ConvGeNBenchmarkResults/data_result/ConvGeN-majority-5/folding_abalone9-18.log

///////////////////////////////////////////
// Running convGAN-majority-5 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: 0.4869
49/56 [=========================>....] - ETA: 0s - loss: 0.2776
56/56 [==============================] - 0s 1ms/step - loss: 0.2772
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2111
49/56 [=========================>....] - ETA: 0s - loss: 0.2653
56/56 [==============================] - 0s 1ms/step - loss: 0.2676
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1532
50/56 [=========================>....] - ETA: 0s - loss: 0.2611
56/56 [==============================] - 0s 1ms/step - loss: 0.2649
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1731
50/56 [=========================>....] - ETA: 0s - loss: 0.2623
56/56 [==============================] - 0s 1ms/step - loss: 0.2629
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2847
50/56 [=========================>....] - ETA: 0s - loss: 0.2604
56/56 [==============================] - 0s 1ms/step - loss: 0.2568
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1675
50/56 [=========================>....] - ETA: 0s - loss: 0.2485
56/56 [==============================] - 0s 1ms/step - loss: 0.2528
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1627
49/56 [=========================>....] - ETA: 0s - loss: 0.2533
56/56 [==============================] - 0s 1ms/step - loss: 0.2479
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2107
50/56 [=========================>....] - ETA: 0s - loss: 0.2452
56/56 [==============================] - 0s 1ms/step - loss: 0.2473
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2453
46/56 [=======================>......] - ETA: 0s - loss: 0.2359
56/56 [==============================] - 0s 1ms/step - loss: 0.2414
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.3505
44/56 [======================>.......] - ETA: 0s - loss: 0.2388
56/56 [==============================] - 0s 1ms/step - loss: 0.2370
-> test with GAN.predict
GAN tn, fp: 122, 16
GAN fn, tp: 0, 9
GAN f1 score: 0.529
GAN cohens kappa score: 0.483

-> 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: 0.904

-> 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: 136, 2
GB fn, tp: 5, 4
GB f1 score: 0.533
GB cohens kappa score: 0.509

-> test with 'KNN'
KNN tn, fp: 121, 17
KNN fn, tp: 4, 5
KNN f1 score: 0.323
KNN cohens kappa score: 0.258


------ 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: 0.1805
49/56 [=========================>....] - ETA: 0s - loss: 0.2067
56/56 [==============================] - 0s 1ms/step - loss: 0.2039
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2280
49/56 [=========================>....] - ETA: 0s - loss: 0.1972
56/56 [==============================] - 0s 1ms/step - loss: 0.2008
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1480
49/56 [=========================>....] - ETA: 0s - loss: 0.1990
56/56 [==============================] - 0s 1ms/step - loss: 0.1996
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.2114
43/56 [======================>.......] - ETA: 0s - loss: 0.1916
56/56 [==============================] - 0s 1ms/step - loss: 0.1949
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1629
44/56 [======================>.......] - ETA: 0s - loss: 0.1947
56/56 [==============================] - 0s 1ms/step - loss: 0.1936
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1718
49/56 [=========================>....] - ETA: 0s - loss: 0.1905
56/56 [==============================] - 0s 1ms/step - loss: 0.1896
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0878
49/56 [=========================>....] - ETA: 0s - loss: 0.1811
56/56 [==============================] - 0s 1ms/step - loss: 0.1867
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2054
49/56 [=========================>....] - ETA: 0s - loss: 0.1816
56/56 [==============================] - 0s 1ms/step - loss: 0.1835
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2872
49/56 [=========================>....] - ETA: 0s - loss: 0.1843
56/56 [==============================] - 0s 1ms/step - loss: 0.1820
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2721
49/56 [=========================>....] - ETA: 0s - loss: 0.1805
56/56 [==============================] - 0s 1ms/step - loss: 0.1810
-> test with GAN.predict
GAN tn, fp: 133, 5
GAN fn, tp: 4, 5
GAN f1 score: 0.526
GAN cohens kappa score: 0.494

-> 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: 0.542

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

-> 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: 118, 20
KNN fn, tp: 3, 6
KNN f1 score: 0.343
KNN cohens kappa score: 0.277


------ 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: 8s - loss: 0.2096
48/56 [========================>.....] - ETA: 0s - loss: 0.2957
56/56 [==============================] - 0s 1ms/step - loss: 0.2953
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2847
49/56 [=========================>....] - ETA: 0s - loss: 0.2897
56/56 [==============================] - 0s 1ms/step - loss: 0.2891
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2916
49/56 [=========================>....] - ETA: 0s - loss: 0.2895
56/56 [==============================] - 0s 1ms/step - loss: 0.2882
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3154
49/56 [=========================>....] - ETA: 0s - loss: 0.2821
56/56 [==============================] - 0s 1ms/step - loss: 0.2801
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.3465
50/56 [=========================>....] - ETA: 0s - loss: 0.2631
56/56 [==============================] - 0s 1ms/step - loss: 0.2719
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.3326
49/56 [=========================>....] - ETA: 0s - loss: 0.2725
56/56 [==============================] - 0s 1ms/step - loss: 0.2714
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.3734
50/56 [=========================>....] - ETA: 0s - loss: 0.2645
56/56 [==============================] - 0s 1ms/step - loss: 0.2661
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.3035
49/56 [=========================>....] - ETA: 0s - loss: 0.2613
56/56 [==============================] - 0s 1ms/step - loss: 0.2605
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2569
49/56 [=========================>....] - ETA: 0s - loss: 0.2605
56/56 [==============================] - 0s 1ms/step - loss: 0.2582
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2691
45/56 [=======================>......] - ETA: 0s - loss: 0.2567
56/56 [==============================] - 0s 1ms/step - loss: 0.2539
-> test with GAN.predict
GAN tn, fp: 129, 9
GAN fn, tp: 2, 7
GAN f1 score: 0.560
GAN cohens kappa score: 0.523

-> test with 'LR'
LR tn, fp: 129, 9
LR fn, tp: 0, 9
LR f1 score: 0.667
LR cohens kappa score: 0.637
LR average precision score: 0.833

-> 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: 133, 5
GB fn, tp: 5, 4
GB f1 score: 0.444
GB cohens kappa score: 0.408

-> test with 'KNN'
KNN tn, fp: 132, 6
KNN fn, tp: 4, 5
KNN f1 score: 0.500
KNN cohens kappa score: 0.464


------ 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: 0.1894
44/56 [======================>.......] - ETA: 0s - loss: 0.2681
56/56 [==============================] - 0s 1ms/step - loss: 0.2587
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.3740
45/56 [=======================>......] - ETA: 0s - loss: 0.2545
56/56 [==============================] - 0s 1ms/step - loss: 0.2518
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3541
49/56 [=========================>....] - ETA: 0s - loss: 0.2506
56/56 [==============================] - 0s 1ms/step - loss: 0.2479
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3100
49/56 [=========================>....] - ETA: 0s - loss: 0.2434
56/56 [==============================] - 0s 1ms/step - loss: 0.2450
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2297
49/56 [=========================>....] - ETA: 0s - loss: 0.2524
56/56 [==============================] - 0s 1ms/step - loss: 0.2478
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1240
49/56 [=========================>....] - ETA: 0s - loss: 0.2449
56/56 [==============================] - 0s 1ms/step - loss: 0.2404
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2424
49/56 [=========================>....] - ETA: 0s - loss: 0.2351
56/56 [==============================] - 0s 1ms/step - loss: 0.2379
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.4393
49/56 [=========================>....] - ETA: 0s - loss: 0.2471
56/56 [==============================] - 0s 1ms/step - loss: 0.2355
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.5742
49/56 [=========================>....] - ETA: 0s - loss: 0.2322
56/56 [==============================] - 0s 1ms/step - loss: 0.2319
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2757
49/56 [=========================>....] - ETA: 0s - loss: 0.2280
56/56 [==============================] - 0s 1ms/step - loss: 0.2292
-> test with GAN.predict
GAN tn, fp: 128, 10
GAN fn, tp: 2, 7
GAN f1 score: 0.538
GAN cohens kappa score: 0.498

-> test with 'LR'
LR tn, fp: 127, 11
LR fn, tp: 2, 7
LR f1 score: 0.519
LR cohens kappa score: 0.476
LR average precision score: 0.527

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

-> test with 'GB'
GB tn, fp: 134, 4
GB fn, tp: 5, 4
GB f1 score: 0.471
GB cohens kappa score: 0.438

-> test with 'KNN'
KNN tn, fp: 123, 15
KNN fn, tp: 2, 7
KNN f1 score: 0.452
KNN cohens kappa score: 0.399


------ 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: 0.1948
49/56 [=========================>....] - ETA: 0s - loss: 0.2131
56/56 [==============================] - 0s 1ms/step - loss: 0.2126
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2389
49/56 [=========================>....] - ETA: 0s - loss: 0.2137
56/56 [==============================] - 0s 1ms/step - loss: 0.2109
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1808
45/56 [=======================>......] - ETA: 0s - loss: 0.2127
56/56 [==============================] - 0s 1ms/step - loss: 0.2089
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1522
49/56 [=========================>....] - ETA: 0s - loss: 0.2062
56/56 [==============================] - 0s 1ms/step - loss: 0.2081
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1189
49/56 [=========================>....] - ETA: 0s - loss: 0.2167
56/56 [==============================] - 0s 1ms/step - loss: 0.2123
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1892
46/56 [=======================>......] - ETA: 0s - loss: 0.2048
56/56 [==============================] - 0s 1ms/step - loss: 0.2108
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.0819
44/56 [======================>.......] - ETA: 0s - loss: 0.2195
56/56 [==============================] - 0s 1ms/step - loss: 0.2077
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2557
43/56 [======================>.......] - ETA: 0s - loss: 0.2074
56/56 [==============================] - 0s 1ms/step - loss: 0.2043
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2056
49/56 [=========================>....] - ETA: 0s - loss: 0.1931
56/56 [==============================] - 0s 1ms/step - loss: 0.2011
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1267
49/56 [=========================>....] - ETA: 0s - loss: 0.1935
56/56 [==============================] - 0s 1ms/step - loss: 0.2017
-> test with GAN.predict
GAN tn, fp: 128, 9
GAN fn, tp: 2, 4
GAN f1 score: 0.421
GAN cohens kappa score: 0.386

-> test with 'LR'
LR tn, fp: 126, 11
LR fn, tp: 1, 5
LR f1 score: 0.455
LR cohens kappa score: 0.419
LR average precision score: 0.487

-> 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: 134, 3
GB fn, tp: 4, 2
GB f1 score: 0.364
GB cohens kappa score: 0.338

-> test with 'KNN'
KNN tn, fp: 127, 10
KNN fn, tp: 2, 4
KNN f1 score: 0.400
KNN cohens kappa score: 0.363


====== 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: 0.2823
48/56 [========================>.....] - ETA: 0s - loss: 0.2177
56/56 [==============================] - 0s 1ms/step - loss: 0.2159
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1172
49/56 [=========================>....] - ETA: 0s - loss: 0.2090
56/56 [==============================] - 0s 1ms/step - loss: 0.2115
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1311
49/56 [=========================>....] - ETA: 0s - loss: 0.2055
56/56 [==============================] - 0s 1ms/step - loss: 0.2058
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1218
49/56 [=========================>....] - ETA: 0s - loss: 0.2070
56/56 [==============================] - 0s 1ms/step - loss: 0.2031
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1554
49/56 [=========================>....] - ETA: 0s - loss: 0.2075
56/56 [==============================] - 0s 1ms/step - loss: 0.2047
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.2930
49/56 [=========================>....] - ETA: 0s - loss: 0.2038
56/56 [==============================] - 0s 1ms/step - loss: 0.2022
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1820
49/56 [=========================>....] - ETA: 0s - loss: 0.1926
56/56 [==============================] - 0s 1ms/step - loss: 0.2015
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1776
49/56 [=========================>....] - ETA: 0s - loss: 0.1995
56/56 [==============================] - 0s 1ms/step - loss: 0.1975
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.3999
49/56 [=========================>....] - ETA: 0s - loss: 0.1975
56/56 [==============================] - 0s 1ms/step - loss: 0.1973
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2655
49/56 [=========================>....] - ETA: 0s - loss: 0.1965
56/56 [==============================] - 0s 1ms/step - loss: 0.1990
-> test with GAN.predict
GAN tn, fp: 130, 8
GAN fn, tp: 3, 6
GAN f1 score: 0.522
GAN cohens kappa score: 0.483

-> test with 'LR'
LR tn, fp: 123, 15
LR fn, tp: 1, 8
LR f1 score: 0.500
LR cohens kappa score: 0.452
LR average precision score: 0.674

-> test with 'RF'
RF tn, fp: 137, 1
RF fn, tp: 5, 4
RF f1 score: 0.571
RF cohens kappa score: 0.552

-> test with 'GB'
GB tn, fp: 136, 2
GB fn, tp: 5, 4
GB f1 score: 0.533
GB cohens kappa score: 0.509

-> test with 'KNN'
KNN tn, fp: 124, 14
KNN fn, tp: 4, 5
KNN f1 score: 0.357
KNN cohens kappa score: 0.299


------ 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: 7s - loss: 0.3289
48/56 [========================>.....] - ETA: 0s - loss: 0.2426
56/56 [==============================] - 0s 1ms/step - loss: 0.2478
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2444
49/56 [=========================>....] - ETA: 0s - loss: 0.2460
56/56 [==============================] - 0s 1ms/step - loss: 0.2447
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2242
48/56 [========================>.....] - ETA: 0s - loss: 0.2425
56/56 [==============================] - 0s 1ms/step - loss: 0.2376
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3313
49/56 [=========================>....] - ETA: 0s - loss: 0.2353
56/56 [==============================] - 0s 1ms/step - loss: 0.2354
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.4224
49/56 [=========================>....] - ETA: 0s - loss: 0.2338
56/56 [==============================] - 0s 1ms/step - loss: 0.2344
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.2022
49/56 [=========================>....] - ETA: 0s - loss: 0.2407
56/56 [==============================] - 0s 1ms/step - loss: 0.2324
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1955
49/56 [=========================>....] - ETA: 0s - loss: 0.2363
56/56 [==============================] - 0s 1ms/step - loss: 0.2309
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2251
49/56 [=========================>....] - ETA: 0s - loss: 0.2213
56/56 [==============================] - 0s 1ms/step - loss: 0.2246
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2772
49/56 [=========================>....] - ETA: 0s - loss: 0.2323
56/56 [==============================] - 0s 1ms/step - loss: 0.2289
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1817
49/56 [=========================>....] - ETA: 0s - loss: 0.2184
56/56 [==============================] - 0s 1ms/step - loss: 0.2211
-> test with GAN.predict
GAN tn, fp: 129, 9
GAN fn, tp: 3, 6
GAN f1 score: 0.500
GAN cohens kappa score: 0.459

-> test with 'LR'
LR tn, fp: 130, 8
LR fn, tp: 1, 8
LR f1 score: 0.640
LR cohens kappa score: 0.609
LR average precision score: 0.771

-> 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: 135, 3
GB fn, tp: 6, 3
GB f1 score: 0.400
GB cohens kappa score: 0.369

-> test with 'KNN'
KNN tn, fp: 127, 11
KNN fn, tp: 4, 5
KNN f1 score: 0.400
KNN cohens kappa score: 0.349


------ 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: 8s - loss: 0.2337
49/56 [=========================>....] - ETA: 0s - loss: 0.2623
56/56 [==============================] - 0s 1ms/step - loss: 0.2560
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1773
47/56 [========================>.....] - ETA: 0s - loss: 0.2522
56/56 [==============================] - 0s 1ms/step - loss: 0.2477
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2557
47/56 [========================>.....] - ETA: 0s - loss: 0.2394
56/56 [==============================] - 0s 1ms/step - loss: 0.2453
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1866
49/56 [=========================>....] - ETA: 0s - loss: 0.2421
56/56 [==============================] - 0s 1ms/step - loss: 0.2442
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2548
49/56 [=========================>....] - ETA: 0s - loss: 0.2468
56/56 [==============================] - 0s 1ms/step - loss: 0.2376
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.2494
49/56 [=========================>....] - ETA: 0s - loss: 0.2467
56/56 [==============================] - 0s 1ms/step - loss: 0.2469
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.4434
49/56 [=========================>....] - ETA: 0s - loss: 0.2214
56/56 [==============================] - 0s 1ms/step - loss: 0.2334
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2234
49/56 [=========================>....] - ETA: 0s - loss: 0.2325
56/56 [==============================] - 0s 1ms/step - loss: 0.2364
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2813
49/56 [=========================>....] - ETA: 0s - loss: 0.2300
56/56 [==============================] - 0s 1ms/step - loss: 0.2309
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1461
49/56 [=========================>....] - ETA: 0s - loss: 0.2229
56/56 [==============================] - 0s 1ms/step - loss: 0.2237
-> test with GAN.predict
GAN tn, fp: 123, 15
GAN fn, tp: 2, 7
GAN f1 score: 0.452
GAN cohens kappa score: 0.399

-> 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: 0.703

-> test with 'RF'
RF tn, fp: 131, 7
RF fn, tp: 8, 1
RF f1 score: 0.118
RF cohens kappa score: 0.064

-> test with 'GB'
GB tn, fp: 128, 10
GB fn, tp: 6, 3
GB f1 score: 0.273
GB cohens kappa score: 0.216

-> test with 'KNN'
KNN tn, fp: 118, 20
KNN fn, tp: 2, 7
KNN f1 score: 0.389
KNN cohens kappa score: 0.327


------ 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: 0.3131
49/56 [=========================>....] - ETA: 0s - loss: 0.2435
56/56 [==============================] - 0s 1ms/step - loss: 0.2411
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2496
50/56 [=========================>....] - ETA: 0s - loss: 0.2356
56/56 [==============================] - 0s 1ms/step - loss: 0.2349
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2542
43/56 [======================>.......] - ETA: 0s - loss: 0.2344
56/56 [==============================] - 0s 1ms/step - loss: 0.2285
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.2558
44/56 [======================>.......] - ETA: 0s - loss: 0.2301
56/56 [==============================] - 0s 1ms/step - loss: 0.2279
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0984
49/56 [=========================>....] - ETA: 0s - loss: 0.2368
56/56 [==============================] - 0s 1ms/step - loss: 0.2295
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.3452
49/56 [=========================>....] - ETA: 0s - loss: 0.2197
56/56 [==============================] - 0s 1ms/step - loss: 0.2213
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1540
49/56 [=========================>....] - ETA: 0s - loss: 0.2279
56/56 [==============================] - 0s 1ms/step - loss: 0.2198
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1208
50/56 [=========================>....] - ETA: 0s - loss: 0.2182
56/56 [==============================] - 0s 1ms/step - loss: 0.2186
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2182
49/56 [=========================>....] - ETA: 0s - loss: 0.2195
56/56 [==============================] - 0s 1ms/step - loss: 0.2135
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1164
46/56 [=======================>......] - ETA: 0s - loss: 0.2148
56/56 [==============================] - 0s 1ms/step - loss: 0.2174
-> test with GAN.predict
GAN tn, fp: 122, 16
GAN fn, tp: 1, 8
GAN f1 score: 0.485
GAN cohens kappa score: 0.434

-> test with 'LR'
LR tn, fp: 125, 13
LR fn, tp: 1, 8
LR f1 score: 0.533
LR cohens kappa score: 0.490
LR average precision score: 0.690

-> test with 'RF'
RF tn, fp: 132, 6
RF fn, tp: 7, 2
RF f1 score: 0.235
RF cohens kappa score: 0.189

-> test with 'GB'
GB tn, fp: 132, 6
GB fn, tp: 5, 4
GB f1 score: 0.421
GB cohens kappa score: 0.381

-> test with 'KNN'
KNN tn, fp: 121, 17
KNN fn, tp: 3, 6
KNN f1 score: 0.375
KNN cohens kappa score: 0.315


------ 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: 7s - loss: 0.1634
45/56 [=======================>......] - ETA: 0s - loss: 0.2322
56/56 [==============================] - 0s 1ms/step - loss: 0.2320
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2844
48/56 [========================>.....] - ETA: 0s - loss: 0.2310
56/56 [==============================] - 0s 1ms/step - loss: 0.2272
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2126
49/56 [=========================>....] - ETA: 0s - loss: 0.2160
56/56 [==============================] - 0s 1ms/step - loss: 0.2242
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3932
49/56 [=========================>....] - ETA: 0s - loss: 0.2236
56/56 [==============================] - 0s 1ms/step - loss: 0.2302
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1848
49/56 [=========================>....] - ETA: 0s - loss: 0.2262
56/56 [==============================] - 0s 1ms/step - loss: 0.2250
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1495
49/56 [=========================>....] - ETA: 0s - loss: 0.2131
56/56 [==============================] - 0s 1ms/step - loss: 0.2194
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1908
49/56 [=========================>....] - ETA: 0s - loss: 0.2178
56/56 [==============================] - 0s 1ms/step - loss: 0.2171
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2610
49/56 [=========================>....] - ETA: 0s - loss: 0.2062
56/56 [==============================] - 0s 1ms/step - loss: 0.2114
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0862
46/56 [=======================>......] - ETA: 0s - loss: 0.2082
56/56 [==============================] - 0s 1ms/step - loss: 0.2107
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.3257
49/56 [=========================>....] - ETA: 0s - loss: 0.2119
56/56 [==============================] - 0s 1ms/step - loss: 0.2086
-> test with GAN.predict
GAN tn, fp: 123, 14
GAN fn, tp: 2, 4
GAN f1 score: 0.333
GAN cohens kappa score: 0.289

-> test with 'LR'
LR tn, fp: 128, 9
LR fn, tp: 1, 5
LR f1 score: 0.500
LR cohens kappa score: 0.469
LR average precision score: 0.569

-> test with 'RF'
RF tn, fp: 134, 3
RF fn, tp: 3, 3
RF f1 score: 0.500
RF cohens kappa score: 0.478

-> test with 'GB'
GB tn, fp: 129, 8
GB fn, tp: 3, 3
GB f1 score: 0.353
GB cohens kappa score: 0.316

-> test with 'KNN'
KNN tn, fp: 122, 15
KNN fn, tp: 2, 4
KNN f1 score: 0.320
KNN cohens kappa score: 0.274


====== 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: 8s - loss: 0.4693
48/56 [========================>.....] - ETA: 0s - loss: 0.2399
56/56 [==============================] - 0s 1ms/step - loss: 0.2309
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.3355
50/56 [=========================>....] - ETA: 0s - loss: 0.2339
56/56 [==============================] - 0s 1ms/step - loss: 0.2294
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3396
49/56 [=========================>....] - ETA: 0s - loss: 0.2226
56/56 [==============================] - 0s 1ms/step - loss: 0.2244
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1729
49/56 [=========================>....] - ETA: 0s - loss: 0.2170
56/56 [==============================] - 0s 1ms/step - loss: 0.2238
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2593
49/56 [=========================>....] - ETA: 0s - loss: 0.2163
56/56 [==============================] - 0s 1ms/step - loss: 0.2200
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1646
49/56 [=========================>....] - ETA: 0s - loss: 0.2127
56/56 [==============================] - 0s 1ms/step - loss: 0.2185
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2795
50/56 [=========================>....] - ETA: 0s - loss: 0.2225
56/56 [==============================] - 0s 1ms/step - loss: 0.2203
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1799
49/56 [=========================>....] - ETA: 0s - loss: 0.2155
56/56 [==============================] - 0s 1ms/step - loss: 0.2147
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2327
49/56 [=========================>....] - ETA: 0s - loss: 0.2132
56/56 [==============================] - 0s 1ms/step - loss: 0.2145
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.3673
49/56 [=========================>....] - ETA: 0s - loss: 0.2136
56/56 [==============================] - 0s 1ms/step - loss: 0.2105
-> test with GAN.predict
GAN tn, fp: 121, 17
GAN fn, tp: 2, 7
GAN f1 score: 0.424
GAN cohens kappa score: 0.368

-> test with 'LR'
LR tn, fp: 127, 11
LR fn, tp: 2, 7
LR f1 score: 0.519
LR cohens kappa score: 0.476
LR average precision score: 0.593

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

-> test with 'GB'
GB tn, fp: 130, 8
GB fn, tp: 8, 1
GB f1 score: 0.111
GB cohens kappa score: 0.053

-> test with 'KNN'
KNN tn, fp: 126, 12
KNN fn, tp: 4, 5
KNN f1 score: 0.385
KNN cohens kappa score: 0.331


------ 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: 0.3872
48/56 [========================>.....] - ETA: 0s - loss: 0.3115
56/56 [==============================] - 0s 1ms/step - loss: 0.3057
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2872
49/56 [=========================>....] - ETA: 0s - loss: 0.2962
56/56 [==============================] - 0s 1ms/step - loss: 0.3002
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3011
49/56 [=========================>....] - ETA: 0s - loss: 0.2978
56/56 [==============================] - 0s 1ms/step - loss: 0.2950
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.2643
49/56 [=========================>....] - ETA: 0s - loss: 0.2848
56/56 [==============================] - 0s 1ms/step - loss: 0.2905
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.4135
49/56 [=========================>....] - ETA: 0s - loss: 0.2862
56/56 [==============================] - 0s 1ms/step - loss: 0.2870
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.2053
49/56 [=========================>....] - ETA: 0s - loss: 0.2873
56/56 [==============================] - 0s 1ms/step - loss: 0.2846
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2099
49/56 [=========================>....] - ETA: 0s - loss: 0.2758
56/56 [==============================] - 0s 1ms/step - loss: 0.2770
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1818
49/56 [=========================>....] - ETA: 0s - loss: 0.2839
56/56 [==============================] - 0s 1ms/step - loss: 0.2807
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1559
49/56 [=========================>....] - ETA: 0s - loss: 0.2745
56/56 [==============================] - 0s 1ms/step - loss: 0.2734
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.3142
43/56 [======================>.......] - ETA: 0s - loss: 0.2839
56/56 [==============================] - 0s 1ms/step - loss: 0.2729
-> test with GAN.predict
GAN tn, fp: 130, 8
GAN fn, tp: 0, 9
GAN f1 score: 0.692
GAN cohens kappa score: 0.666

-> test with 'LR'
LR tn, fp: 131, 7
LR fn, tp: 0, 9
LR f1 score: 0.720
LR cohens kappa score: 0.696
LR average precision score: 0.906

-> test with 'RF'
RF tn, fp: 136, 2
RF fn, tp: 4, 5
RF f1 score: 0.625
RF cohens kappa score: 0.604

-> test with 'GB'
GB tn, fp: 132, 6
GB fn, tp: 4, 5
GB f1 score: 0.500
GB cohens kappa score: 0.464

-> test with 'KNN'
KNN tn, fp: 117, 21
KNN fn, tp: 1, 8
KNN f1 score: 0.421
KNN cohens kappa score: 0.361


------ 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: 9s - loss: 0.1270
48/56 [========================>.....] - ETA: 0s - loss: 0.1764
56/56 [==============================] - 0s 1ms/step - loss: 0.1796
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1544
50/56 [=========================>....] - ETA: 0s - loss: 0.1813
56/56 [==============================] - 0s 1ms/step - loss: 0.1778
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.0878
49/56 [=========================>....] - ETA: 0s - loss: 0.1774
56/56 [==============================] - 0s 1ms/step - loss: 0.1751
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3379
49/56 [=========================>....] - ETA: 0s - loss: 0.1724
56/56 [==============================] - 0s 1ms/step - loss: 0.1702
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0882
46/56 [=======================>......] - ETA: 0s - loss: 0.1599
56/56 [==============================] - 0s 1ms/step - loss: 0.1686
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1441
45/56 [=======================>......] - ETA: 0s - loss: 0.1644
56/56 [==============================] - 0s 1ms/step - loss: 0.1666
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1865
46/56 [=======================>......] - ETA: 0s - loss: 0.1704
56/56 [==============================] - 0s 1ms/step - loss: 0.1660
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1861
49/56 [=========================>....] - ETA: 0s - loss: 0.1714
56/56 [==============================] - 0s 1ms/step - loss: 0.1630
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1590
49/56 [=========================>....] - ETA: 0s - loss: 0.1579
56/56 [==============================] - 0s 1ms/step - loss: 0.1632
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2917
49/56 [=========================>....] - ETA: 0s - loss: 0.1632
56/56 [==============================] - 0s 1ms/step - loss: 0.1592
-> test with GAN.predict
GAN tn, fp: 128, 10
GAN fn, tp: 3, 6
GAN f1 score: 0.480
GAN cohens kappa score: 0.436

-> test with 'LR'
LR tn, fp: 132, 6
LR fn, tp: 4, 5
LR f1 score: 0.500
LR cohens kappa score: 0.464
LR average precision score: 0.693

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

-> test with 'GB'
GB tn, fp: 132, 6
GB fn, tp: 7, 2
GB f1 score: 0.235
GB cohens kappa score: 0.189

-> test with 'KNN'
KNN tn, fp: 125, 13
KNN fn, tp: 5, 4
KNN f1 score: 0.308
KNN cohens kappa score: 0.247


------ 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: 8s - loss: 0.3352
49/56 [=========================>....] - ETA: 0s - loss: 0.2552
56/56 [==============================] - 0s 1ms/step - loss: 0.2512
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2223
49/56 [=========================>....] - ETA: 0s - loss: 0.2428
56/56 [==============================] - 0s 1ms/step - loss: 0.2445
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1835
49/56 [=========================>....] - ETA: 0s - loss: 0.2377
56/56 [==============================] - 0s 1ms/step - loss: 0.2415
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1335
49/56 [=========================>....] - ETA: 0s - loss: 0.2395
56/56 [==============================] - 0s 1ms/step - loss: 0.2368
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1782
48/56 [========================>.....] - ETA: 0s - loss: 0.2319
56/56 [==============================] - 0s 1ms/step - loss: 0.2344
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1417
49/56 [=========================>....] - ETA: 0s - loss: 0.2275
56/56 [==============================] - 0s 1ms/step - loss: 0.2318
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.3927
49/56 [=========================>....] - ETA: 0s - loss: 0.2242
56/56 [==============================] - 0s 1ms/step - loss: 0.2281
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1498
49/56 [=========================>....] - ETA: 0s - loss: 0.2311
56/56 [==============================] - 0s 1ms/step - loss: 0.2242
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1754
49/56 [=========================>....] - ETA: 0s - loss: 0.2251
56/56 [==============================] - 0s 1ms/step - loss: 0.2239
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1270
49/56 [=========================>....] - ETA: 0s - loss: 0.2253
56/56 [==============================] - 0s 1ms/step - loss: 0.2248
-> test with GAN.predict
GAN tn, fp: 122, 16
GAN fn, tp: 3, 6
GAN f1 score: 0.387
GAN cohens kappa score: 0.329

-> test with 'LR'
LR tn, fp: 117, 21
LR fn, tp: 1, 8
LR f1 score: 0.421
LR cohens kappa score: 0.361
LR average precision score: 0.649

-> test with 'RF'
RF tn, fp: 134, 4
RF fn, tp: 7, 2
RF f1 score: 0.267
RF cohens kappa score: 0.229

-> test with 'GB'
GB tn, fp: 128, 10
GB fn, tp: 6, 3
GB f1 score: 0.273
GB cohens kappa score: 0.216

-> test with 'KNN'
KNN tn, fp: 119, 19
KNN fn, tp: 4, 5
KNN f1 score: 0.303
KNN cohens kappa score: 0.235


------ 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: 20s - loss: 0.2082
42/56 [=====================>........] - ETA: 0s - loss: 0.2620 
56/56 [==============================] - 0s 1ms/step - loss: 0.2667
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1746
49/56 [=========================>....] - ETA: 0s - loss: 0.2582
56/56 [==============================] - 0s 1ms/step - loss: 0.2608
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2656
49/56 [=========================>....] - ETA: 0s - loss: 0.2538
56/56 [==============================] - 0s 1ms/step - loss: 0.2535
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.2269
49/56 [=========================>....] - ETA: 0s - loss: 0.2548
56/56 [==============================] - 0s 1ms/step - loss: 0.2533
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2904
49/56 [=========================>....] - ETA: 0s - loss: 0.2326
56/56 [==============================] - 0s 1ms/step - loss: 0.2451
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.4626
49/56 [=========================>....] - ETA: 0s - loss: 0.2497
56/56 [==============================] - 0s 1ms/step - loss: 0.2482
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1902
49/56 [=========================>....] - ETA: 0s - loss: 0.2396
56/56 [==============================] - 0s 1ms/step - loss: 0.2441
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1237
49/56 [=========================>....] - ETA: 0s - loss: 0.2445
56/56 [==============================] - 0s 1ms/step - loss: 0.2407
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1262
49/56 [=========================>....] - ETA: 0s - loss: 0.2377
56/56 [==============================] - 0s 1ms/step - loss: 0.2380
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1731
45/56 [=======================>......] - ETA: 0s - loss: 0.2189
56/56 [==============================] - 0s 1ms/step - loss: 0.2319
-> test with GAN.predict
GAN tn, fp: 127, 10
GAN fn, tp: 2, 4
GAN f1 score: 0.400
GAN cohens kappa score: 0.363

-> test with 'LR'
LR tn, fp: 124, 13
LR fn, tp: 1, 5
LR f1 score: 0.417
LR cohens kappa score: 0.377
LR average precision score: 0.553

-> test with 'RF'
RF tn, fp: 133, 4
RF fn, tp: 5, 1
RF f1 score: 0.182
RF cohens kappa score: 0.149

-> 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: 121, 16
KNN fn, tp: 3, 3
KNN f1 score: 0.240
KNN cohens kappa score: 0.188


====== 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: 9s - loss: 0.1748
49/56 [=========================>....] - ETA: 0s - loss: 0.2386
56/56 [==============================] - 0s 1ms/step - loss: 0.2320
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.4176
49/56 [=========================>....] - ETA: 0s - loss: 0.2279
56/56 [==============================] - 0s 1ms/step - loss: 0.2251
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1040
49/56 [=========================>....] - ETA: 0s - loss: 0.2233
56/56 [==============================] - 0s 1ms/step - loss: 0.2207
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1555
49/56 [=========================>....] - ETA: 0s - loss: 0.2179
56/56 [==============================] - 0s 1ms/step - loss: 0.2177
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.0934
49/56 [=========================>....] - ETA: 0s - loss: 0.2198
56/56 [==============================] - 0s 1ms/step - loss: 0.2143
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.4126
49/56 [=========================>....] - ETA: 0s - loss: 0.2097
56/56 [==============================] - 0s 1ms/step - loss: 0.2119
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.3093
49/56 [=========================>....] - ETA: 0s - loss: 0.2112
56/56 [==============================] - 0s 1ms/step - loss: 0.2100
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1753
49/56 [=========================>....] - ETA: 0s - loss: 0.2087
56/56 [==============================] - 0s 1ms/step - loss: 0.2062
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1420
49/56 [=========================>....] - ETA: 0s - loss: 0.2026
56/56 [==============================] - 0s 1ms/step - loss: 0.2059
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1921
49/56 [=========================>....] - ETA: 0s - loss: 0.1913
56/56 [==============================] - 0s 1ms/step - loss: 0.2010
-> test with GAN.predict
GAN tn, fp: 127, 11
GAN fn, tp: 3, 6
GAN f1 score: 0.462
GAN cohens kappa score: 0.415

-> test with 'LR'
LR tn, fp: 128, 10
LR fn, tp: 4, 5
LR f1 score: 0.417
LR cohens kappa score: 0.368
LR average precision score: 0.534

-> test with 'RF'
RF tn, fp: 134, 4
RF fn, tp: 6, 3
RF f1 score: 0.375
RF cohens kappa score: 0.340

-> test with 'GB'
GB tn, fp: 136, 2
GB fn, tp: 5, 4
GB f1 score: 0.533
GB cohens kappa score: 0.509

-> test with 'KNN'
KNN tn, fp: 127, 11
KNN fn, tp: 4, 5
KNN f1 score: 0.400
KNN cohens kappa score: 0.349


------ 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: 8s - loss: 0.2563
49/56 [=========================>....] - ETA: 0s - loss: 0.2500
56/56 [==============================] - 0s 1ms/step - loss: 0.2488
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1577
49/56 [=========================>....] - ETA: 0s - loss: 0.2518
56/56 [==============================] - 0s 1ms/step - loss: 0.2509
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2190
49/56 [=========================>....] - ETA: 0s - loss: 0.2449
56/56 [==============================] - 0s 1ms/step - loss: 0.2471
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1673
48/56 [========================>.....] - ETA: 0s - loss: 0.2516
56/56 [==============================] - 0s 1ms/step - loss: 0.2459
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2175
49/56 [=========================>....] - ETA: 0s - loss: 0.2382
56/56 [==============================] - 0s 1ms/step - loss: 0.2369
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1866
48/56 [========================>.....] - ETA: 0s - loss: 0.2349
56/56 [==============================] - 0s 1ms/step - loss: 0.2369
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1518
49/56 [=========================>....] - ETA: 0s - loss: 0.2337
56/56 [==============================] - 0s 1ms/step - loss: 0.2367
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1820
49/56 [=========================>....] - ETA: 0s - loss: 0.2352
56/56 [==============================] - 0s 1ms/step - loss: 0.2323
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2641
49/56 [=========================>....] - ETA: 0s - loss: 0.2329
56/56 [==============================] - 0s 1ms/step - loss: 0.2324
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2426
49/56 [=========================>....] - ETA: 0s - loss: 0.2312
56/56 [==============================] - 0s 1ms/step - loss: 0.2256
-> test with GAN.predict
GAN tn, fp: 126, 12
GAN fn, tp: 2, 7
GAN f1 score: 0.500
GAN cohens kappa score: 0.455

-> test with 'LR'
LR tn, fp: 124, 14
LR fn, tp: 2, 7
LR f1 score: 0.467
LR cohens kappa score: 0.417
LR average precision score: 0.711

-> test with 'RF'
RF tn, fp: 132, 6
RF fn, tp: 5, 4
RF f1 score: 0.421
RF cohens kappa score: 0.381

-> test with 'GB'
GB tn, fp: 128, 10
GB fn, tp: 4, 5
GB f1 score: 0.417
GB cohens kappa score: 0.368

-> test with 'KNN'
KNN tn, fp: 117, 21
KNN fn, tp: 2, 7
KNN f1 score: 0.378
KNN cohens kappa score: 0.315


------ 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: 0.3719
48/56 [========================>.....] - ETA: 0s - loss: 0.2790
56/56 [==============================] - 0s 1ms/step - loss: 0.2767
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.3228
47/56 [========================>.....] - ETA: 0s - loss: 0.2657
56/56 [==============================] - 0s 1ms/step - loss: 0.2724
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2493
43/56 [======================>.......] - ETA: 0s - loss: 0.2677
56/56 [==============================] - 0s 1ms/step - loss: 0.2698
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3515
43/56 [======================>.......] - ETA: 0s - loss: 0.2713
56/56 [==============================] - 0s 1ms/step - loss: 0.2637
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2592
49/56 [=========================>....] - ETA: 0s - loss: 0.2653
56/56 [==============================] - 0s 1ms/step - loss: 0.2577
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.3351
49/56 [=========================>....] - ETA: 0s - loss: 0.2517
56/56 [==============================] - 0s 1ms/step - loss: 0.2536
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1440
49/56 [=========================>....] - ETA: 0s - loss: 0.2460
56/56 [==============================] - 0s 1ms/step - loss: 0.2531
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1443
49/56 [=========================>....] - ETA: 0s - loss: 0.2402
56/56 [==============================] - 0s 1ms/step - loss: 0.2452
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1517
49/56 [=========================>....] - ETA: 0s - loss: 0.2463
56/56 [==============================] - 0s 1ms/step - loss: 0.2436
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.3098
49/56 [=========================>....] - ETA: 0s - loss: 0.2386
56/56 [==============================] - 0s 1ms/step - loss: 0.2384
-> test with GAN.predict
GAN tn, fp: 123, 15
GAN fn, tp: 1, 8
GAN f1 score: 0.500
GAN cohens kappa score: 0.452

-> test with 'LR'
LR tn, fp: 129, 9
LR fn, tp: 1, 8
LR f1 score: 0.615
LR cohens kappa score: 0.582
LR average precision score: 0.692

-> 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: 123, 15
KNN fn, tp: 4, 5
KNN f1 score: 0.345
KNN cohens kappa score: 0.284


------ 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: 8s - loss: 0.3076
49/56 [=========================>....] - ETA: 0s - loss: 0.2925
56/56 [==============================] - 0s 1ms/step - loss: 0.2968
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2473
49/56 [=========================>....] - ETA: 0s - loss: 0.2918
56/56 [==============================] - 0s 1ms/step - loss: 0.2912
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2896
49/56 [=========================>....] - ETA: 0s - loss: 0.2946
56/56 [==============================] - 0s 1ms/step - loss: 0.2886
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3263
49/56 [=========================>....] - ETA: 0s - loss: 0.2773
56/56 [==============================] - 0s 1ms/step - loss: 0.2798
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.3581
49/56 [=========================>....] - ETA: 0s - loss: 0.2817
56/56 [==============================] - 0s 1ms/step - loss: 0.2780
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.3136
49/56 [=========================>....] - ETA: 0s - loss: 0.2775
56/56 [==============================] - 0s 1ms/step - loss: 0.2774
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1772
49/56 [=========================>....] - ETA: 0s - loss: 0.2791
56/56 [==============================] - 0s 1ms/step - loss: 0.2730
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2508
48/56 [========================>.....] - ETA: 0s - loss: 0.2722
56/56 [==============================] - 0s 1ms/step - loss: 0.2694
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1902
48/56 [========================>.....] - ETA: 0s - loss: 0.2745
56/56 [==============================] - 0s 1ms/step - loss: 0.2695
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2421
48/56 [========================>.....] - ETA: 0s - loss: 0.2658
56/56 [==============================] - 0s 1ms/step - loss: 0.2627
-> test with GAN.predict
GAN tn, fp: 127, 11
GAN fn, tp: 0, 9
GAN f1 score: 0.621
GAN cohens kappa score: 0.586

-> 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: 0.928

-> test with 'RF'
RF tn, fp: 134, 4
RF fn, tp: 7, 2
RF f1 score: 0.267
RF cohens kappa score: 0.229

-> test with 'GB'
GB tn, fp: 132, 6
GB fn, tp: 5, 4
GB f1 score: 0.421
GB cohens kappa score: 0.381

-> test with 'KNN'
KNN tn, fp: 113, 25
KNN fn, tp: 2, 7
KNN f1 score: 0.341
KNN cohens kappa score: 0.272


------ 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: 7s - loss: 0.1640
48/56 [========================>.....] - ETA: 0s - loss: 0.2664
56/56 [==============================] - 0s 1ms/step - loss: 0.2670
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2876
49/56 [=========================>....] - ETA: 0s - loss: 0.2699
56/56 [==============================] - 0s 1ms/step - loss: 0.2631
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.1235
49/56 [=========================>....] - ETA: 0s - loss: 0.2677
56/56 [==============================] - 0s 1ms/step - loss: 0.2635
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.2784
46/56 [=======================>......] - ETA: 0s - loss: 0.2555
56/56 [==============================] - 0s 1ms/step - loss: 0.2529
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2079
43/56 [======================>.......] - ETA: 0s - loss: 0.2580
56/56 [==============================] - 0s 1ms/step - loss: 0.2511
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.3750
45/56 [=======================>......] - ETA: 0s - loss: 0.2436
56/56 [==============================] - 0s 1ms/step - loss: 0.2439
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.3445
49/56 [=========================>....] - ETA: 0s - loss: 0.2384
56/56 [==============================] - 0s 1ms/step - loss: 0.2424
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2286
49/56 [=========================>....] - ETA: 0s - loss: 0.2444
56/56 [==============================] - 0s 1ms/step - loss: 0.2391
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.3165
47/56 [========================>.....] - ETA: 0s - loss: 0.2512
56/56 [==============================] - 0s 1ms/step - loss: 0.2441
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2572
46/56 [=======================>......] - ETA: 0s - loss: 0.2332
56/56 [==============================] - 0s 1ms/step - loss: 0.2384
-> test with GAN.predict
GAN tn, fp: 128, 9
GAN fn, tp: 2, 4
GAN f1 score: 0.421
GAN cohens kappa score: 0.386

-> 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: 0.588

-> test with 'RF'
RF tn, fp: 131, 6
RF fn, tp: 4, 2
RF f1 score: 0.286
RF cohens kappa score: 0.250

-> test with 'GB'
GB tn, fp: 130, 7
GB fn, tp: 4, 2
GB f1 score: 0.267
GB cohens kappa score: 0.228

-> test with 'KNN'
KNN tn, fp: 124, 13
KNN fn, tp: 1, 5
KNN f1 score: 0.417
KNN cohens kappa score: 0.377


====== 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: 8s - loss: 0.4624
37/56 [==================>...........] - ETA: 0s - loss: 0.2542
56/56 [==============================] - 0s 1ms/step - loss: 0.2520
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1638
41/56 [====================>.........] - ETA: 0s - loss: 0.2497
56/56 [==============================] - 0s 1ms/step - loss: 0.2446
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3759
41/56 [====================>.........] - ETA: 0s - loss: 0.2500
56/56 [==============================] - 0s 1ms/step - loss: 0.2417
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.1845
44/56 [======================>.......] - ETA: 0s - loss: 0.2420
56/56 [==============================] - 0s 1ms/step - loss: 0.2380
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1491
45/56 [=======================>......] - ETA: 0s - loss: 0.2270
56/56 [==============================] - 0s 1ms/step - loss: 0.2329
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.2546
42/56 [=====================>........] - ETA: 0s - loss: 0.2339
56/56 [==============================] - 0s 1ms/step - loss: 0.2335
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2552
44/56 [======================>.......] - ETA: 0s - loss: 0.2182
56/56 [==============================] - 0s 1ms/step - loss: 0.2280
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1376
43/56 [======================>.......] - ETA: 0s - loss: 0.2266
56/56 [==============================] - 0s 1ms/step - loss: 0.2263
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.2556
43/56 [======================>.......] - ETA: 0s - loss: 0.2311
56/56 [==============================] - 0s 1ms/step - loss: 0.2244
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.3892
45/56 [=======================>......] - ETA: 0s - loss: 0.2190
56/56 [==============================] - 0s 1ms/step - loss: 0.2187
-> test with GAN.predict
GAN tn, fp: 127, 11
GAN fn, tp: 4, 5
GAN f1 score: 0.400
GAN cohens kappa score: 0.349

-> test with 'LR'
LR tn, fp: 121, 17
LR fn, tp: 1, 8
LR f1 score: 0.471
LR cohens kappa score: 0.418
LR average precision score: 0.734

-> 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: 132, 6
GB fn, tp: 7, 2
GB f1 score: 0.235
GB cohens kappa score: 0.189

-> test with 'KNN'
KNN tn, fp: 123, 15
KNN fn, tp: 5, 4
KNN f1 score: 0.286
KNN cohens kappa score: 0.221


------ 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: 7s - loss: 0.3119
48/56 [========================>.....] - ETA: 0s - loss: 0.3019
56/56 [==============================] - 0s 1ms/step - loss: 0.2964
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2533
48/56 [========================>.....] - ETA: 0s - loss: 0.2877
56/56 [==============================] - 0s 1ms/step - loss: 0.2845
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2728
49/56 [=========================>....] - ETA: 0s - loss: 0.2775
56/56 [==============================] - 0s 1ms/step - loss: 0.2763
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.2631
49/56 [=========================>....] - ETA: 0s - loss: 0.2768
56/56 [==============================] - 0s 1ms/step - loss: 0.2710
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2075
49/56 [=========================>....] - ETA: 0s - loss: 0.2667
56/56 [==============================] - 0s 1ms/step - loss: 0.2649
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.2397
48/56 [========================>.....] - ETA: 0s - loss: 0.2581
56/56 [==============================] - 0s 1ms/step - loss: 0.2593
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2151
49/56 [=========================>....] - ETA: 0s - loss: 0.2513
56/56 [==============================] - 0s 1ms/step - loss: 0.2549
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.2855
49/56 [=========================>....] - ETA: 0s - loss: 0.2460
56/56 [==============================] - 0s 1ms/step - loss: 0.2449
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1682
49/56 [=========================>....] - ETA: 0s - loss: 0.2497
56/56 [==============================] - 0s 1ms/step - loss: 0.2442
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2379
49/56 [=========================>....] - ETA: 0s - loss: 0.2383
56/56 [==============================] - 0s 1ms/step - loss: 0.2402
-> test with GAN.predict
GAN tn, fp: 125, 13
GAN fn, tp: 4, 5
GAN f1 score: 0.370
GAN cohens kappa score: 0.314

-> test with 'LR'
LR tn, fp: 128, 10
LR fn, tp: 0, 9
LR f1 score: 0.643
LR cohens kappa score: 0.610
LR average precision score: 0.738

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

-> 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: 117, 21
KNN fn, tp: 4, 5
KNN f1 score: 0.286
KNN cohens kappa score: 0.214


------ 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: 8s - loss: 0.1225
47/56 [========================>.....] - ETA: 0s - loss: 0.2280
56/56 [==============================] - 0s 1ms/step - loss: 0.2316
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2083
44/56 [======================>.......] - ETA: 0s - loss: 0.2197
56/56 [==============================] - 0s 1ms/step - loss: 0.2294
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2304
45/56 [=======================>......] - ETA: 0s - loss: 0.2169
56/56 [==============================] - 0s 1ms/step - loss: 0.2286
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3917
49/56 [=========================>....] - ETA: 0s - loss: 0.2270
56/56 [==============================] - 0s 1ms/step - loss: 0.2215
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.1395
49/56 [=========================>....] - ETA: 0s - loss: 0.2137
56/56 [==============================] - 0s 1ms/step - loss: 0.2180
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.3126
43/56 [======================>.......] - ETA: 0s - loss: 0.2161
56/56 [==============================] - 0s 1ms/step - loss: 0.2137
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1918
49/56 [=========================>....] - ETA: 0s - loss: 0.2090
56/56 [==============================] - 0s 1ms/step - loss: 0.2102
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1740
47/56 [========================>.....] - ETA: 0s - loss: 0.2042
56/56 [==============================] - 0s 1ms/step - loss: 0.2083
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.1764
49/56 [=========================>....] - ETA: 0s - loss: 0.2049
56/56 [==============================] - 0s 1ms/step - loss: 0.2048
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.1902
49/56 [=========================>....] - ETA: 0s - loss: 0.2009
56/56 [==============================] - 0s 1ms/step - loss: 0.2031
-> test with GAN.predict
GAN tn, fp: 127, 11
GAN fn, tp: 4, 5
GAN f1 score: 0.400
GAN cohens kappa score: 0.349

-> test with 'LR'
LR tn, fp: 126, 12
LR fn, tp: 3, 6
LR f1 score: 0.444
LR cohens kappa score: 0.395
LR average precision score: 0.526

-> 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: 6, 3
GB f1 score: 0.375
GB cohens kappa score: 0.340

-> test with 'KNN'
KNN tn, fp: 122, 16
KNN fn, tp: 5, 4
KNN f1 score: 0.276
KNN cohens kappa score: 0.209


------ 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: 8s - loss: 0.2216
44/56 [======================>.......] - ETA: 0s - loss: 0.2332
56/56 [==============================] - 0s 1ms/step - loss: 0.2332
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.1283
48/56 [========================>.....] - ETA: 0s - loss: 0.2212
56/56 [==============================] - 0s 1ms/step - loss: 0.2267
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.2455
47/56 [========================>.....] - ETA: 0s - loss: 0.2315
56/56 [==============================] - 0s 1ms/step - loss: 0.2219
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.0764
49/56 [=========================>....] - ETA: 0s - loss: 0.2184
56/56 [==============================] - 0s 1ms/step - loss: 0.2197
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.2308
43/56 [======================>.......] - ETA: 0s - loss: 0.2067
56/56 [==============================] - 0s 1ms/step - loss: 0.2137
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.2273
49/56 [=========================>....] - ETA: 0s - loss: 0.2126
56/56 [==============================] - 0s 1ms/step - loss: 0.2129
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.1713
49/56 [=========================>....] - ETA: 0s - loss: 0.2138
56/56 [==============================] - 0s 1ms/step - loss: 0.2110
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.3789
48/56 [========================>.....] - ETA: 0s - loss: 0.2057
56/56 [==============================] - 0s 1ms/step - loss: 0.2055
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.0935
48/56 [========================>.....] - ETA: 0s - loss: 0.2042
56/56 [==============================] - 0s 1ms/step - loss: 0.2066
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2695
44/56 [======================>.......] - ETA: 0s - loss: 0.2149
56/56 [==============================] - 0s 1ms/step - loss: 0.2061
-> test with GAN.predict
GAN tn, fp: 121, 17
GAN fn, tp: 1, 8
GAN f1 score: 0.471
GAN cohens kappa score: 0.418

-> test with 'LR'
LR tn, fp: 130, 8
LR fn, tp: 1, 8
LR f1 score: 0.640
LR cohens kappa score: 0.609
LR average precision score: 0.931

-> 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: 129, 9
GB fn, tp: 4, 5
GB f1 score: 0.435
GB cohens kappa score: 0.389

-> test with 'KNN'
KNN tn, fp: 125, 13
KNN fn, tp: 3, 6
KNN f1 score: 0.429
KNN cohens kappa score: 0.377


------ 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: 8s - loss: 0.2401
49/56 [=========================>....] - ETA: 0s - loss: 0.2716
56/56 [==============================] - 0s 1ms/step - loss: 0.2773
Epoch 2/10

 1/56 [..............................] - ETA: 0s - loss: 0.2224
49/56 [=========================>....] - ETA: 0s - loss: 0.2789
56/56 [==============================] - 0s 1ms/step - loss: 0.2764
Epoch 3/10

 1/56 [..............................] - ETA: 0s - loss: 0.3275
49/56 [=========================>....] - ETA: 0s - loss: 0.2797
56/56 [==============================] - 0s 1ms/step - loss: 0.2727
Epoch 4/10

 1/56 [..............................] - ETA: 0s - loss: 0.3167
47/56 [========================>.....] - ETA: 0s - loss: 0.2650
56/56 [==============================] - 0s 1ms/step - loss: 0.2681
Epoch 5/10

 1/56 [..............................] - ETA: 0s - loss: 0.3730
50/56 [=========================>....] - ETA: 0s - loss: 0.2665
56/56 [==============================] - 0s 1ms/step - loss: 0.2639
Epoch 6/10

 1/56 [..............................] - ETA: 0s - loss: 0.1524
49/56 [=========================>....] - ETA: 0s - loss: 0.2663
56/56 [==============================] - 0s 1ms/step - loss: 0.2637
Epoch 7/10

 1/56 [..............................] - ETA: 0s - loss: 0.2568
50/56 [=========================>....] - ETA: 0s - loss: 0.2610
56/56 [==============================] - 0s 1ms/step - loss: 0.2582
Epoch 8/10

 1/56 [..............................] - ETA: 0s - loss: 0.1195
49/56 [=========================>....] - ETA: 0s - loss: 0.2568
56/56 [==============================] - 0s 1ms/step - loss: 0.2580
Epoch 9/10

 1/56 [..............................] - ETA: 0s - loss: 0.3048
49/56 [=========================>....] - ETA: 0s - loss: 0.2505
56/56 [==============================] - 0s 1ms/step - loss: 0.2589
Epoch 10/10

 1/56 [..............................] - ETA: 0s - loss: 0.2546
49/56 [=========================>....] - ETA: 0s - loss: 0.2617
56/56 [==============================] - 0s 1ms/step - loss: 0.2569
-> test with GAN.predict
GAN tn, fp: 126, 11
GAN fn, tp: 0, 6
GAN f1 score: 0.522
GAN cohens kappa score: 0.490

-> test with 'LR'
LR tn, fp: 127, 10
LR fn, tp: 0, 6
LR f1 score: 0.545
LR cohens kappa score: 0.516
LR average precision score: 0.797

-> test with 'RF'
RF tn, fp: 134, 3
RF fn, tp: 3, 3
RF f1 score: 0.500
RF cohens kappa score: 0.478

-> test with 'GB'
GB tn, fp: 133, 4
GB fn, tp: 3, 3
GB f1 score: 0.462
GB cohens kappa score: 0.436

-> test with 'KNN'
KNN tn, fp: 125, 12
KNN fn, tp: 2, 4
KNN f1 score: 0.364
KNN cohens kappa score: 0.322

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 132, 21
LR fn, tp: 4, 9
LR f1 score: 0.720
LR cohens kappa score: 0.696
LR average precision score: 0.931


average:
LR tn, fp: 126.84, 10.96
LR fn, tp: 1.32, 7.08
LR f1 score: 0.538
LR cohens kappa score: 0.500
LR average precision score: 0.691


minimum:
LR tn, fp: 117, 6
LR fn, tp: 0, 5
LR f1 score: 0.417
LR cohens kappa score: 0.361
LR average precision score: 0.487


-----[ RF ]-----
maximum:
RF tn, fp: 137, 7
RF fn, tp: 8, 5
RF f1 score: 0.625
RF cohens kappa score: 0.604


average:
RF tn, fp: 134.24, 3.56
RF fn, tp: 6.08, 2.32
RF f1 score: 0.324
RF cohens kappa score: 0.291


minimum:
RF tn, fp: 131, 1
RF fn, tp: 3, 1
RF f1 score: 0.118
RF cohens kappa score: 0.064


-----[ GB ]-----
maximum:
GB tn, fp: 136, 10
GB fn, tp: 8, 5
GB f1 score: 0.533
GB cohens kappa score: 0.509


average:
GB tn, fp: 132.32, 5.48
GB fn, tp: 5.28, 3.12
GB f1 score: 0.367
GB cohens kappa score: 0.329


minimum:
GB tn, fp: 128, 2
GB fn, tp: 3, 1
GB f1 score: 0.111
GB cohens kappa score: 0.053


-----[ KNN ]-----
maximum:
KNN tn, fp: 132, 25
KNN fn, tp: 5, 8
KNN f1 score: 0.500
KNN cohens kappa score: 0.464


average:
KNN tn, fp: 122.28, 15.52
KNN fn, tp: 3.16, 5.24
KNN f1 score: 0.361
KNN cohens kappa score: 0.305


minimum:
KNN tn, fp: 113, 6
KNN fn, tp: 1, 3
KNN f1 score: 0.240
KNN cohens kappa score: 0.188


-----[ GAN ]-----
maximum:
GAN tn, fp: 133, 17
GAN fn, tp: 4, 9
GAN f1 score: 0.692
GAN cohens kappa score: 0.666


average:
GAN tn, fp: 126.08, 11.72
GAN fn, tp: 2.08, 6.32
GAN f1 score: 0.477
GAN cohens kappa score: 0.433


minimum:
GAN tn, fp: 121, 5
GAN fn, tp: 0, 4
GAN f1 score: 0.333
GAN cohens kappa score: 0.289