ConvGeNBenchmarkResults/data_result/convGAN-majority-5/folding_flare-F.log

///////////////////////////////////////////
// Running convGAN-majority-5 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: 15s - loss: 0.1290
35/82 [===========>..................] - ETA: 0s - loss: 0.1773 
67/82 [=======================>......] - ETA: 0s - loss: 0.1703
82/82 [==============================] - 0s 2ms/step - loss: 0.1631
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2184
37/82 [============>.................] - ETA: 0s - loss: 0.1536
73/82 [=========================>....] - ETA: 0s - loss: 0.1563
82/82 [==============================] - 0s 1ms/step - loss: 0.1587
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0601
37/82 [============>.................] - ETA: 0s - loss: 0.1463
72/82 [=========================>....] - ETA: 0s - loss: 0.1501
82/82 [==============================] - 0s 1ms/step - loss: 0.1558
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1287
32/82 [==========>...................] - ETA: 0s - loss: 0.1625
62/82 [=====================>........] - ETA: 0s - loss: 0.1643
82/82 [==============================] - 0s 2ms/step - loss: 0.1515
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1975
34/82 [===========>..................] - ETA: 0s - loss: 0.1499
68/82 [=======================>......] - ETA: 0s - loss: 0.1507
82/82 [==============================] - 0s 2ms/step - loss: 0.1494
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1833
40/82 [=============>................] - ETA: 0s - loss: 0.1202
76/82 [==========================>...] - ETA: 0s - loss: 0.1441
82/82 [==============================] - 0s 1ms/step - loss: 0.1477
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0472
35/82 [===========>..................] - ETA: 0s - loss: 0.1424
69/82 [========================>.....] - ETA: 0s - loss: 0.1362
82/82 [==============================] - 0s 2ms/step - loss: 0.1442
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1435
36/82 [============>.................] - ETA: 0s - loss: 0.1297
69/82 [========================>.....] - ETA: 0s - loss: 0.1386
82/82 [==============================] - 0s 1ms/step - loss: 0.1406
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0248
36/82 [============>.................] - ETA: 0s - loss: 0.1370
72/82 [=========================>....] - ETA: 0s - loss: 0.1393
82/82 [==============================] - 0s 1ms/step - loss: 0.1380
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0751
37/82 [============>.................] - ETA: 0s - loss: 0.1295
74/82 [==========================>...] - ETA: 0s - loss: 0.1369
82/82 [==============================] - 0s 1ms/step - loss: 0.1356
-> test with GAN.predict
GAN tn, fp: 185, 20
GAN fn, tp: 5, 4
GAN f1 score: 0.242
GAN cohens kappa score: 0.193

-> test with 'LR'
LR tn, fp: 171, 34
LR fn, tp: 5, 4
LR f1 score: 0.170
LR cohens kappa score: 0.110
LR average precision score: 0.086

-> 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: 204, 1
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.008

-> test with 'KNN'
KNN tn, fp: 175, 30
KNN fn, tp: 4, 5
KNN f1 score: 0.227
KNN cohens kappa score: 0.172


------ 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: 12s - loss: 0.1459
33/82 [===========>..................] - ETA: 0s - loss: 0.1904 
72/82 [=========================>....] - ETA: 0s - loss: 0.2130
82/82 [==============================] - 0s 1ms/step - loss: 0.2090
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.3843
41/82 [==============>...............] - ETA: 0s - loss: 0.1867
81/82 [============================>.] - ETA: 0s - loss: 0.2017
82/82 [==============================] - 0s 1ms/step - loss: 0.2027
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2287
41/82 [==============>...............] - ETA: 0s - loss: 0.1944
74/82 [==========================>...] - ETA: 0s - loss: 0.1988
82/82 [==============================] - 0s 1ms/step - loss: 0.1967
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1392
39/82 [=============>................] - ETA: 0s - loss: 0.1930
77/82 [===========================>..] - ETA: 0s - loss: 0.1929
82/82 [==============================] - 0s 1ms/step - loss: 0.1898
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2856
38/82 [============>.................] - ETA: 0s - loss: 0.1909
77/82 [===========================>..] - ETA: 0s - loss: 0.1869
82/82 [==============================] - 0s 1ms/step - loss: 0.1862
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1500
40/82 [=============>................] - ETA: 0s - loss: 0.1608
79/82 [===========================>..] - ETA: 0s - loss: 0.1775
82/82 [==============================] - 0s 1ms/step - loss: 0.1781
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.3032
41/82 [==============>...............] - ETA: 0s - loss: 0.1954
82/82 [==============================] - ETA: 0s - loss: 0.1730
82/82 [==============================] - 0s 1ms/step - loss: 0.1730
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0910
40/82 [=============>................] - ETA: 0s - loss: 0.1515
77/82 [===========================>..] - ETA: 0s - loss: 0.1700
82/82 [==============================] - 0s 1ms/step - loss: 0.1686
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1596
40/82 [=============>................] - ETA: 0s - loss: 0.1520
79/82 [===========================>..] - ETA: 0s - loss: 0.1607
82/82 [==============================] - 0s 1ms/step - loss: 0.1638
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0773
40/82 [=============>................] - ETA: 0s - loss: 0.1531
77/82 [===========================>..] - ETA: 0s - loss: 0.1614
82/82 [==============================] - 0s 1ms/step - loss: 0.1607
-> test with GAN.predict
GAN tn, fp: 183, 22
GAN fn, tp: 3, 6
GAN f1 score: 0.324
GAN cohens kappa score: 0.278

-> test with 'LR'
LR tn, fp: 155, 50
LR fn, tp: 1, 8
LR f1 score: 0.239
LR cohens kappa score: 0.179
LR average precision score: 0.339

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

-> 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: 169, 36
KNN fn, tp: 3, 6
KNN f1 score: 0.235
KNN cohens kappa score: 0.178


------ 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: 13s - loss: 0.1255
36/82 [============>.................] - ETA: 0s - loss: 0.1852 
76/82 [==========================>...] - ETA: 0s - loss: 0.1963
82/82 [==============================] - 0s 1ms/step - loss: 0.1980
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2387
34/82 [===========>..................] - ETA: 0s - loss: 0.2014
69/82 [========================>.....] - ETA: 0s - loss: 0.2021
82/82 [==============================] - 0s 1ms/step - loss: 0.1922
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.3369
41/82 [==============>...............] - ETA: 0s - loss: 0.1974
79/82 [===========================>..] - ETA: 0s - loss: 0.1896
82/82 [==============================] - 0s 1ms/step - loss: 0.1895
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0643
39/82 [=============>................] - ETA: 0s - loss: 0.1877
79/82 [===========================>..] - ETA: 0s - loss: 0.1803
82/82 [==============================] - 0s 1ms/step - loss: 0.1841
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.4209
39/82 [=============>................] - ETA: 0s - loss: 0.1644
79/82 [===========================>..] - ETA: 0s - loss: 0.1814
82/82 [==============================] - 0s 1ms/step - loss: 0.1813
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1077
40/82 [=============>................] - ETA: 0s - loss: 0.1704
78/82 [===========================>..] - ETA: 0s - loss: 0.1762
82/82 [==============================] - 0s 1ms/step - loss: 0.1773
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0480
39/82 [=============>................] - ETA: 0s - loss: 0.1665
79/82 [===========================>..] - ETA: 0s - loss: 0.1733
82/82 [==============================] - 0s 1ms/step - loss: 0.1727
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1302
40/82 [=============>................] - ETA: 0s - loss: 0.1765
79/82 [===========================>..] - ETA: 0s - loss: 0.1663
82/82 [==============================] - 0s 1ms/step - loss: 0.1685
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0548
40/82 [=============>................] - ETA: 0s - loss: 0.1574
78/82 [===========================>..] - ETA: 0s - loss: 0.1664
82/82 [==============================] - 0s 1ms/step - loss: 0.1645
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1370
36/82 [============>.................] - ETA: 0s - loss: 0.1643
73/82 [=========================>....] - ETA: 0s - loss: 0.1643
82/82 [==============================] - 0s 1ms/step - loss: 0.1617
-> test with GAN.predict
GAN tn, fp: 187, 18
GAN fn, tp: 4, 5
GAN f1 score: 0.312
GAN cohens kappa score: 0.268

-> 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: 0.336

-> 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: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 179, 26
KNN fn, tp: 4, 5
KNN f1 score: 0.250
KNN cohens kappa score: 0.198


------ 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: 12s - loss: 0.3013
37/82 [============>.................] - ETA: 0s - loss: 0.2138 
76/82 [==========================>...] - ETA: 0s - loss: 0.2223
82/82 [==============================] - 0s 1ms/step - loss: 0.2243
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1537
39/82 [=============>................] - ETA: 0s - loss: 0.2148
77/82 [===========================>..] - ETA: 0s - loss: 0.2206
82/82 [==============================] - 0s 1ms/step - loss: 0.2178
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2063
37/82 [============>.................] - ETA: 0s - loss: 0.2171
74/82 [==========================>...] - ETA: 0s - loss: 0.2133
82/82 [==============================] - 0s 1ms/step - loss: 0.2129
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2024
37/82 [============>.................] - ETA: 0s - loss: 0.1955
68/82 [=======================>......] - ETA: 0s - loss: 0.1983
82/82 [==============================] - 0s 2ms/step - loss: 0.2068
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2534
33/82 [===========>..................] - ETA: 0s - loss: 0.1905
71/82 [========================>.....] - ETA: 0s - loss: 0.2021
82/82 [==============================] - 0s 1ms/step - loss: 0.2021
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1192
42/82 [==============>...............] - ETA: 0s - loss: 0.2131
81/82 [============================>.] - ETA: 0s - loss: 0.1992
82/82 [==============================] - 0s 1ms/step - loss: 0.2001
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1545
40/82 [=============>................] - ETA: 0s - loss: 0.1900
78/82 [===========================>..] - ETA: 0s - loss: 0.1933
82/82 [==============================] - 0s 1ms/step - loss: 0.1921
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2987
38/82 [============>.................] - ETA: 0s - loss: 0.1851
75/82 [==========================>...] - ETA: 0s - loss: 0.1878
82/82 [==============================] - 0s 1ms/step - loss: 0.1907
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1753
41/82 [==============>...............] - ETA: 0s - loss: 0.1979
78/82 [===========================>..] - ETA: 0s - loss: 0.1899
82/82 [==============================] - 0s 1ms/step - loss: 0.1856
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0830
40/82 [=============>................] - ETA: 0s - loss: 0.1737
78/82 [===========================>..] - ETA: 0s - loss: 0.1792
82/82 [==============================] - 0s 1ms/step - loss: 0.1792
-> test with GAN.predict
GAN tn, fp: 194, 11
GAN fn, tp: 6, 3
GAN f1 score: 0.261
GAN cohens kappa score: 0.221

-> test with 'LR'
LR tn, fp: 180, 25
LR fn, tp: 0, 9
LR f1 score: 0.419
LR cohens kappa score: 0.377
LR average precision score: 0.673

-> 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: 204, 1
GB fn, tp: 7, 2
GB f1 score: 0.333
GB cohens kappa score: 0.319

-> 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 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: 10s - loss: 0.1781
42/82 [==============>...............] - ETA: 0s - loss: 0.1905 
82/82 [==============================] - ETA: 0s - loss: 0.1958
82/82 [==============================] - 0s 1ms/step - loss: 0.1958
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1292
42/82 [==============>...............] - ETA: 0s - loss: 0.1998
81/82 [============================>.] - ETA: 0s - loss: 0.1918
82/82 [==============================] - 0s 1ms/step - loss: 0.1906
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1084
43/82 [==============>...............] - ETA: 0s - loss: 0.1873
81/82 [============================>.] - ETA: 0s - loss: 0.1845
82/82 [==============================] - 0s 1ms/step - loss: 0.1848
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2414
38/82 [============>.................] - ETA: 0s - loss: 0.1853
80/82 [============================>.] - ETA: 0s - loss: 0.1787
82/82 [==============================] - 0s 1ms/step - loss: 0.1810
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2644
43/82 [==============>...............] - ETA: 0s - loss: 0.1696
82/82 [==============================] - 0s 1ms/step - loss: 0.1770
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0561
34/82 [===========>..................] - ETA: 0s - loss: 0.1835
69/82 [========================>.....] - ETA: 0s - loss: 0.1739
82/82 [==============================] - 0s 1ms/step - loss: 0.1732
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.3113
37/82 [============>.................] - ETA: 0s - loss: 0.1647
70/82 [========================>.....] - ETA: 0s - loss: 0.1718
82/82 [==============================] - 0s 1ms/step - loss: 0.1681
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0162
32/82 [==========>...................] - ETA: 0s - loss: 0.1685
67/82 [=======================>......] - ETA: 0s - loss: 0.1558
82/82 [==============================] - 0s 2ms/step - loss: 0.1646
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.2407
40/82 [=============>................] - ETA: 0s - loss: 0.1572
81/82 [============================>.] - ETA: 0s - loss: 0.1630
82/82 [==============================] - 0s 1ms/step - loss: 0.1624
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1265
41/82 [==============>...............] - ETA: 0s - loss: 0.1504
82/82 [==============================] - ETA: 0s - loss: 0.1571
82/82 [==============================] - 0s 1ms/step - loss: 0.1571
-> test with GAN.predict
GAN tn, fp: 177, 26
GAN fn, tp: 3, 4
GAN f1 score: 0.216
GAN cohens kappa score: 0.171

-> test with 'LR'
LR tn, fp: 171, 32
LR fn, tp: 3, 4
LR f1 score: 0.186
LR cohens kappa score: 0.138
LR average precision score: 0.281

-> test with 'RF'
RF tn, fp: 198, 5
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.029

-> test with 'GB'
GB tn, fp: 200, 3
GB fn, tp: 7, 0
GB f1 score: 0.000
GB cohens kappa score: -0.020

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


====== 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: 14s - loss: 0.1406
26/82 [========>.....................] - ETA: 0s - loss: 0.1525 
43/82 [==============>...............] - ETA: 0s - loss: 0.1874
60/82 [====================>.........] - ETA: 0s - loss: 0.1886
82/82 [==============================] - 0s 3ms/step - loss: 0.1948
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1502
32/82 [==========>...................] - ETA: 0s - loss: 0.1785
71/82 [========================>.....] - ETA: 0s - loss: 0.1907
82/82 [==============================] - 0s 1ms/step - loss: 0.1888
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1653
39/82 [=============>................] - ETA: 0s - loss: 0.1771
72/82 [=========================>....] - ETA: 0s - loss: 0.1884
82/82 [==============================] - 0s 1ms/step - loss: 0.1851
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.4122
38/82 [============>.................] - ETA: 0s - loss: 0.1898
72/82 [=========================>....] - ETA: 0s - loss: 0.1790
82/82 [==============================] - 0s 2ms/step - loss: 0.1814
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.3370
37/82 [============>.................] - ETA: 0s - loss: 0.1627
66/82 [=======================>......] - ETA: 0s - loss: 0.1753
82/82 [==============================] - 0s 2ms/step - loss: 0.1769
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0940
35/82 [===========>..................] - ETA: 0s - loss: 0.1642
68/82 [=======================>......] - ETA: 0s - loss: 0.1819
82/82 [==============================] - 0s 2ms/step - loss: 0.1733
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2436
33/82 [===========>..................] - ETA: 0s - loss: 0.1929
68/82 [=======================>......] - ETA: 0s - loss: 0.1724
82/82 [==============================] - 0s 2ms/step - loss: 0.1698
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0945
37/82 [============>.................] - ETA: 0s - loss: 0.1588
74/82 [==========================>...] - ETA: 0s - loss: 0.1716
82/82 [==============================] - 0s 1ms/step - loss: 0.1668
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1423
39/82 [=============>................] - ETA: 0s - loss: 0.1768
76/82 [==========================>...] - ETA: 0s - loss: 0.1639
82/82 [==============================] - 0s 1ms/step - loss: 0.1629
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1182
29/82 [=========>....................] - ETA: 0s - loss: 0.1299
55/82 [===================>..........] - ETA: 0s - loss: 0.1522
82/82 [==============================] - 0s 2ms/step - loss: 0.1587
-> test with GAN.predict
GAN tn, fp: 185, 20
GAN fn, tp: 2, 7
GAN f1 score: 0.389
GAN cohens kappa score: 0.348

-> test with 'LR'
LR tn, fp: 168, 37
LR fn, tp: 2, 7
LR f1 score: 0.264
LR cohens kappa score: 0.209
LR average precision score: 0.424

-> 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: 179, 26
KNN fn, tp: 3, 6
KNN f1 score: 0.293
KNN cohens kappa score: 0.243


------ 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: 16s - loss: 0.1975
40/82 [=============>................] - ETA: 0s - loss: 0.1860 
76/82 [==========================>...] - ETA: 0s - loss: 0.1806
82/82 [==============================] - 0s 1ms/step - loss: 0.1824
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0642
40/82 [=============>................] - ETA: 0s - loss: 0.1499
73/82 [=========================>....] - ETA: 0s - loss: 0.1781
82/82 [==============================] - 0s 1ms/step - loss: 0.1796
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2349
36/82 [============>.................] - ETA: 0s - loss: 0.1579
72/82 [=========================>....] - ETA: 0s - loss: 0.1790
82/82 [==============================] - 0s 1ms/step - loss: 0.1735
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1155
40/82 [=============>................] - ETA: 0s - loss: 0.1619
76/82 [==========================>...] - ETA: 0s - loss: 0.1690
82/82 [==============================] - 0s 1ms/step - loss: 0.1702
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0968
41/82 [==============>...............] - ETA: 0s - loss: 0.1948
79/82 [===========================>..] - ETA: 0s - loss: 0.1698
82/82 [==============================] - 0s 1ms/step - loss: 0.1670
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2797
39/82 [=============>................] - ETA: 0s - loss: 0.1619
74/82 [==========================>...] - ETA: 0s - loss: 0.1639
82/82 [==============================] - 0s 1ms/step - loss: 0.1641
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0728
40/82 [=============>................] - ETA: 0s - loss: 0.1560
78/82 [===========================>..] - ETA: 0s - loss: 0.1533
82/82 [==============================] - 0s 1ms/step - loss: 0.1592
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1541
36/82 [============>.................] - ETA: 0s - loss: 0.1718
74/82 [==========================>...] - ETA: 0s - loss: 0.1541
82/82 [==============================] - 0s 1ms/step - loss: 0.1557
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1016
39/82 [=============>................] - ETA: 0s - loss: 0.1669
79/82 [===========================>..] - ETA: 0s - loss: 0.1545
82/82 [==============================] - 0s 1ms/step - loss: 0.1537
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0650
41/82 [==============>...............] - ETA: 0s - loss: 0.1314
78/82 [===========================>..] - ETA: 0s - loss: 0.1498
82/82 [==============================] - 0s 1ms/step - loss: 0.1515
-> test with GAN.predict
GAN tn, fp: 188, 17
GAN fn, tp: 5, 4
GAN f1 score: 0.267
GAN cohens kappa score: 0.221

-> test with 'LR'
LR tn, fp: 172, 33
LR fn, tp: 3, 6
LR f1 score: 0.250
LR cohens kappa score: 0.195
LR average precision score: 0.361

-> 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: 176, 29
KNN fn, tp: 2, 7
KNN f1 score: 0.311
KNN cohens kappa score: 0.261


------ 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: 17s - loss: 0.4273
39/82 [=============>................] - ETA: 0s - loss: 0.1667 
78/82 [===========================>..] - ETA: 0s - loss: 0.1806
82/82 [==============================] - 0s 1ms/step - loss: 0.1781
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0866
40/82 [=============>................] - ETA: 0s - loss: 0.1847
75/82 [==========================>...] - ETA: 0s - loss: 0.1832
82/82 [==============================] - 0s 1ms/step - loss: 0.1751
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0766
38/82 [============>.................] - ETA: 0s - loss: 0.1776
70/82 [========================>.....] - ETA: 0s - loss: 0.1688
82/82 [==============================] - 0s 1ms/step - loss: 0.1711
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2099
35/82 [===========>..................] - ETA: 0s - loss: 0.1752
67/82 [=======================>......] - ETA: 0s - loss: 0.1733
82/82 [==============================] - 0s 2ms/step - loss: 0.1677
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0652
33/82 [===========>..................] - ETA: 0s - loss: 0.1643
70/82 [========================>.....] - ETA: 0s - loss: 0.1642
82/82 [==============================] - 0s 1ms/step - loss: 0.1641
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0563
36/82 [============>.................] - ETA: 0s - loss: 0.1676
74/82 [==========================>...] - ETA: 0s - loss: 0.1628
82/82 [==============================] - 0s 1ms/step - loss: 0.1597
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0712
39/82 [=============>................] - ETA: 0s - loss: 0.1498
77/82 [===========================>..] - ETA: 0s - loss: 0.1541
82/82 [==============================] - 0s 1ms/step - loss: 0.1564
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1850
39/82 [=============>................] - ETA: 0s - loss: 0.1625
75/82 [==========================>...] - ETA: 0s - loss: 0.1500
82/82 [==============================] - 0s 1ms/step - loss: 0.1538
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1486
35/82 [===========>..................] - ETA: 0s - loss: 0.1706
65/82 [======================>.......] - ETA: 0s - loss: 0.1526
82/82 [==============================] - 0s 2ms/step - loss: 0.1507
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2666
36/82 [============>.................] - ETA: 0s - loss: 0.1512
71/82 [========================>.....] - ETA: 0s - loss: 0.1519
82/82 [==============================] - 0s 1ms/step - loss: 0.1456
-> test with GAN.predict
GAN tn, fp: 186, 19
GAN fn, tp: 5, 4
GAN f1 score: 0.250
GAN cohens kappa score: 0.202

-> test with 'LR'
LR tn, fp: 175, 30
LR fn, tp: 3, 6
LR f1 score: 0.267
LR cohens kappa score: 0.214
LR average precision score: 0.228

-> 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: 205, 0
GB fn, tp: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 182, 23
KNN fn, tp: 4, 5
KNN f1 score: 0.270
KNN cohens kappa score: 0.221


------ 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: 16s - loss: 0.0942
26/82 [========>.....................] - ETA: 0s - loss: 0.1810 
56/82 [===================>..........] - ETA: 0s - loss: 0.1647
82/82 [==============================] - 0s 2ms/step - loss: 0.1649
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.3518
32/82 [==========>...................] - ETA: 0s - loss: 0.1664
62/82 [=====================>........] - ETA: 0s - loss: 0.1632
82/82 [==============================] - 0s 2ms/step - loss: 0.1606
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1982
33/82 [===========>..................] - ETA: 0s - loss: 0.1587
61/82 [=====================>........] - ETA: 0s - loss: 0.1565
82/82 [==============================] - 0s 2ms/step - loss: 0.1578
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1788
28/82 [=========>....................] - ETA: 0s - loss: 0.1411
64/82 [======================>.......] - ETA: 0s - loss: 0.1502
82/82 [==============================] - 0s 2ms/step - loss: 0.1537
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1515
36/82 [============>.................] - ETA: 0s - loss: 0.1441
70/82 [========================>.....] - ETA: 0s - loss: 0.1520
82/82 [==============================] - 0s 1ms/step - loss: 0.1515
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0283
36/82 [============>.................] - ETA: 0s - loss: 0.1678
73/82 [=========================>....] - ETA: 0s - loss: 0.1498
82/82 [==============================] - 0s 1ms/step - loss: 0.1481
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2577
39/82 [=============>................] - ETA: 0s - loss: 0.1247
76/82 [==========================>...] - ETA: 0s - loss: 0.1494
82/82 [==============================] - 0s 1ms/step - loss: 0.1468
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1216
38/82 [============>.................] - ETA: 0s - loss: 0.1400
75/82 [==========================>...] - ETA: 0s - loss: 0.1464
82/82 [==============================] - 0s 1ms/step - loss: 0.1441
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0794
37/82 [============>.................] - ETA: 0s - loss: 0.1380
76/82 [==========================>...] - ETA: 0s - loss: 0.1364
82/82 [==============================] - 0s 1ms/step - loss: 0.1405
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0772
40/82 [=============>................] - ETA: 0s - loss: 0.1351
78/82 [===========================>..] - ETA: 0s - loss: 0.1403
82/82 [==============================] - 0s 1ms/step - loss: 0.1392
-> test with GAN.predict
GAN tn, fp: 196, 9
GAN fn, tp: 5, 4
GAN f1 score: 0.364
GAN cohens kappa score: 0.330

-> test with 'LR'
LR tn, fp: 185, 20
LR fn, tp: 4, 5
LR f1 score: 0.294
LR cohens kappa score: 0.248
LR average precision score: 0.290

-> 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: 183, 22
KNN fn, tp: 4, 5
KNN f1 score: 0.278
KNN cohens kappa score: 0.229


------ 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: 10s - loss: 0.2762
43/82 [==============>...............] - ETA: 0s - loss: 0.2263 
82/82 [==============================] - 0s 1ms/step - loss: 0.2138
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1681
41/82 [==============>...............] - ETA: 0s - loss: 0.2198
75/82 [==========================>...] - ETA: 0s - loss: 0.2089
82/82 [==============================] - 0s 1ms/step - loss: 0.2087
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1898
39/82 [=============>................] - ETA: 0s - loss: 0.2120
80/82 [============================>.] - ETA: 0s - loss: 0.2052
82/82 [==============================] - 0s 1ms/step - loss: 0.2036
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1432
40/82 [=============>................] - ETA: 0s - loss: 0.2037
76/82 [==========================>...] - ETA: 0s - loss: 0.1955
82/82 [==============================] - 0s 1ms/step - loss: 0.1988
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1564
37/82 [============>.................] - ETA: 0s - loss: 0.1912
77/82 [===========================>..] - ETA: 0s - loss: 0.1941
82/82 [==============================] - 0s 1ms/step - loss: 0.1931
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1984
43/82 [==============>...............] - ETA: 0s - loss: 0.1929
82/82 [==============================] - 0s 1ms/step - loss: 0.1901
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1065
44/82 [===============>..............] - ETA: 0s - loss: 0.1847
82/82 [==============================] - 0s 1ms/step - loss: 0.1865
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0849
41/82 [==============>...............] - ETA: 0s - loss: 0.1874
72/82 [=========================>....] - ETA: 0s - loss: 0.1832
82/82 [==============================] - 0s 1ms/step - loss: 0.1821
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.3913
41/82 [==============>...............] - ETA: 0s - loss: 0.1776
80/82 [============================>.] - ETA: 0s - loss: 0.1756
82/82 [==============================] - 0s 1ms/step - loss: 0.1767
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0827
36/82 [============>.................] - ETA: 0s - loss: 0.1561
76/82 [==========================>...] - ETA: 0s - loss: 0.1724
82/82 [==============================] - 0s 1ms/step - loss: 0.1725
-> test with GAN.predict
GAN tn, fp: 177, 26
GAN fn, tp: 1, 6
GAN f1 score: 0.308
GAN cohens kappa score: 0.268

-> test with 'LR'
LR tn, fp: 165, 38
LR fn, tp: 0, 7
LR f1 score: 0.269
LR cohens kappa score: 0.224
LR average precision score: 0.370

-> test with 'RF'
RF tn, fp: 202, 1
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.008

-> 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: 174, 29
KNN fn, tp: 1, 6
KNN f1 score: 0.286
KNN cohens kappa score: 0.244


====== 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: 0.0979
39/82 [=============>................] - ETA: 0s - loss: 0.1972 
76/82 [==========================>...] - ETA: 0s - loss: 0.2296
82/82 [==============================] - 0s 1ms/step - loss: 0.2260
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1718
35/82 [===========>..................] - ETA: 0s - loss: 0.2259
69/82 [========================>.....] - ETA: 0s - loss: 0.2186
82/82 [==============================] - 0s 2ms/step - loss: 0.2225
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1916
33/82 [===========>..................] - ETA: 0s - loss: 0.2397
68/82 [=======================>......] - ETA: 0s - loss: 0.2171
82/82 [==============================] - 0s 2ms/step - loss: 0.2147
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2793
32/82 [==========>...................] - ETA: 0s - loss: 0.2266
66/82 [=======================>......] - ETA: 0s - loss: 0.2136
82/82 [==============================] - 0s 2ms/step - loss: 0.2093
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2190
37/82 [============>.................] - ETA: 0s - loss: 0.1967
72/82 [=========================>....] - ETA: 0s - loss: 0.2128
82/82 [==============================] - 0s 1ms/step - loss: 0.2059
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1478
36/82 [============>.................] - ETA: 0s - loss: 0.1683
68/82 [=======================>......] - ETA: 0s - loss: 0.1953
82/82 [==============================] - 0s 2ms/step - loss: 0.1997
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.2228
30/82 [=========>....................] - ETA: 0s - loss: 0.1832
63/82 [======================>.......] - ETA: 0s - loss: 0.1926
82/82 [==============================] - 0s 2ms/step - loss: 0.1950
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2630
33/82 [===========>..................] - ETA: 0s - loss: 0.1852
67/82 [=======================>......] - ETA: 0s - loss: 0.1855
82/82 [==============================] - 0s 2ms/step - loss: 0.1893
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1262
33/82 [===========>..................] - ETA: 0s - loss: 0.1881
54/82 [==================>...........] - ETA: 0s - loss: 0.1779
74/82 [==========================>...] - ETA: 0s - loss: 0.1832
82/82 [==============================] - 0s 2ms/step - loss: 0.1848
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2862
20/82 [======>.......................] - ETA: 0s - loss: 0.1726
37/82 [============>.................] - ETA: 0s - loss: 0.1766
58/82 [====================>.........] - ETA: 0s - loss: 0.1749
76/82 [==========================>...] - ETA: 0s - loss: 0.1807
82/82 [==============================] - 0s 3ms/step - loss: 0.1798
-> test with GAN.predict
GAN tn, fp: 198, 7
GAN fn, tp: 2, 7
GAN f1 score: 0.609
GAN cohens kappa score: 0.588

-> test with 'LR'
LR tn, fp: 187, 18
LR fn, tp: 2, 7
LR f1 score: 0.412
LR cohens kappa score: 0.373
LR average precision score: 0.724

-> 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: 196, 9
KNN fn, tp: 2, 7
KNN f1 score: 0.560
KNN cohens kappa score: 0.535


------ 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: 14s - loss: 0.2017
34/82 [===========>..................] - ETA: 0s - loss: 0.1476 
70/82 [========================>.....] - ETA: 0s - loss: 0.1387
82/82 [==============================] - 0s 1ms/step - loss: 0.1395
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1063
37/82 [============>.................] - ETA: 0s - loss: 0.1410
73/82 [=========================>....] - ETA: 0s - loss: 0.1405
82/82 [==============================] - 0s 1ms/step - loss: 0.1356
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0899
34/82 [===========>..................] - ETA: 0s - loss: 0.1363
69/82 [========================>.....] - ETA: 0s - loss: 0.1336
82/82 [==============================] - 0s 1ms/step - loss: 0.1304
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3463
36/82 [============>.................] - ETA: 0s - loss: 0.1398
74/82 [==========================>...] - ETA: 0s - loss: 0.1234
82/82 [==============================] - 0s 1ms/step - loss: 0.1289
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0949
36/82 [============>.................] - ETA: 0s - loss: 0.1297
70/82 [========================>.....] - ETA: 0s - loss: 0.1245
82/82 [==============================] - 0s 1ms/step - loss: 0.1246
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1099
33/82 [===========>..................] - ETA: 0s - loss: 0.1051
67/82 [=======================>......] - ETA: 0s - loss: 0.1181
82/82 [==============================] - 0s 2ms/step - loss: 0.1233
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1114
36/82 [============>.................] - ETA: 0s - loss: 0.1148
66/82 [=======================>......] - ETA: 0s - loss: 0.1207
82/82 [==============================] - 0s 2ms/step - loss: 0.1204
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1960
33/82 [===========>..................] - ETA: 0s - loss: 0.1380
70/82 [========================>.....] - ETA: 0s - loss: 0.1180
82/82 [==============================] - 0s 1ms/step - loss: 0.1181
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.3252
33/82 [===========>..................] - ETA: 0s - loss: 0.1089
64/82 [======================>.......] - ETA: 0s - loss: 0.1075
82/82 [==============================] - 0s 2ms/step - loss: 0.1150
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0613
39/82 [=============>................] - ETA: 0s - loss: 0.1225
75/82 [==========================>...] - ETA: 0s - loss: 0.1203
82/82 [==============================] - 0s 1ms/step - loss: 0.1147
-> test with GAN.predict
GAN tn, fp: 182, 23
GAN fn, tp: 4, 5
GAN f1 score: 0.270
GAN cohens kappa score: 0.221

-> test with 'LR'
LR tn, fp: 164, 41
LR fn, tp: 2, 7
LR f1 score: 0.246
LR cohens kappa score: 0.188
LR average precision score: 0.203

-> test with 'RF'
RF tn, fp: 197, 8
RF fn, tp: 7, 2
RF f1 score: 0.211
RF cohens kappa score: 0.174

-> test with 'GB'
GB tn, fp: 204, 1
GB fn, tp: 6, 3
GB f1 score: 0.462
GB cohens kappa score: 0.447

-> test with 'KNN'
KNN tn, fp: 165, 40
KNN fn, tp: 4, 5
KNN f1 score: 0.185
KNN cohens kappa score: 0.124


------ 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: 0.0846
39/82 [=============>................] - ETA: 0s - loss: 0.2515 
76/82 [==========================>...] - ETA: 0s - loss: 0.2456
82/82 [==============================] - 0s 1ms/step - loss: 0.2477
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.4130
34/82 [===========>..................] - ETA: 0s - loss: 0.2197
67/82 [=======================>......] - ETA: 0s - loss: 0.2354
82/82 [==============================] - 0s 2ms/step - loss: 0.2423
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1212
36/82 [============>.................] - ETA: 0s - loss: 0.2391
73/82 [=========================>....] - ETA: 0s - loss: 0.2380
82/82 [==============================] - 0s 1ms/step - loss: 0.2377
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1202
36/82 [============>.................] - ETA: 0s - loss: 0.2099
74/82 [==========================>...] - ETA: 0s - loss: 0.2336
82/82 [==============================] - 0s 1ms/step - loss: 0.2334
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2674
38/82 [============>.................] - ETA: 0s - loss: 0.2459
73/82 [=========================>....] - ETA: 0s - loss: 0.2367
82/82 [==============================] - 0s 1ms/step - loss: 0.2296
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1144
35/82 [===========>..................] - ETA: 0s - loss: 0.2325
68/82 [=======================>......] - ETA: 0s - loss: 0.2181
82/82 [==============================] - 0s 2ms/step - loss: 0.2255
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1924
39/82 [=============>................] - ETA: 0s - loss: 0.2138
76/82 [==========================>...] - ETA: 0s - loss: 0.2169
82/82 [==============================] - 0s 1ms/step - loss: 0.2218
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.3301
39/82 [=============>................] - ETA: 0s - loss: 0.1913
74/82 [==========================>...] - ETA: 0s - loss: 0.2103
82/82 [==============================] - 0s 1ms/step - loss: 0.2162
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1470
38/82 [============>.................] - ETA: 0s - loss: 0.2119
75/82 [==========================>...] - ETA: 0s - loss: 0.2143
82/82 [==============================] - 0s 1ms/step - loss: 0.2141
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1103
36/82 [============>.................] - ETA: 0s - loss: 0.2071
73/82 [=========================>....] - ETA: 0s - loss: 0.2069
82/82 [==============================] - 0s 1ms/step - loss: 0.2099
-> test with GAN.predict
GAN tn, fp: 186, 19
GAN fn, tp: 4, 5
GAN f1 score: 0.303
GAN cohens kappa score: 0.258

-> test with 'LR'
LR tn, fp: 169, 36
LR fn, tp: 2, 7
LR f1 score: 0.269
LR cohens kappa score: 0.215
LR average precision score: 0.434

-> 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: 171, 34
KNN fn, tp: 3, 6
KNN f1 score: 0.245
KNN cohens kappa score: 0.189


------ 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: 14s - loss: 0.1426
40/82 [=============>................] - ETA: 0s - loss: 0.1644 
77/82 [===========================>..] - ETA: 0s - loss: 0.1702
82/82 [==============================] - 0s 1ms/step - loss: 0.1685
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0742
40/82 [=============>................] - ETA: 0s - loss: 0.1613
79/82 [===========================>..] - ETA: 0s - loss: 0.1671
82/82 [==============================] - 0s 1ms/step - loss: 0.1656
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0885
36/82 [============>.................] - ETA: 0s - loss: 0.1612
73/82 [=========================>....] - ETA: 0s - loss: 0.1603
82/82 [==============================] - 0s 1ms/step - loss: 0.1615
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3630
31/82 [==========>...................] - ETA: 0s - loss: 0.1653
68/82 [=======================>......] - ETA: 0s - loss: 0.1636
82/82 [==============================] - 0s 1ms/step - loss: 0.1592
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1181
35/82 [===========>..................] - ETA: 0s - loss: 0.1668
70/82 [========================>.....] - ETA: 0s - loss: 0.1581
82/82 [==============================] - 0s 1ms/step - loss: 0.1530
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0265
36/82 [============>.................] - ETA: 0s - loss: 0.1567
61/82 [=====================>........] - ETA: 0s - loss: 0.1536
82/82 [==============================] - 0s 2ms/step - loss: 0.1504
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0649
27/82 [========>.....................] - ETA: 0s - loss: 0.1503
56/82 [===================>..........] - ETA: 0s - loss: 0.1504
82/82 [==============================] - 0s 2ms/step - loss: 0.1464
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1448
35/82 [===========>..................] - ETA: 0s - loss: 0.1315
72/82 [=========================>....] - ETA: 0s - loss: 0.1352
82/82 [==============================] - 0s 1ms/step - loss: 0.1422
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0440
40/82 [=============>................] - ETA: 0s - loss: 0.1451
76/82 [==========================>...] - ETA: 0s - loss: 0.1396
82/82 [==============================] - 0s 1ms/step - loss: 0.1421
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1250
35/82 [===========>..................] - ETA: 0s - loss: 0.1189
67/82 [=======================>......] - ETA: 0s - loss: 0.1349
82/82 [==============================] - 0s 2ms/step - loss: 0.1366
-> test with GAN.predict
GAN tn, fp: 193, 12
GAN fn, tp: 4, 5
GAN f1 score: 0.385
GAN cohens kappa score: 0.349

-> test with 'LR'
LR tn, fp: 182, 23
LR fn, tp: 4, 5
LR f1 score: 0.270
LR cohens kappa score: 0.221
LR average precision score: 0.284

-> 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: 178, 27
KNN fn, tp: 3, 6
KNN f1 score: 0.286
KNN cohens kappa score: 0.235


------ 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: 0.0467
42/82 [==============>...............] - ETA: 0s - loss: 0.1911 
82/82 [==============================] - 0s 1ms/step - loss: 0.1922
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1467
41/82 [==============>...............] - ETA: 0s - loss: 0.1961
81/82 [============================>.] - ETA: 0s - loss: 0.1907
82/82 [==============================] - 0s 1ms/step - loss: 0.1893
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2238
41/82 [==============>...............] - ETA: 0s - loss: 0.1840
82/82 [==============================] - 0s 1ms/step - loss: 0.1842
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1663
38/82 [============>.................] - ETA: 0s - loss: 0.1702
73/82 [=========================>....] - ETA: 0s - loss: 0.1805
82/82 [==============================] - 0s 1ms/step - loss: 0.1815
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.3156
32/82 [==========>...................] - ETA: 0s - loss: 0.1673
74/82 [==========================>...] - ETA: 0s - loss: 0.1727
82/82 [==============================] - 0s 1ms/step - loss: 0.1777
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.1153
42/82 [==============>...............] - ETA: 0s - loss: 0.1805
80/82 [============================>.] - ETA: 0s - loss: 0.1757
82/82 [==============================] - 0s 1ms/step - loss: 0.1749
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1956
42/82 [==============>...............] - ETA: 0s - loss: 0.1949
82/82 [==============================] - ETA: 0s - loss: 0.1714
82/82 [==============================] - 0s 1ms/step - loss: 0.1714
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1972
43/82 [==============>...............] - ETA: 0s - loss: 0.1835
82/82 [==============================] - 0s 1ms/step - loss: 0.1681
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.2279
41/82 [==============>...............] - ETA: 0s - loss: 0.1684
81/82 [============================>.] - ETA: 0s - loss: 0.1631
82/82 [==============================] - 0s 1ms/step - loss: 0.1650
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1425
40/82 [=============>................] - ETA: 0s - loss: 0.1636
82/82 [==============================] - ETA: 0s - loss: 0.1629
82/82 [==============================] - 0s 1ms/step - loss: 0.1629
-> test with GAN.predict
GAN tn, fp: 182, 21
GAN fn, tp: 4, 3
GAN f1 score: 0.194
GAN cohens kappa score: 0.150

-> test with 'LR'
LR tn, fp: 162, 41
LR fn, tp: 1, 6
LR f1 score: 0.222
LR cohens kappa score: 0.174
LR average precision score: 0.239

-> test with 'RF'
RF tn, fp: 196, 7
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.034

-> test with 'GB'
GB tn, fp: 198, 5
GB fn, tp: 6, 1
GB f1 score: 0.154
GB cohens kappa score: 0.127

-> test with 'KNN'
KNN tn, fp: 182, 21
KNN fn, tp: 5, 2
KNN f1 score: 0.133
KNN cohens kappa score: 0.087


====== 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: 14s - loss: 0.1041
41/82 [==============>...............] - ETA: 0s - loss: 0.1736 
78/82 [===========================>..] - ETA: 0s - loss: 0.1846
82/82 [==============================] - 0s 1ms/step - loss: 0.1842
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1311
40/82 [=============>................] - ETA: 0s - loss: 0.1772
79/82 [===========================>..] - ETA: 0s - loss: 0.1769
82/82 [==============================] - 0s 1ms/step - loss: 0.1782
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0542
40/82 [=============>................] - ETA: 0s - loss: 0.1703
80/82 [============================>.] - ETA: 0s - loss: 0.1739
82/82 [==============================] - 0s 1ms/step - loss: 0.1730
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2248
40/82 [=============>................] - ETA: 0s - loss: 0.1861
79/82 [===========================>..] - ETA: 0s - loss: 0.1676
82/82 [==============================] - 0s 1ms/step - loss: 0.1691
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.4594
40/82 [=============>................] - ETA: 0s - loss: 0.1777
80/82 [============================>.] - ETA: 0s - loss: 0.1628
82/82 [==============================] - 0s 1ms/step - loss: 0.1625
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0593
41/82 [==============>...............] - ETA: 0s - loss: 0.1633
80/82 [============================>.] - ETA: 0s - loss: 0.1618
82/82 [==============================] - 0s 1ms/step - loss: 0.1594
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0821
36/82 [============>.................] - ETA: 0s - loss: 0.1406
73/82 [=========================>....] - ETA: 0s - loss: 0.1478
82/82 [==============================] - 0s 1ms/step - loss: 0.1542
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1395
37/82 [============>.................] - ETA: 0s - loss: 0.1463
74/82 [==========================>...] - ETA: 0s - loss: 0.1482
82/82 [==============================] - 0s 1ms/step - loss: 0.1487
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1044
38/82 [============>.................] - ETA: 0s - loss: 0.1549
78/82 [===========================>..] - ETA: 0s - loss: 0.1466
82/82 [==============================] - 0s 1ms/step - loss: 0.1454
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2095
39/82 [=============>................] - ETA: 0s - loss: 0.1527
75/82 [==========================>...] - ETA: 0s - loss: 0.1372
82/82 [==============================] - 0s 1ms/step - loss: 0.1399
-> test with GAN.predict
GAN tn, fp: 189, 16
GAN fn, tp: 3, 6
GAN f1 score: 0.387
GAN cohens kappa score: 0.348

-> test with 'LR'
LR tn, fp: 167, 38
LR fn, tp: 1, 8
LR f1 score: 0.291
LR cohens kappa score: 0.237
LR average precision score: 0.221

-> 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: 200, 5
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.031

-> test with 'KNN'
KNN tn, fp: 178, 27
KNN fn, tp: 3, 6
KNN f1 score: 0.286
KNN cohens kappa score: 0.235


------ 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: 13s - loss: 0.2829
38/82 [============>.................] - ETA: 0s - loss: 0.1775 
77/82 [===========================>..] - ETA: 0s - loss: 0.1713
82/82 [==============================] - 0s 1ms/step - loss: 0.1720
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0908
40/82 [=============>................] - ETA: 0s - loss: 0.1556
79/82 [===========================>..] - ETA: 0s - loss: 0.1665
82/82 [==============================] - 0s 1ms/step - loss: 0.1689
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0951
38/82 [============>.................] - ETA: 0s - loss: 0.1622
78/82 [===========================>..] - ETA: 0s - loss: 0.1653
82/82 [==============================] - 0s 1ms/step - loss: 0.1629
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2892
33/82 [===========>..................] - ETA: 0s - loss: 0.1718
69/82 [========================>.....] - ETA: 0s - loss: 0.1594
82/82 [==============================] - 0s 1ms/step - loss: 0.1579
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1713
39/82 [=============>................] - ETA: 0s - loss: 0.1549
77/82 [===========================>..] - ETA: 0s - loss: 0.1555
82/82 [==============================] - 0s 1ms/step - loss: 0.1548
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0499
39/82 [=============>................] - ETA: 0s - loss: 0.1537
77/82 [===========================>..] - ETA: 0s - loss: 0.1509
82/82 [==============================] - 0s 1ms/step - loss: 0.1503
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0805
38/82 [============>.................] - ETA: 0s - loss: 0.1421
73/82 [=========================>....] - ETA: 0s - loss: 0.1512
82/82 [==============================] - 0s 1ms/step - loss: 0.1455
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.3252
37/82 [============>.................] - ETA: 0s - loss: 0.1492
66/82 [=======================>......] - ETA: 0s - loss: 0.1406
82/82 [==============================] - 0s 2ms/step - loss: 0.1417
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1345
39/82 [=============>................] - ETA: 0s - loss: 0.1211
73/82 [=========================>....] - ETA: 0s - loss: 0.1330
82/82 [==============================] - 0s 1ms/step - loss: 0.1391
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0454
39/82 [=============>................] - ETA: 0s - loss: 0.1329
76/82 [==========================>...] - ETA: 0s - loss: 0.1358
82/82 [==============================] - 0s 1ms/step - loss: 0.1358
-> test with GAN.predict
GAN tn, fp: 199, 6
GAN fn, tp: 5, 4
GAN f1 score: 0.421
GAN cohens kappa score: 0.394

-> test with 'LR'
LR tn, fp: 182, 23
LR fn, tp: 2, 7
LR f1 score: 0.359
LR cohens kappa score: 0.315
LR average precision score: 0.561

-> 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: 202, 3
GB fn, tp: 8, 1
GB f1 score: 0.154
GB cohens kappa score: 0.131

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


------ 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: 12s - loss: 0.2058
35/82 [===========>..................] - ETA: 0s - loss: 0.1794 
67/82 [=======================>......] - ETA: 0s - loss: 0.1561
82/82 [==============================] - 0s 2ms/step - loss: 0.1652
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1968
41/82 [==============>...............] - ETA: 0s - loss: 0.1627
75/82 [==========================>...] - ETA: 0s - loss: 0.1607
82/82 [==============================] - 0s 1ms/step - loss: 0.1624
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.3462
41/82 [==============>...............] - ETA: 0s - loss: 0.1657
80/82 [============================>.] - ETA: 0s - loss: 0.1616
82/82 [==============================] - 0s 1ms/step - loss: 0.1603
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2581
41/82 [==============>...............] - ETA: 0s - loss: 0.1594
80/82 [============================>.] - ETA: 0s - loss: 0.1593
82/82 [==============================] - 0s 1ms/step - loss: 0.1577
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1409
40/82 [=============>................] - ETA: 0s - loss: 0.1651
79/82 [===========================>..] - ETA: 0s - loss: 0.1574
82/82 [==============================] - 0s 1ms/step - loss: 0.1560
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0370
41/82 [==============>...............] - ETA: 0s - loss: 0.1504
80/82 [============================>.] - ETA: 0s - loss: 0.1538
82/82 [==============================] - 0s 1ms/step - loss: 0.1534
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0512
39/82 [=============>................] - ETA: 0s - loss: 0.1437
76/82 [==========================>...] - ETA: 0s - loss: 0.1540
82/82 [==============================] - 0s 1ms/step - loss: 0.1521
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.3079
39/82 [=============>................] - ETA: 0s - loss: 0.1543
74/82 [==========================>...] - ETA: 0s - loss: 0.1549
82/82 [==============================] - 0s 1ms/step - loss: 0.1514
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0617
39/82 [=============>................] - ETA: 0s - loss: 0.1540
78/82 [===========================>..] - ETA: 0s - loss: 0.1515
82/82 [==============================] - 0s 1ms/step - loss: 0.1491
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2526
40/82 [=============>................] - ETA: 0s - loss: 0.1333
78/82 [===========================>..] - ETA: 0s - loss: 0.1447
82/82 [==============================] - 0s 1ms/step - loss: 0.1469
-> test with GAN.predict
GAN tn, fp: 186, 19
GAN fn, tp: 3, 6
GAN f1 score: 0.353
GAN cohens kappa score: 0.310

-> test with 'LR'
LR tn, fp: 167, 38
LR fn, tp: 4, 5
LR f1 score: 0.192
LR cohens kappa score: 0.132
LR average precision score: 0.199

-> 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: 8, 1
GB f1 score: 0.200
GB cohens kappa score: 0.193

-> test with 'KNN'
KNN tn, fp: 179, 26
KNN fn, tp: 4, 5
KNN f1 score: 0.250
KNN cohens kappa score: 0.198


------ 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: 0.2545
39/82 [=============>................] - ETA: 0s - loss: 0.2174 
78/82 [===========================>..] - ETA: 0s - loss: 0.2122
82/82 [==============================] - 0s 1ms/step - loss: 0.2108
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1617
41/82 [==============>...............] - ETA: 0s - loss: 0.2052
79/82 [===========================>..] - ETA: 0s - loss: 0.2047
82/82 [==============================] - 0s 1ms/step - loss: 0.2050
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0589
40/82 [=============>................] - ETA: 0s - loss: 0.2027
80/82 [============================>.] - ETA: 0s - loss: 0.2030
82/82 [==============================] - 0s 1ms/step - loss: 0.2004
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.4058
37/82 [============>.................] - ETA: 0s - loss: 0.2077
74/82 [==========================>...] - ETA: 0s - loss: 0.1973
82/82 [==============================] - 0s 1ms/step - loss: 0.1981
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1730
39/82 [=============>................] - ETA: 0s - loss: 0.1928
77/82 [===========================>..] - ETA: 0s - loss: 0.1930
82/82 [==============================] - 0s 1ms/step - loss: 0.1934
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2888
36/82 [============>.................] - ETA: 0s - loss: 0.1796
70/82 [========================>.....] - ETA: 0s - loss: 0.1831
82/82 [==============================] - 0s 1ms/step - loss: 0.1886
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0788
33/82 [===========>..................] - ETA: 0s - loss: 0.2007
68/82 [=======================>......] - ETA: 0s - loss: 0.1886
82/82 [==============================] - 0s 1ms/step - loss: 0.1864
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0659
39/82 [=============>................] - ETA: 0s - loss: 0.1774
78/82 [===========================>..] - ETA: 0s - loss: 0.1789
82/82 [==============================] - 0s 1ms/step - loss: 0.1803
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1371
41/82 [==============>...............] - ETA: 0s - loss: 0.1794
81/82 [============================>.] - ETA: 0s - loss: 0.1800
82/82 [==============================] - 0s 1ms/step - loss: 0.1797
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.4197
40/82 [=============>................] - ETA: 0s - loss: 0.1926
78/82 [===========================>..] - ETA: 0s - loss: 0.1704
82/82 [==============================] - 0s 1ms/step - loss: 0.1758
-> test with GAN.predict
GAN tn, fp: 183, 22
GAN fn, tp: 3, 6
GAN f1 score: 0.324
GAN cohens kappa score: 0.278

-> test with 'LR'
LR tn, fp: 170, 35
LR fn, tp: 0, 9
LR f1 score: 0.340
LR cohens kappa score: 0.290
LR average precision score: 0.379

-> 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: 6, 3
GB f1 score: 0.429
GB cohens kappa score: 0.411

-> test with 'KNN'
KNN tn, fp: 177, 28
KNN fn, tp: 2, 7
KNN f1 score: 0.318
KNN cohens kappa score: 0.269


------ 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: 11s - loss: 0.2473
40/82 [=============>................] - ETA: 0s - loss: 0.1850 
78/82 [===========================>..] - ETA: 0s - loss: 0.1979
82/82 [==============================] - 0s 1ms/step - loss: 0.1960
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0723
42/82 [==============>...............] - ETA: 0s - loss: 0.1888
81/82 [============================>.] - ETA: 0s - loss: 0.1900
82/82 [==============================] - 0s 1ms/step - loss: 0.1906
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.0988
43/82 [==============>...............] - ETA: 0s - loss: 0.1893
82/82 [==============================] - ETA: 0s - loss: 0.1864
82/82 [==============================] - 0s 1ms/step - loss: 0.1864
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.5651
40/82 [=============>................] - ETA: 0s - loss: 0.1924
80/82 [============================>.] - ETA: 0s - loss: 0.1845
82/82 [==============================] - 0s 1ms/step - loss: 0.1832
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1607
39/82 [=============>................] - ETA: 0s - loss: 0.1639
80/82 [============================>.] - ETA: 0s - loss: 0.1794
82/82 [==============================] - 0s 1ms/step - loss: 0.1781
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0714
43/82 [==============>...............] - ETA: 0s - loss: 0.1877
82/82 [==============================] - 0s 1ms/step - loss: 0.1726
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1468
42/82 [==============>...............] - ETA: 0s - loss: 0.1871
82/82 [==============================] - 0s 1ms/step - loss: 0.1687
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0309
40/82 [=============>................] - ETA: 0s - loss: 0.1860
81/82 [============================>.] - ETA: 0s - loss: 0.1659
82/82 [==============================] - 0s 1ms/step - loss: 0.1646
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.2481
42/82 [==============>...............] - ETA: 0s - loss: 0.1396
82/82 [==============================] - ETA: 0s - loss: 0.1603
82/82 [==============================] - 0s 1ms/step - loss: 0.1603
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.0966
41/82 [==============>...............] - ETA: 0s - loss: 0.1674
82/82 [==============================] - ETA: 0s - loss: 0.1552
82/82 [==============================] - 0s 1ms/step - loss: 0.1552
-> test with GAN.predict
GAN tn, fp: 187, 16
GAN fn, tp: 3, 4
GAN f1 score: 0.296
GAN cohens kappa score: 0.260

-> test with 'LR'
LR tn, fp: 171, 32
LR fn, tp: 1, 6
LR f1 score: 0.267
LR cohens kappa score: 0.223
LR average precision score: 0.624

-> 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: 202, 1
GB fn, tp: 7, 0
GB f1 score: 0.000
GB cohens kappa score: -0.008

-> test with 'KNN'
KNN tn, fp: 170, 33
KNN fn, tp: 3, 4
KNN f1 score: 0.182
KNN cohens kappa score: 0.133


====== 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: 0.3364
39/82 [=============>................] - ETA: 0s - loss: 0.2414 
78/82 [===========================>..] - ETA: 0s - loss: 0.2236
82/82 [==============================] - 0s 1ms/step - loss: 0.2203
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0982
40/82 [=============>................] - ETA: 0s - loss: 0.1941
78/82 [===========================>..] - ETA: 0s - loss: 0.2105
82/82 [==============================] - 0s 1ms/step - loss: 0.2109
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.1426
38/82 [============>.................] - ETA: 0s - loss: 0.2228
76/82 [==========================>...] - ETA: 0s - loss: 0.2047
82/82 [==============================] - 0s 1ms/step - loss: 0.2051
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.2292
40/82 [=============>................] - ETA: 0s - loss: 0.1947
78/82 [===========================>..] - ETA: 0s - loss: 0.1988
82/82 [==============================] - 0s 1ms/step - loss: 0.1990
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1797
39/82 [=============>................] - ETA: 0s - loss: 0.1935
69/82 [========================>.....] - ETA: 0s - loss: 0.2024
82/82 [==============================] - 0s 2ms/step - loss: 0.1939
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0942
35/82 [===========>..................] - ETA: 0s - loss: 0.1758
70/82 [========================>.....] - ETA: 0s - loss: 0.1827
82/82 [==============================] - 0s 1ms/step - loss: 0.1876
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.3201
33/82 [===========>..................] - ETA: 0s - loss: 0.1852
72/82 [=========================>....] - ETA: 0s - loss: 0.1831
82/82 [==============================] - 0s 1ms/step - loss: 0.1826
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.2792
39/82 [=============>................] - ETA: 0s - loss: 0.1869
75/82 [==========================>...] - ETA: 0s - loss: 0.1831
82/82 [==============================] - 0s 1ms/step - loss: 0.1774
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0962
37/82 [============>.................] - ETA: 0s - loss: 0.1914
77/82 [===========================>..] - ETA: 0s - loss: 0.1716
82/82 [==============================] - 0s 1ms/step - loss: 0.1722
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.3415
36/82 [============>.................] - ETA: 0s - loss: 0.1672
73/82 [=========================>....] - ETA: 0s - loss: 0.1682
82/82 [==============================] - 0s 1ms/step - loss: 0.1670
-> test with GAN.predict
GAN tn, fp: 186, 19
GAN fn, tp: 4, 5
GAN f1 score: 0.303
GAN cohens kappa score: 0.258

-> test with 'LR'
LR tn, fp: 173, 32
LR fn, tp: 4, 5
LR f1 score: 0.217
LR cohens kappa score: 0.161
LR average precision score: 0.204

-> 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: 180, 25
KNN fn, tp: 2, 7
KNN f1 score: 0.341
KNN cohens kappa score: 0.295


------ 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: 14s - loss: 0.1398
40/82 [=============>................] - ETA: 0s - loss: 0.2368 
80/82 [============================>.] - ETA: 0s - loss: 0.2190
82/82 [==============================] - 0s 1ms/step - loss: 0.2202
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2936
39/82 [=============>................] - ETA: 0s - loss: 0.2085
78/82 [===========================>..] - ETA: 0s - loss: 0.2137
82/82 [==============================] - 0s 1ms/step - loss: 0.2158
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.3696
39/82 [=============>................] - ETA: 0s - loss: 0.2171
77/82 [===========================>..] - ETA: 0s - loss: 0.2130
82/82 [==============================] - 0s 1ms/step - loss: 0.2115
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1767
40/82 [=============>................] - ETA: 0s - loss: 0.2052
79/82 [===========================>..] - ETA: 0s - loss: 0.2047
82/82 [==============================] - 0s 1ms/step - loss: 0.2086
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.2297
38/82 [============>.................] - ETA: 0s - loss: 0.2185
71/82 [========================>.....] - ETA: 0s - loss: 0.2041
82/82 [==============================] - 0s 2ms/step - loss: 0.2046
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2937
32/82 [==========>...................] - ETA: 0s - loss: 0.1928
65/82 [======================>.......] - ETA: 0s - loss: 0.1947
82/82 [==============================] - 0s 2ms/step - loss: 0.2014
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0518
41/82 [==============>...............] - ETA: 0s - loss: 0.1964
80/82 [============================>.] - ETA: 0s - loss: 0.1979
82/82 [==============================] - 0s 1ms/step - loss: 0.1982
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1558
41/82 [==============>...............] - ETA: 0s - loss: 0.2020
79/82 [===========================>..] - ETA: 0s - loss: 0.1942
82/82 [==============================] - 0s 1ms/step - loss: 0.1970
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.3492
41/82 [==============>...............] - ETA: 0s - loss: 0.1939
81/82 [============================>.] - ETA: 0s - loss: 0.1925
82/82 [==============================] - 0s 1ms/step - loss: 0.1919
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.2684
40/82 [=============>................] - ETA: 0s - loss: 0.1979
79/82 [===========================>..] - ETA: 0s - loss: 0.1865
82/82 [==============================] - 0s 1ms/step - loss: 0.1887
-> test with GAN.predict
GAN tn, fp: 184, 21
GAN fn, tp: 3, 6
GAN f1 score: 0.333
GAN cohens kappa score: 0.288

-> test with 'LR'
LR tn, fp: 172, 33
LR fn, tp: 1, 8
LR f1 score: 0.320
LR cohens kappa score: 0.270
LR average precision score: 0.439

-> 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: 175, 30
KNN fn, tp: 3, 6
KNN f1 score: 0.267
KNN cohens kappa score: 0.214


------ 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: 17s - loss: 0.1566
33/82 [===========>..................] - ETA: 0s - loss: 0.2257 
69/82 [========================>.....] - ETA: 0s - loss: 0.2245
82/82 [==============================] - 0s 2ms/step - loss: 0.2206
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.2726
35/82 [===========>..................] - ETA: 0s - loss: 0.2094
74/82 [==========================>...] - ETA: 0s - loss: 0.2078
82/82 [==============================] - 0s 1ms/step - loss: 0.2123
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.3738
39/82 [=============>................] - ETA: 0s - loss: 0.2201
77/82 [===========================>..] - ETA: 0s - loss: 0.2073
82/82 [==============================] - 0s 1ms/step - loss: 0.2075
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.1669
40/82 [=============>................] - ETA: 0s - loss: 0.1946
77/82 [===========================>..] - ETA: 0s - loss: 0.2031
82/82 [==============================] - 0s 1ms/step - loss: 0.2050
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.3214
39/82 [=============>................] - ETA: 0s - loss: 0.2109
78/82 [===========================>..] - ETA: 0s - loss: 0.2024
82/82 [==============================] - 0s 1ms/step - loss: 0.1987
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2609
40/82 [=============>................] - ETA: 0s - loss: 0.2027
78/82 [===========================>..] - ETA: 0s - loss: 0.1963
82/82 [==============================] - 0s 1ms/step - loss: 0.1962
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1888
40/82 [=============>................] - ETA: 0s - loss: 0.1970
77/82 [===========================>..] - ETA: 0s - loss: 0.1933
82/82 [==============================] - 0s 1ms/step - loss: 0.1912
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1409
38/82 [============>.................] - ETA: 0s - loss: 0.1837
76/82 [==========================>...] - ETA: 0s - loss: 0.1848
82/82 [==============================] - 0s 1ms/step - loss: 0.1874
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1614
38/82 [============>.................] - ETA: 0s - loss: 0.1635
77/82 [===========================>..] - ETA: 0s - loss: 0.1787
82/82 [==============================] - 0s 1ms/step - loss: 0.1824
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1576
39/82 [=============>................] - ETA: 0s - loss: 0.1841
77/82 [===========================>..] - ETA: 0s - loss: 0.1837
82/82 [==============================] - 0s 1ms/step - loss: 0.1793
-> test with GAN.predict
GAN tn, fp: 186, 19
GAN fn, tp: 3, 6
GAN f1 score: 0.353
GAN cohens kappa score: 0.310

-> test with 'LR'
LR tn, fp: 177, 28
LR fn, tp: 0, 9
LR f1 score: 0.391
LR cohens kappa score: 0.347
LR average precision score: 0.446

-> 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: 173, 32
KNN fn, tp: 2, 7
KNN f1 score: 0.292
KNN cohens kappa score: 0.240


------ 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: 17s - loss: 0.0668
39/82 [=============>................] - ETA: 0s - loss: 0.1533 
78/82 [===========================>..] - ETA: 0s - loss: 0.1403
82/82 [==============================] - 0s 1ms/step - loss: 0.1416
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.1049
40/82 [=============>................] - ETA: 0s - loss: 0.1262
74/82 [==========================>...] - ETA: 0s - loss: 0.1362
82/82 [==============================] - 0s 1ms/step - loss: 0.1375
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2235
39/82 [=============>................] - ETA: 0s - loss: 0.1232
78/82 [===========================>..] - ETA: 0s - loss: 0.1279
82/82 [==============================] - 0s 1ms/step - loss: 0.1346
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.0684
40/82 [=============>................] - ETA: 0s - loss: 0.1320
78/82 [===========================>..] - ETA: 0s - loss: 0.1334
82/82 [==============================] - 0s 1ms/step - loss: 0.1308
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.0769
37/82 [============>.................] - ETA: 0s - loss: 0.1272
75/82 [==========================>...] - ETA: 0s - loss: 0.1270
82/82 [==============================] - 0s 1ms/step - loss: 0.1284
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.0927
40/82 [=============>................] - ETA: 0s - loss: 0.1196
76/82 [==========================>...] - ETA: 0s - loss: 0.1252
82/82 [==============================] - 0s 1ms/step - loss: 0.1261
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.0639
40/82 [=============>................] - ETA: 0s - loss: 0.1280
78/82 [===========================>..] - ETA: 0s - loss: 0.1274
82/82 [==============================] - 0s 1ms/step - loss: 0.1245
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.0782
40/82 [=============>................] - ETA: 0s - loss: 0.1272
79/82 [===========================>..] - ETA: 0s - loss: 0.1212
82/82 [==============================] - 0s 1ms/step - loss: 0.1219
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.1015
36/82 [============>.................] - ETA: 0s - loss: 0.1356
74/82 [==========================>...] - ETA: 0s - loss: 0.1129
82/82 [==============================] - 0s 1ms/step - loss: 0.1193
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.3055
39/82 [=============>................] - ETA: 0s - loss: 0.1219
72/82 [=========================>....] - ETA: 0s - loss: 0.1207
82/82 [==============================] - 0s 1ms/step - loss: 0.1173
-> test with GAN.predict
GAN tn, fp: 197, 8
GAN fn, tp: 5, 4
GAN f1 score: 0.381
GAN cohens kappa score: 0.350

-> test with 'LR'
LR tn, fp: 180, 25
LR fn, tp: 4, 5
LR f1 score: 0.256
LR cohens kappa score: 0.205
LR average precision score: 0.188

-> 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: 203, 2
GB fn, tp: 9, 0
GB f1 score: 0.000
GB cohens kappa score: -0.016

-> test with 'KNN'
KNN tn, fp: 189, 16
KNN fn, tp: 5, 4
KNN f1 score: 0.276
KNN cohens kappa score: 0.231


------ 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: 14s - loss: 0.2652
36/82 [============>.................] - ETA: 0s - loss: 0.1835 
72/82 [=========================>....] - ETA: 0s - loss: 0.1811
82/82 [==============================] - 0s 1ms/step - loss: 0.1792
Epoch 2/10

 1/82 [..............................] - ETA: 0s - loss: 0.0945
35/82 [===========>..................] - ETA: 0s - loss: 0.1578
67/82 [=======================>......] - ETA: 0s - loss: 0.1744
82/82 [==============================] - 0s 2ms/step - loss: 0.1730
Epoch 3/10

 1/82 [..............................] - ETA: 0s - loss: 0.2054
34/82 [===========>..................] - ETA: 0s - loss: 0.1671
67/82 [=======================>......] - ETA: 0s - loss: 0.1814
82/82 [==============================] - 0s 2ms/step - loss: 0.1706
Epoch 4/10

 1/82 [..............................] - ETA: 0s - loss: 0.3038
32/82 [==========>...................] - ETA: 0s - loss: 0.1703
62/82 [=====================>........] - ETA: 0s - loss: 0.1743
82/82 [==============================] - 0s 2ms/step - loss: 0.1671
Epoch 5/10

 1/82 [..............................] - ETA: 0s - loss: 0.1198
31/82 [==========>...................] - ETA: 0s - loss: 0.1507
55/82 [===================>..........] - ETA: 0s - loss: 0.1415
82/82 [==============================] - ETA: 0s - loss: 0.1625
82/82 [==============================] - 0s 2ms/step - loss: 0.1625
Epoch 6/10

 1/82 [..............................] - ETA: 0s - loss: 0.2650
30/82 [=========>....................] - ETA: 0s - loss: 0.1807
61/82 [=====================>........] - ETA: 0s - loss: 0.1663
82/82 [==============================] - 0s 2ms/step - loss: 0.1589
Epoch 7/10

 1/82 [..............................] - ETA: 0s - loss: 0.1087
32/82 [==========>...................] - ETA: 0s - loss: 0.1563
65/82 [======================>.......] - ETA: 0s - loss: 0.1619
82/82 [==============================] - 0s 2ms/step - loss: 0.1590
Epoch 8/10

 1/82 [..............................] - ETA: 0s - loss: 0.1275
33/82 [===========>..................] - ETA: 0s - loss: 0.1580
66/82 [=======================>......] - ETA: 0s - loss: 0.1507
82/82 [==============================] - 0s 2ms/step - loss: 0.1526
Epoch 9/10

 1/82 [..............................] - ETA: 0s - loss: 0.0906
28/82 [=========>....................] - ETA: 0s - loss: 0.1676
60/82 [====================>.........] - ETA: 0s - loss: 0.1540
82/82 [==============================] - 0s 2ms/step - loss: 0.1505
Epoch 10/10

 1/82 [..............................] - ETA: 0s - loss: 0.1694
39/82 [=============>................] - ETA: 0s - loss: 0.1509
77/82 [===========================>..] - ETA: 0s - loss: 0.1464
82/82 [==============================] - 0s 1ms/step - loss: 0.1490
-> test with GAN.predict
GAN tn, fp: 178, 25
GAN fn, tp: 4, 3
GAN f1 score: 0.171
GAN cohens kappa score: 0.125

-> test with 'LR'
LR tn, fp: 163, 40
LR fn, tp: 2, 5
LR f1 score: 0.192
LR cohens kappa score: 0.143
LR average precision score: 0.326

-> test with 'RF'
RF tn, fp: 196, 7
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.034

-> test with 'GB'
GB tn, fp: 196, 7
GB fn, tp: 5, 2
GB f1 score: 0.250
GB cohens kappa score: 0.221

-> test with 'KNN'
KNN tn, fp: 173, 30
KNN fn, tp: 4, 3
KNN f1 score: 0.150
KNN cohens kappa score: 0.101

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 187, 50
LR fn, tp: 5, 9
LR f1 score: 0.419
LR cohens kappa score: 0.377
LR average precision score: 0.724


average:
LR tn, fp: 172.16, 32.44
LR fn, tp: 2.2, 6.4
LR f1 score: 0.273
LR cohens kappa score: 0.223
LR average precision score: 0.354


minimum:
LR tn, fp: 155, 18
LR fn, tp: 0, 4
LR f1 score: 0.170
LR cohens kappa score: 0.110
LR average precision score: 0.086


-----[ RF ]-----
maximum:
RF tn, fp: 205, 8
RF fn, tp: 9, 2
RF f1 score: 0.211
RF cohens kappa score: 0.193


average:
RF tn, fp: 201.64, 2.96
RF fn, tp: 8.2, 0.4
RF f1 score: 0.062
RF cohens kappa score: 0.043


minimum:
RF tn, fp: 196, 0
RF fn, tp: 7, 0
RF f1 score: 0.000
RF cohens kappa score: -0.035


-----[ GB ]-----
maximum:
GB tn, fp: 205, 7
GB fn, tp: 9, 3
GB f1 score: 0.462
GB cohens kappa score: 0.447


average:
GB tn, fp: 202.88, 1.72
GB fn, tp: 7.76, 0.84
GB f1 score: 0.139
GB cohens kappa score: 0.125


minimum:
GB tn, fp: 196, 0
GB fn, tp: 5, 0
GB f1 score: 0.000
GB cohens kappa score: -0.031


-----[ KNN ]-----
maximum:
KNN tn, fp: 196, 40
KNN fn, tp: 5, 7
KNN f1 score: 0.560
KNN cohens kappa score: 0.535


average:
KNN tn, fp: 177.76, 26.84
KNN fn, tp: 3.2, 5.4
KNN f1 score: 0.269
KNN cohens kappa score: 0.220


minimum:
KNN tn, fp: 165, 9
KNN fn, tp: 1, 2
KNN f1 score: 0.133
KNN cohens kappa score: 0.087


-----[ GAN ]-----
maximum:
GAN tn, fp: 199, 26
GAN fn, tp: 6, 7
GAN f1 score: 0.609
GAN cohens kappa score: 0.588


average:
GAN tn, fp: 186.96, 17.64
GAN fn, tp: 3.72, 4.88
GAN f1 score: 0.321
GAN cohens kappa score: 0.279


minimum:
GAN tn, fp: 177, 6
GAN fn, tp: 1, 3
GAN f1 score: 0.171
GAN cohens kappa score: 0.125