: 135, 3
RF fn, tp: 8, 1
RF f1 score: 0.154
RF cohens kappa score: 0.121

-> test with 'GB'
GB tn, fp: 134, 4
GB fn, tp: 8, 1
GB f1 score: 0.143
GB cohens kappa score: 0.104

-> test with 'KNN'
KNN tn, fp: 138, 0
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 7s - loss: 0.0014
49/56 [=========================>....] - ETA: 0s - loss: 0.1190
56/56 [==============================] - 0s 1ms/step - loss: 0.1186
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2265
50/56 [=========================>....] - ETA: 0s - loss: 0.1193
56/56 [==============================] - 0s 1ms/step - loss: 0.1125
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1140
46/56 [=======================>......] - ETA: 0s - loss: 0.1171
56/56 [==============================] - 0s 1ms/step - loss: 0.1077
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0555
46/56 [=======================>......] - ETA: 0s - loss: 0.0806
56/56 [==============================] - 0s 1ms/step - loss: 0.0976
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0506
48/56 [========================>.....] - ETA: 0s - loss: 0.0915
56/56 [==============================] - 0s 1ms/step - loss: 0.0936
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.3806
49/56 [=========================>....] - ETA: 0s - loss: 0.0897
56/56 [==============================] - 0s 1ms/step - loss: 0.0954
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0241
48/56 [========================>.....] - ETA: 0s - loss: 0.0877
56/56 [==============================] - 0s 1ms/step - loss: 0.0890
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.5460
49/56 [=========================>....] - ETA: 0s - loss: 0.1312
56/56 [==============================] - 0s 1ms/step - loss: 0.1233
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2517
48/56 [========================>.....] - ETA: 0s - loss: 0.0928
56/56 [==============================] - 0s 1ms/step - loss: 0.0886
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0515
47/56 [========================>.....] - ETA: 0s - loss: 0.0767
56/56 [==============================] - 0s 1ms/step - loss: 0.0882
-> test with GAN.predict
GAN tn, fp: 134, 4
GAN fn, tp: 4, 5
GAN f1 score: 0.556
GAN cohens kappa score: 0.527

-> test with 'LR'
LR tn, fp: 130, 8
LR fn, tp: 2, 7
LR f1 score: 0.583
LR cohens kappa score: 0.549
LR average precision score: 0.750

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 6, 3
RF f1 score: 0.429
RF cohens kappa score: 0.402

-> test with 'GB'
GB tn, fp: 136, 2
GB fn, tp: 6, 3
GB f1 score: 0.429
GB cohens kappa score: 0.402

-> test with 'KNN'
KNN tn, fp: 137, 1
KNN fn, tp: 8, 1
KNN f1 score: 0.182
KNN cohens kappa score: 0.163


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 516 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.1129
49/56 [=========================>....] - ETA: 0s - loss: 0.1050
56/56 [==============================] - 0s 1ms/step - loss: 0.0998
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0088
48/56 [========================>.....] - ETA: 0s - loss: 0.0892
56/56 [==============================] - 0s 1ms/step - loss: 0.0840
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1895
47/56 [========================>.....] - ETA: 0s - loss: 0.0924
56/56 [==============================] - 0s 1ms/step - loss: 0.0825
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0346
36/56 [==================>...........] - ETA: 0s - loss: 0.0824
56/56 [==============================] - 0s 1ms/step - loss: 0.0803
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0221
42/56 [=====================>........] - ETA: 0s - loss: 0.0867
56/56 [==============================] - 0s 1ms/step - loss: 0.0827
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0417
48/56 [========================>.....] - ETA: 0s - loss: 0.0845
56/56 [==============================] - 0s 1ms/step - loss: 0.0769
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1511
43/56 [======================>.......] - ETA: 0s - loss: 0.0729
56/56 [==============================] - 0s 1ms/step - loss: 0.0744
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1631
38/56 [===================>..........] - ETA: 0s - loss: 0.0789
56/56 [==============================] - 0s 1ms/step - loss: 0.0751
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0413
38/56 [===================>..........] - ETA: 0s - loss: 0.0683
56/56 [==============================] - 0s 1ms/step - loss: 0.0780
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0380
42/56 [=====================>........] - ETA: 0s - loss: 0.0837
56/56 [==============================] - 0s 1ms/step - loss: 0.0840
-> test with GAN.predict
GAN tn, fp: 134, 3
GAN fn, tp: 3, 3
GAN f1 score: 0.500
GAN cohens kappa score: 0.478

-> test with 'LR'
LR tn, fp: 130, 7
LR fn, tp: 1, 5
LR f1 score: 0.556
LR cohens kappa score: 0.529
LR average precision score: 0.562

-> test with 'RF'
RF tn, fp: 137, 0
RF fn, tp: 3, 3
RF f1 score: 0.667
RF cohens kappa score: 0.657

-> test with 'GB'
GB tn, fp: 137, 0
GB fn, tp: 4, 2
GB f1 score: 0.500
GB cohens kappa score: 0.489

-> test with 'KNN'
KNN tn, fp: 137, 0
KNN fn, tp: 5, 1
KNN f1 score: 0.286
KNN cohens kappa score: 0.277


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

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 9s - loss: 0.1923
45/56 [=======================>......] - ETA: 0s - loss: 0.0920
56/56 [==============================] - 0s 1ms/step - loss: 0.0973
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0200
48/56 [========================>.....] - ETA: 0s - loss: 0.0913
56/56 [==============================] - 0s 1ms/step - loss: 0.0989
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0100
47/56 [========================>.....] - ETA: 0s - loss: 0.0869
56/56 [==============================] - 0s 1ms/step - loss: 0.0909
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1113
42/56 [=====================>........] - ETA: 0s - loss: 0.0721
56/56 [==============================] - 0s 1ms/step - loss: 0.0839
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0426
42/56 [=====================>........] - ETA: 0s - loss: 0.0854
56/56 [==============================] - 0s 1ms/step - loss: 0.0825
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.5961
48/56 [========================>.....] - ETA: 0s - loss: 0.0869
56/56 [==============================] - 0s 1ms/step - loss: 0.0902
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0257
49/56 [=========================>....] - ETA: 0s - loss: 0.0886
56/56 [==============================] - 0s 1ms/step - loss: 0.0839
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0456
49/56 [=========================>....] - ETA: 0s - loss: 0.0822
56/56 [==============================] - 0s 1ms/step - loss: 0.0784
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0070
49/56 [=========================>....] - ETA: 0s - loss: 0.0773
56/56 [==============================] - 0s 1ms/step - loss: 0.0767
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0067
49/56 [=========================>....] - ETA: 0s - loss: 0.0824
56/56 [==============================] - 0s 1ms/step - loss: 0.0775
-> test with GAN.predict
GAN tn, fp: 134, 4
GAN fn, tp: 5, 4
GAN f1 score: 0.471
GAN cohens kappa score: 0.438

-> test with 'LR'
LR tn, fp: 131, 7
LR fn, tp: 5, 4
LR f1 score: 0.400
LR cohens kappa score: 0.357
LR average precision score: 0.518

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 8, 1
RF f1 score: 0.167
RF cohens kappa score: 0.140

-> test with 'GB'
GB tn, fp: 135, 3
GB fn, tp: 7, 2
GB f1 score: 0.286
GB cohens kappa score: 0.253

-> test with 'KNN'
KNN tn, fp: 136, 2
KNN fn, tp: 8, 1
KNN f1 score: 0.167
KNN cohens kappa score: 0.140


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.2894
47/56 [========================>.....] - ETA: 0s - loss: 0.1709
56/56 [==============================] - 0s 1ms/step - loss: 0.1549
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.3875
49/56 [=========================>....] - ETA: 0s - loss: 0.0979
56/56 [==============================] - 0s 1ms/step - loss: 0.1215
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0590
49/56 [=========================>....] - ETA: 0s - loss: 0.1075
56/56 [==============================] - 0s 1ms/step - loss: 0.1247
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0058
41/56 [====================>.........] - ETA: 0s - loss: 0.1290
56/56 [==============================] - 0s 1ms/step - loss: 0.1141
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0147
48/56 [========================>.....] - ETA: 0s - loss: 0.1075
56/56 [==============================] - 0s 1ms/step - loss: 0.1107
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0956
44/56 [======================>.......] - ETA: 0s - loss: 0.1038
56/56 [==============================] - 0s 1ms/step - loss: 0.1044
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1781
41/56 [====================>.........] - ETA: 0s - loss: 0.1177
56/56 [==============================] - 0s 1ms/step - loss: 0.1039
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1046
48/56 [========================>.....] - ETA: 0s - loss: 0.1060
56/56 [==============================] - 0s 1ms/step - loss: 0.1019
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0267
50/56 [=========================>....] - ETA: 0s - loss: 0.1007
56/56 [==============================] - 0s 1ms/step - loss: 0.0969
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0409
49/56 [=========================>....] - ETA: 0s - loss: 0.1025
56/56 [==============================] - 0s 1ms/step - loss: 0.0985
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 5, 4
GAN f1 score: 0.533
GAN cohens kappa score: 0.509

-> test with 'LR'
LR tn, fp: 134, 4
LR fn, tp: 0, 9
LR f1 score: 0.818
LR cohens kappa score: 0.804
LR average precision score: 0.822

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.163

-> test with 'GB'
GB tn, fp: 135, 3
GB fn, tp: 8, 1
GB f1 score: 0.154
GB cohens kappa score: 0.121

-> test with 'KNN'
KNN tn, fp: 137, 1
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.012


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.1183
48/56 [========================>.....] - ETA: 0s - loss: 0.1010
56/56 [==============================] - 0s 1ms/step - loss: 0.1070
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0080
47/56 [========================>.....] - ETA: 0s - loss: 0.1070
56/56 [==============================] - 0s 1ms/step - loss: 0.0970
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3042
48/56 [========================>.....] - ETA: 0s - loss: 0.0920
56/56 [==============================] - 0s 1ms/step - loss: 0.0877
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0893
48/56 [========================>.....] - ETA: 0s - loss: 0.0973
56/56 [==============================] - 0s 1ms/step - loss: 0.0911
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0152
50/56 [=========================>....] - ETA: 0s - loss: 0.0751
56/56 [==============================] - 0s 1ms/step - loss: 0.0892
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0806
49/56 [=========================>....] - ETA: 0s - loss: 0.1044
56/56 [==============================] - 0s 1ms/step - loss: 0.0982
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0066
49/56 [=========================>....] - ETA: 0s - loss: 0.0901
56/56 [==============================] - 0s 1ms/step - loss: 0.0925
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2340
49/56 [=========================>....] - ETA: 0s - loss: 0.0883
56/56 [==============================] - 0s 1ms/step - loss: 0.0901
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0157
49/56 [=========================>....] - ETA: 0s - loss: 0.0862
56/56 [==============================] - 0s 1ms/step - loss: 0.0871
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0439
47/56 [========================>.....] - ETA: 0s - loss: 0.0844
56/56 [==============================] - 0s 1ms/step - loss: 0.0845
-> test with GAN.predict
GAN tn, fp: 137, 1
GAN fn, tp: 6, 3
GAN f1 score: 0.462
GAN cohens kappa score: 0.440

-> test with 'LR'
LR tn, fp: 134, 4
LR fn, tp: 4, 5
LR f1 score: 0.556
LR cohens kappa score: 0.527
LR average precision score: 0.671

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 7, 2
RF f1 score: 0.308
RF cohens kappa score: 0.281

-> test with 'GB'
GB tn, fp: 134, 4
GB fn, tp: 8, 1
GB f1 score: 0.143
GB cohens kappa score: 0.104

-> test with 'KNN'
KNN tn, fp: 137, 1
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.012


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 7s - loss: 0.2951
48/56 [========================>.....] - ETA: 0s - loss: 0.1680
56/56 [==============================] - 0s 1ms/step - loss: 0.1727
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0977
47/56 [========================>.....] - ETA: 0s - loss: 0.1860
56/56 [==============================] - 0s 1ms/step - loss: 0.1782
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0263
45/56 [=======================>......] - ETA: 0s - loss: 0.1360
56/56 [==============================] - 0s 1ms/step - loss: 0.1518
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.2003
43/56 [======================>.......] - ETA: 0s - loss: 0.1731
56/56 [==============================] - 0s 1ms/step - loss: 0.1523
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2615
49/56 [=========================>....] - ETA: 0s - loss: 0.1519
56/56 [==============================] - 0s 1ms/step - loss: 0.1456
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0732
44/56 [======================>.......] - ETA: 0s - loss: 0.1310
56/56 [==============================] - 0s 1ms/step - loss: 0.1449
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2108
40/56 [====================>.........] - ETA: 0s - loss: 0.1386
56/56 [==============================] - 0s 1ms/step - loss: 0.1393
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2213
49/56 [=========================>....] - ETA: 0s - loss: 0.1402
56/56 [==============================] - 0s 1ms/step - loss: 0.1398
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0459
49/56 [=========================>....] - ETA: 0s - loss: 0.1296
56/56 [==============================] - 0s 1ms/step - loss: 0.1386
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1004
49/56 [=========================>....] - ETA: 0s - loss: 0.1407
56/56 [==============================] - 0s 1ms/step - loss: 0.1358
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 5, 4
GAN f1 score: 0.533
GAN cohens kappa score: 0.509

-> test with 'LR'
LR tn, fp: 122, 16
LR fn, tp: 2, 7
LR f1 score: 0.438
LR cohens kappa score: 0.383
LR average precision score: 0.665

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 6, 3
RF f1 score: 0.429
RF cohens kappa score: 0.402

-> test with 'GB'
GB tn, fp: 137, 1
GB fn, tp: 6, 3
GB f1 score: 0.462
GB cohens kappa score: 0.440

-> test with 'KNN'
KNN tn, fp: 138, 0
KNN fn, tp: 5, 4
KNN f1 score: 0.615
KNN cohens kappa score: 0.600


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 516 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.5741
47/56 [========================>.....] - ETA: 0s - loss: 0.1399
56/56 [==============================] - 0s 1ms/step - loss: 0.1324
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1398
44/56 [======================>.......] - ETA: 0s - loss: 0.1319
56/56 [==============================] - 0s 1ms/step - loss: 0.1256
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0482
42/56 [=====================>........] - ETA: 0s - loss: 0.1076
56/56 [==============================] - 0s 1ms/step - loss: 0.1103
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0248
43/56 [======================>.......] - ETA: 0s - loss: 0.1043
56/56 [==============================] - 0s 1ms/step - loss: 0.1057
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1815
47/56 [========================>.....] - ETA: 0s - loss: 0.0988
56/56 [==============================] - 0s 1ms/step - loss: 0.1068
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0136
44/56 [======================>.......] - ETA: 0s - loss: 0.1117
56/56 [==============================] - 0s 1ms/step - loss: 0.1035
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0135
48/56 [========================>.....] - ETA: 0s - loss: 0.1144
56/56 [==============================] - 0s 1ms/step - loss: 0.1084
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0616
49/56 [=========================>....] - ETA: 0s - loss: 0.0985
56/56 [==============================] - 0s 1ms/step - loss: 0.1007
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0095
45/56 [=======================>......] - ETA: 0s - loss: 0.0919
56/56 [==============================] - 0s 1ms/step - loss: 0.0990
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0952
43/56 [======================>.......] - ETA: 0s - loss: 0.0975
56/56 [==============================] - 0s 1ms/step - loss: 0.0981
-> test with GAN.predict
GAN tn, fp: 136, 1
GAN fn, tp: 4, 2
GAN f1 score: 0.444
GAN cohens kappa score: 0.428

-> test with 'LR'
LR tn, fp: 131, 6
LR fn, tp: 2, 4
LR f1 score: 0.500
LR cohens kappa score: 0.472
LR average precision score: 0.533

-> test with 'RF'
RF tn, fp: 136, 1
RF fn, tp: 4, 2
RF f1 score: 0.444
RF cohens kappa score: 0.428

-> test with 'GB'
GB tn, fp: 133, 4
GB fn, tp: 4, 2
GB f1 score: 0.333
GB cohens kappa score: 0.304

-> test with 'KNN'
KNN tn, fp: 136, 1
KNN fn, tp: 6, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.012


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

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.2522
48/56 [========================>.....] - ETA: 0s - loss: 0.1712
56/56 [==============================] - 0s 1ms/step - loss: 0.1557
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0027
49/56 [=========================>....] - ETA: 0s - loss: 0.1356
56/56 [==============================] - 0s 1ms/step - loss: 0.1396
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0048
49/56 [=========================>....] - ETA: 0s - loss: 0.1406
56/56 [==============================] - 0s 1ms/step - loss: 0.1307
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0112
47/56 [========================>.....] - ETA: 0s - loss: 0.1023
56/56 [==============================] - 0s 1ms/step - loss: 0.1058
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.6295
45/56 [=======================>......] - ETA: 0s - loss: 0.0991
56/56 [==============================] - 0s 1ms/step - loss: 0.1041
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0185
50/56 [=========================>....] - ETA: 0s - loss: 0.0996
56/56 [==============================] - 0s 1ms/step - loss: 0.0979
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0572
48/56 [========================>.....] - ETA: 0s - loss: 0.0930
56/56 [==============================] - 0s 1ms/step - loss: 0.0941
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0139
44/56 [======================>.......] - ETA: 0s - loss: 0.0859
56/56 [==============================] - 0s 1ms/step - loss: 0.0897
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0192
42/56 [=====================>........] - ETA: 0s - loss: 0.0973
56/56 [==============================] - 0s 1ms/step - loss: 0.0860
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0150
39/56 [===================>..........] - ETA: 0s - loss: 0.0850
56/56 [==============================] - 0s 1ms/step - loss: 0.0876
-> test with GAN.predict
GAN tn, fp: 135, 3
GAN fn, tp: 4, 5
GAN f1 score: 0.588
GAN cohens kappa score: 0.563

-> test with 'LR'
LR tn, fp: 130, 8
LR fn, tp: 5, 4
LR f1 score: 0.381
LR cohens kappa score: 0.334
LR average precision score: 0.530

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 6, 3
RF f1 score: 0.429
RF cohens kappa score: 0.402

-> test with 'GB'
GB tn, fp: 133, 5
GB fn, tp: 6, 3
GB f1 score: 0.353
GB cohens kappa score: 0.313

-> test with 'KNN'
KNN tn, fp: 137, 1
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.012


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 9s - loss: 0.4145
44/56 [======================>.......] - ETA: 0s - loss: 0.1608
56/56 [==============================] - 0s 1ms/step - loss: 0.1470
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0501
39/56 [===================>..........] - ETA: 0s - loss: 0.1289
56/56 [==============================] - 0s 1ms/step - loss: 0.1268
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0170
42/56 [=====================>........] - ETA: 0s - loss: 0.1184
56/56 [==============================] - 0s 1ms/step - loss: 0.1203
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0676
42/56 [=====================>........] - ETA: 0s - loss: 0.1146
56/56 [==============================] - 0s 1ms/step - loss: 0.1206
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0242
40/56 [====================>.........] - ETA: 0s - loss: 0.0986
56/56 [==============================] - 0s 1ms/step - loss: 0.1024
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0031
27/56 [=============>................] - ETA: 0s - loss: 0.0787
56/56 [==============================] - 0s 2ms/step - loss: 0.1012
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0391
39/56 [===================>..........] - ETA: 0s - loss: 0.1139
56/56 [==============================] - 0s 1ms/step - loss: 0.0984
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0293
44/56 [======================>.......] - ETA: 0s - loss: 0.1003
56/56 [==============================] - 0s 1ms/step - loss: 0.0958
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0202
44/56 [======================>.......] - ETA: 0s - loss: 0.0887
56/56 [==============================] - 0s 1ms/step - loss: 0.0943
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0156
42/56 [=====================>........] - ETA: 0s - loss: 0.0918
56/56 [==============================] - 0s 1ms/step - loss: 0.0936
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 5, 4
GAN f1 score: 0.533
GAN cohens kappa score: 0.509

-> test with 'LR'
LR tn, fp: 131, 7
LR fn, tp: 3, 6
LR f1 score: 0.545
LR cohens kappa score: 0.510
LR average precision score: 0.712

-> test with 'RF'
RF tn, fp: 133, 5
RF fn, tp: 5, 4
RF f1 score: 0.444
RF cohens kappa score: 0.408

-> test with 'GB'
GB tn, fp: 130, 8
GB fn, tp: 5, 4
GB f1 score: 0.381
GB cohens kappa score: 0.334

-> test with 'KNN'
KNN tn, fp: 138, 0
KNN fn, tp: 8, 1
KNN f1 score: 0.200
KNN cohens kappa score: 0.190


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.0012
44/56 [======================>.......] - ETA: 0s - loss: 0.1475
56/56 [==============================] - 0s 1ms/step - loss: 0.1349
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.3369
47/56 [========================>.....] - ETA: 0s - loss: 0.1431
56/56 [==============================] - 0s 1ms/step - loss: 0.1327
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0018
46/56 [=======================>......] - ETA: 0s - loss: 0.1083
56/56 [==============================] - 0s 1ms/step - loss: 0.1091
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0029
41/56 [====================>.........] - ETA: 0s - loss: 0.0982
56/56 [==============================] - 0s 1ms/step - loss: 0.1108
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1907
40/56 [====================>.........] - ETA: 0s - loss: 0.0837
56/56 [==============================] - 0s 1ms/step - loss: 0.1035
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0211
45/56 [=======================>......] - ETA: 0s - loss: 0.0979
56/56 [==============================] - 0s 1ms/step - loss: 0.1054
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0082
47/56 [========================>.....] - ETA: 0s - loss: 0.0968
56/56 [==============================] - 0s 1ms/step - loss: 0.1011
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1100
43/56 [======================>.......] - ETA: 0s - loss: 0.1057
56/56 [==============================] - 0s 1ms/step - loss: 0.1096
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1300
43/56 [======================>.......] - ETA: 0s - loss: 0.0876
56/56 [==============================] - 0s 1ms/step - loss: 0.0958
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2583
44/56 [======================>.......] - ETA: 0s - loss: 0.0937
56/56 [==============================] - 0s 1ms/step - loss: 0.0952
-> test with GAN.predict
GAN tn, fp: 137, 1
GAN fn, tp: 6, 3
GAN f1 score: 0.462
GAN cohens kappa score: 0.440

-> test with 'LR'
LR tn, fp: 132, 6
LR fn, tp: 2, 7
LR f1 score: 0.636
LR cohens kappa score: 0.608
LR average precision score: 0.657

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 6, 3
RF f1 score: 0.429
RF cohens kappa score: 0.402

-> test with 'GB'
GB tn, fp: 138, 0
GB fn, tp: 6, 3
GB f1 score: 0.500
GB cohens kappa score: 0.484

-> test with 'KNN'
KNN tn, fp: 138, 0
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: 0.000


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 9s - loss: 0.1910
46/56 [=======================>......] - ETA: 0s - loss: 0.1916
56/56 [==============================] - 0s 1ms/step - loss: 0.1728
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0783
43/56 [======================>.......] - ETA: 0s - loss: 0.1174
56/56 [==============================] - 0s 1ms/step - loss: 0.1322
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0049
42/56 [=====================>........] - ETA: 0s - loss: 0.1252
56/56 [==============================] - 0s 1ms/step - loss: 0.1164
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0069
42/56 [=====================>........] - ETA: 0s - loss: 0.1066
56/56 [==============================] - 0s 1ms/step - loss: 0.1118
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1813
41/56 [====================>.........] - ETA: 0s - loss: 0.1183
56/56 [==============================] - 0s 1ms/step - loss: 0.1067
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1993
41/56 [====================>.........] - ETA: 0s - loss: 0.1005
56/56 [==============================] - 0s 1ms/step - loss: 0.1013
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2239
42/56 [=====================>........] - ETA: 0s - loss: 0.0900
56/56 [==============================] - 0s 1ms/step - loss: 0.0998
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0055
41/56 [====================>.........] - ETA: 0s - loss: 0.1275
56/56 [==============================] - 0s 1ms/step - loss: 0.1149
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1471
42/56 [=====================>........] - ETA: 0s - loss: 0.0822
56/56 [==============================] - 0s 1ms/step - loss: 0.0922
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0222
40/56 [====================>.........] - ETA: 0s - loss: 0.1038
56/56 [==============================] - 0s 1ms/step - loss: 0.0967
-> test with GAN.predict
GAN tn, fp: 133, 5
GAN fn, tp: 3, 6
GAN f1 score: 0.600
GAN cohens kappa score: 0.571

-> test with 'LR'
LR tn, fp: 132, 6
LR fn, tp: 0, 9
LR f1 score: 0.750
LR cohens kappa score: 0.729
LR average precision score: 0.906

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.163

-> test with 'GB'
GB tn, fp: 136, 2
GB fn, tp: 8, 1
GB f1 score: 0.167
GB cohens kappa score: 0.140

-> test with 'KNN'
KNN tn, fp: 135, 3
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.032


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 516 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 8s - loss: 0.0961
48/56 [========================>.....] - ETA: 0s - loss: 0.1677
56/56 [==============================] - 0s 1ms/step - loss: 0.1565
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2979
48/56 [========================>.....] - ETA: 0s - loss: 0.1238
56/56 [==============================] - 0s 1ms/step - loss: 0.1422
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0236
48/56 [========================>.....] - ETA: 0s - loss: 0.1375
56/56 [==============================] - 0s 1ms/step - loss: 0.1308
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1299
45/56 [=======================>......] - ETA: 0s - loss: 0.1436
56/56 [==============================] - 0s 1ms/step - loss: 0.1321
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0366
42/56 [=====================>........] - ETA: 0s - loss: 0.1283
56/56 [==============================] - 0s 1ms/step - loss: 0.1240
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0056
42/56 [=====================>........] - ETA: 0s - loss: 0.1321
56/56 [==============================] - 0s 1ms/step - loss: 0.1255
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0895
48/56 [========================>.....] - ETA: 0s - loss: 0.1149
56/56 [==============================] - 0s 1ms/step - loss: 0.1215
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0186
48/56 [========================>.....] - ETA: 0s - loss: 0.1333
56/56 [==============================] - 0s 1ms/step - loss: 0.1278
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2715
48/56 [========================>.....] - ETA: 0s - loss: 0.1212
56/56 [==============================] - 0s 1ms/step - loss: 0.1256
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0270
40/56 [====================>.........] - ETA: 0s - loss: 0.1169
56/56 [==============================] - 0s 1ms/step - loss: 0.1212
-> test with GAN.predict
GAN tn, fp: 132, 5
GAN fn, tp: 2, 4
GAN f1 score: 0.533
GAN cohens kappa score: 0.509

-> test with 'LR'
LR tn, fp: 132, 5
LR fn, tp: 2, 4
LR f1 score: 0.533
LR cohens kappa score: 0.509
LR average precision score: 0.605

-> test with 'RF'
RF tn, fp: 135, 2
RF fn, tp: 4, 2
RF f1 score: 0.400
RF cohens kappa score: 0.379

-> test with 'GB'
GB tn, fp: 135, 2
GB fn, tp: 4, 2
GB f1 score: 0.400
GB cohens kappa score: 0.379

-> test with 'KNN'
KNN tn, fp: 136, 1
KNN fn, tp: 4, 2
KNN f1 score: 0.444
KNN cohens kappa score: 0.428


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

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 9s - loss: 0.0417
44/56 [======================>.......] - ETA: 0s - loss: 0.1535
56/56 [==============================] - 0s 1ms/step - loss: 0.1375
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0689
44/56 [======================>.......] - ETA: 0s - loss: 0.1556
56/56 [==============================] - 0s 1ms/step - loss: 0.1329
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2138
41/56 [====================>.........] - ETA: 0s - loss: 0.1403
56/56 [==============================] - 0s 1ms/step - loss: 0.1246
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1691
39/56 [===================>..........] - ETA: 0s - loss: 0.1116
56/56 [==============================] - 0s 1ms/step - loss: 0.1125
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0829
45/56 [=======================>......] - ETA: 0s - loss: 0.1158
56/56 [==============================] - 0s 1ms/step - loss: 0.1096
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.4549
46/56 [=======================>......] - ETA: 0s - loss: 0.1191
56/56 [==============================] - 0s 1ms/step - loss: 0.1105
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0021
47/56 [========================>.....] - ETA: 0s - loss: 0.0909
56/56 [==============================] - 0s 1ms/step - loss: 0.1086
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0792
38/56 [===================>..........] - ETA: 0s - loss: 0.0991
56/56 [==============================] - 0s 1ms/step - loss: 0.1026
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1227
34/56 [=================>............] - ETA: 0s - loss: 0.1093
56/56 [==============================] - 0s 2ms/step - loss: 0.0983
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1169
39/56 [===================>..........] - ETA: 0s - loss: 0.1060
56/56 [==============================] - 0s 1ms/step - loss: 0.1043
-> test with GAN.predict
GAN tn, fp: 133, 5
GAN fn, tp: 3, 6
GAN f1 score: 0.600
GAN cohens kappa score: 0.571

-> test with 'LR'
LR tn, fp: 129, 9
LR fn, tp: 3, 6
LR f1 score: 0.500
LR cohens kappa score: 0.459
LR average precision score: 0.673

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.163

-> test with 'GB'
GB tn, fp: 137, 1
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.012

-> test with 'KNN'
KNN tn, fp: 136, 2
KNN fn, tp: 9, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.023


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 9s - loss: 0.1101
47/56 [========================>.....] - ETA: 0s - loss: 0.1145
56/56 [==============================] - 0s 1ms/step - loss: 0.1199
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 6.1767e-04
48/56 [========================>.....] - ETA: 0s - loss: 0.1115    
56/56 [==============================] - 0s 1ms/step - loss: 0.1153
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0036
45/56 [=======================>......] - ETA: 0s - loss: 0.1088
56/56 [==============================] - 0s 1ms/step - loss: 0.1053
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1091
47/56 [========================>.....] - ETA: 0s - loss: 0.1036
56/56 [==============================] - 0s 1ms/step - loss: 0.1027
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0317
47/56 [========================>.....] - ETA: 0s - loss: 0.1028
56/56 [==============================] - 0s 1ms/step - loss: 0.1002
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0429
48/56 [========================>.....] - ETA: 0s - loss: 0.1066
56/56 [==============================] - 0s 1ms/step - loss: 0.0971
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0239
42/56 [=====================>........] - ETA: 0s - loss: 0.0986
56/56 [==============================] - 0s 1ms/step - loss: 0.0940
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0875
42/56 [=====================>........] - ETA: 0s - loss: 0.0913
56/56 [==============================] - 0s 1ms/step - loss: 0.0932
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1594
48/56 [========================>.....] - ETA: 0s - loss: 0.0855
56/56 [==============================] - 0s 1ms/step - loss: 0.0914
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0490
49/56 [=========================>....] - ETA: 0s - loss: 0.0857
56/56 [==============================] - 0s 1ms/step - loss: 0.0907
-> test with GAN.predict
GAN tn, fp: 137, 1
GAN fn, tp: 4, 5
GAN f1 score: 0.667
GAN cohens kappa score: 0.649

-> test with 'LR'
LR tn, fp: 130, 8
LR fn, tp: 2, 7
LR f1 score: 0.583
LR cohens kappa score: 0.549
LR average precision score: 0.685

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 7, 2
RF f1 score: 0.333
RF cohens kappa score: 0.312

-> test with 'GB'
GB tn, fp: 137, 1
GB fn, tp: 6, 3
GB f1 score: 0.462
GB cohens kappa score: 0.440

-> test with 'KNN'
KNN tn, fp: 137, 1
KNN fn, tp: 8, 1
KNN f1 score: 0.182
KNN cohens kappa score: 0.163


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 10s - loss: 0.0077
46/56 [=======================>......] - ETA: 0s - loss: 0.1026 
56/56 [==============================] - 0s 1ms/step - loss: 0.0991
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0151
45/56 [=======================>......] - ETA: 0s - loss: 0.0844
56/56 [==============================] - 0s 1ms/step - loss: 0.0845
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1920
46/56 [=======================>......] - ETA: 0s - loss: 0.0893
56/56 [==============================] - 0s 1ms/step - loss: 0.0875
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0223
48/56 [========================>.....] - ETA: 0s - loss: 0.0785
56/56 [==============================] - 0s 1ms/step - loss: 0.0779
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1164
46/56 [=======================>......] - ETA: 0s - loss: 0.0847
56/56 [==============================] - 0s 1ms/step - loss: 0.0805
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0463
47/56 [========================>.....] - ETA: 0s - loss: 0.0780
56/56 [==============================] - 0s 1ms/step - loss: 0.0797
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0264
47/56 [========================>.....] - ETA: 0s - loss: 0.0849
56/56 [==============================] - 0s 1ms/step - loss: 0.0818
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.6580
47/56 [========================>.....] - ETA: 0s - loss: 0.0775
56/56 [==============================] - 0s 1ms/step - loss: 0.0808
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0053
47/56 [========================>.....] - ETA: 0s - loss: 0.0813
56/56 [==============================] - 0s 1ms/step - loss: 0.0794
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0067
48/56 [========================>.....] - ETA: 0s - loss: 0.0761
56/56 [==============================] - 0s 1ms/step - loss: 0.0783
-> test with GAN.predict
GAN tn, fp: 135, 3
GAN fn, tp: 6, 3
GAN f1 score: 0.400
GAN cohens kappa score: 0.369

-> test with 'LR'
LR tn, fp: 130, 8
LR fn, tp: 4, 5
LR f1 score: 0.455
LR cohens kappa score: 0.412
LR average precision score: 0.539

-> test with 'RF'
RF tn, fp: 135, 3
RF fn, tp: 7, 2
RF f1 score: 0.286
RF cohens kappa score: 0.253

-> test with 'GB'
GB tn, fp: 135, 3
GB fn, tp: 8, 1
GB f1 score: 0.154
GB cohens kappa score: 0.121

-> test with 'KNN'
KNN tn, fp: 136, 2
KNN fn, tp: 8, 1
KNN f1 score: 0.167
KNN cohens kappa score: 0.140


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 518 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 7s - loss: 0.0500
47/56 [========================>.....] - ETA: 0s - loss: 0.1273
56/56 [==============================] - 0s 1ms/step - loss: 0.1248
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0014
48/56 [========================>.....] - ETA: 0s - loss: 0.1137
56/56 [==============================] - 0s 1ms/step - loss: 0.1125
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0916
43/56 [======================>.......] - ETA: 0s - loss: 0.0994
56/56 [==============================] - 0s 1ms/step - loss: 0.1064
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0140
39/56 [===================>..........] - ETA: 0s - loss: 0.1118
56/56 [==============================] - 0s 1ms/step - loss: 0.0960
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0271
42/56 [=====================>........] - ETA: 0s - loss: 0.0984
56/56 [==============================] - 0s 1ms/step - loss: 0.0936
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.0046
47/56 [========================>.....] - ETA: 0s - loss: 0.1082
56/56 [==============================] - 0s 1ms/step - loss: 0.1015
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0142
47/56 [========================>.....] - ETA: 0s - loss: 0.1019
56/56 [==============================] - 0s 1ms/step - loss: 0.0894
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0077
47/56 [========================>.....] - ETA: 0s - loss: 0.0754
56/56 [==============================] - 0s 1ms/step - loss: 0.0880
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0993
46/56 [=======================>......] - ETA: 0s - loss: 0.0861
56/56 [==============================] - 0s 1ms/step - loss: 0.0894
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1911
48/56 [========================>.....] - ETA: 0s - loss: 0.0830
56/56 [==============================] - 0s 1ms/step - loss: 0.0867
-> test with GAN.predict
GAN tn, fp: 136, 2
GAN fn, tp: 3, 6
GAN f1 score: 0.706
GAN cohens kappa score: 0.688

-> test with 'LR'
LR tn, fp: 132, 6
LR fn, tp: 1, 8
LR f1 score: 0.696
LR cohens kappa score: 0.671
LR average precision score: 0.908

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 7, 2
RF f1 score: 0.333
RF cohens kappa score: 0.312

-> test with 'GB'
GB tn, fp: 137, 1
GB fn, tp: 7, 2
GB f1 score: 0.333
GB cohens kappa score: 0.312

-> test with 'KNN'
KNN tn, fp: 136, 2
KNN fn, tp: 7, 2
KNN f1 score: 0.308
KNN cohens kappa score: 0.281


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 516 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/56 [..............................] - ETA: 7s - loss: 0.0067
47/56 [========================>.....] - ETA: 0s - loss: 0.1300
56/56 [==============================] - 0s 1ms/step - loss: 0.1364
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.0302
48/56 [========================>.....] - ETA: 0s - loss: 0.1247
56/56 [==============================] - 0s 1ms/step - loss: 0.1246
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0013
48/56 [========================>.....] - ETA: 0s - loss: 0.1002
56/56 [==============================] - 0s 1ms/step - loss: 0.1134
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0203
47/56 [========================>.....] - ETA: 0s - loss: 0.1128
56/56 [==============================] - 0s 1ms/step - loss: 0.1088
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0516
48/56 [========================>.....] - ETA: 0s - loss: 0.0919
56/56 [==============================] - 0s 1ms/step - loss: 0.0942
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.4339
48/56 [========================>.....] - ETA: 0s - loss: 0.1026
56/56 [==============================] - 0s 1ms/step - loss: 0.0920
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0532
42/56 [=====================>........] - ETA: 0s - loss: 0.0910
56/56 [==============================] - 0s 1ms/step - loss: 0.0897
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.0072
48/56 [========================>.....] - ETA: 0s - loss: 0.0983
56/56 [==============================] - 0s 1ms/step - loss: 0.0921
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0026
49/56 [=========================>....] - ETA: 0s - loss: 0.0840
56/56 [==============================] - 0s 1ms/step - loss: 0.0884
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.0122
48/56 [========================>.....] - ETA: 0s - loss: 0.0905
56/56 [==============================] - 0s 1ms/step - loss: 0.0899
-> test with GAN.predict
GAN tn, fp: 135, 2
GAN fn, tp: 2, 4
GAN f1 score: 0.667
GAN cohens kappa score: 0.652

-> test with 'LR'
LR tn, fp: 132, 5
LR fn, tp: 1, 5
LR f1 score: 0.625
LR cohens kappa score: 0.604
LR average precision score: 0.821

-> test with 'RF'
RF tn, fp: 136, 1
RF fn, tp: 3, 3
RF f1 score: 0.600
RF cohens kappa score: 0.586

-> test with 'GB'
GB tn, fp: 137, 0
GB fn, tp: 4, 2
GB f1 score: 0.500
GB cohens kappa score: 0.489

-> test with 'KNN'
KNN tn, fp: 137, 0
KNN fn, tp: 5, 1
KNN f1 score: 0.286
KNN cohens kappa score: 0.277

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 134, 16
LR fn, tp: 5, 9
LR f1 score: 0.818
LR cohens kappa score: 0.804
LR average precision score: 0.918


average:
LR tn, fp: 130.96, 6.84
LR fn, tp: 2.28, 6.12
LR f1 score: 0.574
LR cohens kappa score: 0.543
LR average precision score: 0.680


minimum:
LR tn, fp: 122, 3
LR fn, tp: 0, 4
LR f1 score: 0.381
LR cohens kappa score: 0.334
LR average precision score: 0.447


-----[ RF ]-----
maximum:
RF tn, fp: 138, 5
RF fn, tp: 8, 4
RF f1 score: 0.667
RF cohens kappa score: 0.657


average:
RF tn, fp: 136.28, 1.52
RF fn, tp: 6.24, 2.16
RF f1 score: 0.359
RF cohens kappa score: 0.337


minimum:
RF tn, fp: 133, 0
RF fn, tp: 3, 1
RF f1 score: 0.154
RF cohens kappa score: 0.121


-----[ GB ]-----
maximum:
GB tn, fp: 138, 8
GB fn, tp: 9, 4
GB f1 score: 0.500
GB cohens kappa score: 0.489


average:
GB tn, fp: 135.44, 2.36
GB fn, tp: 6.4, 2.0
GB f1 score: 0.318
GB cohens kappa score: 0.292


minimum:
GB tn, fp: 130, 0
GB fn, tp: 4, 0
GB f1 score: 0.000
GB cohens kappa score: -0.012


-----[ KNN ]-----
maximum:
KNN tn, fp: 138, 3
KNN fn, tp: 9, 4
KNN f1 score: 0.615
KNN cohens kappa score: 0.600


average:
KNN tn, fp: 136.76, 1.04
KNN fn, tp: 7.52, 0.88
KNN f1 score: 0.165
KNN cohens kappa score: 0.149


minimum:
KNN tn, fp: 135, 0
KNN fn, tp: 4, 0
KNN f1 score: 0.000
KNN cohens kappa score: -0.032


-----[ GAN ]-----
maximum:
GAN tn, fp: 137, 5
GAN fn, tp: 6, 8
GAN f1 score: 0.778
GAN cohens kappa score: 0.763


average:
GAN tn, fp: 135.08, 2.72
GAN fn, tp: 4.08, 4.32
GAN f1 score: 0.549
GAN cohens kappa score: 0.525


minimum:
GAN tn, fp: 132, 1
GAN fn, tp: 1, 2
GAN f1 score: 0.375
GAN cohens kappa score: 0.340