ConvGeNBenchmarkResults/data_result/ConvGeN-proximity-full/folding_yeast5.log

///////////////////////////////////////////
// Running convGAN-proximary-full on folding_yeast5
///////////////////////////////////////////

Load 'data_input/folding_yeast5'
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 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.1601
 42/116 [=========>....................] - ETA: 0s - loss: 0.0875 
 84/116 [====================>.........] - ETA: 0s - loss: 0.0711
116/116 [==============================] - 0s 1ms/step - loss: 0.0701
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1408
 41/116 [=========>....................] - ETA: 0s - loss: 0.0572
 83/116 [====================>.........] - ETA: 0s - loss: 0.0619
116/116 [==============================] - 0s 1ms/step - loss: 0.0594
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0207
 41/116 [=========>....................] - ETA: 0s - loss: 0.0714
 84/116 [====================>.........] - ETA: 0s - loss: 0.0635
116/116 [==============================] - 0s 1ms/step - loss: 0.0564
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0051
 42/116 [=========>....................] - ETA: 0s - loss: 0.0546
 83/116 [====================>.........] - ETA: 0s - loss: 0.0441
116/116 [==============================] - 0s 1ms/step - loss: 0.0550
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0460
 42/116 [=========>....................] - ETA: 0s - loss: 0.0527
 82/116 [====================>.........] - ETA: 0s - loss: 0.0502
116/116 [==============================] - 0s 1ms/step - loss: 0.0536
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0238
 43/116 [==========>...................] - ETA: 0s - loss: 0.0461
 82/116 [====================>.........] - ETA: 0s - loss: 0.0500
116/116 [==============================] - ETA: 0s - loss: 0.0533
116/116 [==============================] - 0s 1ms/step - loss: 0.0533
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0185
 38/116 [========>.....................] - ETA: 0s - loss: 0.0442
 78/116 [===================>..........] - ETA: 0s - loss: 0.0543
115/116 [============================>.] - ETA: 0s - loss: 0.0539
116/116 [==============================] - 0s 1ms/step - loss: 0.0541
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1516
 42/116 [=========>....................] - ETA: 0s - loss: 0.0729
 77/116 [==================>...........] - ETA: 0s - loss: 0.0622
113/116 [============================>.] - ETA: 0s - loss: 0.0539
116/116 [==============================] - 0s 1ms/step - loss: 0.0546
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1775
 39/116 [=========>....................] - ETA: 0s - loss: 0.0500
 80/116 [===================>..........] - ETA: 0s - loss: 0.0462
116/116 [==============================] - 0s 1ms/step - loss: 0.0518
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0095
 40/116 [=========>....................] - ETA: 0s - loss: 0.0440
 79/116 [===================>..........] - ETA: 0s - loss: 0.0460
116/116 [==============================] - 0s 1ms/step - loss: 0.0519
-> test with GAN.predict
GAN tn, fp: 282, 6
GAN fn, tp: 3, 6
GAN f1 score: 0.571
GAN cohens kappa score: 0.556

-> test with 'LR'
LR tn, fp: 276, 12
LR fn, tp: 0, 9
LR f1 score: 0.600
LR cohens kappa score: 0.582
LR average precision score: 0.895

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 4, 5
RF f1 score: 0.667
RF cohens kappa score: 0.658

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

-> test with 'KNN'
KNN tn, fp: 280, 8
KNN fn, tp: 0, 9
KNN f1 score: 0.692
KNN cohens kappa score: 0.680


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.1791
 42/116 [=========>....................] - ETA: 0s - loss: 0.1450 
 82/116 [====================>.........] - ETA: 0s - loss: 0.1274
116/116 [==============================] - 0s 1ms/step - loss: 0.1169
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1159
 42/116 [=========>....................] - ETA: 0s - loss: 0.0827
 80/116 [===================>..........] - ETA: 0s - loss: 0.0739
113/116 [============================>.] - ETA: 0s - loss: 0.0715
116/116 [==============================] - 0s 1ms/step - loss: 0.0726
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0071
 42/116 [=========>....................] - ETA: 0s - loss: 0.0722
 83/116 [====================>.........] - ETA: 0s - loss: 0.0682
116/116 [==============================] - 0s 1ms/step - loss: 0.0648
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0331
 42/116 [=========>....................] - ETA: 0s - loss: 0.0505
 83/116 [====================>.........] - ETA: 0s - loss: 0.0635
116/116 [==============================] - 0s 1ms/step - loss: 0.0602
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0043
 42/116 [=========>....................] - ETA: 0s - loss: 0.0615
 84/116 [====================>.........] - ETA: 0s - loss: 0.0635
116/116 [==============================] - 0s 1ms/step - loss: 0.0609
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0646
 42/116 [=========>....................] - ETA: 0s - loss: 0.0456
 82/116 [====================>.........] - ETA: 0s - loss: 0.0568
116/116 [==============================] - 0s 1ms/step - loss: 0.0580
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0787
 42/116 [=========>....................] - ETA: 0s - loss: 0.0794
 82/116 [====================>.........] - ETA: 0s - loss: 0.0589
116/116 [==============================] - 0s 1ms/step - loss: 0.0546
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0105
 42/116 [=========>....................] - ETA: 0s - loss: 0.0403
 80/116 [===================>..........] - ETA: 0s - loss: 0.0513
116/116 [==============================] - 0s 1ms/step - loss: 0.0560
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0021
 42/116 [=========>....................] - ETA: 0s - loss: 0.0592
 82/116 [====================>.........] - ETA: 0s - loss: 0.0530
116/116 [==============================] - 0s 1ms/step - loss: 0.0531
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0101
 42/116 [=========>....................] - ETA: 0s - loss: 0.0508
 84/116 [====================>.........] - ETA: 0s - loss: 0.0489
116/116 [==============================] - 0s 1ms/step - loss: 0.0531
-> test with GAN.predict
GAN tn, fp: 276, 12
GAN fn, tp: 0, 9
GAN f1 score: 0.600
GAN cohens kappa score: 0.582

-> test with 'LR'
LR tn, fp: 273, 15
LR fn, tp: 0, 9
LR f1 score: 0.545
LR cohens kappa score: 0.524
LR average precision score: 0.712

-> test with 'RF'
RF tn, fp: 285, 3
RF fn, tp: 0, 9
RF f1 score: 0.857
RF cohens kappa score: 0.852

-> test with 'GB'
GB tn, fp: 284, 4
GB fn, tp: 1, 8
GB f1 score: 0.762
GB cohens kappa score: 0.753

-> test with 'KNN'
KNN tn, fp: 274, 14
KNN fn, tp: 0, 9
KNN f1 score: 0.562
KNN cohens kappa score: 0.543


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 9.6613e-04
 43/116 [==========>...................] - ETA: 0s - loss: 0.0789     
 85/116 [====================>.........] - ETA: 0s - loss: 0.0643
116/116 [==============================] - 0s 1ms/step - loss: 0.0674
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0026
 40/116 [=========>....................] - ETA: 0s - loss: 0.0530
 78/116 [===================>..........] - ETA: 0s - loss: 0.0583
116/116 [==============================] - 0s 1ms/step - loss: 0.0594
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0129
 42/116 [=========>....................] - ETA: 0s - loss: 0.0592
 82/116 [====================>.........] - ETA: 0s - loss: 0.0604
116/116 [==============================] - 0s 1ms/step - loss: 0.0569
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0053
 42/116 [=========>....................] - ETA: 0s - loss: 0.0486
 77/116 [==================>...........] - ETA: 0s - loss: 0.0581
110/116 [===========================>..] - ETA: 0s - loss: 0.0566
116/116 [==============================] - 0s 1ms/step - loss: 0.0545
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0041
 37/116 [========>.....................] - ETA: 0s - loss: 0.0319
 77/116 [==================>...........] - ETA: 0s - loss: 0.0478
116/116 [==============================] - ETA: 0s - loss: 0.0526
116/116 [==============================] - 0s 1ms/step - loss: 0.0526
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1836
 42/116 [=========>....................] - ETA: 0s - loss: 0.0590
 81/116 [===================>..........] - ETA: 0s - loss: 0.0549
116/116 [==============================] - 0s 1ms/step - loss: 0.0515
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.2397
 40/116 [=========>....................] - ETA: 0s - loss: 0.0608
 80/116 [===================>..........] - ETA: 0s - loss: 0.0543
116/116 [==============================] - 0s 1ms/step - loss: 0.0512
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0156
 41/116 [=========>....................] - ETA: 0s - loss: 0.0245
 82/116 [====================>.........] - ETA: 0s - loss: 0.0525
116/116 [==============================] - 0s 1ms/step - loss: 0.0555
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0040
 41/116 [=========>....................] - ETA: 0s - loss: 0.0535
 83/116 [====================>.........] - ETA: 0s - loss: 0.0517
116/116 [==============================] - 0s 1ms/step - loss: 0.0513
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0038
 41/116 [=========>....................] - ETA: 0s - loss: 0.0590
 82/116 [====================>.........] - ETA: 0s - loss: 0.0488
116/116 [==============================] - 0s 1ms/step - loss: 0.0489
-> test with GAN.predict
GAN tn, fp: 282, 6
GAN fn, tp: 2, 7
GAN f1 score: 0.636
GAN cohens kappa score: 0.623

-> test with 'LR'
LR tn, fp: 278, 10
LR fn, tp: 0, 9
LR f1 score: 0.643
LR cohens kappa score: 0.628
LR average precision score: 0.612

-> test with 'RF'
RF tn, fp: 284, 4
RF fn, tp: 3, 6
RF f1 score: 0.632
RF cohens kappa score: 0.619

-> test with 'GB'
GB tn, fp: 284, 4
GB fn, tp: 2, 7
GB f1 score: 0.700
GB cohens kappa score: 0.690

-> test with 'KNN'
KNN tn, fp: 279, 9
KNN fn, tp: 1, 8
KNN f1 score: 0.615
KNN cohens kappa score: 0.600


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.0107
 42/116 [=========>....................] - ETA: 0s - loss: 0.0498 
 82/116 [====================>.........] - ETA: 0s - loss: 0.0469
116/116 [==============================] - 0s 1ms/step - loss: 0.0483
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0072
 44/116 [==========>...................] - ETA: 0s - loss: 0.0463
 85/116 [====================>.........] - ETA: 0s - loss: 0.0400
116/116 [==============================] - 0s 1ms/step - loss: 0.0433
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0024
 41/116 [=========>....................] - ETA: 0s - loss: 0.0479
 81/116 [===================>..........] - ETA: 0s - loss: 0.0431
116/116 [==============================] - 0s 1ms/step - loss: 0.0420
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0021
 43/116 [==========>...................] - ETA: 0s - loss: 0.0363
 84/116 [====================>.........] - ETA: 0s - loss: 0.0384
116/116 [==============================] - 0s 1ms/step - loss: 0.0405
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0155
 41/116 [=========>....................] - ETA: 0s - loss: 0.0597
 80/116 [===================>..........] - ETA: 0s - loss: 0.0394
116/116 [==============================] - 0s 1ms/step - loss: 0.0417
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0152
 40/116 [=========>....................] - ETA: 0s - loss: 0.0324
 80/116 [===================>..........] - ETA: 0s - loss: 0.0303
116/116 [==============================] - 0s 1ms/step - loss: 0.0392
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0631
 40/116 [=========>....................] - ETA: 0s - loss: 0.0429
 81/116 [===================>..........] - ETA: 0s - loss: 0.0387
116/116 [==============================] - 0s 1ms/step - loss: 0.0379
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0019
 37/116 [========>.....................] - ETA: 0s - loss: 0.0377
 73/116 [=================>............] - ETA: 0s - loss: 0.0427
109/116 [===========================>..] - ETA: 0s - loss: 0.0416
116/116 [==============================] - 0s 1ms/step - loss: 0.0413
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0019
 41/116 [=========>....................] - ETA: 0s - loss: 0.0410
 80/116 [===================>..........] - ETA: 0s - loss: 0.0382
116/116 [==============================] - ETA: 0s - loss: 0.0378
116/116 [==============================] - 0s 1ms/step - loss: 0.0378
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0014
 38/116 [========>.....................] - ETA: 0s - loss: 0.0333
 78/116 [===================>..........] - ETA: 0s - loss: 0.0327
116/116 [==============================] - 0s 1ms/step - loss: 0.0397
-> test with GAN.predict
GAN tn, fp: 286, 2
GAN fn, tp: 3, 6
GAN f1 score: 0.706
GAN cohens kappa score: 0.697

-> test with 'LR'
LR tn, fp: 281, 7
LR fn, tp: 2, 7
LR f1 score: 0.609
LR cohens kappa score: 0.594
LR average precision score: 0.744

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 4, 5
RF f1 score: 0.667
RF cohens kappa score: 0.658

-> test with 'GB'
GB tn, fp: 288, 0
GB fn, tp: 3, 6
GB f1 score: 0.800
GB cohens kappa score: 0.795

-> test with 'KNN'
KNN tn, fp: 287, 1
KNN fn, tp: 0, 9
KNN f1 score: 0.947
KNN cohens kappa score: 0.946


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1116 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.1722
 40/116 [=========>....................] - ETA: 0s - loss: 0.0755 
 74/116 [==================>...........] - ETA: 0s - loss: 0.0837
113/116 [============================>.] - ETA: 0s - loss: 0.0745
116/116 [==============================] - 0s 1ms/step - loss: 0.0733
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0040
 27/116 [=====>........................] - ETA: 0s - loss: 0.0860
 59/116 [==============>...............] - ETA: 0s - loss: 0.0691
 95/116 [=======================>......] - ETA: 0s - loss: 0.0645
116/116 [==============================] - 0s 2ms/step - loss: 0.0672
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0049
 38/116 [========>.....................] - ETA: 0s - loss: 0.0680
 79/116 [===================>..........] - ETA: 0s - loss: 0.0595
116/116 [==============================] - 0s 1ms/step - loss: 0.0653
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0670
 39/116 [=========>....................] - ETA: 0s - loss: 0.0428
 79/116 [===================>..........] - ETA: 0s - loss: 0.0497
116/116 [==============================] - 0s 1ms/step - loss: 0.0609
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0548
 41/116 [=========>....................] - ETA: 0s - loss: 0.0632
 80/116 [===================>..........] - ETA: 0s - loss: 0.0692
116/116 [==============================] - 0s 1ms/step - loss: 0.0595
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1125
 40/116 [=========>....................] - ETA: 0s - loss: 0.0564
 79/116 [===================>..........] - ETA: 0s - loss: 0.0591
116/116 [==============================] - 0s 1ms/step - loss: 0.0585
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.2587
 39/116 [=========>....................] - ETA: 0s - loss: 0.0620
 77/116 [==================>...........] - ETA: 0s - loss: 0.0531
116/116 [==============================] - 0s 1ms/step - loss: 0.0557
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0082
 41/116 [=========>....................] - ETA: 0s - loss: 0.0516
 81/116 [===================>..........] - ETA: 0s - loss: 0.0628
116/116 [==============================] - 0s 1ms/step - loss: 0.0574
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0247
 41/116 [=========>....................] - ETA: 0s - loss: 0.0584
 75/116 [==================>...........] - ETA: 0s - loss: 0.0674
114/116 [============================>.] - ETA: 0s - loss: 0.0543
116/116 [==============================] - 0s 1ms/step - loss: 0.0559
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1520
 41/116 [=========>....................] - ETA: 0s - loss: 0.0790
 81/116 [===================>..........] - ETA: 0s - loss: 0.0625
116/116 [==============================] - 0s 1ms/step - loss: 0.0547
-> test with GAN.predict
GAN tn, fp: 278, 10
GAN fn, tp: 0, 8
GAN f1 score: 0.615
GAN cohens kappa score: 0.600

-> test with 'LR'
LR tn, fp: 274, 14
LR fn, tp: 0, 8
LR f1 score: 0.533
LR cohens kappa score: 0.514
LR average precision score: 0.701

-> test with 'RF'
RF tn, fp: 282, 6
RF fn, tp: 0, 8
RF f1 score: 0.727
RF cohens kappa score: 0.718

-> test with 'GB'
GB tn, fp: 283, 5
GB fn, tp: 0, 8
GB f1 score: 0.762
GB cohens kappa score: 0.754

-> test with 'KNN'
KNN tn, fp: 276, 12
KNN fn, tp: 0, 8
KNN f1 score: 0.571
KNN cohens kappa score: 0.554


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

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 22s - loss: 0.0422
 42/116 [=========>....................] - ETA: 0s - loss: 0.0853 
 81/116 [===================>..........] - ETA: 0s - loss: 0.0624
116/116 [==============================] - ETA: 0s - loss: 0.0671
116/116 [==============================] - 0s 1ms/step - loss: 0.0671
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0196
 36/116 [========>.....................] - ETA: 0s - loss: 0.0471
 73/116 [=================>............] - ETA: 0s - loss: 0.0545
109/116 [===========================>..] - ETA: 0s - loss: 0.0544
116/116 [==============================] - 0s 1ms/step - loss: 0.0576
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1241
 41/116 [=========>....................] - ETA: 0s - loss: 0.0619
 81/116 [===================>..........] - ETA: 0s - loss: 0.0574
116/116 [==============================] - 0s 1ms/step - loss: 0.0554
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0296
 42/116 [=========>....................] - ETA: 0s - loss: 0.0741
 82/116 [====================>.........] - ETA: 0s - loss: 0.0591
116/116 [==============================] - 0s 1ms/step - loss: 0.0550
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0092
 41/116 [=========>....................] - ETA: 0s - loss: 0.0679
 81/116 [===================>..........] - ETA: 0s - loss: 0.0571
116/116 [==============================] - 0s 1ms/step - loss: 0.0545
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.2924
 40/116 [=========>....................] - ETA: 0s - loss: 0.0580
 80/116 [===================>..........] - ETA: 0s - loss: 0.0396
116/116 [==============================] - 0s 1ms/step - loss: 0.0530
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0968
 41/116 [=========>....................] - ETA: 0s - loss: 0.0512
 81/116 [===================>..........] - ETA: 0s - loss: 0.0485
116/116 [==============================] - 0s 1ms/step - loss: 0.0538
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0038
 40/116 [=========>....................] - ETA: 0s - loss: 0.0470
 80/116 [===================>..........] - ETA: 0s - loss: 0.0497
116/116 [==============================] - 0s 1ms/step - loss: 0.0521
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0301
 41/116 [=========>....................] - ETA: 0s - loss: 0.0485
 80/116 [===================>..........] - ETA: 0s - loss: 0.0514
116/116 [==============================] - 0s 1ms/step - loss: 0.0528
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0135
 40/116 [=========>....................] - ETA: 0s - loss: 0.0703
 80/116 [===================>..........] - ETA: 0s - loss: 0.0515
116/116 [==============================] - 0s 1ms/step - loss: 0.0508
-> test with GAN.predict
GAN tn, fp: 278, 10
GAN fn, tp: 0, 9
GAN f1 score: 0.643
GAN cohens kappa score: 0.628

-> test with 'LR'
LR tn, fp: 276, 12
LR fn, tp: 0, 9
LR f1 score: 0.600
LR cohens kappa score: 0.582
LR average precision score: 0.703

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 1, 8
RF f1 score: 0.889
RF cohens kappa score: 0.885

-> test with 'GB'
GB tn, fp: 286, 2
GB fn, tp: 1, 8
GB f1 score: 0.842
GB cohens kappa score: 0.837

-> test with 'KNN'
KNN tn, fp: 279, 9
KNN fn, tp: 0, 9
KNN f1 score: 0.667
KNN cohens kappa score: 0.653


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0626
 42/116 [=========>....................] - ETA: 0s - loss: 0.0482 
 84/116 [====================>.........] - ETA: 0s - loss: 0.0584
116/116 [==============================] - 0s 1ms/step - loss: 0.0617
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 3.7319e-05
 39/116 [=========>....................] - ETA: 0s - loss: 0.0561    
 80/116 [===================>..........] - ETA: 0s - loss: 0.0525
116/116 [==============================] - 0s 1ms/step - loss: 0.0532
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0543
 40/116 [=========>....................] - ETA: 0s - loss: 0.0172
 75/116 [==================>...........] - ETA: 0s - loss: 0.0464
114/116 [============================>.] - ETA: 0s - loss: 0.0482
116/116 [==============================] - 0s 1ms/step - loss: 0.0478
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2851
 35/116 [========>.....................] - ETA: 0s - loss: 0.0678
 68/116 [================>.............] - ETA: 0s - loss: 0.0517
103/116 [=========================>....] - ETA: 0s - loss: 0.0465
116/116 [==============================] - 0s 1ms/step - loss: 0.0447
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.4674
 41/116 [=========>....................] - ETA: 0s - loss: 0.0572
 81/116 [===================>..........] - ETA: 0s - loss: 0.0492
116/116 [==============================] - 0s 1ms/step - loss: 0.0418
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0054
 42/116 [=========>....................] - ETA: 0s - loss: 0.0437
 83/116 [====================>.........] - ETA: 0s - loss: 0.0440
116/116 [==============================] - 0s 1ms/step - loss: 0.0444
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 4.9670e-04
 42/116 [=========>....................] - ETA: 0s - loss: 0.0107    
 81/116 [===================>..........] - ETA: 0s - loss: 0.0287
116/116 [==============================] - 0s 1ms/step - loss: 0.0407
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0057
 42/116 [=========>....................] - ETA: 0s - loss: 0.0441
 82/116 [====================>.........] - ETA: 0s - loss: 0.0378
116/116 [==============================] - 0s 1ms/step - loss: 0.0405
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0282
 42/116 [=========>....................] - ETA: 0s - loss: 0.0322
 82/116 [====================>.........] - ETA: 0s - loss: 0.0377
116/116 [==============================] - 0s 1ms/step - loss: 0.0387
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0022
 42/116 [=========>....................] - ETA: 0s - loss: 0.0258
 83/116 [====================>.........] - ETA: 0s - loss: 0.0408
116/116 [==============================] - 0s 1ms/step - loss: 0.0391
-> test with GAN.predict
GAN tn, fp: 280, 8
GAN fn, tp: 3, 6
GAN f1 score: 0.522
GAN cohens kappa score: 0.503

-> test with 'LR'
LR tn, fp: 271, 17
LR fn, tp: 1, 8
LR f1 score: 0.471
LR cohens kappa score: 0.446
LR average precision score: 0.419

-> test with 'RF'
RF tn, fp: 280, 8
RF fn, tp: 4, 5
RF f1 score: 0.455
RF cohens kappa score: 0.434

-> test with 'GB'
GB tn, fp: 280, 8
GB fn, tp: 6, 3
GB f1 score: 0.300
GB cohens kappa score: 0.276

-> test with 'KNN'
KNN tn, fp: 275, 13
KNN fn, tp: 0, 9
KNN f1 score: 0.581
KNN cohens kappa score: 0.562


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 21s - loss: 0.0096
 41/116 [=========>....................] - ETA: 0s - loss: 0.0875 
 80/116 [===================>..........] - ETA: 0s - loss: 0.0682
116/116 [==============================] - 0s 1ms/step - loss: 0.0668
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0660
 40/116 [=========>....................] - ETA: 0s - loss: 0.0442
 81/116 [===================>..........] - ETA: 0s - loss: 0.0601
116/116 [==============================] - 0s 1ms/step - loss: 0.0614
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0175
 42/116 [=========>....................] - ETA: 0s - loss: 0.0578
 81/116 [===================>..........] - ETA: 0s - loss: 0.0556
116/116 [==============================] - 0s 1ms/step - loss: 0.0582
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0012
 40/116 [=========>....................] - ETA: 0s - loss: 0.0578
 80/116 [===================>..........] - ETA: 0s - loss: 0.0570
116/116 [==============================] - 0s 1ms/step - loss: 0.0568
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0039
 42/116 [=========>....................] - ETA: 0s - loss: 0.0633
 82/116 [====================>.........] - ETA: 0s - loss: 0.0597
116/116 [==============================] - 0s 1ms/step - loss: 0.0595
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0072
 41/116 [=========>....................] - ETA: 0s - loss: 0.0296
 80/116 [===================>..........] - ETA: 0s - loss: 0.0499
116/116 [==============================] - 0s 1ms/step - loss: 0.0557
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0949
 41/116 [=========>....................] - ETA: 0s - loss: 0.0626
 80/116 [===================>..........] - ETA: 0s - loss: 0.0618
116/116 [==============================] - 0s 1ms/step - loss: 0.0571
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0075
 41/116 [=========>....................] - ETA: 0s - loss: 0.0567
 81/116 [===================>..........] - ETA: 0s - loss: 0.0550
116/116 [==============================] - 0s 1ms/step - loss: 0.0526
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0386
 41/116 [=========>....................] - ETA: 0s - loss: 0.0780
 81/116 [===================>..........] - ETA: 0s - loss: 0.0590
116/116 [==============================] - 0s 1ms/step - loss: 0.0538
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0036
 42/116 [=========>....................] - ETA: 0s - loss: 0.0672
 82/116 [====================>.........] - ETA: 0s - loss: 0.0592
116/116 [==============================] - 0s 1ms/step - loss: 0.0529
-> test with GAN.predict
GAN tn, fp: 283, 5
GAN fn, tp: 1, 8
GAN f1 score: 0.727
GAN cohens kappa score: 0.717

-> test with 'LR'
LR tn, fp: 281, 7
LR fn, tp: 0, 9
LR f1 score: 0.720
LR cohens kappa score: 0.709
LR average precision score: 0.755

-> test with 'RF'
RF tn, fp: 288, 0
RF fn, tp: 2, 7
RF f1 score: 0.875
RF cohens kappa score: 0.872

-> test with 'GB'
GB tn, fp: 287, 1
GB fn, tp: 1, 8
GB f1 score: 0.889
GB cohens kappa score: 0.885

-> test with 'KNN'
KNN tn, fp: 283, 5
KNN fn, tp: 0, 9
KNN f1 score: 0.783
KNN cohens kappa score: 0.774


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0247
 40/116 [=========>....................] - ETA: 0s - loss: 0.0919 
 81/116 [===================>..........] - ETA: 0s - loss: 0.0871
116/116 [==============================] - 0s 1ms/step - loss: 0.0825
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0186
 40/116 [=========>....................] - ETA: 0s - loss: 0.0951
 80/116 [===================>..........] - ETA: 0s - loss: 0.0871
116/116 [==============================] - 0s 1ms/step - loss: 0.0823
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0021
 38/116 [========>.....................] - ETA: 0s - loss: 0.0791
 79/116 [===================>..........] - ETA: 0s - loss: 0.0698
116/116 [==============================] - 0s 1ms/step - loss: 0.0673
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0327
 40/116 [=========>....................] - ETA: 0s - loss: 0.0618
 81/116 [===================>..........] - ETA: 0s - loss: 0.0723
116/116 [==============================] - 0s 1ms/step - loss: 0.0607
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0053
 41/116 [=========>....................] - ETA: 0s - loss: 0.0498
 79/116 [===================>..........] - ETA: 0s - loss: 0.0563
114/116 [============================>.] - ETA: 0s - loss: 0.0606
116/116 [==============================] - 0s 1ms/step - loss: 0.0604
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0340
 32/116 [=======>......................] - ETA: 0s - loss: 0.0585
 65/116 [===============>..............] - ETA: 0s - loss: 0.0724
 96/116 [=======================>......] - ETA: 0s - loss: 0.0626
116/116 [==============================] - 0s 2ms/step - loss: 0.0651
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.3152
 32/116 [=======>......................] - ETA: 0s - loss: 0.0701
 62/116 [===============>..............] - ETA: 0s - loss: 0.0582
 93/116 [=======================>......] - ETA: 0s - loss: 0.0593
116/116 [==============================] - 0s 2ms/step - loss: 0.0589
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0115
 34/116 [=======>......................] - ETA: 0s - loss: 0.0511
 67/116 [================>.............] - ETA: 0s - loss: 0.0608
 97/116 [========================>.....] - ETA: 0s - loss: 0.0618
116/116 [==============================] - 0s 2ms/step - loss: 0.0587
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1020
 31/116 [=======>......................] - ETA: 0s - loss: 0.0547
 60/116 [==============>...............] - ETA: 0s - loss: 0.0611
 93/116 [=======================>......] - ETA: 0s - loss: 0.0604
116/116 [==============================] - 0s 2ms/step - loss: 0.0559
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0019
 35/116 [========>.....................] - ETA: 0s - loss: 0.0529
 66/116 [================>.............] - ETA: 0s - loss: 0.0533
 97/116 [========================>.....] - ETA: 0s - loss: 0.0542
116/116 [==============================] - 0s 2ms/step - loss: 0.0558
-> test with GAN.predict
GAN tn, fp: 284, 4
GAN fn, tp: 1, 8
GAN f1 score: 0.762
GAN cohens kappa score: 0.753

-> test with 'LR'
LR tn, fp: 273, 15
LR fn, tp: 0, 9
LR f1 score: 0.545
LR cohens kappa score: 0.524
LR average precision score: 0.891

-> test with 'RF'
RF tn, fp: 285, 3
RF fn, tp: 1, 8
RF f1 score: 0.800
RF cohens kappa score: 0.793

-> test with 'GB'
GB tn, fp: 285, 3
GB fn, tp: 1, 8
GB f1 score: 0.800
GB cohens kappa score: 0.793

-> test with 'KNN'
KNN tn, fp: 277, 11
KNN fn, tp: 0, 9
KNN f1 score: 0.621
KNN cohens kappa score: 0.604


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1116 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0255
 42/116 [=========>....................] - ETA: 0s - loss: 0.0651 
 82/116 [====================>.........] - ETA: 0s - loss: 0.0768
116/116 [==============================] - 0s 1ms/step - loss: 0.0685
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0012
 41/116 [=========>....................] - ETA: 0s - loss: 0.0695
 81/116 [===================>..........] - ETA: 0s - loss: 0.0629
116/116 [==============================] - 0s 1ms/step - loss: 0.0624
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0159
 40/116 [=========>....................] - ETA: 0s - loss: 0.0612
 80/116 [===================>..........] - ETA: 0s - loss: 0.0707
116/116 [==============================] - 0s 1ms/step - loss: 0.0605
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0118
 38/116 [========>.....................] - ETA: 0s - loss: 0.0674
 80/116 [===================>..........] - ETA: 0s - loss: 0.0627
116/116 [==============================] - ETA: 0s - loss: 0.0578
116/116 [==============================] - 0s 1ms/step - loss: 0.0578
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0513
 42/116 [=========>....................] - ETA: 0s - loss: 0.0488
 82/116 [====================>.........] - ETA: 0s - loss: 0.0581
116/116 [==============================] - 0s 1ms/step - loss: 0.0573
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0806
 40/116 [=========>....................] - ETA: 0s - loss: 0.0862
 81/116 [===================>..........] - ETA: 0s - loss: 0.0613
116/116 [==============================] - 0s 1ms/step - loss: 0.0546
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0118
 42/116 [=========>....................] - ETA: 0s - loss: 0.0553
 78/116 [===================>..........] - ETA: 0s - loss: 0.0535
116/116 [==============================] - 0s 1ms/step - loss: 0.0535
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0467
 41/116 [=========>....................] - ETA: 0s - loss: 0.0533
 79/116 [===================>..........] - ETA: 0s - loss: 0.0525
114/116 [============================>.] - ETA: 0s - loss: 0.0529
116/116 [==============================] - 0s 1ms/step - loss: 0.0534
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0466
 36/116 [========>.....................] - ETA: 0s - loss: 0.0480
 74/116 [==================>...........] - ETA: 0s - loss: 0.0589
114/116 [============================>.] - ETA: 0s - loss: 0.0548
116/116 [==============================] - 0s 1ms/step - loss: 0.0543
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.4033
 42/116 [=========>....................] - ETA: 0s - loss: 0.0518
 83/116 [====================>.........] - ETA: 0s - loss: 0.0528
116/116 [==============================] - 0s 1ms/step - loss: 0.0522
-> test with GAN.predict
GAN tn, fp: 283, 5
GAN fn, tp: 1, 7
GAN f1 score: 0.700
GAN cohens kappa score: 0.690

-> test with 'LR'
LR tn, fp: 278, 10
LR fn, tp: 0, 8
LR f1 score: 0.615
LR cohens kappa score: 0.600
LR average precision score: 0.635

-> test with 'RF'
RF tn, fp: 286, 2
RF fn, tp: 3, 5
RF f1 score: 0.667
RF cohens kappa score: 0.658

-> test with 'GB'
GB tn, fp: 286, 2
GB fn, tp: 3, 5
GB f1 score: 0.667
GB cohens kappa score: 0.658

-> test with 'KNN'
KNN tn, fp: 282, 6
KNN fn, tp: 0, 8
KNN f1 score: 0.727
KNN cohens kappa score: 0.718


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

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 21s - loss: 0.0348
 41/116 [=========>....................] - ETA: 0s - loss: 0.0663 
 77/116 [==================>...........] - ETA: 0s - loss: 0.0658
113/116 [============================>.] - ETA: 0s - loss: 0.0716
116/116 [==============================] - 0s 1ms/step - loss: 0.0720
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0467
 40/116 [=========>....................] - ETA: 0s - loss: 0.0667
 80/116 [===================>..........] - ETA: 0s - loss: 0.0685
116/116 [==============================] - 0s 1ms/step - loss: 0.0637
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0102
 40/116 [=========>....................] - ETA: 0s - loss: 0.0524
 78/116 [===================>..........] - ETA: 0s - loss: 0.0460
116/116 [==============================] - 0s 1ms/step - loss: 0.0620
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0153
 40/116 [=========>....................] - ETA: 0s - loss: 0.0653
 76/116 [==================>...........] - ETA: 0s - loss: 0.0620
115/116 [============================>.] - ETA: 0s - loss: 0.0606
116/116 [==============================] - 0s 1ms/step - loss: 0.0605
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0025
 39/116 [=========>....................] - ETA: 0s - loss: 0.0569
 77/116 [==================>...........] - ETA: 0s - loss: 0.0654
115/116 [============================>.] - ETA: 0s - loss: 0.0625
116/116 [==============================] - 0s 1ms/step - loss: 0.0624
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1033
 39/116 [=========>....................] - ETA: 0s - loss: 0.0498
 79/116 [===================>..........] - ETA: 0s - loss: 0.0619
116/116 [==============================] - 0s 1ms/step - loss: 0.0580
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1408
 43/116 [==========>...................] - ETA: 0s - loss: 0.0500
 82/116 [====================>.........] - ETA: 0s - loss: 0.0528
116/116 [==============================] - 0s 1ms/step - loss: 0.0600
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.3535
 41/116 [=========>....................] - ETA: 0s - loss: 0.0541
 81/116 [===================>..........] - ETA: 0s - loss: 0.0579
116/116 [==============================] - 0s 1ms/step - loss: 0.0565
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1110
 40/116 [=========>....................] - ETA: 0s - loss: 0.0578
 80/116 [===================>..........] - ETA: 0s - loss: 0.0530
116/116 [==============================] - 0s 1ms/step - loss: 0.0550
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0033
 41/116 [=========>....................] - ETA: 0s - loss: 0.0449
 81/116 [===================>..........] - ETA: 0s - loss: 0.0545
116/116 [==============================] - 0s 1ms/step - loss: 0.0561
-> test with GAN.predict
GAN tn, fp: 276, 12
GAN fn, tp: 1, 8
GAN f1 score: 0.552
GAN cohens kappa score: 0.532

-> test with 'LR'
LR tn, fp: 272, 16
LR fn, tp: 0, 9
LR f1 score: 0.529
LR cohens kappa score: 0.507
LR average precision score: 0.668

-> test with 'RF'
RF tn, fp: 285, 3
RF fn, tp: 3, 6
RF f1 score: 0.667
RF cohens kappa score: 0.656

-> test with 'GB'
GB tn, fp: 286, 2
GB fn, tp: 2, 7
GB f1 score: 0.778
GB cohens kappa score: 0.771

-> test with 'KNN'
KNN tn, fp: 274, 14
KNN fn, tp: 0, 9
KNN f1 score: 0.562
KNN cohens kappa score: 0.543


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 8.2898e-04
 41/116 [=========>....................] - ETA: 0s - loss: 0.0473     
 79/116 [===================>..........] - ETA: 0s - loss: 0.0515
116/116 [==============================] - 0s 1ms/step - loss: 0.0509
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0040
 38/116 [========>.....................] - ETA: 0s - loss: 0.0277
 77/116 [==================>...........] - ETA: 0s - loss: 0.0363
116/116 [==============================] - ETA: 0s - loss: 0.0489
116/116 [==============================] - 0s 1ms/step - loss: 0.0489
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0010
 40/116 [=========>....................] - ETA: 0s - loss: 0.0423
 79/116 [===================>..........] - ETA: 0s - loss: 0.0529
116/116 [==============================] - 0s 1ms/step - loss: 0.0466
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0539
 42/116 [=========>....................] - ETA: 0s - loss: 0.0441
 83/116 [====================>.........] - ETA: 0s - loss: 0.0445
116/116 [==============================] - 0s 1ms/step - loss: 0.0449
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0796
 41/116 [=========>....................] - ETA: 0s - loss: 0.0502
 78/116 [===================>..........] - ETA: 0s - loss: 0.0502
116/116 [==============================] - 0s 1ms/step - loss: 0.0462
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0140
 39/116 [=========>....................] - ETA: 0s - loss: 0.0491
 76/116 [==================>...........] - ETA: 0s - loss: 0.0430
108/116 [==========================>...] - ETA: 0s - loss: 0.0386
116/116 [==============================] - 0s 1ms/step - loss: 0.0436
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0129
 33/116 [=======>......................] - ETA: 0s - loss: 0.0338
 64/116 [===============>..............] - ETA: 0s - loss: 0.0376
102/116 [=========================>....] - ETA: 0s - loss: 0.0419
116/116 [==============================] - 0s 1ms/step - loss: 0.0440
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0097
 41/116 [=========>....................] - ETA: 0s - loss: 0.0331
 80/116 [===================>..........] - ETA: 0s - loss: 0.0369
116/116 [==============================] - 0s 1ms/step - loss: 0.0441
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0034
 41/116 [=========>....................] - ETA: 0s - loss: 0.0364
 82/116 [====================>.........] - ETA: 0s - loss: 0.0456
116/116 [==============================] - 0s 1ms/step - loss: 0.0434
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0844
 40/116 [=========>....................] - ETA: 0s - loss: 0.0385
 78/116 [===================>..........] - ETA: 0s - loss: 0.0392
116/116 [==============================] - ETA: 0s - loss: 0.0438
116/116 [==============================] - 0s 1ms/step - loss: 0.0438
-> test with GAN.predict
GAN tn, fp: 280, 8
GAN fn, tp: 1, 8
GAN f1 score: 0.640
GAN cohens kappa score: 0.625

-> test with 'LR'
LR tn, fp: 276, 12
LR fn, tp: 0, 9
LR f1 score: 0.600
LR cohens kappa score: 0.582
LR average precision score: 0.701

-> test with 'RF'
RF tn, fp: 285, 3
RF fn, tp: 2, 7
RF f1 score: 0.737
RF cohens kappa score: 0.728

-> test with 'GB'
GB tn, fp: 283, 5
GB fn, tp: 2, 7
GB f1 score: 0.667
GB cohens kappa score: 0.655

-> test with 'KNN'
KNN tn, fp: 277, 11
KNN fn, tp: 0, 9
KNN f1 score: 0.621
KNN cohens kappa score: 0.604


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.0060
 41/116 [=========>....................] - ETA: 0s - loss: 0.0751 
 81/116 [===================>..........] - ETA: 0s - loss: 0.0735
116/116 [==============================] - 0s 1ms/step - loss: 0.0758
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0177
 42/116 [=========>....................] - ETA: 0s - loss: 0.0656
 82/116 [====================>.........] - ETA: 0s - loss: 0.0686
116/116 [==============================] - 0s 1ms/step - loss: 0.0669
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0220
 41/116 [=========>....................] - ETA: 0s - loss: 0.0495
 81/116 [===================>..........] - ETA: 0s - loss: 0.0655
116/116 [==============================] - 0s 1ms/step - loss: 0.0662
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0287
 41/116 [=========>....................] - ETA: 0s - loss: 0.0478
 82/116 [====================>.........] - ETA: 0s - loss: 0.0618
116/116 [==============================] - 0s 1ms/step - loss: 0.0635
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1033
 42/116 [=========>....................] - ETA: 0s - loss: 0.0666
 83/116 [====================>.........] - ETA: 0s - loss: 0.0608
116/116 [==============================] - 0s 1ms/step - loss: 0.0622
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0595
 41/116 [=========>....................] - ETA: 0s - loss: 0.0750
 78/116 [===================>..........] - ETA: 0s - loss: 0.0687
116/116 [==============================] - 0s 1ms/step - loss: 0.0647
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0149
 37/116 [========>.....................] - ETA: 0s - loss: 0.0475
 74/116 [==================>...........] - ETA: 0s - loss: 0.0596
109/116 [===========================>..] - ETA: 0s - loss: 0.0617
116/116 [==============================] - 0s 1ms/step - loss: 0.0605
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0335
 38/116 [========>.....................] - ETA: 0s - loss: 0.0432
 76/116 [==================>...........] - ETA: 0s - loss: 0.0576
113/116 [============================>.] - ETA: 0s - loss: 0.0619
116/116 [==============================] - 0s 1ms/step - loss: 0.0619
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0499
 36/116 [========>.....................] - ETA: 0s - loss: 0.0618
 73/116 [=================>............] - ETA: 0s - loss: 0.0625
111/116 [===========================>..] - ETA: 0s - loss: 0.0580
116/116 [==============================] - 0s 1ms/step - loss: 0.0589
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0263
 36/116 [========>.....................] - ETA: 0s - loss: 0.0562
 73/116 [=================>............] - ETA: 0s - loss: 0.0598
109/116 [===========================>..] - ETA: 0s - loss: 0.0544
116/116 [==============================] - 0s 1ms/step - loss: 0.0591
-> test with GAN.predict
GAN tn, fp: 281, 7
GAN fn, tp: 2, 7
GAN f1 score: 0.609
GAN cohens kappa score: 0.594

-> test with 'LR'
LR tn, fp: 280, 8
LR fn, tp: 0, 9
LR f1 score: 0.692
LR cohens kappa score: 0.680
LR average precision score: 0.835

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 1, 8
RF f1 score: 0.889
RF cohens kappa score: 0.885

-> test with 'GB'
GB tn, fp: 287, 1
GB fn, tp: 2, 7
GB f1 score: 0.824
GB cohens kappa score: 0.818

-> test with 'KNN'
KNN tn, fp: 283, 5
KNN fn, tp: 0, 9
KNN f1 score: 0.783
KNN cohens kappa score: 0.774


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.7578
 41/116 [=========>....................] - ETA: 0s - loss: 0.1472 
 82/116 [====================>.........] - ETA: 0s - loss: 0.1410
116/116 [==============================] - 0s 1ms/step - loss: 0.1191
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0091
 42/116 [=========>....................] - ETA: 0s - loss: 0.0873
 83/116 [====================>.........] - ETA: 0s - loss: 0.0875
116/116 [==============================] - 0s 1ms/step - loss: 0.0869
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 4.2562e-04
 42/116 [=========>....................] - ETA: 0s - loss: 0.1048    
 81/116 [===================>..........] - ETA: 0s - loss: 0.0852
116/116 [==============================] - 0s 1ms/step - loss: 0.0729
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0043
 42/116 [=========>....................] - ETA: 0s - loss: 0.0622
 83/116 [====================>.........] - ETA: 0s - loss: 0.0660
116/116 [==============================] - 0s 1ms/step - loss: 0.0661
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0605
 42/116 [=========>....................] - ETA: 0s - loss: 0.0574
 82/116 [====================>.........] - ETA: 0s - loss: 0.0673
116/116 [==============================] - 0s 1ms/step - loss: 0.0635
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0199
 42/116 [=========>....................] - ETA: 0s - loss: 0.0665
 84/116 [====================>.........] - ETA: 0s - loss: 0.0547
116/116 [==============================] - 0s 1ms/step - loss: 0.0603
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0037
 37/116 [========>.....................] - ETA: 0s - loss: 0.0449
 71/116 [=================>............] - ETA: 0s - loss: 0.0572
103/116 [=========================>....] - ETA: 0s - loss: 0.0620
116/116 [==============================] - 0s 1ms/step - loss: 0.0592
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.3106
 42/116 [=========>....................] - ETA: 0s - loss: 0.0581
 82/116 [====================>.........] - ETA: 0s - loss: 0.0552
116/116 [==============================] - 0s 1ms/step - loss: 0.0569
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0038
 41/116 [=========>....................] - ETA: 0s - loss: 0.0494
 82/116 [====================>.........] - ETA: 0s - loss: 0.0460
116/116 [==============================] - 0s 1ms/step - loss: 0.0588
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0200
 41/116 [=========>....................] - ETA: 0s - loss: 0.0495
 82/116 [====================>.........] - ETA: 0s - loss: 0.0569
116/116 [==============================] - 0s 1ms/step - loss: 0.0569
-> test with GAN.predict
GAN tn, fp: 285, 3
GAN fn, tp: 3, 6
GAN f1 score: 0.667
GAN cohens kappa score: 0.656

-> test with 'LR'
LR tn, fp: 279, 9
LR fn, tp: 0, 9
LR f1 score: 0.667
LR cohens kappa score: 0.653
LR average precision score: 0.738

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 4, 5
RF f1 score: 0.667
RF cohens kappa score: 0.658

-> test with 'GB'
GB tn, fp: 286, 2
GB fn, tp: 5, 4
GB f1 score: 0.533
GB cohens kappa score: 0.522

-> test with 'KNN'
KNN tn, fp: 282, 6
KNN fn, tp: 1, 8
KNN f1 score: 0.696
KNN cohens kappa score: 0.684


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1116 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 21s - loss: 0.0055
 39/116 [=========>....................] - ETA: 0s - loss: 0.0500 
 77/116 [==================>...........] - ETA: 0s - loss: 0.0641
111/116 [===========================>..] - ETA: 0s - loss: 0.0723
116/116 [==============================] - 0s 1ms/step - loss: 0.0720
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0021
 37/116 [========>.....................] - ETA: 0s - loss: 0.0849
 73/116 [=================>............] - ETA: 0s - loss: 0.0617
110/116 [===========================>..] - ETA: 0s - loss: 0.0568
116/116 [==============================] - 0s 1ms/step - loss: 0.0594
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0576
 35/116 [========>.....................] - ETA: 0s - loss: 0.0660
 70/116 [=================>............] - ETA: 0s - loss: 0.0558
106/116 [==========================>...] - ETA: 0s - loss: 0.0544
116/116 [==============================] - 0s 1ms/step - loss: 0.0529
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1772
 39/116 [=========>....................] - ETA: 0s - loss: 0.0636
 78/116 [===================>..........] - ETA: 0s - loss: 0.0569
116/116 [==============================] - ETA: 0s - loss: 0.0516
116/116 [==============================] - 0s 1ms/step - loss: 0.0516
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0189
 36/116 [========>.....................] - ETA: 0s - loss: 0.0603
 71/116 [=================>............] - ETA: 0s - loss: 0.0547
106/116 [==========================>...] - ETA: 0s - loss: 0.0556
116/116 [==============================] - 0s 1ms/step - loss: 0.0519
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0050
 38/116 [========>.....................] - ETA: 0s - loss: 0.0377
 73/116 [=================>............] - ETA: 0s - loss: 0.0546
108/116 [==========================>...] - ETA: 0s - loss: 0.0510
116/116 [==============================] - 0s 1ms/step - loss: 0.0504
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0201
 34/116 [=======>......................] - ETA: 0s - loss: 0.0583
 72/116 [=================>............] - ETA: 0s - loss: 0.0515
106/116 [==========================>...] - ETA: 0s - loss: 0.0510
116/116 [==============================] - 0s 1ms/step - loss: 0.0504
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0035
 31/116 [=======>......................] - ETA: 0s - loss: 0.0494
 60/116 [==============>...............] - ETA: 0s - loss: 0.0505
 93/116 [=======================>......] - ETA: 0s - loss: 0.0549
116/116 [==============================] - 0s 2ms/step - loss: 0.0517
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1998
 37/116 [========>.....................] - ETA: 0s - loss: 0.0598
 72/116 [=================>............] - ETA: 0s - loss: 0.0542
107/116 [==========================>...] - ETA: 0s - loss: 0.0500
116/116 [==============================] - 0s 1ms/step - loss: 0.0480
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0055
 35/116 [========>.....................] - ETA: 0s - loss: 0.0444
 70/116 [=================>............] - ETA: 0s - loss: 0.0417
106/116 [==========================>...] - ETA: 0s - loss: 0.0502
116/116 [==============================] - 0s 1ms/step - loss: 0.0494
-> test with GAN.predict
GAN tn, fp: 278, 10
GAN fn, tp: 0, 8
GAN f1 score: 0.615
GAN cohens kappa score: 0.600

-> test with 'LR'
LR tn, fp: 275, 13
LR fn, tp: 0, 8
LR f1 score: 0.552
LR cohens kappa score: 0.533
LR average precision score: 0.387

-> test with 'RF'
RF tn, fp: 283, 5
RF fn, tp: 1, 7
RF f1 score: 0.700
RF cohens kappa score: 0.690

-> test with 'GB'
GB tn, fp: 283, 5
GB fn, tp: 1, 7
GB f1 score: 0.700
GB cohens kappa score: 0.690

-> test with 'KNN'
KNN tn, fp: 276, 12
KNN fn, tp: 0, 8
KNN f1 score: 0.571
KNN cohens kappa score: 0.554


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

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 3.0308e-05
 41/116 [=========>....................] - ETA: 0s - loss: 0.1005     
 83/116 [====================>.........] - ETA: 0s - loss: 0.1072
116/116 [==============================] - 0s 1ms/step - loss: 0.1018
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.8588
 42/116 [=========>....................] - ETA: 0s - loss: 0.1164
 83/116 [====================>.........] - ETA: 0s - loss: 0.0861
116/116 [==============================] - 0s 1ms/step - loss: 0.0810
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0367
 40/116 [=========>....................] - ETA: 0s - loss: 0.0286
 80/116 [===================>..........] - ETA: 0s - loss: 0.0544
116/116 [==============================] - 0s 1ms/step - loss: 0.0682
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.4283
 42/116 [=========>....................] - ETA: 0s - loss: 0.0523
 83/116 [====================>.........] - ETA: 0s - loss: 0.0662
116/116 [==============================] - 0s 1ms/step - loss: 0.0617
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0026
 41/116 [=========>....................] - ETA: 0s - loss: 0.0390
 82/116 [====================>.........] - ETA: 0s - loss: 0.0593
116/116 [==============================] - 0s 1ms/step - loss: 0.0583
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1007
 43/116 [==========>...................] - ETA: 0s - loss: 0.0685
 83/116 [====================>.........] - ETA: 0s - loss: 0.0645
116/116 [==============================] - 0s 1ms/step - loss: 0.0552
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0060
 42/116 [=========>....................] - ETA: 0s - loss: 0.0476
 84/116 [====================>.........] - ETA: 0s - loss: 0.0556
116/116 [==============================] - 0s 1ms/step - loss: 0.0534
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0487
 42/116 [=========>....................] - ETA: 0s - loss: 0.0517
 82/116 [====================>.........] - ETA: 0s - loss: 0.0518
116/116 [==============================] - 0s 1ms/step - loss: 0.0550
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0051
 43/116 [==========>...................] - ETA: 0s - loss: 0.0435
 83/116 [====================>.........] - ETA: 0s - loss: 0.0520
116/116 [==============================] - 0s 1ms/step - loss: 0.0527
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0067
 41/116 [=========>....................] - ETA: 0s - loss: 0.0509
 81/116 [===================>..........] - ETA: 0s - loss: 0.0512
116/116 [==============================] - 0s 1ms/step - loss: 0.0529
-> test with GAN.predict
GAN tn, fp: 280, 8
GAN fn, tp: 1, 8
GAN f1 score: 0.640
GAN cohens kappa score: 0.625

-> test with 'LR'
LR tn, fp: 275, 13
LR fn, tp: 1, 8
LR f1 score: 0.533
LR cohens kappa score: 0.513
LR average precision score: 0.742

-> test with 'RF'
RF tn, fp: 284, 4
RF fn, tp: 2, 7
RF f1 score: 0.700
RF cohens kappa score: 0.690

-> test with 'GB'
GB tn, fp: 284, 4
GB fn, tp: 1, 8
GB f1 score: 0.762
GB cohens kappa score: 0.753

-> test with 'KNN'
KNN tn, fp: 275, 13
KNN fn, tp: 0, 9
KNN f1 score: 0.581
KNN cohens kappa score: 0.562


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 22s - loss: 0.0055
 38/116 [========>.....................] - ETA: 0s - loss: 0.0691 
 73/116 [=================>............] - ETA: 0s - loss: 0.0979
108/116 [==========================>...] - ETA: 0s - loss: 0.1168
116/116 [==============================] - 0s 1ms/step - loss: 0.1152
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0011
 37/116 [========>.....................] - ETA: 0s - loss: 0.0867
 72/116 [=================>............] - ETA: 0s - loss: 0.1003
107/116 [==========================>...] - ETA: 0s - loss: 0.0886
116/116 [==============================] - 0s 1ms/step - loss: 0.0861
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 6.9561e-04
 36/116 [========>.....................] - ETA: 0s - loss: 0.0677    
 70/116 [=================>............] - ETA: 0s - loss: 0.0616
104/116 [=========================>....] - ETA: 0s - loss: 0.0673
116/116 [==============================] - 0s 1ms/step - loss: 0.0782
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0201
 37/116 [========>.....................] - ETA: 0s - loss: 0.0342
 72/116 [=================>............] - ETA: 0s - loss: 0.0421
105/116 [==========================>...] - ETA: 0s - loss: 0.0734
116/116 [==============================] - 0s 1ms/step - loss: 0.0698
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0087
 35/116 [========>.....................] - ETA: 0s - loss: 0.0855
 69/116 [================>.............] - ETA: 0s - loss: 0.0689
103/116 [=========================>....] - ETA: 0s - loss: 0.0675
116/116 [==============================] - 0s 1ms/step - loss: 0.0682
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0036
 39/116 [=========>....................] - ETA: 0s - loss: 0.0778
 72/116 [=================>............] - ETA: 0s - loss: 0.0614
107/116 [==========================>...] - ETA: 0s - loss: 0.0685
116/116 [==============================] - 0s 1ms/step - loss: 0.0667
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 6.5567e-04
 36/116 [========>.....................] - ETA: 0s - loss: 0.0661    
 72/116 [=================>............] - ETA: 0s - loss: 0.0571
105/116 [==========================>...] - ETA: 0s - loss: 0.0592
116/116 [==============================] - 0s 1ms/step - loss: 0.0593
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0304
 36/116 [========>.....................] - ETA: 0s - loss: 0.0532
 72/116 [=================>............] - ETA: 0s - loss: 0.0609
102/116 [=========================>....] - ETA: 0s - loss: 0.0559
116/116 [==============================] - 0s 2ms/step - loss: 0.0570
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.4278
 35/116 [========>.....................] - ETA: 0s - loss: 0.0446
 73/116 [=================>............] - ETA: 0s - loss: 0.0498
112/116 [===========================>..] - ETA: 0s - loss: 0.0560
116/116 [==============================] - 0s 1ms/step - loss: 0.0546
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0163
 35/116 [========>.....................] - ETA: 0s - loss: 0.0523
 67/116 [================>.............] - ETA: 0s - loss: 0.0633
 98/116 [========================>.....] - ETA: 0s - loss: 0.0546
116/116 [==============================] - 0s 2ms/step - loss: 0.0536
-> test with GAN.predict
GAN tn, fp: 280, 8
GAN fn, tp: 2, 7
GAN f1 score: 0.583
GAN cohens kappa score: 0.567

-> test with 'LR'
LR tn, fp: 276, 12
LR fn, tp: 2, 7
LR f1 score: 0.500
LR cohens kappa score: 0.479
LR average precision score: 0.633

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 2, 7
RF f1 score: 0.824
RF cohens kappa score: 0.818

-> test with 'GB'
GB tn, fp: 286, 2
GB fn, tp: 2, 7
GB f1 score: 0.778
GB cohens kappa score: 0.771

-> test with 'KNN'
KNN tn, fp: 281, 7
KNN fn, tp: 0, 9
KNN f1 score: 0.720
KNN cohens kappa score: 0.709


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.0049
 34/116 [=======>......................] - ETA: 0s - loss: 0.1160 
 68/116 [================>.............] - ETA: 0s - loss: 0.0934
102/116 [=========================>....] - ETA: 0s - loss: 0.0984
116/116 [==============================] - 0s 1ms/step - loss: 0.0982
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 5.5017e-04
 40/116 [=========>....................] - ETA: 0s - loss: 0.0290    
 79/116 [===================>..........] - ETA: 0s - loss: 0.0803
116/116 [==============================] - ETA: 0s - loss: 0.0848
116/116 [==============================] - 0s 1ms/step - loss: 0.0848
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0304
 39/116 [=========>....................] - ETA: 0s - loss: 0.0465
 78/116 [===================>..........] - ETA: 0s - loss: 0.0482
116/116 [==============================] - ETA: 0s - loss: 0.0672
116/116 [==============================] - 0s 1ms/step - loss: 0.0672
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0016
 39/116 [=========>....................] - ETA: 0s - loss: 0.0706
 77/116 [==================>...........] - ETA: 0s - loss: 0.0681
115/116 [============================>.] - ETA: 0s - loss: 0.0605
116/116 [==============================] - 0s 1ms/step - loss: 0.0604
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0027
 41/116 [=========>....................] - ETA: 0s - loss: 0.0514
 80/116 [===================>..........] - ETA: 0s - loss: 0.0538
116/116 [==============================] - 0s 1ms/step - loss: 0.0582
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1179
 42/116 [=========>....................] - ETA: 0s - loss: 0.0553
 80/116 [===================>..........] - ETA: 0s - loss: 0.0584
116/116 [==============================] - 0s 1ms/step - loss: 0.0547
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0035
 39/116 [=========>....................] - ETA: 0s - loss: 0.0331
 78/116 [===================>..........] - ETA: 0s - loss: 0.0511
116/116 [==============================] - 0s 1ms/step - loss: 0.0512
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0088
 37/116 [========>.....................] - ETA: 0s - loss: 0.0694
 75/116 [==================>...........] - ETA: 0s - loss: 0.0609
113/116 [============================>.] - ETA: 0s - loss: 0.0529
116/116 [==============================] - 0s 1ms/step - loss: 0.0522
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0285
 40/116 [=========>....................] - ETA: 0s - loss: 0.0465
 78/116 [===================>..........] - ETA: 0s - loss: 0.0458
116/116 [==============================] - 0s 1ms/step - loss: 0.0508
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.2290
 39/116 [=========>....................] - ETA: 0s - loss: 0.0554
 81/116 [===================>..........] - ETA: 0s - loss: 0.0490
116/116 [==============================] - 0s 1ms/step - loss: 0.0505
-> test with GAN.predict
GAN tn, fp: 279, 9
GAN fn, tp: 3, 6
GAN f1 score: 0.500
GAN cohens kappa score: 0.480

-> test with 'LR'
LR tn, fp: 281, 7
LR fn, tp: 1, 8
LR f1 score: 0.667
LR cohens kappa score: 0.654
LR average precision score: 0.725

-> test with 'RF'
RF tn, fp: 283, 5
RF fn, tp: 4, 5
RF f1 score: 0.526
RF cohens kappa score: 0.511

-> test with 'GB'
GB tn, fp: 283, 5
GB fn, tp: 4, 5
GB f1 score: 0.526
GB cohens kappa score: 0.511

-> test with 'KNN'
KNN tn, fp: 281, 7
KNN fn, tp: 3, 6
KNN f1 score: 0.545
KNN cohens kappa score: 0.529


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 9.7114e-04
 37/116 [========>.....................] - ETA: 0s - loss: 0.0991     
 71/116 [=================>............] - ETA: 0s - loss: 0.1122
103/116 [=========================>....] - ETA: 0s - loss: 0.1067
116/116 [==============================] - 0s 1ms/step - loss: 0.1028
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0041
 38/116 [========>.....................] - ETA: 0s - loss: 0.0586
 74/116 [==================>...........] - ETA: 0s - loss: 0.0570
111/116 [===========================>..] - ETA: 0s - loss: 0.0851
116/116 [==============================] - 0s 1ms/step - loss: 0.0869
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.4952
 39/116 [=========>....................] - ETA: 0s - loss: 0.0731
 76/116 [==================>...........] - ETA: 0s - loss: 0.0662
112/116 [===========================>..] - ETA: 0s - loss: 0.0682
116/116 [==============================] - 0s 1ms/step - loss: 0.0687
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 6.1515e-04
 38/116 [========>.....................] - ETA: 0s - loss: 0.1033    
 75/116 [==================>...........] - ETA: 0s - loss: 0.0810
112/116 [===========================>..] - ETA: 0s - loss: 0.0671
116/116 [==============================] - 0s 1ms/step - loss: 0.0654
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.3281
 40/116 [=========>....................] - ETA: 0s - loss: 0.0455
 78/116 [===================>..........] - ETA: 0s - loss: 0.0482
113/116 [============================>.] - ETA: 0s - loss: 0.0589
116/116 [==============================] - 0s 1ms/step - loss: 0.0580
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0036
 40/116 [=========>....................] - ETA: 0s - loss: 0.0716
 79/116 [===================>..........] - ETA: 0s - loss: 0.0590
116/116 [==============================] - ETA: 0s - loss: 0.0569
116/116 [==============================] - 0s 1ms/step - loss: 0.0569
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.2892
 38/116 [========>.....................] - ETA: 0s - loss: 0.0608
 75/116 [==================>...........] - ETA: 0s - loss: 0.0554
113/116 [============================>.] - ETA: 0s - loss: 0.0548
116/116 [==============================] - 0s 1ms/step - loss: 0.0539
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0160
 40/116 [=========>....................] - ETA: 0s - loss: 0.0528
 78/116 [===================>..........] - ETA: 0s - loss: 0.0548
113/116 [============================>.] - ETA: 0s - loss: 0.0522
116/116 [==============================] - 0s 1ms/step - loss: 0.0530
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1641
 36/116 [========>.....................] - ETA: 0s - loss: 0.0455
 73/116 [=================>............] - ETA: 0s - loss: 0.0553
112/116 [===========================>..] - ETA: 0s - loss: 0.0515
116/116 [==============================] - 0s 1ms/step - loss: 0.0517
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1451
 39/116 [=========>....................] - ETA: 0s - loss: 0.0260
 77/116 [==================>...........] - ETA: 0s - loss: 0.0451
115/116 [============================>.] - ETA: 0s - loss: 0.0528
116/116 [==============================] - 0s 1ms/step - loss: 0.0527
-> test with GAN.predict
GAN tn, fp: 282, 6
GAN fn, tp: 2, 7
GAN f1 score: 0.636
GAN cohens kappa score: 0.623

-> test with 'LR'
LR tn, fp: 282, 6
LR fn, tp: 0, 9
LR f1 score: 0.750
LR cohens kappa score: 0.740
LR average precision score: 0.696

-> test with 'RF'
RF tn, fp: 288, 0
RF fn, tp: 5, 4
RF f1 score: 0.615
RF cohens kappa score: 0.608

-> test with 'GB'
GB tn, fp: 288, 0
GB fn, tp: 3, 6
GB f1 score: 0.800
GB cohens kappa score: 0.795

-> test with 'KNN'
KNN tn, fp: 285, 3
KNN fn, tp: 1, 8
KNN f1 score: 0.800
KNN cohens kappa score: 0.793


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1116 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 22s - loss: 0.1764
 41/116 [=========>....................] - ETA: 0s - loss: 0.1014 
 80/116 [===================>..........] - ETA: 0s - loss: 0.0899
116/116 [==============================] - 0s 1ms/step - loss: 0.0804
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0128
 39/116 [=========>....................] - ETA: 0s - loss: 0.0899
 77/116 [==================>...........] - ETA: 0s - loss: 0.0707
110/116 [===========================>..] - ETA: 0s - loss: 0.0731
116/116 [==============================] - 0s 1ms/step - loss: 0.0717
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 6.9947e-04
 34/116 [=======>......................] - ETA: 0s - loss: 0.0689    
 68/116 [================>.............] - ETA: 0s - loss: 0.0668
107/116 [==========================>...] - ETA: 0s - loss: 0.0650
116/116 [==============================] - 0s 1ms/step - loss: 0.0653
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0993
 41/116 [=========>....................] - ETA: 0s - loss: 0.0837
 80/116 [===================>..........] - ETA: 0s - loss: 0.0670
113/116 [============================>.] - ETA: 0s - loss: 0.0616
116/116 [==============================] - 0s 1ms/step - loss: 0.0639
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0092
 37/116 [========>.....................] - ETA: 0s - loss: 0.0644
 73/116 [=================>............] - ETA: 0s - loss: 0.0529
112/116 [===========================>..] - ETA: 0s - loss: 0.0566
116/116 [==============================] - 0s 1ms/step - loss: 0.0608
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0019
 41/116 [=========>....................] - ETA: 0s - loss: 0.0747
 80/116 [===================>..........] - ETA: 0s - loss: 0.0606
116/116 [==============================] - 0s 1ms/step - loss: 0.0580
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0183
 40/116 [=========>....................] - ETA: 0s - loss: 0.0777
 80/116 [===================>..........] - ETA: 0s - loss: 0.0624
116/116 [==============================] - 0s 1ms/step - loss: 0.0574
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0028
 41/116 [=========>....................] - ETA: 0s - loss: 0.0593
 80/116 [===================>..........] - ETA: 0s - loss: 0.0662
116/116 [==============================] - 0s 1ms/step - loss: 0.0563
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0087
 38/116 [========>.....................] - ETA: 0s - loss: 0.0390
 72/116 [=================>............] - ETA: 0s - loss: 0.0540
111/116 [===========================>..] - ETA: 0s - loss: 0.0554
116/116 [==============================] - 0s 1ms/step - loss: 0.0572
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0144
 41/116 [=========>....................] - ETA: 0s - loss: 0.0584
 80/116 [===================>..........] - ETA: 0s - loss: 0.0570
116/116 [==============================] - 0s 1ms/step - loss: 0.0549
-> test with GAN.predict
GAN tn, fp: 285, 3
GAN fn, tp: 0, 8
GAN f1 score: 0.842
GAN cohens kappa score: 0.837

-> test with 'LR'
LR tn, fp: 276, 12
LR fn, tp: 0, 8
LR f1 score: 0.571
LR cohens kappa score: 0.554
LR average precision score: 0.754

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 1, 7
RF f1 score: 0.875
RF cohens kappa score: 0.872

-> test with 'GB'
GB tn, fp: 285, 3
GB fn, tp: 1, 7
GB f1 score: 0.778
GB cohens kappa score: 0.771

-> test with 'KNN'
KNN tn, fp: 274, 14
KNN fn, tp: 0, 8
KNN f1 score: 0.533
KNN cohens kappa score: 0.514


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

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 21s - loss: 0.0466
 41/116 [=========>....................] - ETA: 0s - loss: 0.0891 
 80/116 [===================>..........] - ETA: 0s - loss: 0.0658
116/116 [==============================] - 0s 1ms/step - loss: 0.0627
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0266
 40/116 [=========>....................] - ETA: 0s - loss: 0.0720
 78/116 [===================>..........] - ETA: 0s - loss: 0.0696
113/116 [============================>.] - ETA: 0s - loss: 0.0581
116/116 [==============================] - 0s 1ms/step - loss: 0.0571
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0033
 38/116 [========>.....................] - ETA: 0s - loss: 0.0726
 72/116 [=================>............] - ETA: 0s - loss: 0.0666
106/116 [==========================>...] - ETA: 0s - loss: 0.0668
116/116 [==============================] - 0s 1ms/step - loss: 0.0626
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0020
 35/116 [========>.....................] - ETA: 0s - loss: 0.0684
 72/116 [=================>............] - ETA: 0s - loss: 0.0630
109/116 [===========================>..] - ETA: 0s - loss: 0.0507
116/116 [==============================] - 0s 1ms/step - loss: 0.0550
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0305
 38/116 [========>.....................] - ETA: 0s - loss: 0.0695
 77/116 [==================>...........] - ETA: 0s - loss: 0.0670
114/116 [============================>.] - ETA: 0s - loss: 0.0536
116/116 [==============================] - 0s 1ms/step - loss: 0.0532
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0011
 37/116 [========>.....................] - ETA: 0s - loss: 0.0668
 74/116 [==================>...........] - ETA: 0s - loss: 0.0567
107/116 [==========================>...] - ETA: 0s - loss: 0.0555
116/116 [==============================] - 0s 1ms/step - loss: 0.0538
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0023
 36/116 [========>.....................] - ETA: 0s - loss: 0.0266
 72/116 [=================>............] - ETA: 0s - loss: 0.0546
111/116 [===========================>..] - ETA: 0s - loss: 0.0505
116/116 [==============================] - 0s 1ms/step - loss: 0.0517
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0034
 39/116 [=========>....................] - ETA: 0s - loss: 0.0364
 75/116 [==================>...........] - ETA: 0s - loss: 0.0474
113/116 [============================>.] - ETA: 0s - loss: 0.0509
116/116 [==============================] - 0s 1ms/step - loss: 0.0503
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0346
 39/116 [=========>....................] - ETA: 0s - loss: 0.0448
 77/116 [==================>...........] - ETA: 0s - loss: 0.0411
115/116 [============================>.] - ETA: 0s - loss: 0.0487
116/116 [==============================] - 0s 1ms/step - loss: 0.0486
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0067
 39/116 [=========>....................] - ETA: 0s - loss: 0.0657
 76/116 [==================>...........] - ETA: 0s - loss: 0.0501
112/116 [===========================>..] - ETA: 0s - loss: 0.0489
116/116 [==============================] - 0s 1ms/step - loss: 0.0485
-> test with GAN.predict
GAN tn, fp: 279, 9
GAN fn, tp: 0, 9
GAN f1 score: 0.667
GAN cohens kappa score: 0.653

-> test with 'LR'
LR tn, fp: 272, 16
LR fn, tp: 0, 9
LR f1 score: 0.529
LR cohens kappa score: 0.507
LR average precision score: 0.716

-> test with 'RF'
RF tn, fp: 285, 3
RF fn, tp: 1, 8
RF f1 score: 0.800
RF cohens kappa score: 0.793

-> test with 'GB'
GB tn, fp: 284, 4
GB fn, tp: 1, 8
GB f1 score: 0.762
GB cohens kappa score: 0.753

-> test with 'KNN'
KNN tn, fp: 273, 15
KNN fn, tp: 0, 9
KNN f1 score: 0.545
KNN cohens kappa score: 0.524


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.0690
 40/116 [=========>....................] - ETA: 0s - loss: 0.0508 
 79/116 [===================>..........] - ETA: 0s - loss: 0.0552
116/116 [==============================] - 0s 1ms/step - loss: 0.0557
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0264
 40/116 [=========>....................] - ETA: 0s - loss: 0.0662
 77/116 [==================>...........] - ETA: 0s - loss: 0.0554
116/116 [==============================] - 0s 1ms/step - loss: 0.0535
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0176
 39/116 [=========>....................] - ETA: 0s - loss: 0.0637
 75/116 [==================>...........] - ETA: 0s - loss: 0.0634
109/116 [===========================>..] - ETA: 0s - loss: 0.0548
116/116 [==============================] - 0s 1ms/step - loss: 0.0522
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0106
 38/116 [========>.....................] - ETA: 0s - loss: 0.0359
 73/116 [=================>............] - ETA: 0s - loss: 0.0385
111/116 [===========================>..] - ETA: 0s - loss: 0.0506
116/116 [==============================] - 0s 1ms/step - loss: 0.0498
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0029
 39/116 [=========>....................] - ETA: 0s - loss: 0.0453
 77/116 [==================>...........] - ETA: 0s - loss: 0.0456
115/116 [============================>.] - ETA: 0s - loss: 0.0481
116/116 [==============================] - 0s 1ms/step - loss: 0.0482
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1185
 38/116 [========>.....................] - ETA: 0s - loss: 0.0652
 75/116 [==================>...........] - ETA: 0s - loss: 0.0588
114/116 [============================>.] - ETA: 0s - loss: 0.0481
116/116 [==============================] - 0s 1ms/step - loss: 0.0476
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0393
 39/116 [=========>....................] - ETA: 0s - loss: 0.0482
 77/116 [==================>...........] - ETA: 0s - loss: 0.0517
115/116 [============================>.] - ETA: 0s - loss: 0.0480
116/116 [==============================] - 0s 1ms/step - loss: 0.0479
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1033
 39/116 [=========>....................] - ETA: 0s - loss: 0.0519
 77/116 [==================>...........] - ETA: 0s - loss: 0.0512
115/116 [============================>.] - ETA: 0s - loss: 0.0495
116/116 [==============================] - 0s 1ms/step - loss: 0.0494
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0458
 39/116 [=========>....................] - ETA: 0s - loss: 0.0419
 78/116 [===================>..........] - ETA: 0s - loss: 0.0412
116/116 [==============================] - 0s 1ms/step - loss: 0.0457
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.3206
 41/116 [=========>....................] - ETA: 0s - loss: 0.0630
 75/116 [==================>...........] - ETA: 0s - loss: 0.0509
106/116 [==========================>...] - ETA: 0s - loss: 0.0480
116/116 [==============================] - 0s 1ms/step - loss: 0.0475
-> test with GAN.predict
GAN tn, fp: 284, 4
GAN fn, tp: 3, 6
GAN f1 score: 0.632
GAN cohens kappa score: 0.619

-> test with 'LR'
LR tn, fp: 281, 7
LR fn, tp: 0, 9
LR f1 score: 0.720
LR cohens kappa score: 0.709
LR average precision score: 0.796

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 3, 6
RF f1 score: 0.750
RF cohens kappa score: 0.743

-> test with 'GB'
GB tn, fp: 287, 1
GB fn, tp: 4, 5
GB f1 score: 0.667
GB cohens kappa score: 0.658

-> test with 'KNN'
KNN tn, fp: 283, 5
KNN fn, tp: 1, 8
KNN f1 score: 0.727
KNN cohens kappa score: 0.717


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.0786
 40/116 [=========>....................] - ETA: 0s - loss: 0.0865 
 77/116 [==================>...........] - ETA: 0s - loss: 0.0743
115/116 [============================>.] - ETA: 0s - loss: 0.0688
116/116 [==============================] - 0s 1ms/step - loss: 0.0687
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0030
 38/116 [========>.....................] - ETA: 0s - loss: 0.0659
 77/116 [==================>...........] - ETA: 0s - loss: 0.0609
113/116 [============================>.] - ETA: 0s - loss: 0.0639
116/116 [==============================] - 0s 1ms/step - loss: 0.0629
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0143
 33/116 [=======>......................] - ETA: 0s - loss: 0.0465
 66/116 [================>.............] - ETA: 0s - loss: 0.0485
100/116 [========================>.....] - ETA: 0s - loss: 0.0609
116/116 [==============================] - 0s 2ms/step - loss: 0.0607
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0387
 39/116 [=========>....................] - ETA: 0s - loss: 0.0764
 77/116 [==================>...........] - ETA: 0s - loss: 0.0722
116/116 [==============================] - ETA: 0s - loss: 0.0634
116/116 [==============================] - 0s 1ms/step - loss: 0.0634
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0238
 40/116 [=========>....................] - ETA: 0s - loss: 0.0576
 78/116 [===================>..........] - ETA: 0s - loss: 0.0707
116/116 [==============================] - ETA: 0s - loss: 0.0619
116/116 [==============================] - 0s 1ms/step - loss: 0.0619
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1732
 41/116 [=========>....................] - ETA: 0s - loss: 0.0459
 80/116 [===================>..........] - ETA: 0s - loss: 0.0524
116/116 [==============================] - 0s 1ms/step - loss: 0.0576
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0909
 38/116 [========>.....................] - ETA: 0s - loss: 0.0577
 76/116 [==================>...........] - ETA: 0s - loss: 0.0640
114/116 [============================>.] - ETA: 0s - loss: 0.0577
116/116 [==============================] - 0s 1ms/step - loss: 0.0574
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0055
 39/116 [=========>....................] - ETA: 0s - loss: 0.0727
 78/116 [===================>..........] - ETA: 0s - loss: 0.0556
116/116 [==============================] - ETA: 0s - loss: 0.0549
116/116 [==============================] - 0s 1ms/step - loss: 0.0549
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0548
 40/116 [=========>....................] - ETA: 0s - loss: 0.0504
 78/116 [===================>..........] - ETA: 0s - loss: 0.0594
116/116 [==============================] - 0s 1ms/step - loss: 0.0528
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0148
 36/116 [========>.....................] - ETA: 0s - loss: 0.0346
 73/116 [=================>............] - ETA: 0s - loss: 0.0463
106/116 [==========================>...] - ETA: 0s - loss: 0.0474
116/116 [==============================] - 0s 1ms/step - loss: 0.0524
-> test with GAN.predict
GAN tn, fp: 285, 3
GAN fn, tp: 1, 8
GAN f1 score: 0.800
GAN cohens kappa score: 0.793

-> test with 'LR'
LR tn, fp: 277, 11
LR fn, tp: 0, 9
LR f1 score: 0.621
LR cohens kappa score: 0.604
LR average precision score: 0.756

-> test with 'RF'
RF tn, fp: 286, 2
RF fn, tp: 1, 8
RF f1 score: 0.842
RF cohens kappa score: 0.837

-> test with 'GB'
GB tn, fp: 286, 2
GB fn, tp: 1, 8
GB f1 score: 0.842
GB cohens kappa score: 0.837

-> test with 'KNN'
KNN tn, fp: 282, 6
KNN fn, tp: 0, 9
KNN f1 score: 0.750
KNN cohens kappa score: 0.740


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1117 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 1.5931
 38/116 [========>.....................] - ETA: 0s - loss: 0.2292 
 74/116 [==================>...........] - ETA: 0s - loss: 0.1895
113/116 [============================>.] - ETA: 0s - loss: 0.1564
116/116 [==============================] - 0s 1ms/step - loss: 0.1605
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.3052
 39/116 [=========>....................] - ETA: 0s - loss: 0.1323
 77/116 [==================>...........] - ETA: 0s - loss: 0.0994
112/116 [===========================>..] - ETA: 0s - loss: 0.0943
116/116 [==============================] - 0s 1ms/step - loss: 0.0920
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0276
 41/116 [=========>....................] - ETA: 0s - loss: 0.0667
 81/116 [===================>..........] - ETA: 0s - loss: 0.0737
116/116 [==============================] - 0s 1ms/step - loss: 0.0686
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0051
 39/116 [=========>....................] - ETA: 0s - loss: 0.0590
 77/116 [==================>...........] - ETA: 0s - loss: 0.0602
115/116 [============================>.] - ETA: 0s - loss: 0.0635
116/116 [==============================] - 0s 1ms/step - loss: 0.0634
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0091
 40/116 [=========>....................] - ETA: 0s - loss: 0.0508
 82/116 [====================>.........] - ETA: 0s - loss: 0.0547
116/116 [==============================] - 0s 1ms/step - loss: 0.0585
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0742
 39/116 [=========>....................] - ETA: 0s - loss: 0.0647
 77/116 [==================>...........] - ETA: 0s - loss: 0.0552
115/116 [============================>.] - ETA: 0s - loss: 0.0570
116/116 [==============================] - 0s 1ms/step - loss: 0.0570
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1070
 38/116 [========>.....................] - ETA: 0s - loss: 0.0432
 70/116 [=================>............] - ETA: 0s - loss: 0.0572
102/116 [=========================>....] - ETA: 0s - loss: 0.0533
116/116 [==============================] - 0s 1ms/step - loss: 0.0542
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0200
 36/116 [========>.....................] - ETA: 0s - loss: 0.0559
 74/116 [==================>...........] - ETA: 0s - loss: 0.0588
112/116 [===========================>..] - ETA: 0s - loss: 0.0543
116/116 [==============================] - 0s 1ms/step - loss: 0.0529
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0477
 40/116 [=========>....................] - ETA: 0s - loss: 0.0377
 79/116 [===================>..........] - ETA: 0s - loss: 0.0513
116/116 [==============================] - ETA: 0s - loss: 0.0536
116/116 [==============================] - 0s 1ms/step - loss: 0.0536
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0153
 34/116 [=======>......................] - ETA: 0s - loss: 0.0449
 71/116 [=================>............] - ETA: 0s - loss: 0.0447
109/116 [===========================>..] - ETA: 0s - loss: 0.0526
116/116 [==============================] - 0s 1ms/step - loss: 0.0526
-> test with GAN.predict
GAN tn, fp: 283, 5
GAN fn, tp: 3, 6
GAN f1 score: 0.600
GAN cohens kappa score: 0.586

-> test with 'LR'
LR tn, fp: 281, 7
LR fn, tp: 1, 8
LR f1 score: 0.667
LR cohens kappa score: 0.654
LR average precision score: 0.579

-> test with 'RF'
RF tn, fp: 287, 1
RF fn, tp: 3, 6
RF f1 score: 0.750
RF cohens kappa score: 0.743

-> test with 'GB'
GB tn, fp: 287, 1
GB fn, tp: 3, 6
GB f1 score: 0.750
GB cohens kappa score: 0.743

-> test with 'KNN'
KNN tn, fp: 283, 5
KNN fn, tp: 0, 9
KNN f1 score: 0.783
KNN cohens kappa score: 0.774


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1116 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 5.3343e-04
 35/116 [========>.....................] - ETA: 0s - loss: 0.0933     
 68/116 [================>.............] - ETA: 0s - loss: 0.0703
102/116 [=========================>....] - ETA: 0s - loss: 0.0661
116/116 [==============================] - 0s 1ms/step - loss: 0.0707
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0011
 40/116 [=========>....................] - ETA: 0s - loss: 0.0344
 73/116 [=================>............] - ETA: 0s - loss: 0.0572
107/116 [==========================>...] - ETA: 0s - loss: 0.0573
116/116 [==============================] - 0s 1ms/step - loss: 0.0614
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0016
 39/116 [=========>....................] - ETA: 0s - loss: 0.0683
 77/116 [==================>...........] - ETA: 0s - loss: 0.0630
113/116 [============================>.] - ETA: 0s - loss: 0.0616
116/116 [==============================] - 0s 1ms/step - loss: 0.0607
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0035
 38/116 [========>.....................] - ETA: 0s - loss: 0.0789
 76/116 [==================>...........] - ETA: 0s - loss: 0.0590
115/116 [============================>.] - ETA: 0s - loss: 0.0556
116/116 [==============================] - 0s 1ms/step - loss: 0.0555
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0497
 40/116 [=========>....................] - ETA: 0s - loss: 0.0424
 79/116 [===================>..........] - ETA: 0s - loss: 0.0622
116/116 [==============================] - 0s 1ms/step - loss: 0.0541
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0307
 39/116 [=========>....................] - ETA: 0s - loss: 0.0637
 77/116 [==================>...........] - ETA: 0s - loss: 0.0617
115/116 [============================>.] - ETA: 0s - loss: 0.0539
116/116 [==============================] - 0s 1ms/step - loss: 0.0538
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0186
 39/116 [=========>....................] - ETA: 0s - loss: 0.0785
 77/116 [==================>...........] - ETA: 0s - loss: 0.0575
115/116 [============================>.] - ETA: 0s - loss: 0.0513
116/116 [==============================] - 0s 1ms/step - loss: 0.0512
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0309
 39/116 [=========>....................] - ETA: 0s - loss: 0.0375
 80/116 [===================>..........] - ETA: 0s - loss: 0.0503
114/116 [============================>.] - ETA: 0s - loss: 0.0501
116/116 [==============================] - 0s 1ms/step - loss: 0.0498
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0185
 38/116 [========>.....................] - ETA: 0s - loss: 0.0519
 77/116 [==================>...........] - ETA: 0s - loss: 0.0509
116/116 [==============================] - 0s 1ms/step - loss: 0.0487
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0045
 39/116 [=========>....................] - ETA: 0s - loss: 0.0545
 78/116 [===================>..........] - ETA: 0s - loss: 0.0572
116/116 [==============================] - 0s 1ms/step - loss: 0.0474
-> test with GAN.predict
GAN tn, fp: 276, 12
GAN fn, tp: 2, 6
GAN f1 score: 0.462
GAN cohens kappa score: 0.441

-> test with 'LR'
LR tn, fp: 275, 13
LR fn, tp: 0, 8
LR f1 score: 0.552
LR cohens kappa score: 0.533
LR average precision score: 0.480

-> test with 'RF'
RF tn, fp: 284, 4
RF fn, tp: 3, 5
RF f1 score: 0.588
RF cohens kappa score: 0.576

-> test with 'GB'
GB tn, fp: 282, 6
GB fn, tp: 3, 5
GB f1 score: 0.526
GB cohens kappa score: 0.511

-> test with 'KNN'
KNN tn, fp: 274, 14
KNN fn, tp: 1, 7
KNN f1 score: 0.483
KNN cohens kappa score: 0.462

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 282, 17
LR fn, tp: 2, 9
LR f1 score: 0.750
LR cohens kappa score: 0.740
LR average precision score: 0.895


average:
LR tn, fp: 276.76, 11.24
LR fn, tp: 0.32, 8.48
LR f1 score: 0.601
LR cohens kappa score: 0.584
LR average precision score: 0.691


minimum:
LR tn, fp: 271, 6
LR fn, tp: 0, 7
LR f1 score: 0.471
LR cohens kappa score: 0.446
LR average precision score: 0.387


-----[ RF ]-----
maximum:
RF tn, fp: 288, 8
RF fn, tp: 5, 9
RF f1 score: 0.889
RF cohens kappa score: 0.885


average:
RF tn, fp: 285.44, 2.56
RF fn, tp: 2.32, 6.48
RF f1 score: 0.727
RF cohens kappa score: 0.718


minimum:
RF tn, fp: 280, 0
RF fn, tp: 0, 4
RF f1 score: 0.455
RF cohens kappa score: 0.434


-----[ GB ]-----
maximum:
GB tn, fp: 288, 8
GB fn, tp: 6, 8
GB f1 score: 0.889
GB cohens kappa score: 0.885


average:
GB tn, fp: 285.04, 2.96
GB fn, tp: 2.28, 6.52
GB f1 score: 0.714
GB cohens kappa score: 0.705


minimum:
GB tn, fp: 280, 0
GB fn, tp: 0, 3
GB f1 score: 0.300
GB cohens kappa score: 0.276


-----[ KNN ]-----
maximum:
KNN tn, fp: 287, 15
KNN fn, tp: 3, 9
KNN f1 score: 0.947
KNN cohens kappa score: 0.946


average:
KNN tn, fp: 279.0, 9.0
KNN fn, tp: 0.32, 8.48
KNN f1 score: 0.659
KNN cohens kappa score: 0.645


minimum:
KNN tn, fp: 273, 1
KNN fn, tp: 0, 6
KNN f1 score: 0.483
KNN cohens kappa score: 0.462


-----[ GAN ]-----
maximum:
GAN tn, fp: 286, 12
GAN fn, tp: 3, 9
GAN f1 score: 0.842
GAN cohens kappa score: 0.837


average:
GAN tn, fp: 281.0, 7.0
GAN fn, tp: 1.52, 7.28
GAN f1 score: 0.637
GAN cohens kappa score: 0.623


minimum:
GAN tn, fp: 276, 2
GAN fn, tp: 0, 6
GAN f1 score: 0.462
GAN cohens kappa score: 0.441