ConvGeNBenchmarkResults/data_result/convGAN-majority-full/folding_yeast6.log

///////////////////////////////////////////
// Running convGAN-majority-full on folding_yeast6
///////////////////////////////////////////

Load 'data_input/folding_yeast6'
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 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0325
 42/116 [=========>....................] - ETA: 0s - loss: 0.0923 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0684
116/116 [==============================] - 0s 1ms/step - loss: 0.0682
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0017
 41/116 [=========>....................] - ETA: 0s - loss: 0.0540
 79/116 [===================>..........] - ETA: 0s - loss: 0.0656
116/116 [==============================] - 0s 1ms/step - loss: 0.0663
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1729
 42/116 [=========>....................] - ETA: 0s - loss: 0.0515
 83/116 [====================>.........] - ETA: 0s - loss: 0.0622
116/116 [==============================] - 0s 1ms/step - loss: 0.0676
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0199
 42/116 [=========>....................] - ETA: 0s - loss: 0.0681
 82/116 [====================>.........] - ETA: 0s - loss: 0.0648
116/116 [==============================] - 0s 1ms/step - loss: 0.0681
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0034
 41/116 [=========>....................] - ETA: 0s - loss: 0.0905
 77/116 [==================>...........] - ETA: 0s - loss: 0.0687
113/116 [============================>.] - ETA: 0s - loss: 0.0668
116/116 [==============================] - 0s 1ms/step - loss: 0.0662
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0106
 42/116 [=========>....................] - ETA: 0s - loss: 0.0557
 84/116 [====================>.........] - ETA: 0s - loss: 0.0663
116/116 [==============================] - 0s 1ms/step - loss: 0.0643
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0061
 43/116 [==========>...................] - ETA: 0s - loss: 0.0716
 82/116 [====================>.........] - ETA: 0s - loss: 0.0626
116/116 [==============================] - 0s 1ms/step - loss: 0.0634
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0148
 41/116 [=========>....................] - ETA: 0s - loss: 0.0518
 81/116 [===================>..........] - ETA: 0s - loss: 0.0581
116/116 [==============================] - 0s 1ms/step - loss: 0.0650
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0111
 42/116 [=========>....................] - ETA: 0s - loss: 0.0808
 78/116 [===================>..........] - ETA: 0s - loss: 0.0663
112/116 [===========================>..] - ETA: 0s - loss: 0.0654
116/116 [==============================] - 0s 1ms/step - loss: 0.0648
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0128
 35/116 [========>.....................] - ETA: 0s - loss: 0.0465
 77/116 [==================>...........] - ETA: 0s - loss: 0.0488
116/116 [==============================] - 0s 1ms/step - loss: 0.0633
-> test with GAN.predict
GAN tn, fp: 280, 10
GAN fn, tp: 1, 6
GAN f1 score: 0.522
GAN cohens kappa score: 0.506

-> test with 'LR'
LR tn, fp: 271, 19
LR fn, tp: 1, 6
LR f1 score: 0.375
LR cohens kappa score: 0.351
LR average precision score: 0.691

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 3, 4
RF f1 score: 0.615
RF cohens kappa score: 0.607

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 4, 3
GB f1 score: 0.462
GB cohens kappa score: 0.450

-> test with 'KNN'
KNN tn, fp: 274, 16
KNN fn, tp: 1, 6
KNN f1 score: 0.414
KNN cohens kappa score: 0.392


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.5048
 42/116 [=========>....................] - ETA: 0s - loss: 0.0595 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0557
116/116 [==============================] - 0s 1ms/step - loss: 0.0591
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0515
 39/116 [=========>....................] - ETA: 0s - loss: 0.0614
 79/116 [===================>..........] - ETA: 0s - loss: 0.0613
116/116 [==============================] - 0s 1ms/step - loss: 0.0565
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0044
 41/116 [=========>....................] - ETA: 0s - loss: 0.0434
 82/116 [====================>.........] - ETA: 0s - loss: 0.0575
116/116 [==============================] - 0s 1ms/step - loss: 0.0554
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1211
 41/116 [=========>....................] - ETA: 0s - loss: 0.0591
 82/116 [====================>.........] - ETA: 0s - loss: 0.0547
116/116 [==============================] - 0s 1ms/step - loss: 0.0554
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0630
 42/116 [=========>....................] - ETA: 0s - loss: 0.0512
 83/116 [====================>.........] - ETA: 0s - loss: 0.0496
116/116 [==============================] - 0s 1ms/step - loss: 0.0533
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0130
 41/116 [=========>....................] - ETA: 0s - loss: 0.0403
 82/116 [====================>.........] - ETA: 0s - loss: 0.0457
116/116 [==============================] - 0s 1ms/step - loss: 0.0527
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0081
 40/116 [=========>....................] - ETA: 0s - loss: 0.0499
 76/116 [==================>...........] - ETA: 0s - loss: 0.0532
110/116 [===========================>..] - ETA: 0s - loss: 0.0541
116/116 [==============================] - 0s 1ms/step - loss: 0.0536
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0216
 34/116 [=======>......................] - ETA: 0s - loss: 0.0474
 70/116 [=================>............] - ETA: 0s - loss: 0.0569
110/116 [===========================>..] - ETA: 0s - loss: 0.0533
116/116 [==============================] - 0s 1ms/step - loss: 0.0523
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0209
 39/116 [=========>....................] - ETA: 0s - loss: 0.0531
 76/116 [==================>...........] - ETA: 0s - loss: 0.0545
116/116 [==============================] - 0s 1ms/step - loss: 0.0503
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0118
 43/116 [==========>...................] - ETA: 0s - loss: 0.0387
 81/116 [===================>..........] - ETA: 0s - loss: 0.0510
116/116 [==============================] - 0s 1ms/step - loss: 0.0525
-> test with GAN.predict
GAN tn, fp: 279, 11
GAN fn, tp: 3, 4
GAN f1 score: 0.364
GAN cohens kappa score: 0.343

-> test with 'LR'
LR tn, fp: 268, 22
LR fn, tp: 2, 5
LR f1 score: 0.294
LR cohens kappa score: 0.267
LR average precision score: 0.425

-> test with 'RF'
RF tn, fp: 286, 4
RF fn, tp: 3, 4
RF f1 score: 0.533
RF cohens kappa score: 0.521

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 3, 4
GB f1 score: 0.533
GB cohens kappa score: 0.521

-> test with 'KNN'
KNN tn, fp: 274, 16
KNN fn, tp: 3, 4
KNN f1 score: 0.296
KNN cohens kappa score: 0.271


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0382
 35/116 [========>.....................] - ETA: 0s - loss: 0.0640 
 70/116 [=================>............] - ETA: 0s - loss: 0.0766
108/116 [==========================>...] - ETA: 0s - loss: 0.0787
116/116 [==============================] - 0s 1ms/step - loss: 0.0779
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0494
 35/116 [========>.....................] - ETA: 0s - loss: 0.0614
 71/116 [=================>............] - ETA: 0s - loss: 0.0617
110/116 [===========================>..] - ETA: 0s - loss: 0.0705
116/116 [==============================] - 0s 1ms/step - loss: 0.0731
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0249
 36/116 [========>.....................] - ETA: 0s - loss: 0.0672
 71/116 [=================>............] - ETA: 0s - loss: 0.0671
108/116 [==========================>...] - ETA: 0s - loss: 0.0726
116/116 [==============================] - 0s 1ms/step - loss: 0.0732
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0310
 37/116 [========>.....................] - ETA: 0s - loss: 0.0752
 71/116 [=================>............] - ETA: 0s - loss: 0.0726
103/116 [=========================>....] - ETA: 0s - loss: 0.0720
116/116 [==============================] - 0s 2ms/step - loss: 0.0753
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0158
 31/116 [=======>......................] - ETA: 0s - loss: 0.0761
 66/116 [================>.............] - ETA: 0s - loss: 0.0724
101/116 [=========================>....] - ETA: 0s - loss: 0.0690
116/116 [==============================] - 0s 2ms/step - loss: 0.0713
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1786
 37/116 [========>.....................] - ETA: 0s - loss: 0.0624
 72/116 [=================>............] - ETA: 0s - loss: 0.0694
104/116 [=========================>....] - ETA: 0s - loss: 0.0748
116/116 [==============================] - 0s 1ms/step - loss: 0.0703
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0086
 37/116 [========>.....................] - ETA: 0s - loss: 0.0561
 72/116 [=================>............] - ETA: 0s - loss: 0.0682
104/116 [=========================>....] - ETA: 0s - loss: 0.0705
116/116 [==============================] - 0s 1ms/step - loss: 0.0703
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.2089
 41/116 [=========>....................] - ETA: 0s - loss: 0.0673
 77/116 [==================>...........] - ETA: 0s - loss: 0.0698
110/116 [===========================>..] - ETA: 0s - loss: 0.0730
116/116 [==============================] - 0s 1ms/step - loss: 0.0735
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1529
 41/116 [=========>....................] - ETA: 0s - loss: 0.0904
 77/116 [==================>...........] - ETA: 0s - loss: 0.0784
111/116 [===========================>..] - ETA: 0s - loss: 0.0666
116/116 [==============================] - 0s 1ms/step - loss: 0.0671
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0292
 35/116 [========>.....................] - ETA: 0s - loss: 0.0489
 71/116 [=================>............] - ETA: 0s - loss: 0.0558
105/116 [==========================>...] - ETA: 0s - loss: 0.0679
116/116 [==============================] - 0s 1ms/step - loss: 0.0663
-> test with GAN.predict
GAN tn, fp: 284, 6
GAN fn, tp: 3, 4
GAN f1 score: 0.471
GAN cohens kappa score: 0.455

-> test with 'LR'
LR tn, fp: 266, 24
LR fn, tp: 1, 6
LR f1 score: 0.324
LR cohens kappa score: 0.297
LR average precision score: 0.309

-> test with 'RF'
RF tn, fp: 290, 0
RF fn, tp: 3, 4
RF f1 score: 0.727
RF cohens kappa score: 0.723

-> test with 'GB'
GB tn, fp: 289, 1
GB fn, tp: 2, 5
GB f1 score: 0.769
GB cohens kappa score: 0.764

-> test with 'KNN'
KNN tn, fp: 278, 12
KNN fn, tp: 1, 6
KNN f1 score: 0.480
KNN cohens kappa score: 0.462


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0099
 38/116 [========>.....................] - ETA: 0s - loss: 0.0406 
 78/116 [===================>..........] - ETA: 0s - loss: 0.0619
116/116 [==============================] - 0s 1ms/step - loss: 0.0629
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0457
 40/116 [=========>....................] - ETA: 0s - loss: 0.0771
 80/116 [===================>..........] - ETA: 0s - loss: 0.0604
116/116 [==============================] - 0s 1ms/step - loss: 0.0631
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0108
 38/116 [========>.....................] - ETA: 0s - loss: 0.0645
 78/116 [===================>..........] - ETA: 0s - loss: 0.0663
116/116 [==============================] - 0s 1ms/step - loss: 0.0618
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0490
 41/116 [=========>....................] - ETA: 0s - loss: 0.0647
 82/116 [====================>.........] - ETA: 0s - loss: 0.0595
116/116 [==============================] - 0s 1ms/step - loss: 0.0611
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0198
 42/116 [=========>....................] - ETA: 0s - loss: 0.0523
 82/116 [====================>.........] - ETA: 0s - loss: 0.0586
116/116 [==============================] - 0s 1ms/step - loss: 0.0589
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1889
 42/116 [=========>....................] - ETA: 0s - loss: 0.0578
 83/116 [====================>.........] - ETA: 0s - loss: 0.0596
116/116 [==============================] - 0s 1ms/step - loss: 0.0596
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0445
 39/116 [=========>....................] - ETA: 0s - loss: 0.0617
 77/116 [==================>...........] - ETA: 0s - loss: 0.0556
111/116 [===========================>..] - ETA: 0s - loss: 0.0597
116/116 [==============================] - 0s 1ms/step - loss: 0.0585
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0064
 37/116 [========>.....................] - ETA: 0s - loss: 0.0393
 76/116 [==================>...........] - ETA: 0s - loss: 0.0592
112/116 [===========================>..] - ETA: 0s - loss: 0.0574
116/116 [==============================] - 0s 1ms/step - loss: 0.0588
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0294
 40/116 [=========>....................] - ETA: 0s - loss: 0.0893
 80/116 [===================>..........] - ETA: 0s - loss: 0.0671
116/116 [==============================] - 0s 1ms/step - loss: 0.0598
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0195
 41/116 [=========>....................] - ETA: 0s - loss: 0.0637
 80/116 [===================>..........] - ETA: 0s - loss: 0.0530
116/116 [==============================] - 0s 1ms/step - loss: 0.0603
-> test with GAN.predict
GAN tn, fp: 287, 3
GAN fn, tp: 4, 3
GAN f1 score: 0.462
GAN cohens kappa score: 0.450

-> test with 'LR'
LR tn, fp: 275, 15
LR fn, tp: 2, 5
LR f1 score: 0.370
LR cohens kappa score: 0.348
LR average precision score: 0.620

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 4, 3
RF f1 score: 0.545
RF cohens kappa score: 0.538

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 4, 3
GB f1 score: 0.429
GB cohens kappa score: 0.415

-> test with 'KNN'
KNN tn, fp: 282, 8
KNN fn, tp: 1, 6
KNN f1 score: 0.571
KNN cohens kappa score: 0.558


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 16s - loss: 0.0157
 38/116 [========>.....................] - ETA: 0s - loss: 0.0677 
 79/116 [===================>..........] - ETA: 0s - loss: 0.0687
116/116 [==============================] - 0s 1ms/step - loss: 0.0686
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0086
 41/116 [=========>....................] - ETA: 0s - loss: 0.0576
 80/116 [===================>..........] - ETA: 0s - loss: 0.0618
116/116 [==============================] - ETA: 0s - loss: 0.0664
116/116 [==============================] - 0s 1ms/step - loss: 0.0664
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1168
 39/116 [=========>....................] - ETA: 0s - loss: 0.0612
 77/116 [==================>...........] - ETA: 0s - loss: 0.0623
116/116 [==============================] - 0s 1ms/step - loss: 0.0665
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0106
 38/116 [========>.....................] - ETA: 0s - loss: 0.0401
 77/116 [==================>...........] - ETA: 0s - loss: 0.0548
111/116 [===========================>..] - ETA: 0s - loss: 0.0620
116/116 [==============================] - 0s 1ms/step - loss: 0.0639
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0745
 37/116 [========>.....................] - ETA: 0s - loss: 0.0616
 73/116 [=================>............] - ETA: 0s - loss: 0.0578
112/116 [===========================>..] - ETA: 0s - loss: 0.0628
116/116 [==============================] - 0s 1ms/step - loss: 0.0631
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0539
 36/116 [========>.....................] - ETA: 0s - loss: 0.0535
 76/116 [==================>...........] - ETA: 0s - loss: 0.0549
114/116 [============================>.] - ETA: 0s - loss: 0.0622
116/116 [==============================] - 0s 1ms/step - loss: 0.0624
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0522
 36/116 [========>.....................] - ETA: 0s - loss: 0.0646
 74/116 [==================>...........] - ETA: 0s - loss: 0.0637
110/116 [===========================>..] - ETA: 0s - loss: 0.0621
116/116 [==============================] - 0s 1ms/step - loss: 0.0625
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0574
 37/116 [========>.....................] - ETA: 0s - loss: 0.0590
 74/116 [==================>...........] - ETA: 0s - loss: 0.0611
113/116 [============================>.] - ETA: 0s - loss: 0.0637
116/116 [==============================] - 0s 1ms/step - loss: 0.0626
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0768
 37/116 [========>.....................] - ETA: 0s - loss: 0.0708
 69/116 [================>.............] - ETA: 0s - loss: 0.0614
103/116 [=========================>....] - ETA: 0s - loss: 0.0622
116/116 [==============================] - 0s 1ms/step - loss: 0.0597
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1747
 38/116 [========>.....................] - ETA: 0s - loss: 0.0719
 75/116 [==================>...........] - ETA: 0s - loss: 0.0653
112/116 [===========================>..] - ETA: 0s - loss: 0.0623
116/116 [==============================] - 0s 1ms/step - loss: 0.0612
-> test with GAN.predict
GAN tn, fp: 284, 5
GAN fn, tp: 2, 5
GAN f1 score: 0.588
GAN cohens kappa score: 0.576

-> test with 'LR'
LR tn, fp: 257, 32
LR fn, tp: 0, 7
LR f1 score: 0.304
LR cohens kappa score: 0.275
LR average precision score: 0.604

-> test with 'RF'
RF tn, fp: 287, 2
RF fn, tp: 2, 5
RF f1 score: 0.714
RF cohens kappa score: 0.707

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

-> test with 'KNN'
KNN tn, fp: 271, 18
KNN fn, tp: 1, 6
KNN f1 score: 0.387
KNN cohens kappa score: 0.364


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

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.0174
 43/116 [==========>...................] - ETA: 0s - loss: 0.0746 
 85/116 [====================>.........] - ETA: 0s - loss: 0.0571
116/116 [==============================] - 0s 1ms/step - loss: 0.0543
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1193
 34/116 [=======>......................] - ETA: 0s - loss: 0.0283
 74/116 [==================>...........] - ETA: 0s - loss: 0.0474
114/116 [============================>.] - ETA: 0s - loss: 0.0497
116/116 [==============================] - 0s 1ms/step - loss: 0.0491
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.3540
 42/116 [=========>....................] - ETA: 0s - loss: 0.0720
 82/116 [====================>.........] - ETA: 0s - loss: 0.0579
116/116 [==============================] - 0s 1ms/step - loss: 0.0481
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0796
 41/116 [=========>....................] - ETA: 0s - loss: 0.0372
 82/116 [====================>.........] - ETA: 0s - loss: 0.0462
116/116 [==============================] - 0s 1ms/step - loss: 0.0505
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0836
 40/116 [=========>....................] - ETA: 0s - loss: 0.0521
 79/116 [===================>..........] - ETA: 0s - loss: 0.0523
116/116 [==============================] - 0s 1ms/step - loss: 0.0491
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0086
 40/116 [=========>....................] - ETA: 0s - loss: 0.0400
 81/116 [===================>..........] - ETA: 0s - loss: 0.0514
116/116 [==============================] - 0s 1ms/step - loss: 0.0470
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0188
 42/116 [=========>....................] - ETA: 0s - loss: 0.0414
 82/116 [====================>.........] - ETA: 0s - loss: 0.0476
116/116 [==============================] - 0s 1ms/step - loss: 0.0476
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0132
 41/116 [=========>....................] - ETA: 0s - loss: 0.0383
 81/116 [===================>..........] - ETA: 0s - loss: 0.0446
116/116 [==============================] - 0s 1ms/step - loss: 0.0468
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0115
 41/116 [=========>....................] - ETA: 0s - loss: 0.0501
 82/116 [====================>.........] - ETA: 0s - loss: 0.0487
116/116 [==============================] - 0s 1ms/step - loss: 0.0449
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0183
 35/116 [========>.....................] - ETA: 0s - loss: 0.0489
 67/116 [================>.............] - ETA: 0s - loss: 0.0411
107/116 [==========================>...] - ETA: 0s - loss: 0.0402
116/116 [==============================] - 0s 1ms/step - loss: 0.0467
-> test with GAN.predict
GAN tn, fp: 280, 10
GAN fn, tp: 2, 5
GAN f1 score: 0.455
GAN cohens kappa score: 0.436

-> test with 'LR'
LR tn, fp: 277, 13
LR fn, tp: 1, 6
LR f1 score: 0.462
LR cohens kappa score: 0.442
LR average precision score: 0.669

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 3, 4
RF f1 score: 0.571
RF cohens kappa score: 0.561

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 3, 4
GB f1 score: 0.533
GB cohens kappa score: 0.521

-> test with 'KNN'
KNN tn, fp: 279, 11
KNN fn, tp: 2, 5
KNN f1 score: 0.435
KNN cohens kappa score: 0.416


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.0153
 41/116 [=========>....................] - ETA: 0s - loss: 0.0787 
 82/116 [====================>.........] - ETA: 0s - loss: 0.0736
116/116 [==============================] - 0s 1ms/step - loss: 0.0868
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0783
 41/116 [=========>....................] - ETA: 0s - loss: 0.0750
 82/116 [====================>.........] - ETA: 0s - loss: 0.0873
116/116 [==============================] - 0s 1ms/step - loss: 0.0859
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.1277
 42/116 [=========>....................] - ETA: 0s - loss: 0.0885
 82/116 [====================>.........] - ETA: 0s - loss: 0.0842
116/116 [==============================] - 0s 1ms/step - loss: 0.0787
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0055
 41/116 [=========>....................] - ETA: 0s - loss: 0.0687
 81/116 [===================>..........] - ETA: 0s - loss: 0.0791
116/116 [==============================] - 0s 1ms/step - loss: 0.0787
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0100
 38/116 [========>.....................] - ETA: 0s - loss: 0.0532
 78/116 [===================>..........] - ETA: 0s - loss: 0.0699
116/116 [==============================] - 0s 1ms/step - loss: 0.0759
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0334
 41/116 [=========>....................] - ETA: 0s - loss: 0.0918
 80/116 [===================>..........] - ETA: 0s - loss: 0.0706
116/116 [==============================] - 0s 1ms/step - loss: 0.0734
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0301
 42/116 [=========>....................] - ETA: 0s - loss: 0.0560
 83/116 [====================>.........] - ETA: 0s - loss: 0.0604
116/116 [==============================] - 0s 1ms/step - loss: 0.0754
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0971
 42/116 [=========>....................] - ETA: 0s - loss: 0.0762
 83/116 [====================>.........] - ETA: 0s - loss: 0.0745
116/116 [==============================] - 0s 1ms/step - loss: 0.0744
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.2248
 41/116 [=========>....................] - ETA: 0s - loss: 0.0926
 82/116 [====================>.........] - ETA: 0s - loss: 0.0779
116/116 [==============================] - 0s 1ms/step - loss: 0.0740
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.1185
 35/116 [========>.....................] - ETA: 0s - loss: 0.0538
 69/116 [================>.............] - ETA: 0s - loss: 0.0696
106/116 [==========================>...] - ETA: 0s - loss: 0.0682
116/116 [==============================] - 0s 1ms/step - loss: 0.0722
-> test with GAN.predict
GAN tn, fp: 275, 15
GAN fn, tp: 1, 6
GAN f1 score: 0.429
GAN cohens kappa score: 0.408

-> test with 'LR'
LR tn, fp: 261, 29
LR fn, tp: 0, 7
LR f1 score: 0.326
LR cohens kappa score: 0.298
LR average precision score: 0.293

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 3, 4
RF f1 score: 0.615
RF cohens kappa score: 0.607

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 0, 7
GB f1 score: 0.778
GB cohens kappa score: 0.771

-> test with 'KNN'
KNN tn, fp: 272, 18
KNN fn, tp: 0, 7
KNN f1 score: 0.438
KNN cohens kappa score: 0.416


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0378
 42/116 [=========>....................] - ETA: 0s - loss: 0.0748 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0604
116/116 [==============================] - 0s 1ms/step - loss: 0.0617
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0675
 39/116 [=========>....................] - ETA: 0s - loss: 0.0645
 79/116 [===================>..........] - ETA: 0s - loss: 0.0715
116/116 [==============================] - 0s 1ms/step - loss: 0.0627
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0067
 40/116 [=========>....................] - ETA: 0s - loss: 0.0606
 78/116 [===================>..........] - ETA: 0s - loss: 0.0623
116/116 [==============================] - 0s 1ms/step - loss: 0.0604
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0435
 41/116 [=========>....................] - ETA: 0s - loss: 0.0565
 81/116 [===================>..........] - ETA: 0s - loss: 0.0573
116/116 [==============================] - 0s 1ms/step - loss: 0.0578
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0099
 42/116 [=========>....................] - ETA: 0s - loss: 0.0698
 83/116 [====================>.........] - ETA: 0s - loss: 0.0662
116/116 [==============================] - 0s 1ms/step - loss: 0.0605
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1095
 41/116 [=========>....................] - ETA: 0s - loss: 0.0576
 80/116 [===================>..........] - ETA: 0s - loss: 0.0626
116/116 [==============================] - 0s 1ms/step - loss: 0.0585
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1753
 35/116 [========>.....................] - ETA: 0s - loss: 0.0540
 73/116 [=================>............] - ETA: 0s - loss: 0.0503
109/116 [===========================>..] - ETA: 0s - loss: 0.0624
116/116 [==============================] - 0s 1ms/step - loss: 0.0611
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0670
 42/116 [=========>....................] - ETA: 0s - loss: 0.0601
 80/116 [===================>..........] - ETA: 0s - loss: 0.0515
116/116 [==============================] - 0s 1ms/step - loss: 0.0581
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0096
 35/116 [========>.....................] - ETA: 0s - loss: 0.0638
 70/116 [=================>............] - ETA: 0s - loss: 0.0666
102/116 [=========================>....] - ETA: 0s - loss: 0.0628
116/116 [==============================] - 0s 1ms/step - loss: 0.0629
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0674
 40/116 [=========>....................] - ETA: 0s - loss: 0.0695
 79/116 [===================>..........] - ETA: 0s - loss: 0.0659
116/116 [==============================] - 0s 1ms/step - loss: 0.0584
-> test with GAN.predict
GAN tn, fp: 282, 8
GAN fn, tp: 2, 5
GAN f1 score: 0.500
GAN cohens kappa score: 0.484

-> test with 'LR'
LR tn, fp: 264, 26
LR fn, tp: 1, 6
LR f1 score: 0.308
LR cohens kappa score: 0.280
LR average precision score: 0.536

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 3, 4
RF f1 score: 0.615
RF cohens kappa score: 0.607

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 3, 4
GB f1 score: 0.533
GB cohens kappa score: 0.521

-> test with 'KNN'
KNN tn, fp: 274, 16
KNN fn, tp: 2, 5
KNN f1 score: 0.357
KNN cohens kappa score: 0.334


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0154
 42/116 [=========>....................] - ETA: 0s - loss: 0.0650 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0536
116/116 [==============================] - 0s 1ms/step - loss: 0.0519
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0435
 42/116 [=========>....................] - ETA: 0s - loss: 0.0285
 82/116 [====================>.........] - ETA: 0s - loss: 0.0541
116/116 [==============================] - 0s 1ms/step - loss: 0.0507
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0051
 44/116 [==========>...................] - ETA: 0s - loss: 0.0516
 85/116 [====================>.........] - ETA: 0s - loss: 0.0478
116/116 [==============================] - 0s 1ms/step - loss: 0.0523
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1251
 42/116 [=========>....................] - ETA: 0s - loss: 0.0477
 83/116 [====================>.........] - ETA: 0s - loss: 0.0538
116/116 [==============================] - 0s 1ms/step - loss: 0.0556
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0285
 41/116 [=========>....................] - ETA: 0s - loss: 0.0407
 82/116 [====================>.........] - ETA: 0s - loss: 0.0449
116/116 [==============================] - 0s 1ms/step - loss: 0.0518
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1378
 41/116 [=========>....................] - ETA: 0s - loss: 0.0506
 80/116 [===================>..........] - ETA: 0s - loss: 0.0557
116/116 [==============================] - 0s 1ms/step - loss: 0.0506
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0321
 40/116 [=========>....................] - ETA: 0s - loss: 0.0409
 81/116 [===================>..........] - ETA: 0s - loss: 0.0472
116/116 [==============================] - 0s 1ms/step - loss: 0.0533
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0054
 41/116 [=========>....................] - ETA: 0s - loss: 0.0524
 82/116 [====================>.........] - ETA: 0s - loss: 0.0504
116/116 [==============================] - 0s 1ms/step - loss: 0.0507
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0065
 38/116 [========>.....................] - ETA: 0s - loss: 0.0586
 72/116 [=================>............] - ETA: 0s - loss: 0.0489
106/116 [==========================>...] - ETA: 0s - loss: 0.0470
116/116 [==============================] - 0s 1ms/step - loss: 0.0483
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0264
 41/116 [=========>....................] - ETA: 0s - loss: 0.0474
 79/116 [===================>..........] - ETA: 0s - loss: 0.0499
116/116 [==============================] - 0s 1ms/step - loss: 0.0492
-> test with GAN.predict
GAN tn, fp: 284, 6
GAN fn, tp: 2, 5
GAN f1 score: 0.556
GAN cohens kappa score: 0.542

-> test with 'LR'
LR tn, fp: 269, 21
LR fn, tp: 2, 5
LR f1 score: 0.303
LR cohens kappa score: 0.276
LR average precision score: 0.576

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 5, 2
RF f1 score: 0.400
RF cohens kappa score: 0.391

-> test with 'GB'
GB tn, fp: 287, 3
GB fn, tp: 5, 2
GB f1 score: 0.333
GB cohens kappa score: 0.320

-> test with 'KNN'
KNN tn, fp: 276, 14
KNN fn, tp: 3, 4
KNN f1 score: 0.320
KNN cohens kappa score: 0.296


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 41s - loss: 0.1905
 40/116 [=========>....................] - ETA: 0s - loss: 0.0578 
 78/116 [===================>..........] - ETA: 0s - loss: 0.0604
114/116 [============================>.] - ETA: 0s - loss: 0.0625
116/116 [==============================] - 1s 1ms/step - loss: 0.0620
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0272
 39/116 [=========>....................] - ETA: 0s - loss: 0.0671
 76/116 [==================>...........] - ETA: 0s - loss: 0.0676
108/116 [==========================>...] - ETA: 0s - loss: 0.0645
116/116 [==============================] - 0s 1ms/step - loss: 0.0619
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0353
 42/116 [=========>....................] - ETA: 0s - loss: 0.0477
 80/116 [===================>..........] - ETA: 0s - loss: 0.0531
116/116 [==============================] - 0s 1ms/step - loss: 0.0603
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0049
 41/116 [=========>....................] - ETA: 0s - loss: 0.0693
 85/116 [====================>.........] - ETA: 0s - loss: 0.0593
116/116 [==============================] - 0s 1ms/step - loss: 0.0586
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0533
 38/116 [========>.....................] - ETA: 0s - loss: 0.0399
 76/116 [==================>...........] - ETA: 0s - loss: 0.0609
116/116 [==============================] - ETA: 0s - loss: 0.0585
116/116 [==============================] - 0s 1ms/step - loss: 0.0585
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0070
 38/116 [========>.....................] - ETA: 0s - loss: 0.0652
 76/116 [==================>...........] - ETA: 0s - loss: 0.0581
112/116 [===========================>..] - ETA: 0s - loss: 0.0593
116/116 [==============================] - 0s 1ms/step - loss: 0.0588
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1955
 42/116 [=========>....................] - ETA: 0s - loss: 0.0615
 75/116 [==================>...........] - ETA: 0s - loss: 0.0618
114/116 [============================>.] - ETA: 0s - loss: 0.0594
116/116 [==============================] - 0s 1ms/step - loss: 0.0589
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0852
 38/116 [========>.....................] - ETA: 0s - loss: 0.0508
 75/116 [==================>...........] - ETA: 0s - loss: 0.0569
112/116 [===========================>..] - ETA: 0s - loss: 0.0593
116/116 [==============================] - 0s 1ms/step - loss: 0.0584
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0697
 38/116 [========>.....................] - ETA: 0s - loss: 0.0596
 74/116 [==================>...........] - ETA: 0s - loss: 0.0646
110/116 [===========================>..] - ETA: 0s - loss: 0.0609
116/116 [==============================] - 0s 1ms/step - loss: 0.0606
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0196
 35/116 [========>.....................] - ETA: 0s - loss: 0.0634
 68/116 [================>.............] - ETA: 0s - loss: 0.0672
101/116 [=========================>....] - ETA: 0s - loss: 0.0591
116/116 [==============================] - 0s 2ms/step - loss: 0.0589
-> test with GAN.predict
GAN tn, fp: 284, 5
GAN fn, tp: 2, 5
GAN f1 score: 0.588
GAN cohens kappa score: 0.576

-> test with 'LR'
LR tn, fp: 276, 13
LR fn, tp: 1, 6
LR f1 score: 0.462
LR cohens kappa score: 0.442
LR average precision score: 0.488

-> test with 'RF'
RF tn, fp: 289, 0
RF fn, tp: 6, 1
RF f1 score: 0.250
RF cohens kappa score: 0.246

-> test with 'GB'
GB tn, fp: 288, 1
GB fn, tp: 4, 3
GB f1 score: 0.545
GB cohens kappa score: 0.537

-> test with 'KNN'
KNN tn, fp: 282, 7
KNN fn, tp: 2, 5
KNN f1 score: 0.526
KNN cohens kappa score: 0.512


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

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0028
 42/116 [=========>....................] - ETA: 0s - loss: 0.0640 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0652
116/116 [==============================] - 0s 1ms/step - loss: 0.0583
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2149
 41/116 [=========>....................] - ETA: 0s - loss: 0.0822
 80/116 [===================>..........] - ETA: 0s - loss: 0.0568
116/116 [==============================] - 0s 1ms/step - loss: 0.0554
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0017
 41/116 [=========>....................] - ETA: 0s - loss: 0.0571
 82/116 [====================>.........] - ETA: 0s - loss: 0.0505
116/116 [==============================] - 0s 1ms/step - loss: 0.0530
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0032
 36/116 [========>.....................] - ETA: 0s - loss: 0.0372
 69/116 [================>.............] - ETA: 0s - loss: 0.0504
103/116 [=========================>....] - ETA: 0s - loss: 0.0523
116/116 [==============================] - 0s 1ms/step - loss: 0.0527
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0148
 42/116 [=========>....................] - ETA: 0s - loss: 0.0425
 82/116 [====================>.........] - ETA: 0s - loss: 0.0554
116/116 [==============================] - 0s 1ms/step - loss: 0.0525
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0158
 39/116 [=========>....................] - ETA: 0s - loss: 0.0431
 75/116 [==================>...........] - ETA: 0s - loss: 0.0473
115/116 [============================>.] - ETA: 0s - loss: 0.0516
116/116 [==============================] - 0s 1ms/step - loss: 0.0514
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0109
 42/116 [=========>....................] - ETA: 0s - loss: 0.0516
 83/116 [====================>.........] - ETA: 0s - loss: 0.0494
116/116 [==============================] - 0s 1ms/step - loss: 0.0529
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0052
 42/116 [=========>....................] - ETA: 0s - loss: 0.0462
 81/116 [===================>..........] - ETA: 0s - loss: 0.0576
116/116 [==============================] - 0s 1ms/step - loss: 0.0525
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0338
 41/116 [=========>....................] - ETA: 0s - loss: 0.0417
 77/116 [==================>...........] - ETA: 0s - loss: 0.0560
116/116 [==============================] - 0s 1ms/step - loss: 0.0540
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0294
 40/116 [=========>....................] - ETA: 0s - loss: 0.0465
 80/116 [===================>..........] - ETA: 0s - loss: 0.0546
116/116 [==============================] - 0s 1ms/step - loss: 0.0514
-> test with GAN.predict
GAN tn, fp: 285, 5
GAN fn, tp: 2, 5
GAN f1 score: 0.588
GAN cohens kappa score: 0.576

-> test with 'LR'
LR tn, fp: 269, 21
LR fn, tp: 1, 6
LR f1 score: 0.353
LR cohens kappa score: 0.328
LR average precision score: 0.651

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 3, 4
RF f1 score: 0.667
RF cohens kappa score: 0.660

-> test with 'GB'
GB tn, fp: 288, 2
GB fn, tp: 3, 4
GB f1 score: 0.615
GB cohens kappa score: 0.607

-> test with 'KNN'
KNN tn, fp: 281, 9
KNN fn, tp: 1, 6
KNN f1 score: 0.545
KNN cohens kappa score: 0.530


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0282
 43/116 [==========>...................] - ETA: 0s - loss: 0.0637 
 85/116 [====================>.........] - ETA: 0s - loss: 0.0632
116/116 [==============================] - 0s 1ms/step - loss: 0.0752
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0165
 37/116 [========>.....................] - ETA: 0s - loss: 0.0704
 70/116 [=================>............] - ETA: 0s - loss: 0.0683
109/116 [===========================>..] - ETA: 0s - loss: 0.0673
116/116 [==============================] - 0s 1ms/step - loss: 0.0737
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0348
 42/116 [=========>....................] - ETA: 0s - loss: 0.0595
 83/116 [====================>.........] - ETA: 0s - loss: 0.0551
116/116 [==============================] - 0s 1ms/step - loss: 0.0686
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0080
 42/116 [=========>....................] - ETA: 0s - loss: 0.0585
 82/116 [====================>.........] - ETA: 0s - loss: 0.0732
116/116 [==============================] - 0s 1ms/step - loss: 0.0719
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0185
 42/116 [=========>....................] - ETA: 0s - loss: 0.0679
 82/116 [====================>.........] - ETA: 0s - loss: 0.0659
116/116 [==============================] - 0s 1ms/step - loss: 0.0696
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0773
 41/116 [=========>....................] - ETA: 0s - loss: 0.0750
 82/116 [====================>.........] - ETA: 0s - loss: 0.0742
116/116 [==============================] - 0s 1ms/step - loss: 0.0668
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1069
 41/116 [=========>....................] - ETA: 0s - loss: 0.0652
 81/116 [===================>..........] - ETA: 0s - loss: 0.0606
116/116 [==============================] - 0s 1ms/step - loss: 0.0672
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0101
 41/116 [=========>....................] - ETA: 0s - loss: 0.0655
 81/116 [===================>..........] - ETA: 0s - loss: 0.0658
116/116 [==============================] - 0s 1ms/step - loss: 0.0664
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1889
 41/116 [=========>....................] - ETA: 0s - loss: 0.0706
 82/116 [====================>.........] - ETA: 0s - loss: 0.0616
116/116 [==============================] - 0s 1ms/step - loss: 0.0647
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0261
 41/116 [=========>....................] - ETA: 0s - loss: 0.0631
 81/116 [===================>..........] - ETA: 0s - loss: 0.0656
116/116 [==============================] - 0s 1ms/step - loss: 0.0651
-> test with GAN.predict
GAN tn, fp: 275, 15
GAN fn, tp: 0, 7
GAN f1 score: 0.483
GAN cohens kappa score: 0.464

-> test with 'LR'
LR tn, fp: 262, 28
LR fn, tp: 0, 7
LR f1 score: 0.333
LR cohens kappa score: 0.306
LR average precision score: 0.793

-> test with 'RF'
RF tn, fp: 286, 4
RF fn, tp: 3, 4
RF f1 score: 0.533
RF cohens kappa score: 0.521

-> test with 'GB'
GB tn, fp: 286, 4
GB fn, tp: 3, 4
GB f1 score: 0.533
GB cohens kappa score: 0.521

-> test with 'KNN'
KNN tn, fp: 267, 23
KNN fn, tp: 0, 7
KNN f1 score: 0.378
KNN cohens kappa score: 0.354


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 18s - loss: 0.0228
 32/116 [=======>......................] - ETA: 0s - loss: 0.0560 
 69/116 [================>.............] - ETA: 0s - loss: 0.0608
109/116 [===========================>..] - ETA: 0s - loss: 0.0619
116/116 [==============================] - 0s 1ms/step - loss: 0.0610
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0926
 38/116 [========>.....................] - ETA: 0s - loss: 0.0585
 76/116 [==================>...........] - ETA: 0s - loss: 0.0577
116/116 [==============================] - 0s 1ms/step - loss: 0.0553
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0109
 42/116 [=========>....................] - ETA: 0s - loss: 0.0626
 83/116 [====================>.........] - ETA: 0s - loss: 0.0623
116/116 [==============================] - 0s 1ms/step - loss: 0.0549
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1438
 41/116 [=========>....................] - ETA: 0s - loss: 0.0502
 82/116 [====================>.........] - ETA: 0s - loss: 0.0591
116/116 [==============================] - 0s 1ms/step - loss: 0.0544
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0112
 41/116 [=========>....................] - ETA: 0s - loss: 0.0633
 76/116 [==================>...........] - ETA: 0s - loss: 0.0575
111/116 [===========================>..] - ETA: 0s - loss: 0.0551
116/116 [==============================] - 0s 1ms/step - loss: 0.0544
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0079
 39/116 [=========>....................] - ETA: 0s - loss: 0.0552
 80/116 [===================>..........] - ETA: 0s - loss: 0.0582
116/116 [==============================] - 0s 1ms/step - loss: 0.0548
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0156
 40/116 [=========>....................] - ETA: 0s - loss: 0.0626
 80/116 [===================>..........] - ETA: 0s - loss: 0.0499
116/116 [==============================] - 0s 1ms/step - loss: 0.0525
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1336
 42/116 [=========>....................] - ETA: 0s - loss: 0.0536
 82/116 [====================>.........] - ETA: 0s - loss: 0.0491
116/116 [==============================] - 0s 1ms/step - loss: 0.0556
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0440
 42/116 [=========>....................] - ETA: 0s - loss: 0.0579
 82/116 [====================>.........] - ETA: 0s - loss: 0.0537
116/116 [==============================] - 0s 1ms/step - loss: 0.0527
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0221
 42/116 [=========>....................] - ETA: 0s - loss: 0.0707
 83/116 [====================>.........] - ETA: 0s - loss: 0.0545
116/116 [==============================] - 0s 1ms/step - loss: 0.0511
-> test with GAN.predict
GAN tn, fp: 283, 7
GAN fn, tp: 3, 4
GAN f1 score: 0.444
GAN cohens kappa score: 0.428

-> test with 'LR'
LR tn, fp: 275, 15
LR fn, tp: 2, 5
LR f1 score: 0.370
LR cohens kappa score: 0.348
LR average precision score: 0.419

-> test with 'RF'
RF tn, fp: 288, 2
RF fn, tp: 3, 4
RF f1 score: 0.615
RF cohens kappa score: 0.607

-> test with 'GB'
GB tn, fp: 288, 2
GB fn, tp: 3, 4
GB f1 score: 0.615
GB cohens kappa score: 0.607

-> test with 'KNN'
KNN tn, fp: 280, 10
KNN fn, tp: 3, 4
KNN f1 score: 0.381
KNN cohens kappa score: 0.361


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0540
 40/116 [=========>....................] - ETA: 0s - loss: 0.0823 
 81/116 [===================>..........] - ETA: 0s - loss: 0.0812
116/116 [==============================] - 0s 1ms/step - loss: 0.0777
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0238
 41/116 [=========>....................] - ETA: 0s - loss: 0.0544
 79/116 [===================>..........] - ETA: 0s - loss: 0.0576
116/116 [==============================] - 0s 1ms/step - loss: 0.0739
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0386
 39/116 [=========>....................] - ETA: 0s - loss: 0.0765
 80/116 [===================>..........] - ETA: 0s - loss: 0.0705
116/116 [==============================] - 0s 1ms/step - loss: 0.0715
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0474
 41/116 [=========>....................] - ETA: 0s - loss: 0.0688
 76/116 [==================>...........] - ETA: 0s - loss: 0.0694
111/116 [===========================>..] - ETA: 0s - loss: 0.0719
116/116 [==============================] - 0s 1ms/step - loss: 0.0734
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0304
 37/116 [========>.....................] - ETA: 0s - loss: 0.0598
 75/116 [==================>...........] - ETA: 0s - loss: 0.0577
116/116 [==============================] - 0s 1ms/step - loss: 0.0692
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.2570
 40/116 [=========>....................] - ETA: 0s - loss: 0.0841
 79/116 [===================>..........] - ETA: 0s - loss: 0.0751
116/116 [==============================] - 0s 1ms/step - loss: 0.0703
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1121
 41/116 [=========>....................] - ETA: 0s - loss: 0.0676
 83/116 [====================>.........] - ETA: 0s - loss: 0.0701
116/116 [==============================] - 0s 1ms/step - loss: 0.0699
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0450
 41/116 [=========>....................] - ETA: 0s - loss: 0.0626
 82/116 [====================>.........] - ETA: 0s - loss: 0.0650
116/116 [==============================] - 0s 1ms/step - loss: 0.0692
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0298
 41/116 [=========>....................] - ETA: 0s - loss: 0.0925
 81/116 [===================>..........] - ETA: 0s - loss: 0.0835
116/116 [==============================] - 0s 1ms/step - loss: 0.0745
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0034
 42/116 [=========>....................] - ETA: 0s - loss: 0.0767
 82/116 [====================>.........] - ETA: 0s - loss: 0.0729
116/116 [==============================] - 0s 1ms/step - loss: 0.0697
-> test with GAN.predict
GAN tn, fp: 280, 10
GAN fn, tp: 2, 5
GAN f1 score: 0.455
GAN cohens kappa score: 0.436

-> test with 'LR'
LR tn, fp: 264, 26
LR fn, tp: 1, 6
LR f1 score: 0.308
LR cohens kappa score: 0.280
LR average precision score: 0.442

-> test with 'RF'
RF tn, fp: 286, 4
RF fn, tp: 3, 4
RF f1 score: 0.533
RF cohens kappa score: 0.521

-> test with 'GB'
GB tn, fp: 281, 9
GB fn, tp: 3, 4
GB f1 score: 0.400
GB cohens kappa score: 0.381

-> test with 'KNN'
KNN tn, fp: 273, 17
KNN fn, tp: 2, 5
KNN f1 score: 0.345
KNN cohens kappa score: 0.321


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 15s - loss: 0.0093
 37/116 [========>.....................] - ETA: 0s - loss: 0.0854 
 79/116 [===================>..........] - ETA: 0s - loss: 0.0863
115/116 [============================>.] - ETA: 0s - loss: 0.0821
116/116 [==============================] - 0s 1ms/step - loss: 0.0820
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0087
 34/116 [=======>......................] - ETA: 0s - loss: 0.0781
 67/116 [================>.............] - ETA: 0s - loss: 0.0785
 98/116 [========================>.....] - ETA: 0s - loss: 0.0773
116/116 [==============================] - 0s 2ms/step - loss: 0.0754
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0500
 44/116 [==========>...................] - ETA: 0s - loss: 0.0655
 82/116 [====================>.........] - ETA: 0s - loss: 0.0774
116/116 [==============================] - 0s 1ms/step - loss: 0.0763
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1682
 39/116 [=========>....................] - ETA: 0s - loss: 0.1028
 78/116 [===================>..........] - ETA: 0s - loss: 0.0739
116/116 [==============================] - ETA: 0s - loss: 0.0720
116/116 [==============================] - 0s 1ms/step - loss: 0.0720
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0191
 38/116 [========>.....................] - ETA: 0s - loss: 0.0686
 76/116 [==================>...........] - ETA: 0s - loss: 0.0733
114/116 [============================>.] - ETA: 0s - loss: 0.0713
116/116 [==============================] - 0s 1ms/step - loss: 0.0716
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0220
 37/116 [========>.....................] - ETA: 0s - loss: 0.0764
 76/116 [==================>...........] - ETA: 0s - loss: 0.0704
113/116 [============================>.] - ETA: 0s - loss: 0.0717
116/116 [==============================] - 0s 1ms/step - loss: 0.0706
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.2317
 37/116 [========>.....................] - ETA: 0s - loss: 0.0775
 74/116 [==================>...........] - ETA: 0s - loss: 0.0744
116/116 [==============================] - ETA: 0s - loss: 0.0690
116/116 [==============================] - 0s 1ms/step - loss: 0.0690
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0595
 37/116 [========>.....................] - ETA: 0s - loss: 0.0769
 76/116 [==================>...........] - ETA: 0s - loss: 0.0710
113/116 [============================>.] - ETA: 0s - loss: 0.0709
116/116 [==============================] - 0s 1ms/step - loss: 0.0709
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0872
 40/116 [=========>....................] - ETA: 0s - loss: 0.0742
 80/116 [===================>..........] - ETA: 0s - loss: 0.0689
116/116 [==============================] - 0s 1ms/step - loss: 0.0691
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0068
 37/116 [========>.....................] - ETA: 0s - loss: 0.0503
 72/116 [=================>............] - ETA: 0s - loss: 0.0662
111/116 [===========================>..] - ETA: 0s - loss: 0.0692
116/116 [==============================] - 0s 1ms/step - loss: 0.0675
-> test with GAN.predict
GAN tn, fp: 283, 6
GAN fn, tp: 4, 3
GAN f1 score: 0.375
GAN cohens kappa score: 0.358

-> test with 'LR'
LR tn, fp: 273, 16
LR fn, tp: 1, 6
LR f1 score: 0.414
LR cohens kappa score: 0.392
LR average precision score: 0.502

-> test with 'RF'
RF tn, fp: 288, 1
RF fn, tp: 6, 1
RF f1 score: 0.222
RF cohens kappa score: 0.214

-> test with 'GB'
GB tn, fp: 287, 2
GB fn, tp: 4, 3
GB f1 score: 0.500
GB cohens kappa score: 0.490

-> test with 'KNN'
KNN tn, fp: 278, 11
KNN fn, tp: 1, 6
KNN f1 score: 0.500
KNN cohens kappa score: 0.483


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

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 21s - loss: 0.0144
 42/116 [=========>....................] - ETA: 0s - loss: 0.0611 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0627
116/116 [==============================] - 0s 1ms/step - loss: 0.0645
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0043
 40/116 [=========>....................] - ETA: 0s - loss: 0.0459
 80/116 [===================>..........] - ETA: 0s - loss: 0.0448
116/116 [==============================] - 0s 1ms/step - loss: 0.0637
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0225
 42/116 [=========>....................] - ETA: 0s - loss: 0.0964
 83/116 [====================>.........] - ETA: 0s - loss: 0.0629
116/116 [==============================] - 0s 1ms/step - loss: 0.0639
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.5400
 41/116 [=========>....................] - ETA: 0s - loss: 0.0773
 79/116 [===================>..........] - ETA: 0s - loss: 0.0680
116/116 [==============================] - 0s 1ms/step - loss: 0.0581
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1331
 40/116 [=========>....................] - ETA: 0s - loss: 0.0473
 79/116 [===================>..........] - ETA: 0s - loss: 0.0533
113/116 [============================>.] - ETA: 0s - loss: 0.0583
116/116 [==============================] - 0s 1ms/step - loss: 0.0572
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0066
 35/116 [========>.....................] - ETA: 0s - loss: 0.0623
 73/116 [=================>............] - ETA: 0s - loss: 0.0620
113/116 [============================>.] - ETA: 0s - loss: 0.0544
116/116 [==============================] - 0s 1ms/step - loss: 0.0550
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0561
 40/116 [=========>....................] - ETA: 0s - loss: 0.0637
 81/116 [===================>..........] - ETA: 0s - loss: 0.0551
116/116 [==============================] - 0s 1ms/step - loss: 0.0562
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0190
 42/116 [=========>....................] - ETA: 0s - loss: 0.0697
 77/116 [==================>...........] - ETA: 0s - loss: 0.0606
115/116 [============================>.] - ETA: 0s - loss: 0.0558
116/116 [==============================] - 0s 1ms/step - loss: 0.0554
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0737
 41/116 [=========>....................] - ETA: 0s - loss: 0.0438
 81/116 [===================>..........] - ETA: 0s - loss: 0.0459
116/116 [==============================] - 0s 1ms/step - loss: 0.0559
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0141
 41/116 [=========>....................] - ETA: 0s - loss: 0.0450
 80/116 [===================>..........] - ETA: 0s - loss: 0.0574
116/116 [==============================] - 0s 1ms/step - loss: 0.0579
-> test with GAN.predict
GAN tn, fp: 288, 2
GAN fn, tp: 4, 3
GAN f1 score: 0.500
GAN cohens kappa score: 0.490

-> test with 'LR'
LR tn, fp: 276, 14
LR fn, tp: 1, 6
LR f1 score: 0.444
LR cohens kappa score: 0.424
LR average precision score: 0.741

-> test with 'RF'
RF tn, fp: 290, 0
RF fn, tp: 3, 4
RF f1 score: 0.727
RF cohens kappa score: 0.723

-> test with 'GB'
GB tn, fp: 288, 2
GB fn, tp: 1, 6
GB f1 score: 0.800
GB cohens kappa score: 0.795

-> test with 'KNN'
KNN tn, fp: 279, 11
KNN fn, tp: 1, 6
KNN f1 score: 0.500
KNN cohens kappa score: 0.483


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0092
 41/116 [=========>....................] - ETA: 0s - loss: 0.0729 
 82/116 [====================>.........] - ETA: 0s - loss: 0.0770
116/116 [==============================] - 0s 1ms/step - loss: 0.0783
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1526
 41/116 [=========>....................] - ETA: 0s - loss: 0.0822
 78/116 [===================>..........] - ETA: 0s - loss: 0.0846
116/116 [==============================] - 0s 1ms/step - loss: 0.0832
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0717
 41/116 [=========>....................] - ETA: 0s - loss: 0.0746
 81/116 [===================>..........] - ETA: 0s - loss: 0.0732
115/116 [============================>.] - ETA: 0s - loss: 0.0737
116/116 [==============================] - 0s 1ms/step - loss: 0.0745
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.2795
 39/116 [=========>....................] - ETA: 0s - loss: 0.0819
 74/116 [==================>...........] - ETA: 0s - loss: 0.0772
115/116 [============================>.] - ETA: 0s - loss: 0.0728
116/116 [==============================] - 0s 1ms/step - loss: 0.0732
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0710
 42/116 [=========>....................] - ETA: 0s - loss: 0.0698
 81/116 [===================>..........] - ETA: 0s - loss: 0.0742
116/116 [==============================] - 0s 1ms/step - loss: 0.0710
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.3352
 41/116 [=========>....................] - ETA: 0s - loss: 0.0798
 81/116 [===================>..........] - ETA: 0s - loss: 0.0735
116/116 [==============================] - 0s 1ms/step - loss: 0.0730
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0122
 42/116 [=========>....................] - ETA: 0s - loss: 0.0667
 83/116 [====================>.........] - ETA: 0s - loss: 0.0687
116/116 [==============================] - 0s 1ms/step - loss: 0.0700
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0062
 41/116 [=========>....................] - ETA: 0s - loss: 0.0571
 82/116 [====================>.........] - ETA: 0s - loss: 0.0709
116/116 [==============================] - 0s 1ms/step - loss: 0.0704
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0658
 42/116 [=========>....................] - ETA: 0s - loss: 0.0712
 81/116 [===================>..........] - ETA: 0s - loss: 0.0724
116/116 [==============================] - 0s 1ms/step - loss: 0.0702
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0119
 41/116 [=========>....................] - ETA: 0s - loss: 0.0640
 81/116 [===================>..........] - ETA: 0s - loss: 0.0696
116/116 [==============================] - 0s 1ms/step - loss: 0.0682
-> test with GAN.predict
GAN tn, fp: 282, 8
GAN fn, tp: 2, 5
GAN f1 score: 0.500
GAN cohens kappa score: 0.484

-> test with 'LR'
LR tn, fp: 265, 25
LR fn, tp: 0, 7
LR f1 score: 0.359
LR cohens kappa score: 0.333
LR average precision score: 0.290

-> test with 'RF'
RF tn, fp: 286, 4
RF fn, tp: 3, 4
RF f1 score: 0.533
RF cohens kappa score: 0.521

-> test with 'GB'
GB tn, fp: 285, 5
GB fn, tp: 3, 4
GB f1 score: 0.500
GB cohens kappa score: 0.486

-> test with 'KNN'
KNN tn, fp: 274, 16
KNN fn, tp: 1, 6
KNN f1 score: 0.414
KNN cohens kappa score: 0.392


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.0955
 42/116 [=========>....................] - ETA: 0s - loss: 0.0523 
 78/116 [===================>..........] - ETA: 0s - loss: 0.0654
116/116 [==============================] - 0s 1ms/step - loss: 0.0657
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0108
 40/116 [=========>....................] - ETA: 0s - loss: 0.0509
 80/116 [===================>..........] - ETA: 0s - loss: 0.0537
116/116 [==============================] - 0s 1ms/step - loss: 0.0599
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0116
 41/116 [=========>....................] - ETA: 0s - loss: 0.0393
 81/116 [===================>..........] - ETA: 0s - loss: 0.0577
116/116 [==============================] - 0s 1ms/step - loss: 0.0588
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0329
 41/116 [=========>....................] - ETA: 0s - loss: 0.0548
 75/116 [==================>...........] - ETA: 0s - loss: 0.0595
108/116 [==========================>...] - ETA: 0s - loss: 0.0632
116/116 [==============================] - 0s 1ms/step - loss: 0.0627
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0140
 38/116 [========>.....................] - ETA: 0s - loss: 0.0717
 76/116 [==================>...........] - ETA: 0s - loss: 0.0558
116/116 [==============================] - 0s 1ms/step - loss: 0.0588
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0629
 42/116 [=========>....................] - ETA: 0s - loss: 0.0471
 83/116 [====================>.........] - ETA: 0s - loss: 0.0554
116/116 [==============================] - 0s 1ms/step - loss: 0.0597
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1409
 41/116 [=========>....................] - ETA: 0s - loss: 0.0605
 82/116 [====================>.........] - ETA: 0s - loss: 0.0617
116/116 [==============================] - 0s 1ms/step - loss: 0.0581
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0550
 41/116 [=========>....................] - ETA: 0s - loss: 0.0704
 81/116 [===================>..........] - ETA: 0s - loss: 0.0580
116/116 [==============================] - 0s 1ms/step - loss: 0.0581
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0727
 41/116 [=========>....................] - ETA: 0s - loss: 0.0538
 79/116 [===================>..........] - ETA: 0s - loss: 0.0543
116/116 [==============================] - 0s 1ms/step - loss: 0.0568
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0095
 41/116 [=========>....................] - ETA: 0s - loss: 0.0723
 82/116 [====================>.........] - ETA: 0s - loss: 0.0533
116/116 [==============================] - 0s 1ms/step - loss: 0.0580
-> test with GAN.predict
GAN tn, fp: 278, 12
GAN fn, tp: 1, 6
GAN f1 score: 0.480
GAN cohens kappa score: 0.462

-> test with 'LR'
LR tn, fp: 262, 28
LR fn, tp: 1, 6
LR f1 score: 0.293
LR cohens kappa score: 0.264
LR average precision score: 0.554

-> test with 'RF'
RF tn, fp: 286, 4
RF fn, tp: 1, 6
RF f1 score: 0.706
RF cohens kappa score: 0.697

-> test with 'GB'
GB tn, fp: 284, 6
GB fn, tp: 2, 5
GB f1 score: 0.556
GB cohens kappa score: 0.542

-> test with 'KNN'
KNN tn, fp: 270, 20
KNN fn, tp: 1, 6
KNN f1 score: 0.364
KNN cohens kappa score: 0.339


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 22s - loss: 0.0394
 41/116 [=========>....................] - ETA: 0s - loss: 0.0654 
 81/116 [===================>..........] - ETA: 0s - loss: 0.0660
116/116 [==============================] - 0s 1ms/step - loss: 0.0658
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.2063
 42/116 [=========>....................] - ETA: 0s - loss: 0.0530
 82/116 [====================>.........] - ETA: 0s - loss: 0.0552
116/116 [==============================] - 0s 1ms/step - loss: 0.0645
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0117
 38/116 [========>.....................] - ETA: 0s - loss: 0.0529
 78/116 [===================>..........] - ETA: 0s - loss: 0.0615
116/116 [==============================] - ETA: 0s - loss: 0.0630
116/116 [==============================] - 0s 1ms/step - loss: 0.0630
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0127
 43/116 [==========>...................] - ETA: 0s - loss: 0.0724
 83/116 [====================>.........] - ETA: 0s - loss: 0.0690
116/116 [==============================] - 0s 1ms/step - loss: 0.0635
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0116
 41/116 [=========>....................] - ETA: 0s - loss: 0.0610
 82/116 [====================>.........] - ETA: 0s - loss: 0.0599
116/116 [==============================] - 0s 1ms/step - loss: 0.0621
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0544
 40/116 [=========>....................] - ETA: 0s - loss: 0.0470
 82/116 [====================>.........] - ETA: 0s - loss: 0.0535
116/116 [==============================] - 0s 1ms/step - loss: 0.0605
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0243
 42/116 [=========>....................] - ETA: 0s - loss: 0.0729
 82/116 [====================>.........] - ETA: 0s - loss: 0.0659
116/116 [==============================] - 0s 1ms/step - loss: 0.0625
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0199
 42/116 [=========>....................] - ETA: 0s - loss: 0.0615
 83/116 [====================>.........] - ETA: 0s - loss: 0.0567
116/116 [==============================] - 0s 1ms/step - loss: 0.0606
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0064
 42/116 [=========>....................] - ETA: 0s - loss: 0.0497
 83/116 [====================>.........] - ETA: 0s - loss: 0.0674
116/116 [==============================] - 0s 1ms/step - loss: 0.0594
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0054
 39/116 [=========>....................] - ETA: 0s - loss: 0.0674
 79/116 [===================>..........] - ETA: 0s - loss: 0.0642
116/116 [==============================] - 0s 1ms/step - loss: 0.0589
-> test with GAN.predict
GAN tn, fp: 283, 7
GAN fn, tp: 2, 5
GAN f1 score: 0.526
GAN cohens kappa score: 0.512

-> test with 'LR'
LR tn, fp: 271, 19
LR fn, tp: 1, 6
LR f1 score: 0.375
LR cohens kappa score: 0.351
LR average precision score: 0.646

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 4, 3
RF f1 score: 0.545
RF cohens kappa score: 0.538

-> test with 'GB'
GB tn, fp: 289, 1
GB fn, tp: 4, 3
GB f1 score: 0.545
GB cohens kappa score: 0.538

-> test with 'KNN'
KNN tn, fp: 279, 11
KNN fn, tp: 2, 5
KNN f1 score: 0.435
KNN cohens kappa score: 0.416


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 16s - loss: 0.0087
 44/116 [==========>...................] - ETA: 0s - loss: 0.0428 
 87/116 [=====================>........] - ETA: 0s - loss: 0.0507
116/116 [==============================] - 0s 1ms/step - loss: 0.0563
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0063
 45/116 [==========>...................] - ETA: 0s - loss: 0.0520
 89/116 [======================>.......] - ETA: 0s - loss: 0.0495
116/116 [==============================] - 0s 1ms/step - loss: 0.0565
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0306
 44/116 [==========>...................] - ETA: 0s - loss: 0.0655
 85/116 [====================>.........] - ETA: 0s - loss: 0.0518
116/116 [==============================] - 0s 1ms/step - loss: 0.0558
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0627
 36/116 [========>.....................] - ETA: 0s - loss: 0.0961
 74/116 [==================>...........] - ETA: 0s - loss: 0.0713
108/116 [==========================>...] - ETA: 0s - loss: 0.0587
116/116 [==============================] - 0s 1ms/step - loss: 0.0587
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0204
 45/116 [==========>...................] - ETA: 0s - loss: 0.0385
 86/116 [=====================>........] - ETA: 0s - loss: 0.0468
116/116 [==============================] - 0s 1ms/step - loss: 0.0549
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0063
 44/116 [==========>...................] - ETA: 0s - loss: 0.0763
 87/116 [=====================>........] - ETA: 0s - loss: 0.0622
116/116 [==============================] - 0s 1ms/step - loss: 0.0553
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0333
 43/116 [==========>...................] - ETA: 0s - loss: 0.0461
 81/116 [===================>..........] - ETA: 0s - loss: 0.0509
116/116 [==============================] - 0s 1ms/step - loss: 0.0530
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.1172
 45/116 [==========>...................] - ETA: 0s - loss: 0.0613
 90/116 [======================>.......] - ETA: 0s - loss: 0.0555
116/116 [==============================] - 0s 1ms/step - loss: 0.0558
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0071
 41/116 [=========>....................] - ETA: 0s - loss: 0.0424
 85/116 [====================>.........] - ETA: 0s - loss: 0.0538
116/116 [==============================] - 0s 1ms/step - loss: 0.0557
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0414
 44/116 [==========>...................] - ETA: 0s - loss: 0.0500
 87/116 [=====================>........] - ETA: 0s - loss: 0.0464
116/116 [==============================] - 0s 1ms/step - loss: 0.0521
-> test with GAN.predict
GAN tn, fp: 284, 5
GAN fn, tp: 4, 3
GAN f1 score: 0.400
GAN cohens kappa score: 0.384

-> test with 'LR'
LR tn, fp: 272, 17
LR fn, tp: 2, 5
LR f1 score: 0.345
LR cohens kappa score: 0.320
LR average precision score: 0.670

-> test with 'RF'
RF tn, fp: 288, 1
RF fn, tp: 4, 3
RF f1 score: 0.545
RF cohens kappa score: 0.537

-> test with 'GB'
GB tn, fp: 288, 1
GB fn, tp: 4, 3
GB f1 score: 0.545
GB cohens kappa score: 0.537

-> test with 'KNN'
KNN tn, fp: 279, 10
KNN fn, tp: 2, 5
KNN f1 score: 0.455
KNN cohens kappa score: 0.436


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

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 20s - loss: 0.0086
 42/116 [=========>....................] - ETA: 0s - loss: 0.0695 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0660
116/116 [==============================] - ETA: 0s - loss: 0.0619
116/116 [==============================] - 0s 1ms/step - loss: 0.0619
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0049
 34/116 [=======>......................] - ETA: 0s - loss: 0.0689
 71/116 [=================>............] - ETA: 0s - loss: 0.0651
112/116 [===========================>..] - ETA: 0s - loss: 0.0650
116/116 [==============================] - 0s 1ms/step - loss: 0.0634
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0114
 42/116 [=========>....................] - ETA: 0s - loss: 0.0641
 84/116 [====================>.........] - ETA: 0s - loss: 0.0652
116/116 [==============================] - 0s 1ms/step - loss: 0.0602
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0121
 42/116 [=========>....................] - ETA: 0s - loss: 0.0609
 83/116 [====================>.........] - ETA: 0s - loss: 0.0487
116/116 [==============================] - 0s 1ms/step - loss: 0.0581
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0108
 40/116 [=========>....................] - ETA: 0s - loss: 0.0492
 81/116 [===================>..........] - ETA: 0s - loss: 0.0607
116/116 [==============================] - 0s 1ms/step - loss: 0.0605
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0654
 42/116 [=========>....................] - ETA: 0s - loss: 0.0579
 82/116 [====================>.........] - ETA: 0s - loss: 0.0584
116/116 [==============================] - 0s 1ms/step - loss: 0.0603
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0345
 42/116 [=========>....................] - ETA: 0s - loss: 0.0626
 80/116 [===================>..........] - ETA: 0s - loss: 0.0591
116/116 [==============================] - 0s 1ms/step - loss: 0.0585
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0194
 40/116 [=========>....................] - ETA: 0s - loss: 0.0585
 80/116 [===================>..........] - ETA: 0s - loss: 0.0584
116/116 [==============================] - 0s 1ms/step - loss: 0.0610
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0114
 43/116 [==========>...................] - ETA: 0s - loss: 0.0618
 80/116 [===================>..........] - ETA: 0s - loss: 0.0603
116/116 [==============================] - 0s 1ms/step - loss: 0.0578
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0336
 41/116 [=========>....................] - ETA: 0s - loss: 0.0407
 81/116 [===================>..........] - ETA: 0s - loss: 0.0537
116/116 [==============================] - 0s 1ms/step - loss: 0.0575
-> test with GAN.predict
GAN tn, fp: 282, 8
GAN fn, tp: 1, 6
GAN f1 score: 0.571
GAN cohens kappa score: 0.558

-> test with 'LR'
LR tn, fp: 270, 20
LR fn, tp: 0, 7
LR f1 score: 0.412
LR cohens kappa score: 0.389
LR average precision score: 0.505

-> test with 'RF'
RF tn, fp: 287, 3
RF fn, tp: 3, 4
RF f1 score: 0.571
RF cohens kappa score: 0.561

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

-> test with 'KNN'
KNN tn, fp: 272, 18
KNN fn, tp: 1, 6
KNN f1 score: 0.387
KNN cohens kappa score: 0.364


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0293
 37/116 [========>.....................] - ETA: 0s - loss: 0.0603 
 81/116 [===================>..........] - ETA: 0s - loss: 0.0780
116/116 [==============================] - 0s 1ms/step - loss: 0.0724
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0389
 41/116 [=========>....................] - ETA: 0s - loss: 0.0802
 82/116 [====================>.........] - ETA: 0s - loss: 0.0695
116/116 [==============================] - 0s 1ms/step - loss: 0.0714
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0389
 40/116 [=========>....................] - ETA: 0s - loss: 0.0717
 80/116 [===================>..........] - ETA: 0s - loss: 0.0654
116/116 [==============================] - 0s 1ms/step - loss: 0.0722
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.1047
 38/116 [========>.....................] - ETA: 0s - loss: 0.0773
 78/116 [===================>..........] - ETA: 0s - loss: 0.0736
116/116 [==============================] - 0s 1ms/step - loss: 0.0703
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.2928
 41/116 [=========>....................] - ETA: 0s - loss: 0.0705
 82/116 [====================>.........] - ETA: 0s - loss: 0.0744
116/116 [==============================] - 0s 1ms/step - loss: 0.0708
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0592
 37/116 [========>.....................] - ETA: 0s - loss: 0.0561
 77/116 [==================>...........] - ETA: 0s - loss: 0.0646
115/116 [============================>.] - ETA: 0s - loss: 0.0686
116/116 [==============================] - 0s 1ms/step - loss: 0.0688
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0527
 33/116 [=======>......................] - ETA: 0s - loss: 0.0617
 71/116 [=================>............] - ETA: 0s - loss: 0.0646
109/116 [===========================>..] - ETA: 0s - loss: 0.0663
116/116 [==============================] - 0s 1ms/step - loss: 0.0679
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0470
 32/116 [=======>......................] - ETA: 0s - loss: 0.0641
 62/116 [===============>..............] - ETA: 0s - loss: 0.0641
 95/116 [=======================>......] - ETA: 0s - loss: 0.0685
116/116 [==============================] - 0s 2ms/step - loss: 0.0692
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0113
 34/116 [=======>......................] - ETA: 0s - loss: 0.0741
 65/116 [===============>..............] - ETA: 0s - loss: 0.0694
 97/116 [========================>.....] - ETA: 0s - loss: 0.0620
116/116 [==============================] - 0s 2ms/step - loss: 0.0680
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0122
 34/116 [=======>......................] - ETA: 0s - loss: 0.0502
 70/116 [=================>............] - ETA: 0s - loss: 0.0736
108/116 [==========================>...] - ETA: 0s - loss: 0.0631
116/116 [==============================] - 0s 1ms/step - loss: 0.0656
-> test with GAN.predict
GAN tn, fp: 285, 5
GAN fn, tp: 3, 4
GAN f1 score: 0.500
GAN cohens kappa score: 0.486

-> test with 'LR'
LR tn, fp: 272, 18
LR fn, tp: 3, 4
LR f1 score: 0.276
LR cohens kappa score: 0.249
LR average precision score: 0.245

-> test with 'RF'
RF tn, fp: 289, 1
RF fn, tp: 3, 4
RF f1 score: 0.667
RF cohens kappa score: 0.660

-> test with 'GB'
GB tn, fp: 289, 1
GB fn, tp: 3, 4
GB f1 score: 0.667
GB cohens kappa score: 0.660

-> test with 'KNN'
KNN tn, fp: 279, 11
KNN fn, tp: 3, 4
KNN f1 score: 0.364
KNN cohens kappa score: 0.343


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 17s - loss: 0.0054
 38/116 [========>.....................] - ETA: 0s - loss: 0.0531 
 77/116 [==================>...........] - ETA: 0s - loss: 0.0573
115/116 [============================>.] - ETA: 0s - loss: 0.0636
116/116 [==============================] - 0s 1ms/step - loss: 0.0632
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0700
 41/116 [=========>....................] - ETA: 0s - loss: 0.0414
 82/116 [====================>.........] - ETA: 0s - loss: 0.0438
116/116 [==============================] - 0s 1ms/step - loss: 0.0640
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0032
 39/116 [=========>....................] - ETA: 0s - loss: 0.0662
 79/116 [===================>..........] - ETA: 0s - loss: 0.0624
116/116 [==============================] - 0s 1ms/step - loss: 0.0630
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0260
 40/116 [=========>....................] - ETA: 0s - loss: 0.0505
 80/116 [===================>..........] - ETA: 0s - loss: 0.0621
116/116 [==============================] - 0s 1ms/step - loss: 0.0667
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0031
 37/116 [========>.....................] - ETA: 0s - loss: 0.0496
 78/116 [===================>..........] - ETA: 0s - loss: 0.0539
116/116 [==============================] - 0s 1ms/step - loss: 0.0582
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0957
 42/116 [=========>....................] - ETA: 0s - loss: 0.0599
 83/116 [====================>.........] - ETA: 0s - loss: 0.0654
116/116 [==============================] - 0s 1ms/step - loss: 0.0610
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.1456
 40/116 [=========>....................] - ETA: 0s - loss: 0.0536
 80/116 [===================>..........] - ETA: 0s - loss: 0.0565
116/116 [==============================] - 0s 1ms/step - loss: 0.0590
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0708
 41/116 [=========>....................] - ETA: 0s - loss: 0.0780
 81/116 [===================>..........] - ETA: 0s - loss: 0.0595
116/116 [==============================] - 0s 1ms/step - loss: 0.0589
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1368
 41/116 [=========>....................] - ETA: 0s - loss: 0.0800
 81/116 [===================>..........] - ETA: 0s - loss: 0.0668
116/116 [==============================] - 0s 1ms/step - loss: 0.0586
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0459
 41/116 [=========>....................] - ETA: 0s - loss: 0.0419
 82/116 [====================>.........] - ETA: 0s - loss: 0.0440
116/116 [==============================] - 0s 1ms/step - loss: 0.0573
-> test with GAN.predict
GAN tn, fp: 282, 8
GAN fn, tp: 0, 7
GAN f1 score: 0.636
GAN cohens kappa score: 0.624

-> test with 'LR'
LR tn, fp: 268, 22
LR fn, tp: 0, 7
LR f1 score: 0.389
LR cohens kappa score: 0.365
LR average precision score: 0.773

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

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

-> test with 'KNN'
KNN tn, fp: 278, 12
KNN fn, tp: 0, 7
KNN f1 score: 0.538
KNN cohens kappa score: 0.522


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1131 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 22s - loss: 0.1037
 41/116 [=========>....................] - ETA: 0s - loss: 0.0607 
 83/116 [====================>.........] - ETA: 0s - loss: 0.0628
116/116 [==============================] - 0s 1ms/step - loss: 0.0617
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.1633
 41/116 [=========>....................] - ETA: 0s - loss: 0.0881
 82/116 [====================>.........] - ETA: 0s - loss: 0.0678
116/116 [==============================] - 0s 1ms/step - loss: 0.0599
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0069
 41/116 [=========>....................] - ETA: 0s - loss: 0.0723
 82/116 [====================>.........] - ETA: 0s - loss: 0.0582
116/116 [==============================] - 0s 1ms/step - loss: 0.0584
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0635
 42/116 [=========>....................] - ETA: 0s - loss: 0.0632
 81/116 [===================>..........] - ETA: 0s - loss: 0.0653
116/116 [==============================] - 0s 1ms/step - loss: 0.0592
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.0323
 36/116 [========>.....................] - ETA: 0s - loss: 0.0465
 70/116 [=================>............] - ETA: 0s - loss: 0.0608
103/116 [=========================>....] - ETA: 0s - loss: 0.0610
116/116 [==============================] - 0s 1ms/step - loss: 0.0597
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.1660
 41/116 [=========>....................] - ETA: 0s - loss: 0.0552
 79/116 [===================>..........] - ETA: 0s - loss: 0.0621
116/116 [==============================] - 0s 1ms/step - loss: 0.0577
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0476
 40/116 [=========>....................] - ETA: 0s - loss: 0.0468
 80/116 [===================>..........] - ETA: 0s - loss: 0.0645
116/116 [==============================] - 0s 1ms/step - loss: 0.0595
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0388
 40/116 [=========>....................] - ETA: 0s - loss: 0.0609
 80/116 [===================>..........] - ETA: 0s - loss: 0.0600
116/116 [==============================] - 0s 1ms/step - loss: 0.0592
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.0320
 42/116 [=========>....................] - ETA: 0s - loss: 0.0478
 84/116 [====================>.........] - ETA: 0s - loss: 0.0527
116/116 [==============================] - 0s 1ms/step - loss: 0.0565
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0061
 42/116 [=========>....................] - ETA: 0s - loss: 0.0448
 84/116 [====================>.........] - ETA: 0s - loss: 0.0524
116/116 [==============================] - 0s 1ms/step - loss: 0.0571
-> test with GAN.predict
GAN tn, fp: 286, 4
GAN fn, tp: 4, 3
GAN f1 score: 0.429
GAN cohens kappa score: 0.415

-> test with 'LR'
LR tn, fp: 264, 26
LR fn, tp: 2, 5
LR f1 score: 0.263
LR cohens kappa score: 0.234
LR average precision score: 0.451

-> test with 'RF'
RF tn, fp: 290, 0
RF fn, tp: 5, 2
RF f1 score: 0.444
RF cohens kappa score: 0.439

-> test with 'GB'
GB tn, fp: 290, 0
GB fn, tp: 5, 2
GB f1 score: 0.444
GB cohens kappa score: 0.439

-> test with 'KNN'
KNN tn, fp: 276, 14
KNN fn, tp: 2, 5
KNN f1 score: 0.385
KNN cohens kappa score: 0.363


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1132 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/116 [..............................] - ETA: 19s - loss: 0.0212
 42/116 [=========>....................] - ETA: 0s - loss: 0.0467 
 84/116 [====================>.........] - ETA: 0s - loss: 0.0448
116/116 [==============================] - 0s 1ms/step - loss: 0.0506
Epoch 2/10

  1/116 [..............................] - ETA: 0s - loss: 0.0105
 44/116 [==========>...................] - ETA: 0s - loss: 0.0567
 88/116 [=====================>........] - ETA: 0s - loss: 0.0525
116/116 [==============================] - 0s 1ms/step - loss: 0.0520
Epoch 3/10

  1/116 [..............................] - ETA: 0s - loss: 0.0042
 39/116 [=========>....................] - ETA: 0s - loss: 0.0402
 83/116 [====================>.........] - ETA: 0s - loss: 0.0375
116/116 [==============================] - 0s 1ms/step - loss: 0.0489
Epoch 4/10

  1/116 [..............................] - ETA: 0s - loss: 0.0163
 44/116 [==========>...................] - ETA: 0s - loss: 0.0426
 88/116 [=====================>........] - ETA: 0s - loss: 0.0504
116/116 [==============================] - 0s 1ms/step - loss: 0.0496
Epoch 5/10

  1/116 [..............................] - ETA: 0s - loss: 0.1148
 40/116 [=========>....................] - ETA: 0s - loss: 0.0413
 76/116 [==================>...........] - ETA: 0s - loss: 0.0485
111/116 [===========================>..] - ETA: 0s - loss: 0.0488
116/116 [==============================] - 0s 1ms/step - loss: 0.0493
Epoch 6/10

  1/116 [..............................] - ETA: 0s - loss: 0.0031
 42/116 [=========>....................] - ETA: 0s - loss: 0.0340
 86/116 [=====================>........] - ETA: 0s - loss: 0.0512
116/116 [==============================] - 0s 1ms/step - loss: 0.0482
Epoch 7/10

  1/116 [..............................] - ETA: 0s - loss: 0.0875
 43/116 [==========>...................] - ETA: 0s - loss: 0.0617
 84/116 [====================>.........] - ETA: 0s - loss: 0.0524
116/116 [==============================] - 0s 1ms/step - loss: 0.0509
Epoch 8/10

  1/116 [..............................] - ETA: 0s - loss: 0.0017
 43/116 [==========>...................] - ETA: 0s - loss: 0.0624
 81/116 [===================>..........] - ETA: 0s - loss: 0.0460
116/116 [==============================] - 0s 1ms/step - loss: 0.0490
Epoch 9/10

  1/116 [..............................] - ETA: 0s - loss: 0.1950
 43/116 [==========>...................] - ETA: 0s - loss: 0.0509
 86/116 [=====================>........] - ETA: 0s - loss: 0.0472
116/116 [==============================] - 0s 1ms/step - loss: 0.0474
Epoch 10/10

  1/116 [..............................] - ETA: 0s - loss: 0.0222
 43/116 [==========>...................] - ETA: 0s - loss: 0.0454
 86/116 [=====================>........] - ETA: 0s - loss: 0.0514
116/116 [==============================] - 0s 1ms/step - loss: 0.0487
-> test with GAN.predict
GAN tn, fp: 282, 7
GAN fn, tp: 3, 4
GAN f1 score: 0.444
GAN cohens kappa score: 0.428

-> test with 'LR'
LR tn, fp: 273, 16
LR fn, tp: 2, 5
LR f1 score: 0.357
LR cohens kappa score: 0.334
LR average precision score: 0.442

-> test with 'RF'
RF tn, fp: 289, 0
RF fn, tp: 4, 3
RF f1 score: 0.600
RF cohens kappa score: 0.594

-> test with 'GB'
GB tn, fp: 285, 4
GB fn, tp: 5, 2
GB f1 score: 0.308
GB cohens kappa score: 0.292

-> test with 'KNN'
KNN tn, fp: 278, 11
KNN fn, tp: 2, 5
KNN f1 score: 0.435
KNN cohens kappa score: 0.416

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 277, 32
LR fn, tp: 3, 7
LR f1 score: 0.462
LR cohens kappa score: 0.442
LR average precision score: 0.793


average:
LR tn, fp: 268.8, 21.0
LR fn, tp: 1.12, 5.88
LR f1 score: 0.353
LR cohens kappa score: 0.328
LR average precision score: 0.533


minimum:
LR tn, fp: 257, 13
LR fn, tp: 0, 4
LR f1 score: 0.263
LR cohens kappa score: 0.234
LR average precision score: 0.245


-----[ RF ]-----
maximum:
RF tn, fp: 290, 4
RF fn, tp: 6, 7
RF f1 score: 0.875
RF cohens kappa score: 0.872


average:
RF tn, fp: 288.0, 1.8
RF fn, tp: 3.32, 3.68
RF f1 score: 0.575
RF cohens kappa score: 0.567


minimum:
RF tn, fp: 286, 0
RF fn, tp: 0, 1
RF f1 score: 0.222
RF cohens kappa score: 0.214


-----[ GB ]-----
maximum:
GB tn, fp: 290, 9
GB fn, tp: 5, 7
GB f1 score: 0.875
GB cohens kappa score: 0.872


average:
GB tn, fp: 286.76, 3.04
GB fn, tp: 3.0, 4.0
GB f1 score: 0.564
GB cohens kappa score: 0.554


minimum:
GB tn, fp: 281, 0
GB fn, tp: 0, 2
GB f1 score: 0.308
GB cohens kappa score: 0.292


-----[ KNN ]-----
maximum:
KNN tn, fp: 282, 23
KNN fn, tp: 3, 7
KNN f1 score: 0.571
KNN cohens kappa score: 0.558


average:
KNN tn, fp: 276.2, 13.6
KNN fn, tp: 1.52, 5.48
KNN f1 score: 0.426
KNN cohens kappa score: 0.406


minimum:
KNN tn, fp: 267, 7
KNN fn, tp: 0, 4
KNN f1 score: 0.296
KNN cohens kappa score: 0.271


-----[ GAN ]-----
maximum:
GAN tn, fp: 288, 15
GAN fn, tp: 4, 7
GAN f1 score: 0.636
GAN cohens kappa score: 0.624


average:
GAN tn, fp: 282.28, 7.52
GAN fn, tp: 2.28, 4.72
GAN f1 score: 0.491
GAN cohens kappa score: 0.475


minimum:
GAN tn, fp: 275, 2
GAN fn, tp: 0, 3
GAN f1 score: 0.364
GAN cohens kappa score: 0.343