ConvGeNBenchmarkResults/data_result/ConvGeN-majority-full/folding_flare-F.log

///////////////////////////////////////////
// Running convGAN-majority-full on folding_flare-F
///////////////////////////////////////////

Load 'data_input/folding_flare-F'
from pickle file
non empty cut in data_input/folding_flare-F! (23 points)
Data loaded.
-> Shuffling data
### Start exercise for synthetic point generator

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

------ Step 1/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 4.9632e-05
37/82 [============>.................] - ETA: 0s - loss: 0.1286     
67/82 [=======================>......] - ETA: 0s - loss: 0.1133
82/82 [==============================] - 0s 2ms/step - loss: 0.1065
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 2.2218e-04
36/82 [============>.................] - ETA: 0s - loss: 0.0639    
65/82 [======================>.......] - ETA: 0s - loss: 0.0854
82/82 [==============================] - 0s 2ms/step - loss: 0.0840
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1552
32/82 [==========>...................] - ETA: 0s - loss: 0.0727
66/82 [=======================>......] - ETA: 0s - loss: 0.0749
82/82 [==============================] - 0s 2ms/step - loss: 0.0732
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 6.5896e-05
36/82 [============>.................] - ETA: 0s - loss: 0.0795    
68/82 [=======================>......] - ETA: 0s - loss: 0.0724
82/82 [==============================] - 0s 2ms/step - loss: 0.0696
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0071
28/82 [=========>....................] - ETA: 0s - loss: 0.0730
56/82 [===================>..........] - ETA: 0s - loss: 0.0611
82/82 [==============================] - 0s 2ms/step - loss: 0.0615
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0845
33/82 [===========>..................] - ETA: 0s - loss: 0.0662
66/82 [=======================>......] - ETA: 0s - loss: 0.0589
82/82 [==============================] - 0s 2ms/step - loss: 0.0582
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0802
36/82 [============>.................] - ETA: 0s - loss: 0.0746
72/82 [=========================>....] - ETA: 0s - loss: 0.0589
82/82 [==============================] - 0s 1ms/step - loss: 0.0555
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.3370
33/82 [===========>..................] - ETA: 0s - loss: 0.0602
71/82 [========================>.....] - ETA: 0s - loss: 0.0560
82/82 [==============================] - 0s 1ms/step - loss: 0.0548
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0636
35/82 [===========>..................] - ETA: 0s - loss: 0.0483
73/82 [=========================>....] - ETA: 0s - loss: 0.0581
82/82 [==============================] - 0s 1ms/step - loss: 0.0540
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0019
36/82 [============>.................] - ETA: 0s - loss: 0.0478
70/82 [========================>.....] - ETA: 0s - loss: 0.0505
82/82 [==============================] - 0s 1ms/step - loss: 0.0518
-> test with GAN.predict
GAN tn, fp: 195, 10
GAN fn, tp: 8, 1
GAN f1 score: 0.100
GAN cohens kappa score: 0.056

-> test with 'LR'
LR tn, fp: 183, 22
LR fn, tp: 8, 1
LR f1 score: 0.062
LR cohens kappa score: 0.002
LR average precision score: 0.089

-> test with 'RF'
RF tn, fp: 198, 7
RF fn, tp: 8, 1
RF f1 score: 0.118
RF cohens kappa score: 0.081

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

-> test with 'KNN'
KNN tn, fp: 187, 18
KNN fn, tp: 6, 3
KNN f1 score: 0.200
KNN cohens kappa score: 0.150


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.0482
38/82 [============>.................] - ETA: 0s - loss: 0.1049 
76/82 [==========================>...] - ETA: 0s - loss: 0.1098
82/82 [==============================] - 0s 1ms/step - loss: 0.1065
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0098
39/82 [=============>................] - ETA: 0s - loss: 0.0859
77/82 [===========================>..] - ETA: 0s - loss: 0.0957
82/82 [==============================] - 0s 1ms/step - loss: 0.0970
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0977
35/82 [===========>..................] - ETA: 0s - loss: 0.1076
66/82 [=======================>......] - ETA: 0s - loss: 0.0971
82/82 [==============================] - 0s 2ms/step - loss: 0.0982
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0377
32/82 [==========>...................] - ETA: 0s - loss: 0.1151
71/82 [========================>.....] - ETA: 0s - loss: 0.0987
82/82 [==============================] - 0s 1ms/step - loss: 0.0971
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2431
40/82 [=============>................] - ETA: 0s - loss: 0.0926
75/82 [==========================>...] - ETA: 0s - loss: 0.0975
82/82 [==============================] - 0s 1ms/step - loss: 0.0960
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0696
35/82 [===========>..................] - ETA: 0s - loss: 0.0894
70/82 [========================>.....] - ETA: 0s - loss: 0.0893
82/82 [==============================] - 0s 1ms/step - loss: 0.0932
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0761
39/82 [=============>................] - ETA: 0s - loss: 0.0910
79/82 [===========================>..] - ETA: 0s - loss: 0.0928
82/82 [==============================] - 0s 1ms/step - loss: 0.0929
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1336
39/82 [=============>................] - ETA: 0s - loss: 0.0877
74/82 [==========================>...] - ETA: 0s - loss: 0.0863
82/82 [==============================] - 0s 1ms/step - loss: 0.0896
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0309
39/82 [=============>................] - ETA: 0s - loss: 0.1007
77/82 [===========================>..] - ETA: 0s - loss: 0.0888
82/82 [==============================] - 0s 1ms/step - loss: 0.0875
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0761
36/82 [============>.................] - ETA: 0s - loss: 0.0906
73/82 [=========================>....] - ETA: 0s - loss: 0.0872
82/82 [==============================] - 0s 1ms/step - loss: 0.0912
-> test with GAN.predict
GAN tn, fp: 193, 12
GAN fn, tp: 6, 3
GAN f1 score: 0.250
GAN cohens kappa score: 0.208

-> test with 'LR'
LR tn, fp: 167, 38
LR fn, tp: 0, 9
LR f1 score: 0.321
LR cohens kappa score: 0.270
LR average precision score: 0.382

-> test with 'RF'
RF tn, fp: 200, 5
RF fn, tp: 8, 1
RF f1 score: 0.133
RF cohens kappa score: 0.103

-> test with 'GB'
GB tn, fp: 202, 3
GB fn, tp: 7, 2
GB f1 score: 0.286
GB cohens kappa score: 0.264

-> test with 'KNN'
KNN tn, fp: 166, 39
KNN fn, tp: 2, 7
KNN f1 score: 0.255
KNN cohens kappa score: 0.198


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 15s - loss: 0.0152
34/82 [===========>..................] - ETA: 0s - loss: 0.1003 
68/82 [=======================>......] - ETA: 0s - loss: 0.0807
82/82 [==============================] - 0s 2ms/step - loss: 0.0760
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0875
35/82 [===========>..................] - ETA: 0s - loss: 0.0847
68/82 [=======================>......] - ETA: 0s - loss: 0.0757
82/82 [==============================] - 0s 2ms/step - loss: 0.0760
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0113
31/82 [==========>...................] - ETA: 0s - loss: 0.0735
61/82 [=====================>........] - ETA: 0s - loss: 0.0696
82/82 [==============================] - 0s 2ms/step - loss: 0.0688
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1143
33/82 [===========>..................] - ETA: 0s - loss: 0.0616
63/82 [======================>.......] - ETA: 0s - loss: 0.0678
82/82 [==============================] - 0s 2ms/step - loss: 0.0722
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0235
33/82 [===========>..................] - ETA: 0s - loss: 0.0767
64/82 [======================>.......] - ETA: 0s - loss: 0.0699
82/82 [==============================] - 0s 2ms/step - loss: 0.0661
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 3.0378e-04
31/82 [==========>...................] - ETA: 0s - loss: 0.0632    
60/82 [====================>.........] - ETA: 0s - loss: 0.0597
82/82 [==============================] - 0s 2ms/step - loss: 0.0667
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0015
35/82 [===========>..................] - ETA: 0s - loss: 0.0386
65/82 [======================>.......] - ETA: 0s - loss: 0.0638
82/82 [==============================] - 0s 2ms/step - loss: 0.0634
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0199
34/82 [===========>..................] - ETA: 0s - loss: 0.0411
61/82 [=====================>........] - ETA: 0s - loss: 0.0557
82/82 [==============================] - 0s 2ms/step - loss: 0.0646
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1357
34/82 [===========>..................] - ETA: 0s - loss: 0.0651
71/82 [========================>.....] - ETA: 0s - loss: 0.0618
82/82 [==============================] - 0s 2ms/step - loss: 0.0624
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2484
33/82 [===========>..................] - ETA: 0s - loss: 0.0727
65/82 [======================>.......] - ETA: 0s - loss: 0.0688
82/82 [==============================] - 0s 2ms/step - loss: 0.0620
-> test with GAN.predict
GAN tn, fp: 201, 4
GAN fn, tp: 7, 2
GAN f1 score: 0.267
GAN cohens kappa score: 0.241

-> test with 'LR'
LR tn, fp: 181, 24
LR fn, tp: 3, 6
LR f1 score: 0.308
LR cohens kappa score: 0.260
LR average precision score: 0.504

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.021

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

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


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 0.0227
27/82 [========>.....................] - ETA: 0s - loss: 0.0920 
55/82 [===================>..........] - ETA: 0s - loss: 0.0824
82/82 [==============================] - ETA: 0s - loss: 0.0894
82/82 [==============================] - 0s 2ms/step - loss: 0.0894
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1863
26/82 [========>.....................] - ETA: 0s - loss: 0.0787
51/82 [=================>............] - ETA: 0s - loss: 0.0898
76/82 [==========================>...] - ETA: 0s - loss: 0.0957
82/82 [==============================] - 0s 2ms/step - loss: 0.0964
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0826
27/82 [========>.....................] - ETA: 0s - loss: 0.0869
55/82 [===================>..........] - ETA: 0s - loss: 0.0875
82/82 [==============================] - ETA: 0s - loss: 0.0861
82/82 [==============================] - 0s 2ms/step - loss: 0.0861
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0463
27/82 [========>.....................] - ETA: 0s - loss: 0.1063
54/82 [==================>...........] - ETA: 0s - loss: 0.0888
82/82 [==============================] - 0s 2ms/step - loss: 0.0828
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1628
37/82 [============>.................] - ETA: 0s - loss: 0.0834
73/82 [=========================>....] - ETA: 0s - loss: 0.0725
82/82 [==============================] - 0s 1ms/step - loss: 0.0785
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0040
34/82 [===========>..................] - ETA: 0s - loss: 0.0784
66/82 [=======================>......] - ETA: 0s - loss: 0.0770
82/82 [==============================] - 0s 2ms/step - loss: 0.0771
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2374
30/82 [=========>....................] - ETA: 0s - loss: 0.0717
65/82 [======================>.......] - ETA: 0s - loss: 0.0743
82/82 [==============================] - 0s 2ms/step - loss: 0.0749
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0060
38/82 [============>.................] - ETA: 0s - loss: 0.0757
74/82 [==========================>...] - ETA: 0s - loss: 0.0730
82/82 [==============================] - 0s 1ms/step - loss: 0.0728
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0611
36/82 [============>.................] - ETA: 0s - loss: 0.0748
71/82 [========================>.....] - ETA: 0s - loss: 0.0703
82/82 [==============================] - 0s 1ms/step - loss: 0.0718
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0242
38/82 [============>.................] - ETA: 0s - loss: 0.0719
76/82 [==========================>...] - ETA: 0s - loss: 0.0618
82/82 [==============================] - 0s 1ms/step - loss: 0.0705
-> test with GAN.predict
GAN tn, fp: 203, 2
GAN fn, tp: 8, 1
GAN f1 score: 0.167
GAN cohens kappa score: 0.149

-> test with 'LR'
LR tn, fp: 190, 15
LR fn, tp: 0, 9
LR f1 score: 0.545
LR cohens kappa score: 0.516
LR average precision score: 0.796

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.169

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 7, 2
GB f1 score: 0.364
GB cohens kappa score: 0.354

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


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 11s - loss: 0.0348
38/82 [============>.................] - ETA: 0s - loss: 0.1220 
75/82 [==========================>...] - ETA: 0s - loss: 0.1026
82/82 [==============================] - 0s 1ms/step - loss: 0.1034
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0806
41/82 [==============>...............] - ETA: 0s - loss: 0.0772
81/82 [============================>.] - ETA: 0s - loss: 0.0879
82/82 [==============================] - 0s 1ms/step - loss: 0.0868
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2511
33/82 [===========>..................] - ETA: 0s - loss: 0.0726
72/82 [=========================>....] - ETA: 0s - loss: 0.0738
82/82 [==============================] - 0s 1ms/step - loss: 0.0772
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0015
41/82 [==============>...............] - ETA: 0s - loss: 0.0673
82/82 [==============================] - ETA: 0s - loss: 0.0751
82/82 [==============================] - 0s 1ms/step - loss: 0.0751
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1432
39/82 [=============>................] - ETA: 0s - loss: 0.0853
79/82 [===========================>..] - ETA: 0s - loss: 0.0759
82/82 [==============================] - 0s 1ms/step - loss: 0.0740
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0029
41/82 [==============>...............] - ETA: 0s - loss: 0.0749
77/82 [===========================>..] - ETA: 0s - loss: 0.0694
82/82 [==============================] - 0s 1ms/step - loss: 0.0696
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0053
40/82 [=============>................] - ETA: 0s - loss: 0.0690
77/82 [===========================>..] - ETA: 0s - loss: 0.0693
82/82 [==============================] - 0s 1ms/step - loss: 0.0678
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0080
39/82 [=============>................] - ETA: 0s - loss: 0.0655
78/82 [===========================>..] - ETA: 0s - loss: 0.0649
82/82 [==============================] - 0s 1ms/step - loss: 0.0642
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0240
38/82 [============>.................] - ETA: 0s - loss: 0.0703
77/82 [===========================>..] - ETA: 0s - loss: 0.0627
82/82 [==============================] - 0s 1ms/step - loss: 0.0658
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0327
38/82 [============>.................] - ETA: 0s - loss: 0.0540
76/82 [==========================>...] - ETA: 0s - loss: 0.0631
82/82 [==============================] - 0s 1ms/step - loss: 0.0628
-> test with GAN.predict
GAN tn, fp: 192, 11
GAN fn, tp: 5, 2
GAN f1 score: 0.200
GAN cohens kappa score: 0.164

-> test with 'LR'
LR tn, fp: 182, 21
LR fn, tp: 3, 4
LR f1 score: 0.250
LR cohens kappa score: 0.209
LR average precision score: 0.218

-> test with 'RF'
RF tn, fp: 199, 4
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.025

-> test with 'GB'
GB tn, fp: 199, 4
GB fn, tp: 4, 3
GB f1 score: 0.429
GB cohens kappa score: 0.409

-> test with 'KNN'
KNN tn, fp: 183, 20
KNN fn, tp: 2, 5
KNN f1 score: 0.312
KNN cohens kappa score: 0.275


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

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 15s - loss: 0.0387
34/82 [===========>..................] - ETA: 0s - loss: 0.0730 
71/82 [========================>.....] - ETA: 0s - loss: 0.0723
82/82 [==============================] - 0s 1ms/step - loss: 0.0745
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0026
37/82 [============>.................] - ETA: 0s - loss: 0.0560
73/82 [=========================>....] - ETA: 0s - loss: 0.0696
82/82 [==============================] - 0s 1ms/step - loss: 0.0697
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2029
33/82 [===========>..................] - ETA: 0s - loss: 0.0480
70/82 [========================>.....] - ETA: 0s - loss: 0.0584
82/82 [==============================] - 0s 1ms/step - loss: 0.0677
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0014
38/82 [============>.................] - ETA: 0s - loss: 0.0699
72/82 [=========================>....] - ETA: 0s - loss: 0.0654
82/82 [==============================] - 0s 1ms/step - loss: 0.0667
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0692
37/82 [============>.................] - ETA: 0s - loss: 0.0630
72/82 [=========================>....] - ETA: 0s - loss: 0.0674
82/82 [==============================] - 0s 1ms/step - loss: 0.0643
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0126
38/82 [============>.................] - ETA: 0s - loss: 0.0583
75/82 [==========================>...] - ETA: 0s - loss: 0.0643
82/82 [==============================] - 0s 1ms/step - loss: 0.0649
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1636
37/82 [============>.................] - ETA: 0s - loss: 0.0495
73/82 [=========================>....] - ETA: 0s - loss: 0.0702
82/82 [==============================] - 0s 1ms/step - loss: 0.0651
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0018
35/82 [===========>..................] - ETA: 0s - loss: 0.0650
71/82 [========================>.....] - ETA: 0s - loss: 0.0560
82/82 [==============================] - 0s 1ms/step - loss: 0.0613
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0017
34/82 [===========>..................] - ETA: 0s - loss: 0.0506
64/82 [======================>.......] - ETA: 0s - loss: 0.0570
82/82 [==============================] - 0s 2ms/step - loss: 0.0587
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0310
29/82 [=========>....................] - ETA: 0s - loss: 0.0555
56/82 [===================>..........] - ETA: 0s - loss: 0.0569
79/82 [===========================>..] - ETA: 0s - loss: 0.0607
82/82 [==============================] - 0s 2ms/step - loss: 0.0614
-> test with GAN.predict
GAN tn, fp: 198, 7
GAN fn, tp: 6, 3
GAN f1 score: 0.316
GAN cohens kappa score: 0.284

-> test with 'LR'
LR tn, fp: 178, 27
LR fn, tp: 2, 7
LR f1 score: 0.326
LR cohens kappa score: 0.278
LR average precision score: 0.422

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 7, 2
RF f1 score: 0.286
RF cohens kappa score: 0.264

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 8, 1
GB f1 score: 0.167
GB cohens kappa score: 0.149

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


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 40s - loss: 2.5342e-04
36/82 [============>.................] - ETA: 0s - loss: 0.1244     
72/82 [=========================>....] - ETA: 0s - loss: 0.1184
82/82 [==============================] - 1s 1ms/step - loss: 0.1095
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0093
38/82 [============>.................] - ETA: 0s - loss: 0.0830
72/82 [=========================>....] - ETA: 0s - loss: 0.0854
82/82 [==============================] - 0s 1ms/step - loss: 0.0888
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0016
27/82 [========>.....................] - ETA: 0s - loss: 0.0559
62/82 [=====================>........] - ETA: 0s - loss: 0.0702
82/82 [==============================] - 0s 2ms/step - loss: 0.0771
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2124
35/82 [===========>..................] - ETA: 0s - loss: 0.0849
68/82 [=======================>......] - ETA: 0s - loss: 0.0739
82/82 [==============================] - 0s 1ms/step - loss: 0.0731
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0026
38/82 [============>.................] - ETA: 0s - loss: 0.0777
73/82 [=========================>....] - ETA: 0s - loss: 0.0734
82/82 [==============================] - 0s 1ms/step - loss: 0.0703
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0093
38/82 [============>.................] - ETA: 0s - loss: 0.0757
75/82 [==========================>...] - ETA: 0s - loss: 0.0662
82/82 [==============================] - 0s 1ms/step - loss: 0.0639
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0187
35/82 [===========>..................] - ETA: 0s - loss: 0.0587
65/82 [======================>.......] - ETA: 0s - loss: 0.0619
82/82 [==============================] - 0s 2ms/step - loss: 0.0631
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0010
26/82 [========>.....................] - ETA: 0s - loss: 0.0665
52/82 [==================>...........] - ETA: 0s - loss: 0.0707
77/82 [===========================>..] - ETA: 0s - loss: 0.0639
82/82 [==============================] - 0s 2ms/step - loss: 0.0622
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0120
28/82 [=========>....................] - ETA: 0s - loss: 0.0609
57/82 [===================>..........] - ETA: 0s - loss: 0.0597
82/82 [==============================] - 0s 2ms/step - loss: 0.0613
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0016
30/82 [=========>....................] - ETA: 0s - loss: 0.0629
57/82 [===================>..........] - ETA: 0s - loss: 0.0608
82/82 [==============================] - 0s 2ms/step - loss: 0.0576
-> test with GAN.predict
GAN tn, fp: 200, 5
GAN fn, tp: 8, 1
GAN f1 score: 0.133
GAN cohens kappa score: 0.103

-> test with 'LR'
LR tn, fp: 176, 29
LR fn, tp: 4, 5
LR f1 score: 0.233
LR cohens kappa score: 0.178
LR average precision score: 0.374

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 8, 1
RF f1 score: 0.154
RF cohens kappa score: 0.131

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

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


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.0050
37/82 [============>.................] - ETA: 0s - loss: 0.1025 
67/82 [=======================>......] - ETA: 0s - loss: 0.0978
82/82 [==============================] - 0s 2ms/step - loss: 0.1085
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0970
33/82 [===========>..................] - ETA: 0s - loss: 0.0670
67/82 [=======================>......] - ETA: 0s - loss: 0.0965
82/82 [==============================] - 0s 2ms/step - loss: 0.0902
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0083
40/82 [=============>................] - ETA: 0s - loss: 0.0910
78/82 [===========================>..] - ETA: 0s - loss: 0.0815
82/82 [==============================] - 0s 1ms/step - loss: 0.0828
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0305
39/82 [=============>................] - ETA: 0s - loss: 0.0889
79/82 [===========================>..] - ETA: 0s - loss: 0.0716
82/82 [==============================] - 0s 1ms/step - loss: 0.0766
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0307
37/82 [============>.................] - ETA: 0s - loss: 0.0830
76/82 [==========================>...] - ETA: 0s - loss: 0.0772
82/82 [==============================] - 0s 1ms/step - loss: 0.0742
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0051
41/82 [==============>...............] - ETA: 0s - loss: 0.0737
80/82 [============================>.] - ETA: 0s - loss: 0.0698
82/82 [==============================] - 0s 1ms/step - loss: 0.0684
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0079
40/82 [=============>................] - ETA: 0s - loss: 0.0787
78/82 [===========================>..] - ETA: 0s - loss: 0.0673
82/82 [==============================] - 0s 1ms/step - loss: 0.0649
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1827
40/82 [=============>................] - ETA: 0s - loss: 0.0700
76/82 [==========================>...] - ETA: 0s - loss: 0.0643
82/82 [==============================] - 0s 1ms/step - loss: 0.0638
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0011
40/82 [=============>................] - ETA: 0s - loss: 0.0514
77/82 [===========================>..] - ETA: 0s - loss: 0.0611
82/82 [==============================] - 0s 1ms/step - loss: 0.0598
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0257
37/82 [============>.................] - ETA: 0s - loss: 0.0596
75/82 [==========================>...] - ETA: 0s - loss: 0.0652
82/82 [==============================] - 0s 1ms/step - loss: 0.0609
-> test with GAN.predict
GAN tn, fp: 205, 0
GAN fn, tp: 8, 1
GAN f1 score: 0.200
GAN cohens kappa score: 0.193

-> test with 'LR'
LR tn, fp: 180, 25
LR fn, tp: 3, 6
LR f1 score: 0.300
LR cohens kappa score: 0.251
LR average precision score: 0.386

-> test with 'RF'
RF tn, fp: 203, 2
RF fn, tp: 8, 1
RF f1 score: 0.167
RF cohens kappa score: 0.149

-> test with 'GB'
GB tn, fp: 204, 1
GB fn, tp: 8, 1
GB f1 score: 0.182
GB cohens kappa score: 0.169

-> test with 'KNN'
KNN tn, fp: 191, 14
KNN fn, tp: 4, 5
KNN f1 score: 0.357
KNN cohens kappa score: 0.318


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.2398
40/82 [=============>................] - ETA: 0s - loss: 0.1093 
79/82 [===========================>..] - ETA: 0s - loss: 0.0965
82/82 [==============================] - 0s 1ms/step - loss: 0.0958
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0037
39/82 [=============>................] - ETA: 0s - loss: 0.0806
75/82 [==========================>...] - ETA: 0s - loss: 0.0899
82/82 [==============================] - 0s 1ms/step - loss: 0.0863
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0439
39/82 [=============>................] - ETA: 0s - loss: 0.0743
77/82 [===========================>..] - ETA: 0s - loss: 0.0785
82/82 [==============================] - 0s 1ms/step - loss: 0.0776
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0017
33/82 [===========>..................] - ETA: 0s - loss: 0.0537
69/82 [========================>.....] - ETA: 0s - loss: 0.0719
82/82 [==============================] - 0s 1ms/step - loss: 0.0735
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0071
37/82 [============>.................] - ETA: 0s - loss: 0.0561
71/82 [========================>.....] - ETA: 0s - loss: 0.0663
82/82 [==============================] - 0s 1ms/step - loss: 0.0695
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0077
36/82 [============>.................] - ETA: 0s - loss: 0.0594
69/82 [========================>.....] - ETA: 0s - loss: 0.0700
82/82 [==============================] - 0s 1ms/step - loss: 0.0690
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0496
37/82 [============>.................] - ETA: 0s - loss: 0.0876
75/82 [==========================>...] - ETA: 0s - loss: 0.0711
82/82 [==============================] - 0s 1ms/step - loss: 0.0677
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0357
36/82 [============>.................] - ETA: 0s - loss: 0.0705
68/82 [=======================>......] - ETA: 0s - loss: 0.0640
82/82 [==============================] - 0s 2ms/step - loss: 0.0640
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0029
31/82 [==========>...................] - ETA: 0s - loss: 0.0750
67/82 [=======================>......] - ETA: 0s - loss: 0.0647
82/82 [==============================] - 0s 1ms/step - loss: 0.0640
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2749
39/82 [=============>................] - ETA: 0s - loss: 0.0535
76/82 [==========================>...] - ETA: 0s - loss: 0.0615
82/82 [==============================] - 0s 1ms/step - loss: 0.0627
-> test with GAN.predict
GAN tn, fp: 202, 3
GAN fn, tp: 8, 1
GAN f1 score: 0.154
GAN cohens kappa score: 0.131

-> test with 'LR'
LR tn, fp: 193, 12
LR fn, tp: 5, 4
LR f1 score: 0.320
LR cohens kappa score: 0.281
LR average precision score: 0.295

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 8, 1
RF f1 score: 0.154
RF cohens kappa score: 0.131

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 8, 1
GB f1 score: 0.167
GB cohens kappa score: 0.149

-> test with 'KNN'
KNN tn, fp: 192, 13
KNN fn, tp: 3, 6
KNN f1 score: 0.429
KNN cohens kappa score: 0.394


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 12s - loss: 0.0764
40/82 [=============>................] - ETA: 0s - loss: 0.0755 
82/82 [==============================] - ETA: 0s - loss: 0.0873
82/82 [==============================] - 0s 1ms/step - loss: 0.0873
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0146
42/82 [==============>...............] - ETA: 0s - loss: 0.0837
80/82 [============================>.] - ETA: 0s - loss: 0.0786
82/82 [==============================] - 0s 1ms/step - loss: 0.0776
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0196
41/82 [==============>...............] - ETA: 0s - loss: 0.0977
82/82 [==============================] - ETA: 0s - loss: 0.0847
82/82 [==============================] - 0s 1ms/step - loss: 0.0847
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0348
41/82 [==============>...............] - ETA: 0s - loss: 0.0758
77/82 [===========================>..] - ETA: 0s - loss: 0.0743
82/82 [==============================] - 0s 1ms/step - loss: 0.0783
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1130
38/82 [============>.................] - ETA: 0s - loss: 0.0709
69/82 [========================>.....] - ETA: 0s - loss: 0.0723
82/82 [==============================] - 0s 1ms/step - loss: 0.0792
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0696
42/82 [==============>...............] - ETA: 0s - loss: 0.0845
82/82 [==============================] - ETA: 0s - loss: 0.0790
82/82 [==============================] - 0s 1ms/step - loss: 0.0790
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0121
41/82 [==============>...............] - ETA: 0s - loss: 0.0728
78/82 [===========================>..] - ETA: 0s - loss: 0.0764
82/82 [==============================] - 0s 1ms/step - loss: 0.0768
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0802
42/82 [==============>...............] - ETA: 0s - loss: 0.0628
82/82 [==============================] - ETA: 0s - loss: 0.0724
82/82 [==============================] - 0s 1ms/step - loss: 0.0724
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0037
42/82 [==============>...............] - ETA: 0s - loss: 0.0796
82/82 [==============================] - 0s 1ms/step - loss: 0.0773
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0419
41/82 [==============>...............] - ETA: 0s - loss: 0.0668
82/82 [==============================] - ETA: 0s - loss: 0.0741
82/82 [==============================] - 0s 1ms/step - loss: 0.0741
-> test with GAN.predict
GAN tn, fp: 191, 12
GAN fn, tp: 5, 2
GAN f1 score: 0.190
GAN cohens kappa score: 0.153

-> test with 'LR'
LR tn, fp: 176, 27
LR fn, tp: 0, 7
LR f1 score: 0.341
LR cohens kappa score: 0.303
LR average precision score: 0.392

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

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

-> test with 'KNN'
KNN tn, fp: 180, 23
KNN fn, tp: 1, 6
KNN f1 score: 0.333
KNN cohens kappa score: 0.295


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

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.3820
40/82 [=============>................] - ETA: 0s - loss: 0.1146 
79/82 [===========================>..] - ETA: 0s - loss: 0.1147
82/82 [==============================] - 0s 1ms/step - loss: 0.1114
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0871
36/82 [============>.................] - ETA: 0s - loss: 0.0916
72/82 [=========================>....] - ETA: 0s - loss: 0.0989
82/82 [==============================] - 0s 1ms/step - loss: 0.0961
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0108
31/82 [==========>...................] - ETA: 0s - loss: 0.0920
70/82 [========================>.....] - ETA: 0s - loss: 0.0860
82/82 [==============================] - 0s 1ms/step - loss: 0.0921
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0790
38/82 [============>.................] - ETA: 0s - loss: 0.0929
74/82 [==========================>...] - ETA: 0s - loss: 0.0876
82/82 [==============================] - 0s 1ms/step - loss: 0.0891
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0884
40/82 [=============>................] - ETA: 0s - loss: 0.0662
78/82 [===========================>..] - ETA: 0s - loss: 0.0843
82/82 [==============================] - 0s 1ms/step - loss: 0.0852
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0634
41/82 [==============>...............] - ETA: 0s - loss: 0.0861
79/82 [===========================>..] - ETA: 0s - loss: 0.0822
82/82 [==============================] - 0s 1ms/step - loss: 0.0798
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1097
40/82 [=============>................] - ETA: 0s - loss: 0.0809
72/82 [=========================>....] - ETA: 0s - loss: 0.0847
82/82 [==============================] - 0s 1ms/step - loss: 0.0852
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0913
34/82 [===========>..................] - ETA: 0s - loss: 0.0933
69/82 [========================>.....] - ETA: 0s - loss: 0.0794
82/82 [==============================] - 0s 1ms/step - loss: 0.0823
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0195
41/82 [==============>...............] - ETA: 0s - loss: 0.0846
79/82 [===========================>..] - ETA: 0s - loss: 0.0786
82/82 [==============================] - 0s 1ms/step - loss: 0.0818
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0747
40/82 [=============>................] - ETA: 0s - loss: 0.0761
77/82 [===========================>..] - ETA: 0s - loss: 0.0822
82/82 [==============================] - 0s 1ms/step - loss: 0.0821
-> test with GAN.predict
GAN tn, fp: 204, 1
GAN fn, tp: 7, 2
GAN f1 score: 0.333
GAN cohens kappa score: 0.319

-> test with 'LR'
LR tn, fp: 188, 17
LR fn, tp: 1, 8
LR f1 score: 0.471
LR cohens kappa score: 0.436
LR average precision score: 0.820

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: 0.000

-> test with 'KNN'
KNN tn, fp: 193, 12
KNN fn, tp: 3, 6
KNN f1 score: 0.444
KNN cohens kappa score: 0.411


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 15s - loss: 7.2936e-05
40/82 [=============>................] - ETA: 0s - loss: 0.0904     
79/82 [===========================>..] - ETA: 0s - loss: 0.0896
82/82 [==============================] - 0s 1ms/step - loss: 0.0908
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2217
40/82 [=============>................] - ETA: 0s - loss: 0.0768
79/82 [===========================>..] - ETA: 0s - loss: 0.0783
82/82 [==============================] - 0s 1ms/step - loss: 0.0774
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 2.0882e-04
39/82 [=============>................] - ETA: 0s - loss: 0.0601    
76/82 [==========================>...] - ETA: 0s - loss: 0.0648
82/82 [==============================] - 0s 1ms/step - loss: 0.0727
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0039
35/82 [===========>..................] - ETA: 0s - loss: 0.0431
66/82 [=======================>......] - ETA: 0s - loss: 0.0703
82/82 [==============================] - 0s 2ms/step - loss: 0.0685
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0216
36/82 [============>.................] - ETA: 0s - loss: 0.0742
72/82 [=========================>....] - ETA: 0s - loss: 0.0649
82/82 [==============================] - 0s 1ms/step - loss: 0.0613
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0418
40/82 [=============>................] - ETA: 0s - loss: 0.0740
79/82 [===========================>..] - ETA: 0s - loss: 0.0610
82/82 [==============================] - 0s 1ms/step - loss: 0.0596
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0046
40/82 [=============>................] - ETA: 0s - loss: 0.0559
76/82 [==========================>...] - ETA: 0s - loss: 0.0578
82/82 [==============================] - 0s 1ms/step - loss: 0.0576
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0487
39/82 [=============>................] - ETA: 0s - loss: 0.0413
78/82 [===========================>..] - ETA: 0s - loss: 0.0567
82/82 [==============================] - 0s 1ms/step - loss: 0.0557
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1747
38/82 [============>.................] - ETA: 0s - loss: 0.0456
76/82 [==========================>...] - ETA: 0s - loss: 0.0506
82/82 [==============================] - 0s 1ms/step - loss: 0.0545
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 3.9321e-04
39/82 [=============>................] - ETA: 0s - loss: 0.0474    
77/82 [===========================>..] - ETA: 0s - loss: 0.0509
82/82 [==============================] - 0s 1ms/step - loss: 0.0520
-> test with GAN.predict
GAN tn, fp: 188, 17
GAN fn, tp: 6, 3
GAN f1 score: 0.207
GAN cohens kappa score: 0.158

-> test with 'LR'
LR tn, fp: 176, 29
LR fn, tp: 2, 7
LR f1 score: 0.311
LR cohens kappa score: 0.261
LR average precision score: 0.247

-> test with 'RF'
RF tn, fp: 198, 7
RF fn, tp: 6, 3
RF f1 score: 0.316
RF cohens kappa score: 0.284

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

-> test with 'KNN'
KNN tn, fp: 181, 24
KNN fn, tp: 5, 4
KNN f1 score: 0.216
KNN cohens kappa score: 0.163


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.0052
40/82 [=============>................] - ETA: 0s - loss: 0.0727 
79/82 [===========================>..] - ETA: 0s - loss: 0.0901
82/82 [==============================] - 0s 1ms/step - loss: 0.0927
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2623
40/82 [=============>................] - ETA: 0s - loss: 0.0968
78/82 [===========================>..] - ETA: 0s - loss: 0.0850
82/82 [==============================] - 0s 1ms/step - loss: 0.0826
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0177
39/82 [=============>................] - ETA: 0s - loss: 0.0621
78/82 [===========================>..] - ETA: 0s - loss: 0.0757
82/82 [==============================] - 0s 1ms/step - loss: 0.0737
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0381
39/82 [=============>................] - ETA: 0s - loss: 0.0703
70/82 [========================>.....] - ETA: 0s - loss: 0.0689
82/82 [==============================] - 0s 1ms/step - loss: 0.0704
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1204
32/82 [==========>...................] - ETA: 0s - loss: 0.0670
67/82 [=======================>......] - ETA: 0s - loss: 0.0634
82/82 [==============================] - 0s 1ms/step - loss: 0.0668
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0552
39/82 [=============>................] - ETA: 0s - loss: 0.0612
77/82 [===========================>..] - ETA: 0s - loss: 0.0666
82/82 [==============================] - 0s 1ms/step - loss: 0.0647
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0087
38/82 [============>.................] - ETA: 0s - loss: 0.0716
72/82 [=========================>....] - ETA: 0s - loss: 0.0678
82/82 [==============================] - 0s 1ms/step - loss: 0.0635
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0171
37/82 [============>.................] - ETA: 0s - loss: 0.0423
76/82 [==========================>...] - ETA: 0s - loss: 0.0580
82/82 [==============================] - 0s 1ms/step - loss: 0.0651
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0041
39/82 [=============>................] - ETA: 0s - loss: 0.0520
79/82 [===========================>..] - ETA: 0s - loss: 0.0595
82/82 [==============================] - 0s 1ms/step - loss: 0.0604
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0612
37/82 [============>.................] - ETA: 0s - loss: 0.0514
75/82 [==========================>...] - ETA: 0s - loss: 0.0569
82/82 [==============================] - 0s 1ms/step - loss: 0.0578
-> test with GAN.predict
GAN tn, fp: 200, 5
GAN fn, tp: 9, 0
GAN f1 score: 0.000
GAN cohens kappa score: -0.031

-> test with 'LR'
LR tn, fp: 192, 13
LR fn, tp: 3, 6
LR f1 score: 0.429
LR cohens kappa score: 0.394
LR average precision score: 0.349

-> test with 'RF'
RF tn, fp: 203, 2
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.016

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

-> test with 'KNN'
KNN tn, fp: 193, 12
KNN fn, tp: 3, 6
KNN f1 score: 0.444
KNN cohens kappa score: 0.411


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 17s - loss: 0.0037
35/82 [===========>..................] - ETA: 0s - loss: 0.1026 
72/82 [=========================>....] - ETA: 0s - loss: 0.1239
82/82 [==============================] - 0s 1ms/step - loss: 0.1159
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0139
41/82 [==============>...............] - ETA: 0s - loss: 0.0810
79/82 [===========================>..] - ETA: 0s - loss: 0.1006
82/82 [==============================] - 0s 1ms/step - loss: 0.0980
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0038
37/82 [============>.................] - ETA: 0s - loss: 0.1350
74/82 [==========================>...] - ETA: 0s - loss: 0.0876
82/82 [==============================] - 0s 1ms/step - loss: 0.0884
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3633
40/82 [=============>................] - ETA: 0s - loss: 0.0608
78/82 [===========================>..] - ETA: 0s - loss: 0.0770
82/82 [==============================] - 0s 1ms/step - loss: 0.0776
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0072
40/82 [=============>................] - ETA: 0s - loss: 0.0581
79/82 [===========================>..] - ETA: 0s - loss: 0.0782
82/82 [==============================] - 0s 1ms/step - loss: 0.0761
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1112
35/82 [===========>..................] - ETA: 0s - loss: 0.0656
67/82 [=======================>......] - ETA: 0s - loss: 0.0617
82/82 [==============================] - 0s 2ms/step - loss: 0.0709
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0160
36/82 [============>.................] - ETA: 0s - loss: 0.0610
75/82 [==========================>...] - ETA: 0s - loss: 0.0692
82/82 [==============================] - 0s 1ms/step - loss: 0.0684
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0055
39/82 [=============>................] - ETA: 0s - loss: 0.0648
78/82 [===========================>..] - ETA: 0s - loss: 0.0673
82/82 [==============================] - 0s 1ms/step - loss: 0.0680
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0483
39/82 [=============>................] - ETA: 0s - loss: 0.0670
66/82 [=======================>......] - ETA: 0s - loss: 0.0701
82/82 [==============================] - 0s 2ms/step - loss: 0.0644
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 6.7240e-04
27/82 [========>.....................] - ETA: 0s - loss: 0.0380    
57/82 [===================>..........] - ETA: 0s - loss: 0.0398
82/82 [==============================] - 0s 2ms/step - loss: 0.0605
-> test with GAN.predict
GAN tn, fp: 201, 4
GAN fn, tp: 5, 4
GAN f1 score: 0.471
GAN cohens kappa score: 0.449

-> test with 'LR'
LR tn, fp: 191, 14
LR fn, tp: 5, 4
LR f1 score: 0.296
LR cohens kappa score: 0.254
LR average precision score: 0.235

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

-> test with 'KNN'
KNN tn, fp: 193, 12
KNN fn, tp: 4, 5
KNN f1 score: 0.385
KNN cohens kappa score: 0.349


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 10s - loss: 0.1932
42/82 [==============>...............] - ETA: 0s - loss: 0.0973 
82/82 [==============================] - ETA: 0s - loss: 0.0825
82/82 [==============================] - 0s 1ms/step - loss: 0.0825
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0142
41/82 [==============>...............] - ETA: 0s - loss: 0.0651
81/82 [============================>.] - ETA: 0s - loss: 0.0878
82/82 [==============================] - 0s 1ms/step - loss: 0.0871
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0390
43/82 [==============>...............] - ETA: 0s - loss: 0.0610
82/82 [==============================] - 0s 1ms/step - loss: 0.0726
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0140
39/82 [=============>................] - ETA: 0s - loss: 0.0762
80/82 [============================>.] - ETA: 0s - loss: 0.0699
82/82 [==============================] - 0s 1ms/step - loss: 0.0688
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0262
36/82 [============>.................] - ETA: 0s - loss: 0.0651
68/82 [=======================>......] - ETA: 0s - loss: 0.0651
82/82 [==============================] - 0s 1ms/step - loss: 0.0652
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0768
36/82 [============>.................] - ETA: 0s - loss: 0.0382
70/82 [========================>.....] - ETA: 0s - loss: 0.0578
82/82 [==============================] - 0s 1ms/step - loss: 0.0631
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0057
43/82 [==============>...............] - ETA: 0s - loss: 0.0637
82/82 [==============================] - 0s 1ms/step - loss: 0.0627
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0868
35/82 [===========>..................] - ETA: 0s - loss: 0.0562
69/82 [========================>.....] - ETA: 0s - loss: 0.0556
82/82 [==============================] - 0s 1ms/step - loss: 0.0618
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1293
41/82 [==============>...............] - ETA: 0s - loss: 0.0505
82/82 [==============================] - ETA: 0s - loss: 0.0589
82/82 [==============================] - 0s 1ms/step - loss: 0.0589
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0122
35/82 [===========>..................] - ETA: 0s - loss: 0.0657
70/82 [========================>.....] - ETA: 0s - loss: 0.0563
82/82 [==============================] - 0s 1ms/step - loss: 0.0585
-> test with GAN.predict
GAN tn, fp: 194, 9
GAN fn, tp: 5, 2
GAN f1 score: 0.222
GAN cohens kappa score: 0.189

-> test with 'LR'
LR tn, fp: 173, 30
LR fn, tp: 2, 5
LR f1 score: 0.238
LR cohens kappa score: 0.193
LR average precision score: 0.265

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

-> test with 'GB'
GB tn, fp: 198, 5
GB fn, tp: 5, 2
GB f1 score: 0.286
GB cohens kappa score: 0.261

-> test with 'KNN'
KNN tn, fp: 184, 19
KNN fn, tp: 6, 1
KNN f1 score: 0.074
KNN cohens kappa score: 0.026


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

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 12s - loss: 0.1829
40/82 [=============>................] - ETA: 0s - loss: 0.0839 
78/82 [===========================>..] - ETA: 0s - loss: 0.0744
82/82 [==============================] - 0s 1ms/step - loss: 0.0723
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0609
40/82 [=============>................] - ETA: 0s - loss: 0.0590
77/82 [===========================>..] - ETA: 0s - loss: 0.0710
82/82 [==============================] - 0s 1ms/step - loss: 0.0736
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1760
31/82 [==========>...................] - ETA: 0s - loss: 0.0735
69/82 [========================>.....] - ETA: 0s - loss: 0.0699
82/82 [==============================] - 0s 1ms/step - loss: 0.0677
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0041
39/82 [=============>................] - ETA: 0s - loss: 0.0491
76/82 [==========================>...] - ETA: 0s - loss: 0.0681
82/82 [==============================] - 0s 1ms/step - loss: 0.0651
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0339
40/82 [=============>................] - ETA: 0s - loss: 0.0549
77/82 [===========================>..] - ETA: 0s - loss: 0.0640
82/82 [==============================] - 0s 1ms/step - loss: 0.0638
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1011
41/82 [==============>...............] - ETA: 0s - loss: 0.0559
80/82 [============================>.] - ETA: 0s - loss: 0.0616
82/82 [==============================] - 0s 1ms/step - loss: 0.0611
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0458
40/82 [=============>................] - ETA: 0s - loss: 0.0687
78/82 [===========================>..] - ETA: 0s - loss: 0.0595
82/82 [==============================] - 0s 1ms/step - loss: 0.0584
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0497
40/82 [=============>................] - ETA: 0s - loss: 0.0616
79/82 [===========================>..] - ETA: 0s - loss: 0.0583
82/82 [==============================] - 0s 1ms/step - loss: 0.0584
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0056
41/82 [==============>...............] - ETA: 0s - loss: 0.0506
80/82 [============================>.] - ETA: 0s - loss: 0.0550
82/82 [==============================] - 0s 1ms/step - loss: 0.0571
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1359
37/82 [============>.................] - ETA: 0s - loss: 0.0505
74/82 [==========================>...] - ETA: 0s - loss: 0.0536
82/82 [==============================] - 0s 1ms/step - loss: 0.0559
-> test with GAN.predict
GAN tn, fp: 195, 10
GAN fn, tp: 7, 2
GAN f1 score: 0.190
GAN cohens kappa score: 0.150

-> test with 'LR'
LR tn, fp: 184, 21
LR fn, tp: 4, 5
LR f1 score: 0.286
LR cohens kappa score: 0.238
LR average precision score: 0.193

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

-> test with 'GB'
GB tn, fp: 201, 4
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.027

-> test with 'KNN'
KNN tn, fp: 187, 18
KNN fn, tp: 4, 5
KNN f1 score: 0.312
KNN cohens kappa score: 0.268


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 16s - loss: 0.6266
40/82 [=============>................] - ETA: 0s - loss: 0.1282 
79/82 [===========================>..] - ETA: 0s - loss: 0.1283
82/82 [==============================] - 0s 1ms/step - loss: 0.1288
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0124
33/82 [===========>..................] - ETA: 0s - loss: 0.1148
66/82 [=======================>......] - ETA: 0s - loss: 0.0942
82/82 [==============================] - 0s 2ms/step - loss: 0.0895
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0287
38/82 [============>.................] - ETA: 0s - loss: 0.0858
74/82 [==========================>...] - ETA: 0s - loss: 0.0725
82/82 [==============================] - 0s 1ms/step - loss: 0.0726
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0277
39/82 [=============>................] - ETA: 0s - loss: 0.0621
76/82 [==========================>...] - ETA: 0s - loss: 0.0672
82/82 [==============================] - 0s 1ms/step - loss: 0.0642
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0913
30/82 [=========>....................] - ETA: 0s - loss: 0.0408
66/82 [=======================>......] - ETA: 0s - loss: 0.0600
82/82 [==============================] - 0s 2ms/step - loss: 0.0607
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0193
37/82 [============>.................] - ETA: 0s - loss: 0.0508
74/82 [==========================>...] - ETA: 0s - loss: 0.0558
82/82 [==============================] - 0s 1ms/step - loss: 0.0595
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0173
39/82 [=============>................] - ETA: 0s - loss: 0.0625
79/82 [===========================>..] - ETA: 0s - loss: 0.0579
82/82 [==============================] - 0s 1ms/step - loss: 0.0565
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0132
38/82 [============>.................] - ETA: 0s - loss: 0.0579
76/82 [==========================>...] - ETA: 0s - loss: 0.0586
82/82 [==============================] - 0s 1ms/step - loss: 0.0557
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0145
38/82 [============>.................] - ETA: 0s - loss: 0.0633
76/82 [==========================>...] - ETA: 0s - loss: 0.0564
82/82 [==============================] - 0s 1ms/step - loss: 0.0548
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0043
39/82 [=============>................] - ETA: 0s - loss: 0.0602
76/82 [==========================>...] - ETA: 0s - loss: 0.0572
82/82 [==============================] - 0s 1ms/step - loss: 0.0540
-> test with GAN.predict
GAN tn, fp: 204, 1
GAN fn, tp: 8, 1
GAN f1 score: 0.182
GAN cohens kappa score: 0.169

-> test with 'LR'
LR tn, fp: 193, 12
LR fn, tp: 4, 5
LR f1 score: 0.385
LR cohens kappa score: 0.349
LR average precision score: 0.605

-> test with 'RF'
RF tn, fp: 202, 3
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.021

-> test with 'GB'
GB tn, fp: 204, 1
GB fn, tp: 7, 2
GB f1 score: 0.333
GB cohens kappa score: 0.319

-> test with 'KNN'
KNN tn, fp: 195, 10
KNN fn, tp: 7, 2
KNN f1 score: 0.190
KNN cohens kappa score: 0.150


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 16s - loss: 0.0012
33/82 [===========>..................] - ETA: 0s - loss: 0.1523 
66/82 [=======================>......] - ETA: 0s - loss: 0.1430
82/82 [==============================] - 0s 2ms/step - loss: 0.1447
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 3.5356e-04
35/82 [===========>..................] - ETA: 0s - loss: 0.0473    
67/82 [=======================>......] - ETA: 0s - loss: 0.0747
82/82 [==============================] - 0s 2ms/step - loss: 0.0968
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0321
34/82 [===========>..................] - ETA: 0s - loss: 0.0810
68/82 [=======================>......] - ETA: 0s - loss: 0.0638
82/82 [==============================] - 0s 2ms/step - loss: 0.0828
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0073
38/82 [============>.................] - ETA: 0s - loss: 0.0786
77/82 [===========================>..] - ETA: 0s - loss: 0.0789
82/82 [==============================] - 0s 1ms/step - loss: 0.0794
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0109
34/82 [===========>..................] - ETA: 0s - loss: 0.0736
67/82 [=======================>......] - ETA: 0s - loss: 0.0788
82/82 [==============================] - 0s 2ms/step - loss: 0.0676
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0711
34/82 [===========>..................] - ETA: 0s - loss: 0.0743
70/82 [========================>.....] - ETA: 0s - loss: 0.0664
82/82 [==============================] - 0s 1ms/step - loss: 0.0656
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0047
40/82 [=============>................] - ETA: 0s - loss: 0.0709
79/82 [===========================>..] - ETA: 0s - loss: 0.0655
82/82 [==============================] - 0s 1ms/step - loss: 0.0653
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0135
34/82 [===========>..................] - ETA: 0s - loss: 0.0634
69/82 [========================>.....] - ETA: 0s - loss: 0.0616
82/82 [==============================] - 0s 1ms/step - loss: 0.0603
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0621
39/82 [=============>................] - ETA: 0s - loss: 0.0494
71/82 [========================>.....] - ETA: 0s - loss: 0.0606
82/82 [==============================] - 0s 1ms/step - loss: 0.0591
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0347
35/82 [===========>..................] - ETA: 0s - loss: 0.0670
70/82 [========================>.....] - ETA: 0s - loss: 0.0657
82/82 [==============================] - 0s 1ms/step - loss: 0.0595
-> test with GAN.predict
GAN tn, fp: 201, 4
GAN fn, tp: 5, 4
GAN f1 score: 0.471
GAN cohens kappa score: 0.449

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

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 7, 2
RF f1 score: 0.333
RF cohens kappa score: 0.319

-> test with 'GB'
GB tn, fp: 204, 1
GB fn, tp: 8, 1
GB f1 score: 0.182
GB cohens kappa score: 0.169

-> test with 'KNN'
KNN tn, fp: 187, 18
KNN fn, tp: 5, 4
KNN f1 score: 0.258
KNN cohens kappa score: 0.211


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 0.3983
37/82 [============>.................] - ETA: 0s - loss: 0.0823 
77/82 [===========================>..] - ETA: 0s - loss: 0.0864
82/82 [==============================] - 0s 1ms/step - loss: 0.0915
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0286
40/82 [=============>................] - ETA: 0s - loss: 0.0758
78/82 [===========================>..] - ETA: 0s - loss: 0.0743
82/82 [==============================] - 0s 1ms/step - loss: 0.0818
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1552
40/82 [=============>................] - ETA: 0s - loss: 0.0738
81/82 [============================>.] - ETA: 0s - loss: 0.0776
82/82 [==============================] - 0s 1ms/step - loss: 0.0768
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0011
37/82 [============>.................] - ETA: 0s - loss: 0.0903
76/82 [==========================>...] - ETA: 0s - loss: 0.0777
82/82 [==============================] - 0s 1ms/step - loss: 0.0769
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0173
39/82 [=============>................] - ETA: 0s - loss: 0.0683
76/82 [==========================>...] - ETA: 0s - loss: 0.0705
82/82 [==============================] - 0s 1ms/step - loss: 0.0740
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0298
38/82 [============>.................] - ETA: 0s - loss: 0.0484
76/82 [==========================>...] - ETA: 0s - loss: 0.0705
82/82 [==============================] - 0s 1ms/step - loss: 0.0701
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2012
39/82 [=============>................] - ETA: 0s - loss: 0.0617
77/82 [===========================>..] - ETA: 0s - loss: 0.0665
82/82 [==============================] - 0s 1ms/step - loss: 0.0696
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0641
37/82 [============>.................] - ETA: 0s - loss: 0.0627
71/82 [========================>.....] - ETA: 0s - loss: 0.0684
82/82 [==============================] - 0s 2ms/step - loss: 0.0689
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0588
34/82 [===========>..................] - ETA: 0s - loss: 0.0664
72/82 [=========================>....] - ETA: 0s - loss: 0.0707
82/82 [==============================] - 0s 1ms/step - loss: 0.0679
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0086
39/82 [=============>................] - ETA: 0s - loss: 0.0703
71/82 [========================>.....] - ETA: 0s - loss: 0.0626
82/82 [==============================] - 0s 1ms/step - loss: 0.0651
-> test with GAN.predict
GAN tn, fp: 196, 9
GAN fn, tp: 7, 2
GAN f1 score: 0.200
GAN cohens kappa score: 0.161

-> test with 'LR'
LR tn, fp: 179, 26
LR fn, tp: 1, 8
LR f1 score: 0.372
LR cohens kappa score: 0.327
LR average precision score: 0.395

-> test with 'RF'
RF tn, fp: 203, 2
RF fn, tp: 7, 2
RF f1 score: 0.308
RF cohens kappa score: 0.289

-> test with 'GB'
GB tn, fp: 203, 2
GB fn, tp: 7, 2
GB f1 score: 0.308
GB cohens kappa score: 0.289

-> test with 'KNN'
KNN tn, fp: 190, 15
KNN fn, tp: 5, 4
KNN f1 score: 0.286
KNN cohens kappa score: 0.242


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 10s - loss: 0.0057
41/82 [==============>...............] - ETA: 0s - loss: 0.0850 
82/82 [==============================] - ETA: 0s - loss: 0.1001
82/82 [==============================] - 0s 1ms/step - loss: 0.1001
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0078
39/82 [=============>................] - ETA: 0s - loss: 0.1064
79/82 [===========================>..] - ETA: 0s - loss: 0.0857
82/82 [==============================] - 0s 1ms/step - loss: 0.0886
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1584
41/82 [==============>...............] - ETA: 0s - loss: 0.0835
82/82 [==============================] - ETA: 0s - loss: 0.0780
82/82 [==============================] - 0s 1ms/step - loss: 0.0780
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0074
42/82 [==============>...............] - ETA: 0s - loss: 0.0654
80/82 [============================>.] - ETA: 0s - loss: 0.0764
82/82 [==============================] - 0s 1ms/step - loss: 0.0751
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0660
35/82 [===========>..................] - ETA: 0s - loss: 0.0914
71/82 [========================>.....] - ETA: 0s - loss: 0.0777
82/82 [==============================] - 0s 1ms/step - loss: 0.0707
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0105
37/82 [============>.................] - ETA: 0s - loss: 0.0771
79/82 [===========================>..] - ETA: 0s - loss: 0.0739
82/82 [==============================] - 0s 1ms/step - loss: 0.0742
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0227
40/82 [=============>................] - ETA: 0s - loss: 0.0666
81/82 [============================>.] - ETA: 0s - loss: 0.0716
82/82 [==============================] - 0s 1ms/step - loss: 0.0708
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0257
42/82 [==============>...............] - ETA: 0s - loss: 0.0460
82/82 [==============================] - 0s 1ms/step - loss: 0.0617
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0987
41/82 [==============>...............] - ETA: 0s - loss: 0.0628
80/82 [============================>.] - ETA: 0s - loss: 0.0642
82/82 [==============================] - 0s 1ms/step - loss: 0.0645
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1820
42/82 [==============>...............] - ETA: 0s - loss: 0.0602
82/82 [==============================] - ETA: 0s - loss: 0.0622
82/82 [==============================] - 0s 1ms/step - loss: 0.0622
-> test with GAN.predict
GAN tn, fp: 194, 9
GAN fn, tp: 4, 3
GAN f1 score: 0.316
GAN cohens kappa score: 0.286

-> test with 'LR'
LR tn, fp: 186, 17
LR fn, tp: 1, 6
LR f1 score: 0.400
LR cohens kappa score: 0.368
LR average precision score: 0.434

-> test with 'RF'
RF tn, fp: 201, 2
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.015

-> test with 'GB'
GB tn, fp: 203, 0
GB fn, tp: 6, 1
GB f1 score: 0.250
GB cohens kappa score: 0.244

-> test with 'KNN'
KNN tn, fp: 188, 15
KNN fn, tp: 4, 3
KNN f1 score: 0.240
KNN cohens kappa score: 0.202


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

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.2794
41/82 [==============>...............] - ETA: 0s - loss: 0.1009 
80/82 [============================>.] - ETA: 0s - loss: 0.0990
82/82 [==============================] - 0s 1ms/step - loss: 0.0969
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0034
36/82 [============>.................] - ETA: 0s - loss: 0.0785
72/82 [=========================>....] - ETA: 0s - loss: 0.0782
82/82 [==============================] - 0s 1ms/step - loss: 0.0924
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0346
40/82 [=============>................] - ETA: 0s - loss: 0.0968
77/82 [===========================>..] - ETA: 0s - loss: 0.0837
82/82 [==============================] - 0s 1ms/step - loss: 0.0855
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0310
38/82 [============>.................] - ETA: 0s - loss: 0.0741
76/82 [==========================>...] - ETA: 0s - loss: 0.0670
82/82 [==============================] - 0s 1ms/step - loss: 0.0738
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0087
37/82 [============>.................] - ETA: 0s - loss: 0.0960
76/82 [==========================>...] - ETA: 0s - loss: 0.0711
82/82 [==============================] - 0s 1ms/step - loss: 0.0717
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0372
41/82 [==============>...............] - ETA: 0s - loss: 0.0554
80/82 [============================>.] - ETA: 0s - loss: 0.0702
82/82 [==============================] - 0s 1ms/step - loss: 0.0701
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0333
40/82 [=============>................] - ETA: 0s - loss: 0.0656
79/82 [===========================>..] - ETA: 0s - loss: 0.0666
82/82 [==============================] - 0s 1ms/step - loss: 0.0687
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0360
40/82 [=============>................] - ETA: 0s - loss: 0.0518
77/82 [===========================>..] - ETA: 0s - loss: 0.0694
82/82 [==============================] - 0s 1ms/step - loss: 0.0703
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0068
41/82 [==============>...............] - ETA: 0s - loss: 0.0560
79/82 [===========================>..] - ETA: 0s - loss: 0.0633
82/82 [==============================] - 0s 1ms/step - loss: 0.0650
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0881
40/82 [=============>................] - ETA: 0s - loss: 0.0611
80/82 [============================>.] - ETA: 0s - loss: 0.0636
82/82 [==============================] - 0s 1ms/step - loss: 0.0627
-> test with GAN.predict
GAN tn, fp: 192, 13
GAN fn, tp: 5, 4
GAN f1 score: 0.308
GAN cohens kappa score: 0.267

-> test with 'LR'
LR tn, fp: 184, 21
LR fn, tp: 5, 4
LR f1 score: 0.235
LR cohens kappa score: 0.185
LR average precision score: 0.264

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 8, 1
RF f1 score: 0.182
RF cohens kappa score: 0.169

-> test with 'GB'
GB tn, fp: 202, 3
GB fn, tp: 8, 1
GB f1 score: 0.154
GB cohens kappa score: 0.131

-> test with 'KNN'
KNN tn, fp: 186, 19
KNN fn, tp: 2, 7
KNN f1 score: 0.400
KNN cohens kappa score: 0.360


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 0.0209
40/82 [=============>................] - ETA: 0s - loss: 0.0778 
79/82 [===========================>..] - ETA: 0s - loss: 0.0774
82/82 [==============================] - 0s 1ms/step - loss: 0.0754
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0220
39/82 [=============>................] - ETA: 0s - loss: 0.0636
78/82 [===========================>..] - ETA: 0s - loss: 0.0711
82/82 [==============================] - 0s 1ms/step - loss: 0.0691
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0660
39/82 [=============>................] - ETA: 0s - loss: 0.0722
74/82 [==========================>...] - ETA: 0s - loss: 0.0647
82/82 [==============================] - 0s 1ms/step - loss: 0.0651
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0248
38/82 [============>.................] - ETA: 0s - loss: 0.0669
78/82 [===========================>..] - ETA: 0s - loss: 0.0707
82/82 [==============================] - 0s 1ms/step - loss: 0.0684
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0220
40/82 [=============>................] - ETA: 0s - loss: 0.0714
77/82 [===========================>..] - ETA: 0s - loss: 0.0647
82/82 [==============================] - 0s 1ms/step - loss: 0.0662
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2651
40/82 [=============>................] - ETA: 0s - loss: 0.0773
79/82 [===========================>..] - ETA: 0s - loss: 0.0674
82/82 [==============================] - 0s 1ms/step - loss: 0.0664
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0222
39/82 [=============>................] - ETA: 0s - loss: 0.0674
69/82 [========================>.....] - ETA: 0s - loss: 0.0609
82/82 [==============================] - 0s 1ms/step - loss: 0.0647
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2348
35/82 [===========>..................] - ETA: 0s - loss: 0.0670
68/82 [=======================>......] - ETA: 0s - loss: 0.0671
82/82 [==============================] - 0s 2ms/step - loss: 0.0667
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0037
35/82 [===========>..................] - ETA: 0s - loss: 0.0732
71/82 [========================>.....] - ETA: 0s - loss: 0.0635
82/82 [==============================] - 0s 1ms/step - loss: 0.0645
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.3478
38/82 [============>.................] - ETA: 0s - loss: 0.0650
76/82 [==========================>...] - ETA: 0s - loss: 0.0675
82/82 [==============================] - 0s 1ms/step - loss: 0.0652
-> test with GAN.predict
GAN tn, fp: 199, 6
GAN fn, tp: 9, 0
GAN f1 score: 0.000
GAN cohens kappa score: -0.035

-> test with 'LR'
LR tn, fp: 184, 21
LR fn, tp: 3, 6
LR f1 score: 0.333
LR cohens kappa score: 0.288
LR average precision score: 0.360

-> test with 'RF'
RF tn, fp: 204, 1
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: 0.000

-> test with 'KNN'
KNN tn, fp: 184, 21
KNN fn, tp: 3, 6
KNN f1 score: 0.333
KNN cohens kappa score: 0.288


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 13s - loss: 8.8213e-04
41/82 [==============>...............] - ETA: 0s - loss: 0.1870     
80/82 [============================>.] - ETA: 0s - loss: 0.1391
82/82 [==============================] - 0s 1ms/step - loss: 0.1381
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.9977
41/82 [==============>...............] - ETA: 0s - loss: 0.1080
81/82 [============================>.] - ETA: 0s - loss: 0.1146
82/82 [==============================] - 0s 1ms/step - loss: 0.1135
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.4322
40/82 [=============>................] - ETA: 0s - loss: 0.1053
79/82 [===========================>..] - ETA: 0s - loss: 0.1006
82/82 [==============================] - 0s 1ms/step - loss: 0.0995
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2067
41/82 [==============>...............] - ETA: 0s - loss: 0.0936
80/82 [============================>.] - ETA: 0s - loss: 0.0899
82/82 [==============================] - 0s 1ms/step - loss: 0.0889
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0247
40/82 [=============>................] - ETA: 0s - loss: 0.0783
80/82 [============================>.] - ETA: 0s - loss: 0.0873
82/82 [==============================] - 0s 1ms/step - loss: 0.0867
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 7.2989e-04
38/82 [============>.................] - ETA: 0s - loss: 0.0860    
74/82 [==========================>...] - ETA: 0s - loss: 0.0801
82/82 [==============================] - 0s 1ms/step - loss: 0.0788
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2191
38/82 [============>.................] - ETA: 0s - loss: 0.0736
78/82 [===========================>..] - ETA: 0s - loss: 0.0773
82/82 [==============================] - 0s 1ms/step - loss: 0.0759
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1451
40/82 [=============>................] - ETA: 0s - loss: 0.0645
81/82 [============================>.] - ETA: 0s - loss: 0.0740
82/82 [==============================] - 0s 1ms/step - loss: 0.0764
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0011
40/82 [=============>................] - ETA: 0s - loss: 0.0891
76/82 [==========================>...] - ETA: 0s - loss: 0.0751
82/82 [==============================] - 0s 1ms/step - loss: 0.0702
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0140
37/82 [============>.................] - ETA: 0s - loss: 0.0704
73/82 [=========================>....] - ETA: 0s - loss: 0.0711
82/82 [==============================] - 0s 1ms/step - loss: 0.0693
-> test with GAN.predict
GAN tn, fp: 200, 5
GAN fn, tp: 7, 2
GAN f1 score: 0.250
GAN cohens kappa score: 0.221

-> test with 'LR'
LR tn, fp: 183, 22
LR fn, tp: 0, 9
LR f1 score: 0.450
LR cohens kappa score: 0.412
LR average precision score: 0.503

-> test with 'RF'
RF tn, fp: 205, 0
RF fn, tp: 8, 1
RF f1 score: 0.200
RF cohens kappa score: 0.193

-> test with 'GB'
GB tn, fp: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

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


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 14s - loss: 0.0098
40/82 [=============>................] - ETA: 0s - loss: 0.0968 
78/82 [===========================>..] - ETA: 0s - loss: 0.0973
82/82 [==============================] - 0s 1ms/step - loss: 0.0951
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2358
40/82 [=============>................] - ETA: 0s - loss: 0.0690
75/82 [==========================>...] - ETA: 0s - loss: 0.0809
82/82 [==============================] - 0s 1ms/step - loss: 0.0787
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0823
40/82 [=============>................] - ETA: 0s - loss: 0.0647
80/82 [============================>.] - ETA: 0s - loss: 0.0699
82/82 [==============================] - 0s 1ms/step - loss: 0.0696
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0059
41/82 [==============>...............] - ETA: 0s - loss: 0.0492
80/82 [============================>.] - ETA: 0s - loss: 0.0657
82/82 [==============================] - 0s 1ms/step - loss: 0.0672
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0095
39/82 [=============>................] - ETA: 0s - loss: 0.0551
77/82 [===========================>..] - ETA: 0s - loss: 0.0651
82/82 [==============================] - 0s 1ms/step - loss: 0.0641
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0228
39/82 [=============>................] - ETA: 0s - loss: 0.0565
79/82 [===========================>..] - ETA: 0s - loss: 0.0630
82/82 [==============================] - 0s 1ms/step - loss: 0.0627
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2187
39/82 [=============>................] - ETA: 0s - loss: 0.0681
77/82 [===========================>..] - ETA: 0s - loss: 0.0628
82/82 [==============================] - 0s 1ms/step - loss: 0.0608
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0034
40/82 [=============>................] - ETA: 0s - loss: 0.0635
76/82 [==========================>...] - ETA: 0s - loss: 0.0601
82/82 [==============================] - 0s 1ms/step - loss: 0.0567
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0169
35/82 [===========>..................] - ETA: 0s - loss: 0.0453
67/82 [=======================>......] - ETA: 0s - loss: 0.0599
82/82 [==============================] - 0s 2ms/step - loss: 0.0554
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0010
39/82 [=============>................] - ETA: 0s - loss: 0.0451
75/82 [==========================>...] - ETA: 0s - loss: 0.0569
82/82 [==============================] - 0s 1ms/step - loss: 0.0556
-> test with GAN.predict
GAN tn, fp: 198, 7
GAN fn, tp: 6, 3
GAN f1 score: 0.316
GAN cohens kappa score: 0.284

-> test with 'LR'
LR tn, fp: 195, 10
LR fn, tp: 5, 4
LR f1 score: 0.348
LR cohens kappa score: 0.313
LR average precision score: 0.209

-> test with 'RF'
RF tn, fp: 201, 4
RF fn, tp: 9, 0
RF f1 score: 0.000
RF cohens kappa score: -0.027

-> test with 'GB'
GB tn, fp: 202, 3
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.021

-> test with 'KNN'
KNN tn, fp: 197, 8
KNN fn, tp: 6, 3
KNN f1 score: 0.300
KNN cohens kappa score: 0.266


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 784 synthetic samples
-> retrain GAN for predict
Epoch 1/10

 1/82 [..............................] - ETA: 10s - loss: 0.0223
43/82 [==============>...............] - ETA: 0s - loss: 0.1028 
82/82 [==============================] - 0s 1ms/step - loss: 0.0828
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0533
43/82 [==============>...............] - ETA: 0s - loss: 0.0887
82/82 [==============================] - 0s 1ms/step - loss: 0.0756
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1852
43/82 [==============>...............] - ETA: 0s - loss: 0.0566
82/82 [==============================] - 0s 1ms/step - loss: 0.0749
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0253
43/82 [==============>...............] - ETA: 0s - loss: 0.0707
82/82 [==============================] - 0s 1ms/step - loss: 0.0698
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0063
43/82 [==============>...............] - ETA: 0s - loss: 0.0649
82/82 [==============================] - 0s 1ms/step - loss: 0.0692
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0443
44/82 [===============>..............] - ETA: 0s - loss: 0.0624
82/82 [==============================] - 0s 1ms/step - loss: 0.0682
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0322
43/82 [==============>...............] - ETA: 0s - loss: 0.0727
82/82 [==============================] - 0s 1ms/step - loss: 0.0651
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2224
43/82 [==============>...............] - ETA: 0s - loss: 0.0739
82/82 [==============================] - 0s 1ms/step - loss: 0.0684
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0193
44/82 [===============>..............] - ETA: 0s - loss: 0.0583
82/82 [==============================] - 0s 1ms/step - loss: 0.0648
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0614
43/82 [==============>...............] - ETA: 0s - loss: 0.0626
82/82 [==============================] - 0s 1ms/step - loss: 0.0615
-> test with GAN.predict
GAN tn, fp: 196, 7
GAN fn, tp: 6, 1
GAN f1 score: 0.133
GAN cohens kappa score: 0.101

-> test with 'LR'
LR tn, fp: 171, 32
LR fn, tp: 2, 5
LR f1 score: 0.227
LR cohens kappa score: 0.181
LR average precision score: 0.390

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

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

-> test with 'KNN'
KNN tn, fp: 178, 25
KNN fn, tp: 4, 3
KNN f1 score: 0.171
KNN cohens kappa score: 0.125

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 195, 38
LR fn, tp: 8, 9
LR f1 score: 0.545
LR cohens kappa score: 0.516
LR average precision score: 0.820


average:
LR tn, fp: 182.76, 21.84
LR fn, tp: 2.8, 5.8
LR f1 score: 0.323
LR cohens kappa score: 0.279
LR average precision score: 0.376


minimum:
LR tn, fp: 167, 10
LR fn, tp: 0, 1
LR f1 score: 0.062
LR cohens kappa score: 0.002
LR average precision score: 0.089


-----[ RF ]-----
maximum:
RF tn, fp: 205, 7
RF fn, tp: 9, 3
RF f1 score: 0.333
RF cohens kappa score: 0.319


average:
RF tn, fp: 201.48, 3.12
RF fn, tp: 7.8, 0.8
RF f1 score: 0.120
RF cohens kappa score: 0.099


minimum:
RF tn, fp: 196, 0
RF fn, tp: 6, 0
RF f1 score: 0.000
RF cohens kappa score: -0.035


-----[ GB ]-----
maximum:
GB tn, fp: 205, 7
GB fn, tp: 9, 4
GB f1 score: 0.429
GB cohens kappa score: 0.409


average:
GB tn, fp: 202.36, 2.24
GB fn, tp: 7.44, 1.16
GB f1 score: 0.181
GB cohens kappa score: 0.164


minimum:
GB tn, fp: 197, 0
GB fn, tp: 4, 0
GB f1 score: 0.000
GB cohens kappa score: -0.027


-----[ KNN ]-----
maximum:
KNN tn, fp: 198, 39
KNN fn, tp: 7, 7
KNN f1 score: 0.444
KNN cohens kappa score: 0.411


average:
KNN tn, fp: 187.56, 17.04
KNN fn, tp: 4.0, 4.6
KNN f1 score: 0.306
KNN cohens kappa score: 0.265


minimum:
KNN tn, fp: 166, 7
KNN fn, tp: 1, 1
KNN f1 score: 0.074
KNN cohens kappa score: 0.026


-----[ GAN ]-----
maximum:
GAN tn, fp: 205, 17
GAN fn, tp: 9, 4
GAN f1 score: 0.471
GAN cohens kappa score: 0.449


average:
GAN tn, fp: 197.68, 6.92
GAN fn, tp: 6.6, 2.0
GAN f1 score: 0.223
GAN cohens kappa score: 0.193


minimum:
GAN tn, fp: 188, 0
GAN fn, tp: 4, 0
GAN f1 score: 0.000
GAN cohens kappa score: -0.035