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folding_winequality-red-4.log

folding_winequality-red-4.log 180 KB
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
  1. 

  2. 

  3. ///////////////////////////////////////////
    4. 

  4. // Running convGAN-majority-5 on folding_winequality-red-4
    5. 

  5. ///////////////////////////////////////////
    6. 

  6. 

  7. Load 'data_input/folding_winequality-red-4'
    8. 

  8. from pickle file
    9. 

  9. Data loaded.
    10. 

  10. -> Shuffling data
    11. 

  11. ### Start exercise for synthetic point generator
    12. 

  12. 

  13. ====== Step 1/5 =======
    14. 

  14. -> Shuffling data
    15. 

  15. -> Spliting data to slices
    16. 

  16. 

  17. ------ Step 1/5: Slice 1/5 -------
    18. 

  18. -> Reset the GAN
    19. 

  19. -> Train generator for synthetic samples
    20. 

  20. -> create 1194 synthetic samples
    21. 

  21. -> retrain GAN for predict
    22. 

  22. Epoch 1/10
    23. 

  23. 
  1/124 [..............................] - ETA: 1:00 - loss: 0.4768
 13/124 [==>...........................] - ETA: 0s - loss: 0.5458  
 26/124 [=====>........................] - ETA: 0s - loss: 0.5136
 41/124 [========>.....................] - ETA: 0s - loss: 0.5127
 55/124 [============>.................] - ETA: 0s - loss: 0.5013
 71/124 [================>.............] - ETA: 0s - loss: 0.4961
 82/124 [==================>...........] - ETA: 0s - loss: 0.4947
 93/124 [=====================>........] - ETA: 0s - loss: 0.4958
106/124 [========================>.....] - ETA: 0s - loss: 0.4992
121/124 [============================>.] - ETA: 0s - loss: 0.4971
124/124 [==============================] - 1s 4ms/step - loss: 0.4968
    24. 

  24. Epoch 2/10
    25. 

  25. 
  1/124 [..............................] - ETA: 0s - loss: 0.4026
 15/124 [==>...........................] - ETA: 0s - loss: 0.4657
 27/124 [=====>........................] - ETA: 0s - loss: 0.4761
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 68/124 [===============>..............] - ETA: 0s - loss: 0.4875
 82/124 [==================>...........] - ETA: 0s - loss: 0.4819
 97/124 [======================>.......] - ETA: 0s - loss: 0.4856
109/124 [=========================>....] - ETA: 0s - loss: 0.4842
120/124 [============================>.] - ETA: 0s - loss: 0.4831
124/124 [==============================] - 0s 4ms/step - loss: 0.4815
    26. 

  26. Epoch 3/10
    27. 

  27. 
  1/124 [..............................] - ETA: 0s - loss: 0.5150
 13/124 [==>...........................] - ETA: 0s - loss: 0.4639
 26/124 [=====>........................] - ETA: 0s - loss: 0.4724
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 55/124 [============>.................] - ETA: 0s - loss: 0.4771
 68/124 [===============>..............] - ETA: 0s - loss: 0.4778
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 92/124 [=====================>........] - ETA: 0s - loss: 0.4770
103/124 [=======================>......] - ETA: 0s - loss: 0.4753
120/124 [============================>.] - ETA: 0s - loss: 0.4755
124/124 [==============================] - 0s 4ms/step - loss: 0.4747
    28. 

  28. Epoch 4/10
    29. 

  29. 
  1/124 [..............................] - ETA: 0s - loss: 0.4538
 15/124 [==>...........................] - ETA: 0s - loss: 0.4741
 28/124 [=====>........................] - ETA: 0s - loss: 0.4607
 42/124 [=========>....................] - ETA: 0s - loss: 0.4649
 52/124 [===========>..................] - ETA: 0s - loss: 0.4674
 63/124 [==============>...............] - ETA: 0s - loss: 0.4718
 78/124 [=================>............] - ETA: 0s - loss: 0.4699
 90/124 [====================>.........] - ETA: 0s - loss: 0.4744
105/124 [========================>.....] - ETA: 0s - loss: 0.4675
117/124 [===========================>..] - ETA: 0s - loss: 0.4661
124/124 [==============================] - 0s 4ms/step - loss: 0.4644
    30. 

  30. Epoch 5/10
    31. 

  31. 
  1/124 [..............................] - ETA: 0s - loss: 0.4415
 14/124 [==>...........................] - ETA: 0s - loss: 0.4402
 24/124 [====>.........................] - ETA: 0s - loss: 0.4551
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 78/124 [=================>............] - ETA: 0s - loss: 0.4499
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105/124 [========================>.....] - ETA: 0s - loss: 0.4524
116/124 [===========================>..] - ETA: 0s - loss: 0.4543
124/124 [==============================] - 1s 4ms/step - loss: 0.4539
    32. 

  32. Epoch 6/10
    33. 

  33. 
  1/124 [..............................] - ETA: 0s - loss: 0.6242
 15/124 [==>...........................] - ETA: 0s - loss: 0.4834
 27/124 [=====>........................] - ETA: 0s - loss: 0.4745
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106/124 [========================>.....] - ETA: 0s - loss: 0.4472
118/124 [===========================>..] - ETA: 0s - loss: 0.4484
124/124 [==============================] - 0s 4ms/step - loss: 0.4480
    34. 

  34. Epoch 7/10
    35. 

  35. 
  1/124 [..............................] - ETA: 0s - loss: 0.4467
 14/124 [==>...........................] - ETA: 0s - loss: 0.4447
 28/124 [=====>........................] - ETA: 0s - loss: 0.4483
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108/124 [=========================>....] - ETA: 0s - loss: 0.4386
124/124 [==============================] - ETA: 0s - loss: 0.4346
124/124 [==============================] - 1s 4ms/step - loss: 0.4346
    36. 

  36. Epoch 8/10
    37. 

  37. 
  1/124 [..............................] - ETA: 0s - loss: 0.3637
 11/124 [=>............................] - ETA: 0s - loss: 0.4483
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107/124 [========================>.....] - ETA: 0s - loss: 0.4284
116/124 [===========================>..] - ETA: 0s - loss: 0.4246
124/124 [==============================] - 1s 5ms/step - loss: 0.4267
    38. 

  38. Epoch 9/10
    39. 

  39. 
  1/124 [..............................] - ETA: 0s - loss: 0.3448
 14/124 [==>...........................] - ETA: 0s - loss: 0.3963
 25/124 [=====>........................] - ETA: 0s - loss: 0.4222
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112/124 [==========================>...] - ETA: 0s - loss: 0.4215
122/124 [============================>.] - ETA: 0s - loss: 0.4179
124/124 [==============================] - 1s 5ms/step - loss: 0.4187
    40. 

  40. Epoch 10/10
    41. 

  41. 
  1/124 [..............................] - ETA: 0s - loss: 0.4127
 10/124 [=>............................] - ETA: 0s - loss: 0.4422
 23/124 [====>.........................] - ETA: 0s - loss: 0.4207
 35/124 [=======>......................] - ETA: 0s - loss: 0.4127
 46/124 [==========>...................] - ETA: 0s - loss: 0.4089
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 69/124 [===============>..............] - ETA: 0s - loss: 0.4127
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109/124 [=========================>....] - ETA: 0s - loss: 0.4092
119/124 [===========================>..] - ETA: 0s - loss: 0.4106
124/124 [==============================] - 1s 5ms/step - loss: 0.4098
    42. 

  42. -> test with GAN.predict
    43. 

  43. GAN tn, fp: 212, 98
    44. 

  44. GAN fn, tp: 4, 7
    45. 

  45. GAN f1 score: 0.121
    46. 

  46. GAN cohens kappa score: 0.063
    47. 

  47. 

  48. -> test with 'LR'
    49. 

  49. LR tn, fp: 210, 100
    50. 

  50. LR fn, tp: 6, 5
    51. 

  51. LR f1 score: 0.086
    52. 

  52. LR cohens kappa score: 0.026
    53. 

  53. LR average precision score: 0.095
    54. 

  54. 

  55. -> test with 'RF'
    56. 

  56. RF tn, fp: 309, 1
    57. 

  57. RF fn, tp: 11, 0
    58. 

  58. RF f1 score: 0.000
    59. 

  59. RF cohens kappa score: -0.006
    60. 

  60. 

  61. -> test with 'GB'
    62. 

  62. GB tn, fp: 284, 26
    63. 

  63. GB fn, tp: 11, 0
    64. 

  64. GB f1 score: 0.000
    65. 

  65. GB cohens kappa score: -0.051
    66. 

  66. 

  67. -> test with 'KNN'
    68. 

  68. KNN tn, fp: 206, 104
    69. 

  69. KNN fn, tp: 8, 3
    70. 

  70. KNN f1 score: 0.051
    71. 

  71. KNN cohens kappa score: -0.012
    72. 

  72. 

  73. 

  74. ------ Step 1/5: Slice 2/5 -------
    75. 

  75. -> Reset the GAN
    76. 

  76. -> Train generator for synthetic samples
    77. 

  77. -> create 1194 synthetic samples
    78. 

  78. -> retrain GAN for predict
    79. 

  79. Epoch 1/10
    80. 

  80. 
  1/124 [..............................] - ETA: 23s - loss: 0.4301
 25/124 [=====>........................] - ETA: 0s - loss: 0.4842 
 51/124 [===========>..................] - ETA: 0s - loss: 0.4743
 81/124 [==================>...........] - ETA: 0s - loss: 0.4774
110/124 [=========================>....] - ETA: 0s - loss: 0.4751
124/124 [==============================] - 0s 2ms/step - loss: 0.4738
    81. 

  81. Epoch 2/10
    82. 

  82. 
  1/124 [..............................] - ETA: 0s - loss: 0.4416
 32/124 [======>.......................] - ETA: 0s - loss: 0.4364
 57/124 [============>.................] - ETA: 0s - loss: 0.4565
 91/124 [=====================>........] - ETA: 0s - loss: 0.4589
121/124 [============================>.] - ETA: 0s - loss: 0.4602
124/124 [==============================] - 0s 2ms/step - loss: 0.4593
    83. 

  83. Epoch 3/10
    84. 

  84. 
  1/124 [..............................] - ETA: 0s - loss: 0.4543
 33/124 [======>.......................] - ETA: 0s - loss: 0.4700
 64/124 [==============>...............] - ETA: 0s - loss: 0.4550
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122/124 [============================>.] - ETA: 0s - loss: 0.4497
124/124 [==============================] - 0s 2ms/step - loss: 0.4504
    85. 

  85. Epoch 4/10
    86. 

  86. 
  1/124 [..............................] - ETA: 0s - loss: 0.3431
 29/124 [======>.......................] - ETA: 0s - loss: 0.4602
 55/124 [============>.................] - ETA: 0s - loss: 0.4611
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115/124 [==========================>...] - ETA: 0s - loss: 0.4511
124/124 [==============================] - 0s 2ms/step - loss: 0.4568
    87. 

  87. Epoch 5/10
    88. 

  88. 
  1/124 [..............................] - ETA: 0s - loss: 0.4567
 30/124 [======>.......................] - ETA: 0s - loss: 0.4596
 61/124 [=============>................] - ETA: 0s - loss: 0.4551
 88/124 [====================>.........] - ETA: 0s - loss: 0.4352
113/124 [==========================>...] - ETA: 0s - loss: 0.4384
124/124 [==============================] - 0s 2ms/step - loss: 0.4378
    89. 

  89. Epoch 6/10
    90. 

  90. 
  1/124 [..............................] - ETA: 0s - loss: 0.3781
 22/124 [====>.........................] - ETA: 0s - loss: 0.4622
 44/124 [=========>....................] - ETA: 0s - loss: 0.4379
 68/124 [===============>..............] - ETA: 0s - loss: 0.4366
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121/124 [============================>.] - ETA: 0s - loss: 0.4300
124/124 [==============================] - 0s 2ms/step - loss: 0.4272
    91. 

  91. Epoch 7/10
    92. 

  92. 
  1/124 [..............................] - ETA: 0s - loss: 0.3587
 30/124 [======>.......................] - ETA: 0s - loss: 0.4274
 59/124 [=============>................] - ETA: 0s - loss: 0.4412
 87/124 [====================>.........] - ETA: 0s - loss: 0.4317
118/124 [===========================>..] - ETA: 0s - loss: 0.4328
124/124 [==============================] - 0s 2ms/step - loss: 0.4316
    93. 

  93. Epoch 8/10
    94. 

  94. 
  1/124 [..............................] - ETA: 0s - loss: 0.3859
 30/124 [======>.......................] - ETA: 0s - loss: 0.4039
 56/124 [============>.................] - ETA: 0s - loss: 0.4053
 87/124 [====================>.........] - ETA: 0s - loss: 0.4094
113/124 [==========================>...] - ETA: 0s - loss: 0.4066
124/124 [==============================] - 0s 2ms/step - loss: 0.4107
    95. 

  95. Epoch 9/10
    96. 

  96. 
  1/124 [..............................] - ETA: 0s - loss: 0.4669
 28/124 [=====>........................] - ETA: 0s - loss: 0.4085
 59/124 [=============>................] - ETA: 0s - loss: 0.4158
 85/124 [===================>..........] - ETA: 0s - loss: 0.4068
110/124 [=========================>....] - ETA: 0s - loss: 0.4032
124/124 [==============================] - 0s 2ms/step - loss: 0.4072
    97. 

  97. Epoch 10/10
    98. 

  98. 
  1/124 [..............................] - ETA: 0s - loss: 0.2395
 28/124 [=====>........................] - ETA: 0s - loss: 0.3915
 56/124 [============>.................] - ETA: 0s - loss: 0.3871
 78/124 [=================>............] - ETA: 0s - loss: 0.4001
105/124 [========================>.....] - ETA: 0s - loss: 0.4040
124/124 [==============================] - 0s 2ms/step - loss: 0.3977
    99. 

  99. -> test with GAN.predict
    100. 

  100. GAN tn, fp: 260, 50
    101. 

  101. GAN fn, tp: 6, 5
    102. 

  102. GAN f1 score: 0.152
    103. 

  103. GAN cohens kappa score: 0.100
    104. 

  104. 

  105. -> test with 'LR'
    106. 

  106. LR tn, fp: 226, 84
    107. 

  107. LR fn, tp: 4, 7
    108. 

  108. LR f1 score: 0.137
    109. 

  109. LR cohens kappa score: 0.081
    110. 

  110. LR average precision score: 0.114
    111. 

  111. 

  112. -> test with 'RF'
    113. 

  113. RF tn, fp: 303, 7
    114. 

  114. RF fn, tp: 9, 2
    115. 

  115. RF f1 score: 0.200
    116. 

  116. RF cohens kappa score: 0.175
    117. 

  117. 

  118. -> test with 'GB'
    119. 

  119. GB tn, fp: 292, 18
    120. 

  120. GB fn, tp: 9, 2
    121. 

  121. GB f1 score: 0.129
    122. 

  122. GB cohens kappa score: 0.089
    123. 

  123. 

  124. -> test with 'KNN'
    125. 

  125. KNN tn, fp: 226, 84
    126. 

  126. KNN fn, tp: 5, 6
    127. 

  127. KNN f1 score: 0.119
    128. 

  128. KNN cohens kappa score: 0.061
    129. 

  129. 

  130. 

  131. ------ Step 1/5: Slice 3/5 -------
    132. 

  132. -> Reset the GAN
    133. 

  133. -> Train generator for synthetic samples
    134. 

  134. -> create 1194 synthetic samples
    135. 

  135. -> retrain GAN for predict
    136. 

  136. Epoch 1/10
    137. 

  137. 
  1/124 [..............................] - ETA: 1:03 - loss: 0.5268
 27/124 [=====>........................] - ETA: 0s - loss: 0.4970  
 47/124 [==========>...................] - ETA: 0s - loss: 0.4883
 69/124 [===============>..............] - ETA: 0s - loss: 0.4854
 90/124 [====================>.........] - ETA: 0s - loss: 0.4912
117/124 [===========================>..] - ETA: 0s - loss: 0.4871
124/124 [==============================] - 1s 2ms/step - loss: 0.4872
    138. 

  138. Epoch 2/10
    139. 

  139. 
  1/124 [..............................] - ETA: 0s - loss: 0.4823
 22/124 [====>.........................] - ETA: 0s - loss: 0.4859
 43/124 [=========>....................] - ETA: 0s - loss: 0.4841
 59/124 [=============>................] - ETA: 0s - loss: 0.4856
 76/124 [=================>............] - ETA: 0s - loss: 0.4764
 97/124 [======================>.......] - ETA: 0s - loss: 0.4752
117/124 [===========================>..] - ETA: 0s - loss: 0.4763
124/124 [==============================] - 0s 3ms/step - loss: 0.4778
    140. 

  140. Epoch 3/10
    141. 

  141. 
  1/124 [..............................] - ETA: 0s - loss: 0.4313
 12/124 [=>............................] - ETA: 0s - loss: 0.5303
 23/124 [====>.........................] - ETA: 0s - loss: 0.4981
 35/124 [=======>......................] - ETA: 0s - loss: 0.4836
 47/124 [==========>...................] - ETA: 0s - loss: 0.4828
 59/124 [=============>................] - ETA: 0s - loss: 0.4750
 71/124 [================>.............] - ETA: 0s - loss: 0.4773
 82/124 [==================>...........] - ETA: 0s - loss: 0.4750
 92/124 [=====================>........] - ETA: 0s - loss: 0.4736
104/124 [========================>.....] - ETA: 0s - loss: 0.4728
115/124 [==========================>...] - ETA: 0s - loss: 0.4672
124/124 [==============================] - 1s 5ms/step - loss: 0.4676
    142. 

  142. Epoch 4/10
    143. 

  143. 
  1/124 [..............................] - ETA: 0s - loss: 0.5566
 12/124 [=>............................] - ETA: 0s - loss: 0.4533
 24/124 [====>.........................] - ETA: 0s - loss: 0.4563
 37/124 [=======>......................] - ETA: 0s - loss: 0.4581
 50/124 [===========>..................] - ETA: 0s - loss: 0.4677
 61/124 [=============>................] - ETA: 0s - loss: 0.4748
 74/124 [================>.............] - ETA: 0s - loss: 0.4725
 87/124 [====================>.........] - ETA: 0s - loss: 0.4667
100/124 [=======================>......] - ETA: 0s - loss: 0.4644
111/124 [=========================>....] - ETA: 0s - loss: 0.4643
122/124 [============================>.] - ETA: 0s - loss: 0.4653
124/124 [==============================] - 1s 4ms/step - loss: 0.4664
    144. 

  144. Epoch 5/10
    145. 

  145. 
  1/124 [..............................] - ETA: 0s - loss: 0.4833
 12/124 [=>............................] - ETA: 0s - loss: 0.4581
 25/124 [=====>........................] - ETA: 0s - loss: 0.4647
 37/124 [=======>......................] - ETA: 0s - loss: 0.4616
 49/124 [==========>...................] - ETA: 0s - loss: 0.4539
 60/124 [=============>................] - ETA: 0s - loss: 0.4523
 74/124 [================>.............] - ETA: 0s - loss: 0.4615
 85/124 [===================>..........] - ETA: 0s - loss: 0.4569
 97/124 [======================>.......] - ETA: 0s - loss: 0.4537
109/124 [=========================>....] - ETA: 0s - loss: 0.4514
121/124 [============================>.] - ETA: 0s - loss: 0.4549
124/124 [==============================] - 1s 4ms/step - loss: 0.4543
    146. 

  146. Epoch 6/10
    147. 

  147. 
  1/124 [..............................] - ETA: 0s - loss: 0.4527
 13/124 [==>...........................] - ETA: 0s - loss: 0.4209
 25/124 [=====>........................] - ETA: 0s - loss: 0.4273
 38/124 [========>.....................] - ETA: 0s - loss: 0.4400
 50/124 [===========>..................] - ETA: 0s - loss: 0.4347
 61/124 [=============>................] - ETA: 0s - loss: 0.4358
 73/124 [================>.............] - ETA: 0s - loss: 0.4380
 84/124 [===================>..........] - ETA: 0s - loss: 0.4516
 94/124 [=====================>........] - ETA: 0s - loss: 0.4431
103/124 [=======================>......] - ETA: 0s - loss: 0.4435
112/124 [==========================>...] - ETA: 0s - loss: 0.4445
124/124 [==============================] - 1s 5ms/step - loss: 0.4463
    148. 

  148. Epoch 7/10
    149. 

  149. 
  1/124 [..............................] - ETA: 0s - loss: 0.5131
 16/124 [==>...........................] - ETA: 0s - loss: 0.4761
 28/124 [=====>........................] - ETA: 0s - loss: 0.4349
 40/124 [========>.....................] - ETA: 0s - loss: 0.4424
 51/124 [===========>..................] - ETA: 0s - loss: 0.4327
 62/124 [==============>...............] - ETA: 0s - loss: 0.4371
 73/124 [================>.............] - ETA: 0s - loss: 0.4365
 85/124 [===================>..........] - ETA: 0s - loss: 0.4434
 97/124 [======================>.......] - ETA: 0s - loss: 0.4436
110/124 [=========================>....] - ETA: 0s - loss: 0.4449
124/124 [==============================] - ETA: 0s - loss: 0.4410
124/124 [==============================] - 1s 4ms/step - loss: 0.4410
    150. 

  150. Epoch 8/10
    151. 

  151. 
  1/124 [..............................] - ETA: 0s - loss: 0.4456
 14/124 [==>...........................] - ETA: 0s - loss: 0.4067
 27/124 [=====>........................] - ETA: 0s - loss: 0.4369
 39/124 [========>.....................] - ETA: 0s - loss: 0.4291
 51/124 [===========>..................] - ETA: 0s - loss: 0.4224
 63/124 [==============>...............] - ETA: 0s - loss: 0.4251
 77/124 [=================>............] - ETA: 0s - loss: 0.4303
 91/124 [=====================>........] - ETA: 0s - loss: 0.4337
103/124 [=======================>......] - ETA: 0s - loss: 0.4333
113/124 [==========================>...] - ETA: 0s - loss: 0.4349
124/124 [==============================] - 1s 4ms/step - loss: 0.4351
    152. 

  152. Epoch 9/10
    153. 

  153. 
  1/124 [..............................] - ETA: 0s - loss: 0.3553
 17/124 [===>..........................] - ETA: 0s - loss: 0.3908
 38/124 [========>.....................] - ETA: 0s - loss: 0.4201
 62/124 [==============>...............] - ETA: 0s - loss: 0.4279
 78/124 [=================>............] - ETA: 0s - loss: 0.4234
 89/124 [====================>.........] - ETA: 0s - loss: 0.4282
100/124 [=======================>......] - ETA: 0s - loss: 0.4285
110/124 [=========================>....] - ETA: 0s - loss: 0.4308
121/124 [============================>.] - ETA: 0s - loss: 0.4307
124/124 [==============================] - 0s 3ms/step - loss: 0.4324
    154. 

  154. Epoch 10/10
    155. 

  155. 
  1/124 [..............................] - ETA: 0s - loss: 0.3203
 13/124 [==>...........................] - ETA: 0s - loss: 0.4803
 24/124 [====>.........................] - ETA: 0s - loss: 0.4625
 36/124 [=======>......................] - ETA: 0s - loss: 0.4480
 46/124 [==========>...................] - ETA: 0s - loss: 0.4460
 57/124 [============>.................] - ETA: 0s - loss: 0.4400
 65/124 [==============>...............] - ETA: 0s - loss: 0.4333
 75/124 [=================>............] - ETA: 0s - loss: 0.4311
 83/124 [===================>..........] - ETA: 0s - loss: 0.4313
 95/124 [=====================>........] - ETA: 0s - loss: 0.4332
108/124 [=========================>....] - ETA: 0s - loss: 0.4335
116/124 [===========================>..] - ETA: 0s - loss: 0.4316
124/124 [==============================] - 1s 5ms/step - loss: 0.4325
    156. 

  156. -> test with GAN.predict
    157. 

  157. GAN tn, fp: 215, 95
    158. 

  158. GAN fn, tp: 5, 6
    159. 

  159. GAN f1 score: 0.107
    160. 

  160. GAN cohens kappa score: 0.048
    161. 

  161. 

  162. -> test with 'LR'
    163. 

  163. LR tn, fp: 188, 122
    164. 

  164. LR fn, tp: 1, 10
    165. 

  165. LR f1 score: 0.140
    166. 

  166. LR cohens kappa score: 0.082
    167. 

  167. LR average precision score: 0.246
    168. 

  168. 

  169. -> test with 'RF'
    170. 

  170. RF tn, fp: 305, 5
    171. 

  171. RF fn, tp: 10, 1
    172. 

  172. RF f1 score: 0.118
    173. 

  173. RF cohens kappa score: 0.096
    174. 

  174. 

  175. -> test with 'GB'
    176. 

  176. GB tn, fp: 282, 28
    177. 

  177. GB fn, tp: 5, 6
    178. 

  178. GB f1 score: 0.267
    179. 

  179. GB cohens kappa score: 0.227
    180. 

  180. 

  181. -> test with 'KNN'
    182. 

  182. KNN tn, fp: 203, 107
    183. 

  183. KNN fn, tp: 8, 3
    184. 

  184. KNN f1 score: 0.050
    185. 

  185. KNN cohens kappa score: -0.014
    186. 

  186. 

  187. 

  188. ------ Step 1/5: Slice 4/5 -------
    189. 

  189. -> Reset the GAN
    190. 

  190. -> Train generator for synthetic samples
    191. 

  191. -> create 1194 synthetic samples
    192. 

  192. -> retrain GAN for predict
    193. 

  193. Epoch 1/10
    194. 

  194. 
  1/124 [..............................] - ETA: 33s - loss: 0.4276
 22/124 [====>.........................] - ETA: 0s - loss: 0.4205 
 45/124 [=========>....................] - ETA: 0s - loss: 0.4290
 68/124 [===============>..............] - ETA: 0s - loss: 0.4234
 89/124 [====================>.........] - ETA: 0s - loss: 0.4269
111/124 [=========================>....] - ETA: 0s - loss: 0.4252
124/124 [==============================] - 1s 2ms/step - loss: 0.4243
    195. 

  195. Epoch 2/10
    196. 

  196. 
  1/124 [..............................] - ETA: 0s - loss: 0.4360
 21/124 [====>.........................] - ETA: 0s - loss: 0.3854
 43/124 [=========>....................] - ETA: 0s - loss: 0.4000
 63/124 [==============>...............] - ETA: 0s - loss: 0.4059
 86/124 [===================>..........] - ETA: 0s - loss: 0.4126
110/124 [=========================>....] - ETA: 0s - loss: 0.4126
124/124 [==============================] - 0s 2ms/step - loss: 0.4104
    197. 

  197. Epoch 3/10
    198. 

  198. 
  1/124 [..............................] - ETA: 0s - loss: 0.3127
 24/124 [====>.........................] - ETA: 0s - loss: 0.3935
 48/124 [==========>...................] - ETA: 0s - loss: 0.4042
 71/124 [================>.............] - ETA: 0s - loss: 0.3936
 93/124 [=====================>........] - ETA: 0s - loss: 0.4021
115/124 [==========================>...] - ETA: 0s - loss: 0.4061
124/124 [==============================] - 0s 2ms/step - loss: 0.4056
    199. 

  199. Epoch 4/10
    200. 

  200. 
  1/124 [..............................] - ETA: 0s - loss: 0.3713
 21/124 [====>.........................] - ETA: 0s - loss: 0.4003
 43/124 [=========>....................] - ETA: 0s - loss: 0.4054
 66/124 [==============>...............] - ETA: 0s - loss: 0.3989
 88/124 [====================>.........] - ETA: 0s - loss: 0.4027
108/124 [=========================>....] - ETA: 0s - loss: 0.3973
124/124 [==============================] - 0s 2ms/step - loss: 0.3956
    201. 

  201. Epoch 5/10
    202. 

  202. 
  1/124 [..............................] - ETA: 0s - loss: 0.4179
 31/124 [======>.......................] - ETA: 0s - loss: 0.3564
 64/124 [==============>...............] - ETA: 0s - loss: 0.3749
 97/124 [======================>.......] - ETA: 0s - loss: 0.3823
124/124 [==============================] - 0s 2ms/step - loss: 0.3818
    203. 

  203. Epoch 6/10
    204. 

  204. 
  1/124 [..............................] - ETA: 0s - loss: 0.4486
 26/124 [=====>........................] - ETA: 0s - loss: 0.3610
 63/124 [==============>...............] - ETA: 0s - loss: 0.3607
 96/124 [======================>.......] - ETA: 0s - loss: 0.3762
124/124 [==============================] - 0s 2ms/step - loss: 0.3769
    205. 

  205. Epoch 7/10
    206. 

  206. 
  1/124 [..............................] - ETA: 0s - loss: 0.2783
 28/124 [=====>........................] - ETA: 0s - loss: 0.3589
 59/124 [=============>................] - ETA: 0s - loss: 0.3721
 92/124 [=====================>........] - ETA: 0s - loss: 0.3660
120/124 [============================>.] - ETA: 0s - loss: 0.3717
124/124 [==============================] - 0s 2ms/step - loss: 0.3714
    207. 

  207. Epoch 8/10
    208. 

  208. 
  1/124 [..............................] - ETA: 0s - loss: 0.3270
 36/124 [=======>......................] - ETA: 0s - loss: 0.3748
 69/124 [===============>..............] - ETA: 0s - loss: 0.3741
103/124 [=======================>......] - ETA: 0s - loss: 0.3664
124/124 [==============================] - 0s 2ms/step - loss: 0.3652
    209. 

  209. Epoch 9/10
    210. 

  210. 
  1/124 [..............................] - ETA: 0s - loss: 0.2543
 33/124 [======>.......................] - ETA: 0s - loss: 0.3718
 70/124 [===============>..............] - ETA: 0s - loss: 0.3537
102/124 [=======================>......] - ETA: 0s - loss: 0.3606
124/124 [==============================] - 0s 1ms/step - loss: 0.3601
    211. 

  211. Epoch 10/10
    212. 

  212. 
  1/124 [..............................] - ETA: 0s - loss: 0.3188
 32/124 [======>.......................] - ETA: 0s - loss: 0.3626
 68/124 [===============>..............] - ETA: 0s - loss: 0.3556
100/124 [=======================>......] - ETA: 0s - loss: 0.3531
124/124 [==============================] - 0s 2ms/step - loss: 0.3500
    213. 

  213. -> test with GAN.predict
    214. 

  214. GAN tn, fp: 257, 53
    215. 

  215. GAN fn, tp: 8, 3
    216. 

  216. GAN f1 score: 0.090
    217. 

  217. GAN cohens kappa score: 0.034
    218. 

  218. 

  219. -> test with 'LR'
    220. 

  220. LR tn, fp: 241, 69
    221. 

  221. LR fn, tp: 6, 5
    222. 

  222. LR f1 score: 0.118
    223. 

  223. LR cohens kappa score: 0.062
    224. 

  224. LR average precision score: 0.138
    225. 

  225. 

  226. -> test with 'RF'
    227. 

  227. RF tn, fp: 305, 5
    228. 

  228. RF fn, tp: 11, 0
    229. 

  229. RF f1 score: 0.000
    230. 

  230. RF cohens kappa score: -0.022
    231. 

  231. 

  232. -> test with 'GB'
    233. 

  233. GB tn, fp: 291, 19
    234. 

  234. GB fn, tp: 10, 1
    235. 

  235. GB f1 score: 0.065
    236. 

  236. GB cohens kappa score: 0.021
    237. 

  237. 

  238. -> test with 'KNN'
    239. 

  239. KNN tn, fp: 223, 87
    240. 

  240. KNN fn, tp: 6, 5
    241. 

  241. KNN f1 score: 0.097
    242. 

  242. KNN cohens kappa score: 0.038
    243. 

  243. 

  244. 

  245. ------ Step 1/5: Slice 5/5 -------
    246. 

  246. -> Reset the GAN
    247. 

  247. -> Train generator for synthetic samples
    248. 

  248. -> create 1196 synthetic samples
    249. 

  249. -> retrain GAN for predict
    250. 

  250. Epoch 1/10
    251. 

  251. 
  1/124 [..............................] - ETA: 18s - loss: 0.4467
 44/124 [=========>....................] - ETA: 0s - loss: 0.4812 
 80/124 [==================>...........] - ETA: 0s - loss: 0.4818
115/124 [==========================>...] - ETA: 0s - loss: 0.4827
124/124 [==============================] - 0s 1ms/step - loss: 0.4836
    252. 

  252. Epoch 2/10
    253. 

  253. 
  1/124 [..............................] - ETA: 0s - loss: 0.3882
 43/124 [=========>....................] - ETA: 0s - loss: 0.4726
 86/124 [===================>..........] - ETA: 0s - loss: 0.4655
124/124 [==============================] - 0s 1ms/step - loss: 0.4695
    254. 

  254. Epoch 3/10
    255. 

  255. 
  1/124 [..............................] - ETA: 0s - loss: 0.3798
 45/124 [=========>....................] - ETA: 0s - loss: 0.4611
 84/124 [===================>..........] - ETA: 0s - loss: 0.4704
124/124 [==============================] - 0s 1ms/step - loss: 0.4602
    256. 

  256. Epoch 4/10
    257. 

  257. 
  1/124 [..............................] - ETA: 0s - loss: 0.4043
 44/124 [=========>....................] - ETA: 0s - loss: 0.4648
 87/124 [====================>.........] - ETA: 0s - loss: 0.4568
124/124 [==============================] - 0s 1ms/step - loss: 0.4567
    258. 

  258. Epoch 5/10
    259. 

  259. 
  1/124 [..............................] - ETA: 0s - loss: 0.4438
 44/124 [=========>....................] - ETA: 0s - loss: 0.4685
 88/124 [====================>.........] - ETA: 0s - loss: 0.4544
122/124 [============================>.] - ETA: 0s - loss: 0.4549
124/124 [==============================] - 0s 1ms/step - loss: 0.4538
    260. 

  260. Epoch 6/10
    261. 

  261. 
  1/124 [..............................] - ETA: 0s - loss: 0.3726
 39/124 [========>.....................] - ETA: 0s - loss: 0.4357
 81/124 [==================>...........] - ETA: 0s - loss: 0.4410
121/124 [============================>.] - ETA: 0s - loss: 0.4402
124/124 [==============================] - 0s 1ms/step - loss: 0.4404
    262. 

  262. Epoch 7/10
    263. 

  263. 
  1/124 [..............................] - ETA: 0s - loss: 0.3385
 44/124 [=========>....................] - ETA: 0s - loss: 0.4566
 87/124 [====================>.........] - ETA: 0s - loss: 0.4508
124/124 [==============================] - 0s 1ms/step - loss: 0.4389
    264. 

  264. Epoch 8/10
    265. 

  265. 
  1/124 [..............................] - ETA: 0s - loss: 0.2838
 45/124 [=========>....................] - ETA: 0s - loss: 0.4416
 88/124 [====================>.........] - ETA: 0s - loss: 0.4298
124/124 [==============================] - 0s 1ms/step - loss: 0.4323
    266. 

  266. Epoch 9/10
    267. 

  267. 
  1/124 [..............................] - ETA: 0s - loss: 0.3598
 46/124 [==========>...................] - ETA: 0s - loss: 0.4529
 90/124 [====================>.........] - ETA: 0s - loss: 0.4327
124/124 [==============================] - 0s 1ms/step - loss: 0.4253
    268. 

  268. Epoch 10/10
    269. 

  269. 
  1/124 [..............................] - ETA: 0s - loss: 0.4014
 45/124 [=========>....................] - ETA: 0s - loss: 0.4069
 90/124 [====================>.........] - ETA: 0s - loss: 0.4158
124/124 [==============================] - 0s 1ms/step - loss: 0.4182
    270. 

  270. -> test with GAN.predict
    271. 

  271. GAN tn, fp: 215, 91
    272. 

  272. GAN fn, tp: 6, 3
    273. 

  273. GAN f1 score: 0.058
    274. 

  274. GAN cohens kappa score: 0.006
    275. 

  275. 

  276. -> test with 'LR'
    277. 

  277. LR tn, fp: 227, 79
    278. 

  278. LR fn, tp: 4, 5
    279. 

  279. LR f1 score: 0.108
    280. 

  280. LR cohens kappa score: 0.059
    281. 

  281. LR average precision score: 0.219
    282. 

  282. 

  283. -> test with 'RF'
    284. 

  284. RF tn, fp: 306, 0
    285. 

  285. RF fn, tp: 9, 0
    286. 

  286. RF f1 score: 0.000
    287. 

  287. RF cohens kappa score: 0.000
    288. 

  288. 

  289. -> test with 'GB'
    290. 

  290. GB tn, fp: 291, 15
    291. 

  291. GB fn, tp: 9, 0
    292. 

  292. GB f1 score: 0.000
    293. 

  293. GB cohens kappa score: -0.037
    294. 

  294. 

  295. -> test with 'KNN'
    296. 

  296. KNN tn, fp: 243, 63
    297. 

  297. KNN fn, tp: 6, 3
    298. 

  298. KNN f1 score: 0.080
    299. 

  299. KNN cohens kappa score: 0.031
    300. 

  300. 

  301. 

  302. ====== Step 2/5 =======
    303. 

  303. -> Shuffling data
    304. 

  304. -> Spliting data to slices
    305. 

  305. 

  306. ------ Step 2/5: Slice 1/5 -------
    307. 

  307. -> Reset the GAN
    308. 

  308. -> Train generator for synthetic samples
    309. 

  309. -> create 1194 synthetic samples
    310. 

  310. -> retrain GAN for predict
    311. 

  311. Epoch 1/10
    312. 

  312. 
  1/124 [..............................] - ETA: 18s - loss: 0.5780
 42/124 [=========>....................] - ETA: 0s - loss: 0.5034 
 83/124 [===================>..........] - ETA: 0s - loss: 0.5029
124/124 [==============================] - ETA: 0s - loss: 0.5016
124/124 [==============================] - 0s 1ms/step - loss: 0.5016
    313. 

  313. Epoch 2/10
    314. 

  314. 
  1/124 [..............................] - ETA: 0s - loss: 0.4354
 39/124 [========>.....................] - ETA: 0s - loss: 0.4958
 74/124 [================>.............] - ETA: 0s - loss: 0.4867
110/124 [=========================>....] - ETA: 0s - loss: 0.4947
124/124 [==============================] - 0s 1ms/step - loss: 0.4933
    315. 

  315. Epoch 3/10
    316. 

  316. 
  1/124 [..............................] - ETA: 0s - loss: 0.5962
 40/124 [========>.....................] - ETA: 0s - loss: 0.4785
 82/124 [==================>...........] - ETA: 0s - loss: 0.4723
124/124 [==============================] - ETA: 0s - loss: 0.4774
124/124 [==============================] - 0s 1ms/step - loss: 0.4774
    317. 

  317. Epoch 4/10
    318. 

  318. 
  1/124 [..............................] - ETA: 0s - loss: 0.3800
 43/124 [=========>....................] - ETA: 0s - loss: 0.4853
 84/124 [===================>..........] - ETA: 0s - loss: 0.4773
124/124 [==============================] - 0s 1ms/step - loss: 0.4698
    319. 

  319. Epoch 5/10
    320. 

  320. 
  1/124 [..............................] - ETA: 0s - loss: 0.3724
 42/124 [=========>....................] - ETA: 0s - loss: 0.4867
 84/124 [===================>..........] - ETA: 0s - loss: 0.4637
124/124 [==============================] - 0s 1ms/step - loss: 0.4627
    321. 

  321. Epoch 6/10
    322. 

  322. 
  1/124 [..............................] - ETA: 0s - loss: 0.4963
 44/124 [=========>....................] - ETA: 0s - loss: 0.4379
 85/124 [===================>..........] - ETA: 0s - loss: 0.4494
124/124 [==============================] - 0s 1ms/step - loss: 0.4512
    323. 

  323. Epoch 7/10
    324. 

  324. 
  1/124 [..............................] - ETA: 0s - loss: 0.4501
 42/124 [=========>....................] - ETA: 0s - loss: 0.4493
 84/124 [===================>..........] - ETA: 0s - loss: 0.4382
124/124 [==============================] - 0s 1ms/step - loss: 0.4537
    325. 

  325. Epoch 8/10
    326. 

  326. 
  1/124 [..............................] - ETA: 0s - loss: 0.5336
 42/124 [=========>....................] - ETA: 0s - loss: 0.4469
 83/124 [===================>..........] - ETA: 0s - loss: 0.4496
120/124 [============================>.] - ETA: 0s - loss: 0.4439
124/124 [==============================] - 0s 1ms/step - loss: 0.4425
    327. 

  327. Epoch 9/10
    328. 

  328. 
  1/124 [..............................] - ETA: 0s - loss: 0.4295
 43/124 [=========>....................] - ETA: 0s - loss: 0.4549
 85/124 [===================>..........] - ETA: 0s - loss: 0.4447
124/124 [==============================] - 0s 1ms/step - loss: 0.4336
    329. 

  329. Epoch 10/10
    330. 

  330. 
  1/124 [..............................] - ETA: 0s - loss: 0.4222
 42/124 [=========>....................] - ETA: 0s - loss: 0.4273
 82/124 [==================>...........] - ETA: 0s - loss: 0.4295
123/124 [============================>.] - ETA: 0s - loss: 0.4244
124/124 [==============================] - 0s 1ms/step - loss: 0.4236
    331. 

  331. -> test with GAN.predict
    332. 

  332. GAN tn, fp: 227, 83
    333. 

  333. GAN fn, tp: 3, 8
    334. 

  334. GAN f1 score: 0.157
    335. 

  335. GAN cohens kappa score: 0.102
    336. 

  336. 

  337. -> test with 'LR'
    338. 

  338. LR tn, fp: 203, 107
    339. 

  339. LR fn, tp: 3, 8
    340. 

  340. LR f1 score: 0.127
    341. 

  341. LR cohens kappa score: 0.069
    342. 

  342. LR average precision score: 0.132
    343. 

  343. 

  344. -> test with 'RF'
    345. 

  345. RF tn, fp: 302, 8
    346. 

  346. RF fn, tp: 10, 1
    347. 

  347. RF f1 score: 0.100
    348. 

  348. RF cohens kappa score: 0.071
    349. 

  349. 

  350. -> test with 'GB'
    351. 

  351. GB tn, fp: 287, 23
    352. 

  352. GB fn, tp: 7, 4
    353. 

  353. GB f1 score: 0.211
    354. 

  354. GB cohens kappa score: 0.170
    355. 

  355. 

  356. -> test with 'KNN'
    357. 

  357. KNN tn, fp: 214, 96
    358. 

  358. KNN fn, tp: 8, 3
    359. 

  359. KNN f1 score: 0.055
    360. 

  360. KNN cohens kappa score: -0.008
    361. 

  361. 

  362. 

  363. ------ Step 2/5: Slice 2/5 -------
    364. 

  364. -> Reset the GAN
    365. 

  365. -> Train generator for synthetic samples
    366. 

  366. -> create 1194 synthetic samples
    367. 

  367. -> retrain GAN for predict
    368. 

  368. Epoch 1/10
    369. 

  369. 
  1/124 [..............................] - ETA: 18s - loss: 0.5455
 40/124 [========>.....................] - ETA: 0s - loss: 0.4819 
 82/124 [==================>...........] - ETA: 0s - loss: 0.4695
122/124 [============================>.] - ETA: 0s - loss: 0.4620
124/124 [==============================] - 0s 1ms/step - loss: 0.4636
    370. 

  370. Epoch 2/10
    371. 

  371. 
  1/124 [..............................] - ETA: 0s - loss: 0.5037
 41/124 [========>.....................] - ETA: 0s - loss: 0.4705
 80/124 [==================>...........] - ETA: 0s - loss: 0.4668
120/124 [============================>.] - ETA: 0s - loss: 0.4618
124/124 [==============================] - 0s 1ms/step - loss: 0.4614
    372. 

  372. Epoch 3/10
    373. 

  373. 
  1/124 [..............................] - ETA: 0s - loss: 0.3938
 40/124 [========>.....................] - ETA: 0s - loss: 0.4703
 81/124 [==================>...........] - ETA: 0s - loss: 0.4593
120/124 [============================>.] - ETA: 0s - loss: 0.4508
124/124 [==============================] - 0s 1ms/step - loss: 0.4476
    374. 

  374. Epoch 4/10
    375. 

  375. 
  1/124 [..............................] - ETA: 0s - loss: 0.3599
 42/124 [=========>....................] - ETA: 0s - loss: 0.4381
 83/124 [===================>..........] - ETA: 0s - loss: 0.4501
124/124 [==============================] - ETA: 0s - loss: 0.4422
124/124 [==============================] - 0s 1ms/step - loss: 0.4422
    376. 

  376. Epoch 5/10
    377. 

  377. 
  1/124 [..............................] - ETA: 0s - loss: 0.7665
 41/124 [========>.....................] - ETA: 0s - loss: 0.4388
 81/124 [==================>...........] - ETA: 0s - loss: 0.4314
121/124 [============================>.] - ETA: 0s - loss: 0.4297
124/124 [==============================] - 0s 1ms/step - loss: 0.4283
    378. 

  378. Epoch 6/10
    379. 

  379. 
  1/124 [..............................] - ETA: 0s - loss: 0.3979
 42/124 [=========>....................] - ETA: 0s - loss: 0.4107
 79/124 [==================>...........] - ETA: 0s - loss: 0.4198
120/124 [============================>.] - ETA: 0s - loss: 0.4236
124/124 [==============================] - 0s 1ms/step - loss: 0.4252
    380. 

  380. Epoch 7/10
    381. 

  381. 
  1/124 [..............................] - ETA: 0s - loss: 0.2742
 37/124 [=======>......................] - ETA: 0s - loss: 0.4201
 71/124 [================>.............] - ETA: 0s - loss: 0.4305
105/124 [========================>.....] - ETA: 0s - loss: 0.4233
124/124 [==============================] - 0s 1ms/step - loss: 0.4210
    382. 

  382. Epoch 8/10
    383. 

  383. 
  1/124 [..............................] - ETA: 0s - loss: 0.3316
 40/124 [========>.....................] - ETA: 0s - loss: 0.3945
 77/124 [=================>............] - ETA: 0s - loss: 0.4064
118/124 [===========================>..] - ETA: 0s - loss: 0.4063
124/124 [==============================] - 0s 1ms/step - loss: 0.4083
    384. 

  384. Epoch 9/10
    385. 

  385. 
  1/124 [..............................] - ETA: 0s - loss: 0.5679
 41/124 [========>.....................] - ETA: 0s - loss: 0.3893
 76/124 [=================>............] - ETA: 0s - loss: 0.4072
112/124 [==========================>...] - ETA: 0s - loss: 0.4205
124/124 [==============================] - 0s 1ms/step - loss: 0.4205
    386. 

  386. Epoch 10/10
    387. 

  387. 
  1/124 [..............................] - ETA: 0s - loss: 0.5255
 34/124 [=======>......................] - ETA: 0s - loss: 0.4238
 73/124 [================>.............] - ETA: 0s - loss: 0.4111
114/124 [==========================>...] - ETA: 0s - loss: 0.4010
124/124 [==============================] - 0s 1ms/step - loss: 0.4002
    388. 

  388. -> test with GAN.predict
    389. 

  389. GAN tn, fp: 228, 82
    390. 

  390. GAN fn, tp: 8, 3
    391. 

  391. GAN f1 score: 0.062
    392. 

  392. GAN cohens kappa score: 0.002
    393. 

  393. 

  394. -> test with 'LR'
    395. 

  395. LR tn, fp: 230, 80
    396. 

  396. LR fn, tp: 4, 7
    397. 

  397. LR f1 score: 0.143
    398. 

  398. LR cohens kappa score: 0.087
    399. 

  399. LR average precision score: 0.165
    400. 

  400. 

  401. -> test with 'RF'
    402. 

  402. RF tn, fp: 309, 1
    403. 

  403. RF fn, tp: 11, 0
    404. 

  404. RF f1 score: 0.000
    405. 

  405. RF cohens kappa score: -0.006
    406. 

  406. 

  407. -> test with 'GB'
    408. 

  408. GB tn, fp: 301, 9
    409. 

  409. GB fn, tp: 11, 0
    410. 

  410. GB f1 score: 0.000
    411. 

  411. GB cohens kappa score: -0.032
    412. 

  412. 

  413. -> test with 'KNN'
    414. 

  414. KNN tn, fp: 232, 78
    415. 

  415. KNN fn, tp: 7, 4
    416. 

  416. KNN f1 score: 0.086
    417. 

  417. KNN cohens kappa score: 0.027
    418. 

  418. 

  419. 

  420. ------ Step 2/5: Slice 3/5 -------
    421. 

  421. -> Reset the GAN
    422. 

  422. -> Train generator for synthetic samples
    423. 

  423. -> create 1194 synthetic samples
    424. 

  424. -> retrain GAN for predict
    425. 

  425. Epoch 1/10
    426. 

  426. 
  1/124 [..............................] - ETA: 21s - loss: 0.5098
 42/124 [=========>....................] - ETA: 0s - loss: 0.4809 
 83/124 [===================>..........] - ETA: 0s - loss: 0.4781
121/124 [============================>.] - ETA: 0s - loss: 0.4819
124/124 [==============================] - 0s 1ms/step - loss: 0.4815
    427. 

  427. Epoch 2/10
    428. 

  428. 
  1/124 [..............................] - ETA: 0s - loss: 0.3662
 45/124 [=========>....................] - ETA: 0s - loss: 0.4624
 89/124 [====================>.........] - ETA: 0s - loss: 0.4692
124/124 [==============================] - 0s 1ms/step - loss: 0.4705
    429. 

  429. Epoch 3/10
    430. 

  430. 
  1/124 [..............................] - ETA: 0s - loss: 0.3922
 42/124 [=========>....................] - ETA: 0s - loss: 0.4578
 82/124 [==================>...........] - ETA: 0s - loss: 0.4697
124/124 [==============================] - 0s 1ms/step - loss: 0.4644
    431. 

  431. Epoch 4/10
    432. 

  432. 
  1/124 [..............................] - ETA: 0s - loss: 0.4596
 42/124 [=========>....................] - ETA: 0s - loss: 0.4604
 82/124 [==================>...........] - ETA: 0s - loss: 0.4690
121/124 [============================>.] - ETA: 0s - loss: 0.4599
124/124 [==============================] - 0s 1ms/step - loss: 0.4587
    433. 

  433. Epoch 5/10
    434. 

  434. 
  1/124 [..............................] - ETA: 0s - loss: 0.4573
 37/124 [=======>......................] - ETA: 0s - loss: 0.4564
 73/124 [================>.............] - ETA: 0s - loss: 0.4674
114/124 [==========================>...] - ETA: 0s - loss: 0.4515
124/124 [==============================] - 0s 1ms/step - loss: 0.4494
    435. 

  435. Epoch 6/10
    436. 

  436. 
  1/124 [..............................] - ETA: 0s - loss: 0.4076
 42/124 [=========>....................] - ETA: 0s - loss: 0.4540
 82/124 [==================>...........] - ETA: 0s - loss: 0.4372
124/124 [==============================] - ETA: 0s - loss: 0.4449
124/124 [==============================] - 0s 1ms/step - loss: 0.4449
    437. 

  437. Epoch 7/10
    438. 

  438. 
  1/124 [..............................] - ETA: 0s - loss: 0.5746
 42/124 [=========>....................] - ETA: 0s - loss: 0.4241
 85/124 [===================>..........] - ETA: 0s - loss: 0.4483
124/124 [==============================] - 0s 1ms/step - loss: 0.4453
    439. 

  439. Epoch 8/10
    440. 

  440. 
  1/124 [..............................] - ETA: 0s - loss: 0.6577
 43/124 [=========>....................] - ETA: 0s - loss: 0.4423
 84/124 [===================>..........] - ETA: 0s - loss: 0.4325
124/124 [==============================] - 0s 1ms/step - loss: 0.4306
    441. 

  441. Epoch 9/10
    442. 

  442. 
  1/124 [..............................] - ETA: 0s - loss: 0.5566
 43/124 [=========>....................] - ETA: 0s - loss: 0.4435
 84/124 [===================>..........] - ETA: 0s - loss: 0.4341
124/124 [==============================] - 0s 1ms/step - loss: 0.4269
    443. 

  443. Epoch 10/10
    444. 

  444. 
  1/124 [..............................] - ETA: 0s - loss: 0.4991
 40/124 [========>.....................] - ETA: 0s - loss: 0.4309
 81/124 [==================>...........] - ETA: 0s - loss: 0.4245
122/124 [============================>.] - ETA: 0s - loss: 0.4190
124/124 [==============================] - 0s 1ms/step - loss: 0.4185
    445. 

  445. -> test with GAN.predict
    446. 

  446. GAN tn, fp: 273, 37
    447. 

  447. GAN fn, tp: 8, 3
    448. 

  448. GAN f1 score: 0.118
    449. 

  449. GAN cohens kappa score: 0.068
    450. 

  450. 

  451. -> test with 'LR'
    452. 

  452. LR tn, fp: 220, 90
    453. 

  453. LR fn, tp: 3, 8
    454. 

  454. LR f1 score: 0.147
    455. 

  455. LR cohens kappa score: 0.091
    456. 

  456. LR average precision score: 0.154
    457. 

  457. 

  458. -> test with 'RF'
    459. 

  459. RF tn, fp: 301, 9
    460. 

  460. RF fn, tp: 10, 1
    461. 

  461. RF f1 score: 0.095
    462. 

  462. RF cohens kappa score: 0.065
    463. 

  463. 

  464. -> test with 'GB'
    465. 

  465. GB tn, fp: 295, 15
    466. 

  466. GB fn, tp: 9, 2
    467. 

  467. GB f1 score: 0.143
    468. 

  468. GB cohens kappa score: 0.106
    469. 

  469. 

  470. -> test with 'KNN'
    471. 

  471. KNN tn, fp: 238, 72
    472. 

  472. KNN fn, tp: 9, 2
    473. 

  473. KNN f1 score: 0.047
    474. 

  474. KNN cohens kappa score: -0.013
    475. 

  475. 

  476. 

  477. ------ Step 2/5: Slice 4/5 -------
    478. 

  478. -> Reset the GAN
    479. 

  479. -> Train generator for synthetic samples
    480. 

  480. -> create 1194 synthetic samples
    481. 

  481. -> retrain GAN for predict
    482. 

  482. Epoch 1/10
    483. 

  483. 
  1/124 [..............................] - ETA: 20s - loss: 0.4727
 36/124 [=======>......................] - ETA: 0s - loss: 0.4582 
 76/124 [=================>............] - ETA: 0s - loss: 0.4568
116/124 [===========================>..] - ETA: 0s - loss: 0.4518
124/124 [==============================] - 0s 1ms/step - loss: 0.4539
    484. 

  484. Epoch 2/10
    485. 

  485. 
  1/124 [..............................] - ETA: 0s - loss: 0.4035
 43/124 [=========>....................] - ETA: 0s - loss: 0.4490
 84/124 [===================>..........] - ETA: 0s - loss: 0.4341
124/124 [==============================] - 0s 1ms/step - loss: 0.4366
    486. 

  486. Epoch 3/10
    487. 

  487. 
  1/124 [..............................] - ETA: 0s - loss: 0.4118
 40/124 [========>.....................] - ETA: 0s - loss: 0.4287
 81/124 [==================>...........] - ETA: 0s - loss: 0.4381
122/124 [============================>.] - ETA: 0s - loss: 0.4390
124/124 [==============================] - 0s 1ms/step - loss: 0.4382
    488. 

  488. Epoch 4/10
    489. 

  489. 
  1/124 [..............................] - ETA: 0s - loss: 0.4079
 43/124 [=========>....................] - ETA: 0s - loss: 0.4299
 85/124 [===================>..........] - ETA: 0s - loss: 0.4297
124/124 [==============================] - 0s 1ms/step - loss: 0.4276
    490. 

  490. Epoch 5/10
    491. 

  491. 
  1/124 [..............................] - ETA: 0s - loss: 0.2833
 41/124 [========>.....................] - ETA: 0s - loss: 0.4101
 81/124 [==================>...........] - ETA: 0s - loss: 0.4066
121/124 [============================>.] - ETA: 0s - loss: 0.4196
124/124 [==============================] - 0s 1ms/step - loss: 0.4196
    492. 

  492. Epoch 6/10
    493. 

  493. 
  1/124 [..............................] - ETA: 0s - loss: 0.4824
 42/124 [=========>....................] - ETA: 0s - loss: 0.3919
 84/124 [===================>..........] - ETA: 0s - loss: 0.4048
121/124 [============================>.] - ETA: 0s - loss: 0.4170
124/124 [==============================] - 0s 1ms/step - loss: 0.4169
    494. 

  494. Epoch 7/10
    495. 

  495. 
  1/124 [..............................] - ETA: 0s - loss: 0.4188
 40/124 [========>.....................] - ETA: 0s - loss: 0.4137
 78/124 [=================>............] - ETA: 0s - loss: 0.4050
116/124 [===========================>..] - ETA: 0s - loss: 0.4063
124/124 [==============================] - 0s 1ms/step - loss: 0.4104
    496. 

  496. Epoch 8/10
    497. 

  497. 
  1/124 [..............................] - ETA: 0s - loss: 0.4140
 35/124 [=======>......................] - ETA: 0s - loss: 0.4010
 71/124 [================>.............] - ETA: 0s - loss: 0.4010
110/124 [=========================>....] - ETA: 0s - loss: 0.4101
124/124 [==============================] - 0s 1ms/step - loss: 0.4047
    498. 

  498. Epoch 9/10
    499. 

  499. 
  1/124 [..............................] - ETA: 0s - loss: 0.4044
 42/124 [=========>....................] - ETA: 0s - loss: 0.4146
 83/124 [===================>..........] - ETA: 0s - loss: 0.4182
124/124 [==============================] - ETA: 0s - loss: 0.4105
124/124 [==============================] - 0s 1ms/step - loss: 0.4105
    500. 

  500. Epoch 10/10
    501. 

  501. 
  1/124 [..............................] - ETA: 0s - loss: 0.3688
 43/124 [=========>....................] - ETA: 0s - loss: 0.3809
 84/124 [===================>..........] - ETA: 0s - loss: 0.3860
124/124 [==============================] - 0s 1ms/step - loss: 0.3975
    502. 

  502. -> test with GAN.predict
    503. 

  503. GAN tn, fp: 282, 28
    504. 

  504. GAN fn, tp: 6, 5
    505. 

  505. GAN f1 score: 0.227
    506. 

  506. GAN cohens kappa score: 0.185
    507. 

  507. 

  508. -> test with 'LR'
    509. 

  509. LR tn, fp: 211, 99
    510. 

  510. LR fn, tp: 5, 6
    511. 

  511. LR f1 score: 0.103
    512. 

  512. LR cohens kappa score: 0.044
    513. 

  513. LR average precision score: 0.282
    514. 

  514. 

  515. -> test with 'RF'
    516. 

  516. RF tn, fp: 307, 3
    517. 

  517. RF fn, tp: 10, 1
    518. 

  518. RF f1 score: 0.133
    519. 

  519. RF cohens kappa score: 0.117
    520. 

  520. 

  521. -> test with 'GB'
    522. 

  522. GB tn, fp: 297, 13
    523. 

  523. GB fn, tp: 9, 2
    524. 

  524. GB f1 score: 0.154
    525. 

  525. GB cohens kappa score: 0.119
    526. 

  526. 

  527. -> test with 'KNN'
    528. 

  528. KNN tn, fp: 222, 88
    529. 

  529. KNN fn, tp: 7, 4
    530. 

  530. KNN f1 score: 0.078
    531. 

  531. KNN cohens kappa score: 0.018
    532. 

  532. 

  533. 

  534. ------ Step 2/5: Slice 5/5 -------
    535. 

  535. -> Reset the GAN
    536. 

  536. -> Train generator for synthetic samples
    537. 

  537. -> create 1196 synthetic samples
    538. 

  538. -> retrain GAN for predict
    539. 

  539. Epoch 1/10
    540. 

  540. 
  1/124 [..............................] - ETA: 16s - loss: 0.3709
 38/124 [========>.....................] - ETA: 0s - loss: 0.4510 
 72/124 [================>.............] - ETA: 0s - loss: 0.4430
109/124 [=========================>....] - ETA: 0s - loss: 0.4445
124/124 [==============================] - 0s 1ms/step - loss: 0.4451
    541. 

  541. Epoch 2/10
    542. 

  542. 
  1/124 [..............................] - ETA: 0s - loss: 0.2933
 39/124 [========>.....................] - ETA: 0s - loss: 0.4242
 75/124 [=================>............] - ETA: 0s - loss: 0.4356
114/124 [==========================>...] - ETA: 0s - loss: 0.4360
124/124 [==============================] - 0s 1ms/step - loss: 0.4333
    543. 

  543. Epoch 3/10
    544. 

  544. 
  1/124 [..............................] - ETA: 0s - loss: 0.5600
 41/124 [========>.....................] - ETA: 0s - loss: 0.4591
 80/124 [==================>...........] - ETA: 0s - loss: 0.4352
123/124 [============================>.] - ETA: 0s - loss: 0.4291
124/124 [==============================] - 0s 1ms/step - loss: 0.4297
    545. 

  545. Epoch 4/10
    546. 

  546. 
  1/124 [..............................] - ETA: 0s - loss: 0.3511
 37/124 [=======>......................] - ETA: 0s - loss: 0.4348
 78/124 [=================>............] - ETA: 0s - loss: 0.4431
112/124 [==========================>...] - ETA: 0s - loss: 0.4237
124/124 [==============================] - 0s 1ms/step - loss: 0.4239
    547. 

  547. Epoch 5/10
    548. 

  548. 
  1/124 [..............................] - ETA: 0s - loss: 0.4091
 38/124 [========>.....................] - ETA: 0s - loss: 0.4010
 73/124 [================>.............] - ETA: 0s - loss: 0.4150
115/124 [==========================>...] - ETA: 0s - loss: 0.4159
124/124 [==============================] - 0s 1ms/step - loss: 0.4160
    549. 

  549. Epoch 6/10
    550. 

  550. 
  1/124 [..............................] - ETA: 0s - loss: 0.3407
 38/124 [========>.....................] - ETA: 0s - loss: 0.3876
 74/124 [================>.............] - ETA: 0s - loss: 0.4094
114/124 [==========================>...] - ETA: 0s - loss: 0.4097
124/124 [==============================] - 0s 1ms/step - loss: 0.4084
    551. 

  551. Epoch 7/10
    552. 

  552. 
  1/124 [..............................] - ETA: 0s - loss: 0.1953
 37/124 [=======>......................] - ETA: 0s - loss: 0.4003
 78/124 [=================>............] - ETA: 0s - loss: 0.4019
111/124 [=========================>....] - ETA: 0s - loss: 0.4074
124/124 [==============================] - 0s 1ms/step - loss: 0.4049
    553. 

  553. Epoch 8/10
    554. 

  554. 
  1/124 [..............................] - ETA: 0s - loss: 0.3835
 38/124 [========>.....................] - ETA: 0s - loss: 0.4048
 75/124 [=================>............] - ETA: 0s - loss: 0.4046
115/124 [==========================>...] - ETA: 0s - loss: 0.4023
124/124 [==============================] - 0s 1ms/step - loss: 0.3997
    555. 

  555. Epoch 9/10
    556. 

  556. 
  1/124 [..............................] - ETA: 0s - loss: 0.3379
 39/124 [========>.....................] - ETA: 0s - loss: 0.4183
 82/124 [==================>...........] - ETA: 0s - loss: 0.3976
116/124 [===========================>..] - ETA: 0s - loss: 0.3957
124/124 [==============================] - 0s 1ms/step - loss: 0.3954
    557. 

  557. Epoch 10/10
    558. 

  558. 
  1/124 [..............................] - ETA: 0s - loss: 0.3315
 43/124 [=========>....................] - ETA: 0s - loss: 0.3968
 82/124 [==================>...........] - ETA: 0s - loss: 0.3843
120/124 [============================>.] - ETA: 0s - loss: 0.3878
124/124 [==============================] - 0s 1ms/step - loss: 0.3869
    559. 

  559. -> test with GAN.predict
    560. 

  560. GAN tn, fp: 260, 46
    561. 

  561. GAN fn, tp: 4, 5
    562. 

  562. GAN f1 score: 0.167
    563. 

  563. GAN cohens kappa score: 0.124
    564. 

  564. 

  565. -> test with 'LR'
    566. 

  566. LR tn, fp: 229, 77
    567. 

  567. LR fn, tp: 3, 6
    568. 

  568. LR f1 score: 0.130
    569. 

  569. LR cohens kappa score: 0.083
    570. 

  570. LR average precision score: 0.143
    571. 

  571. 

  572. -> test with 'RF'
    573. 

  573. RF tn, fp: 305, 1
    574. 

  574. RF fn, tp: 8, 1
    575. 

  575. RF f1 score: 0.182
    576. 

  576. RF cohens kappa score: 0.173
    577. 

  577. 

  578. -> test with 'GB'
    579. 

  579. GB tn, fp: 291, 15
    580. 

  580. GB fn, tp: 6, 3
    581. 

  581. GB f1 score: 0.222
    582. 

  582. GB cohens kappa score: 0.191
    583. 

  583. 

  584. -> test with 'KNN'
    585. 

  585. KNN tn, fp: 231, 75
    586. 

  586. KNN fn, tp: 6, 3
    587. 

  587. KNN f1 score: 0.069
    588. 

  588. KNN cohens kappa score: 0.019
    589. 

  589. 

  590. 

  591. ====== Step 3/5 =======
    592. 

  592. -> Shuffling data
    593. 

  593. -> Spliting data to slices
    594. 

  594. 

  595. ------ Step 3/5: Slice 1/5 -------
    596. 

  596. -> Reset the GAN
    597. 

  597. -> Train generator for synthetic samples
    598. 

  598. -> create 1194 synthetic samples
    599. 

  599. -> retrain GAN for predict
    600. 

  600. Epoch 1/10
    601. 

  601. 
  1/124 [..............................] - ETA: 19s - loss: 0.3382
 42/124 [=========>....................] - ETA: 0s - loss: 0.4235 
 84/124 [===================>..........] - ETA: 0s - loss: 0.4337
123/124 [============================>.] - ETA: 0s - loss: 0.4247
124/124 [==============================] - 0s 1ms/step - loss: 0.4237
    602. 

  602. Epoch 2/10
    603. 

  603. 
  1/124 [..............................] - ETA: 0s - loss: 0.4062
 41/124 [========>.....................] - ETA: 0s - loss: 0.4316
 81/124 [==================>...........] - ETA: 0s - loss: 0.4277
123/124 [============================>.] - ETA: 0s - loss: 0.4129
124/124 [==============================] - 0s 1ms/step - loss: 0.4132
    604. 

  604. Epoch 3/10
    605. 

  605. 
  1/124 [..............................] - ETA: 0s - loss: 0.4265
 42/124 [=========>....................] - ETA: 0s - loss: 0.4421
 78/124 [=================>............] - ETA: 0s - loss: 0.4134
117/124 [===========================>..] - ETA: 0s - loss: 0.4101
124/124 [==============================] - 0s 1ms/step - loss: 0.4084
    606. 

  606. Epoch 4/10
    607. 

  607. 
  1/124 [..............................] - ETA: 0s - loss: 0.4757
 43/124 [=========>....................] - ETA: 0s - loss: 0.3980
 84/124 [===================>..........] - ETA: 0s - loss: 0.3987
123/124 [============================>.] - ETA: 0s - loss: 0.3978
124/124 [==============================] - 0s 1ms/step - loss: 0.3976
    608. 

  608. Epoch 5/10
    609. 

  609. 
  1/124 [..............................] - ETA: 0s - loss: 0.3434
 42/124 [=========>....................] - ETA: 0s - loss: 0.3936
 82/124 [==================>...........] - ETA: 0s - loss: 0.3935
123/124 [============================>.] - ETA: 0s - loss: 0.3896
124/124 [==============================] - 0s 1ms/step - loss: 0.3891
    610. 

  610. Epoch 6/10
    611. 

  611. 
  1/124 [..............................] - ETA: 0s - loss: 0.3832
 42/124 [=========>....................] - ETA: 0s - loss: 0.3889
 83/124 [===================>..........] - ETA: 0s - loss: 0.3795
123/124 [============================>.] - ETA: 0s - loss: 0.3824
124/124 [==============================] - 0s 1ms/step - loss: 0.3847
    612. 

  612. Epoch 7/10
    613. 

  613. 
  1/124 [..............................] - ETA: 0s - loss: 0.3615
 43/124 [=========>....................] - ETA: 0s - loss: 0.3801
 83/124 [===================>..........] - ETA: 0s - loss: 0.3797
118/124 [===========================>..] - ETA: 0s - loss: 0.3772
124/124 [==============================] - 0s 1ms/step - loss: 0.3777
    614. 

  614. Epoch 8/10
    615. 

  615. 
  1/124 [..............................] - ETA: 0s - loss: 0.3988
 36/124 [=======>......................] - ETA: 0s - loss: 0.3783
 73/124 [================>.............] - ETA: 0s - loss: 0.3917
112/124 [==========================>...] - ETA: 0s - loss: 0.3787
124/124 [==============================] - 0s 1ms/step - loss: 0.3744
    616. 

  616. Epoch 9/10
    617. 

  617. 
  1/124 [..............................] - ETA: 0s - loss: 0.3167
 40/124 [========>.....................] - ETA: 0s - loss: 0.3368
 81/124 [==================>...........] - ETA: 0s - loss: 0.3652
118/124 [===========================>..] - ETA: 0s - loss: 0.3618
124/124 [==============================] - 0s 1ms/step - loss: 0.3644
    618. 

  618. Epoch 10/10
    619. 

  619. 
  1/124 [..............................] - ETA: 0s - loss: 0.3238
 42/124 [=========>....................] - ETA: 0s - loss: 0.3653
 82/124 [==================>...........] - ETA: 0s - loss: 0.3537
124/124 [==============================] - ETA: 0s - loss: 0.3601
124/124 [==============================] - 0s 1ms/step - loss: 0.3601
    620. 

  620. -> test with GAN.predict
    621. 

  621. GAN tn, fp: 265, 45
    622. 

  622. GAN fn, tp: 6, 5
    623. 

  623. GAN f1 score: 0.164
    624. 

  624. GAN cohens kappa score: 0.114
    625. 

  625. 

  626. -> test with 'LR'
    627. 

  627. LR tn, fp: 228, 82
    628. 

  628. LR fn, tp: 5, 6
    629. 

  629. LR f1 score: 0.121
    630. 

  630. LR cohens kappa score: 0.064
    631. 

  631. LR average precision score: 0.164
    632. 

  632. 

  633. -> test with 'RF'
    634. 

  634. RF tn, fp: 307, 3
    635. 

  635. RF fn, tp: 11, 0
    636. 

  636. RF f1 score: 0.000
    637. 

  637. RF cohens kappa score: -0.015
    638. 

  638. 

  639. -> test with 'GB'
    640. 

  640. GB tn, fp: 301, 9
    641. 

  641. GB fn, tp: 11, 0
    642. 

  642. GB f1 score: 0.000
    643. 

  643. GB cohens kappa score: -0.032
    644. 

  644. 

  645. -> test with 'KNN'
    646. 

  646. KNN tn, fp: 237, 73
    647. 

  647. KNN fn, tp: 8, 3
    648. 

  648. KNN f1 score: 0.069
    649. 

  649. KNN cohens kappa score: 0.010
    650. 

  650. 

  651. 

  652. ------ Step 3/5: Slice 2/5 -------
    653. 

  653. -> Reset the GAN
    654. 

  654. -> Train generator for synthetic samples
    655. 

  655. -> create 1194 synthetic samples
    656. 

  656. -> retrain GAN for predict
    657. 

  657. Epoch 1/10
    658. 

  658. 
  1/124 [..............................] - ETA: 18s - loss: 0.4099
 32/124 [======>.......................] - ETA: 0s - loss: 0.5148 
 70/124 [===============>..............] - ETA: 0s - loss: 0.5185
109/124 [=========================>....] - ETA: 0s - loss: 0.5110
124/124 [==============================] - 0s 1ms/step - loss: 0.5092
    659. 

  659. Epoch 2/10
    660. 

  660. 
  1/124 [..............................] - ETA: 0s - loss: 0.3695
 39/124 [========>.....................] - ETA: 0s - loss: 0.5009
 82/124 [==================>...........] - ETA: 0s - loss: 0.4929
122/124 [============================>.] - ETA: 0s - loss: 0.4958
124/124 [==============================] - 0s 1ms/step - loss: 0.4954
    661. 

  661. Epoch 3/10
    662. 

  662. 
  1/124 [..............................] - ETA: 0s - loss: 0.5073
 42/124 [=========>....................] - ETA: 0s - loss: 0.5170
 83/124 [===================>..........] - ETA: 0s - loss: 0.4998
123/124 [============================>.] - ETA: 0s - loss: 0.4903
124/124 [==============================] - 0s 1ms/step - loss: 0.4897
    663. 

  663. Epoch 4/10
    664. 

  664. 
  1/124 [..............................] - ETA: 0s - loss: 0.5810
 39/124 [========>.....................] - ETA: 0s - loss: 0.4960
 80/124 [==================>...........] - ETA: 0s - loss: 0.4886
122/124 [============================>.] - ETA: 0s - loss: 0.4823
124/124 [==============================] - 0s 1ms/step - loss: 0.4830
    665. 

  665. Epoch 5/10
    666. 

  666. 
  1/124 [..............................] - ETA: 0s - loss: 0.4056
 41/124 [========>.....................] - ETA: 0s - loss: 0.4451
 83/124 [===================>..........] - ETA: 0s - loss: 0.4586
123/124 [============================>.] - ETA: 0s - loss: 0.4650
124/124 [==============================] - 0s 1ms/step - loss: 0.4644
    667. 

  667. Epoch 6/10
    668. 

  668. 
  1/124 [..............................] - ETA: 0s - loss: 0.6202
 41/124 [========>.....................] - ETA: 0s - loss: 0.4816
 83/124 [===================>..........] - ETA: 0s - loss: 0.4676
124/124 [==============================] - 0s 1ms/step - loss: 0.4555
    669. 

  669. Epoch 7/10
    670. 

  670. 
  1/124 [..............................] - ETA: 0s - loss: 0.4692
 42/124 [=========>....................] - ETA: 0s - loss: 0.4404
 82/124 [==================>...........] - ETA: 0s - loss: 0.4542
123/124 [============================>.] - ETA: 0s - loss: 0.4492
124/124 [==============================] - 0s 1ms/step - loss: 0.4482
    671. 

  671. Epoch 8/10
    672. 

  672. 
  1/124 [..............................] - ETA: 0s - loss: 0.3755
 38/124 [========>.....................] - ETA: 0s - loss: 0.4389
 79/124 [==================>...........] - ETA: 0s - loss: 0.4307
120/124 [============================>.] - ETA: 0s - loss: 0.4328
124/124 [==============================] - 0s 1ms/step - loss: 0.4324
    673. 

  673. Epoch 9/10
    674. 

  674. 
  1/124 [..............................] - ETA: 0s - loss: 0.4250
 41/124 [========>.....................] - ETA: 0s - loss: 0.4240
 82/124 [==================>...........] - ETA: 0s - loss: 0.4279
124/124 [==============================] - ETA: 0s - loss: 0.4288
124/124 [==============================] - 0s 1ms/step - loss: 0.4288
    675. 

  675. Epoch 10/10
    676. 

  676. 
  1/124 [..............................] - ETA: 0s - loss: 0.4705
 38/124 [========>.....................] - ETA: 0s - loss: 0.4222
 74/124 [================>.............] - ETA: 0s - loss: 0.4161
111/124 [=========================>....] - ETA: 0s - loss: 0.4209
124/124 [==============================] - 0s 1ms/step - loss: 0.4169
    677. 

  677. -> test with GAN.predict
    678. 

  678. GAN tn, fp: 252, 58
    679. 

  679. GAN fn, tp: 6, 5
    680. 

  680. GAN f1 score: 0.135
    681. 

  681. GAN cohens kappa score: 0.082
    682. 

  682. 

  683. -> test with 'LR'
    684. 

  684. LR tn, fp: 207, 103
    685. 

  685. LR fn, tp: 3, 8
    686. 

  686. LR f1 score: 0.131
    687. 

  687. LR cohens kappa score: 0.073
    688. 

  688. LR average precision score: 0.250
    689. 

  689. 

  690. -> test with 'RF'
    691. 

  691. RF tn, fp: 308, 2
    692. 

  692. RF fn, tp: 9, 2
    693. 

  693. RF f1 score: 0.267
    694. 

  694. RF cohens kappa score: 0.253
    695. 

  695. 

  696. -> test with 'GB'
    697. 

  697. GB tn, fp: 289, 21
    698. 

  698. GB fn, tp: 9, 2
    699. 

  699. GB f1 score: 0.118
    700. 

  700. GB cohens kappa score: 0.075
    701. 

  701. 

  702. -> test with 'KNN'
    703. 

  703. KNN tn, fp: 234, 76
    704. 

  704. KNN fn, tp: 8, 3
    705. 

  705. KNN f1 score: 0.067
    706. 

  706. KNN cohens kappa score: 0.007
    707. 

  707. 

  708. 

  709. ------ Step 3/5: Slice 3/5 -------
    710. 

  710. -> Reset the GAN
    711. 

  711. -> Train generator for synthetic samples
    712. 

  712. -> create 1194 synthetic samples
    713. 

  713. -> retrain GAN for predict
    714. 

  714. Epoch 1/10
    715. 

  715. 
  1/124 [..............................] - ETA: 19s - loss: 0.5794
 43/124 [=========>....................] - ETA: 0s - loss: 0.4860 
 84/124 [===================>..........] - ETA: 0s - loss: 0.4671
120/124 [============================>.] - ETA: 0s - loss: 0.4619
124/124 [==============================] - 0s 1ms/step - loss: 0.4602
    716. 

  716. Epoch 2/10
    717. 

  717. 
  1/124 [..............................] - ETA: 0s - loss: 0.3820
 34/124 [=======>......................] - ETA: 0s - loss: 0.4561
 70/124 [===============>..............] - ETA: 0s - loss: 0.4478
111/124 [=========================>....] - ETA: 0s - loss: 0.4544
124/124 [==============================] - 0s 1ms/step - loss: 0.4530
    718. 

  718. Epoch 3/10
    719. 

  719. 
  1/124 [..............................] - ETA: 0s - loss: 0.3292
 43/124 [=========>....................] - ETA: 0s - loss: 0.4395
 82/124 [==================>...........] - ETA: 0s - loss: 0.4406
122/124 [============================>.] - ETA: 0s - loss: 0.4423
124/124 [==============================] - 0s 1ms/step - loss: 0.4422
    720. 

  720. Epoch 4/10
    721. 

  721. 
  1/124 [..............................] - ETA: 0s - loss: 0.5872
 43/124 [=========>....................] - ETA: 0s - loss: 0.4312
 80/124 [==================>...........] - ETA: 0s - loss: 0.4396
120/124 [============================>.] - ETA: 0s - loss: 0.4381
124/124 [==============================] - 0s 1ms/step - loss: 0.4341
    722. 

  722. Epoch 5/10
    723. 

  723. 
  1/124 [..............................] - ETA: 0s - loss: 0.4594
 40/124 [========>.....................] - ETA: 0s - loss: 0.4377
 81/124 [==================>...........] - ETA: 0s - loss: 0.4278
121/124 [============================>.] - ETA: 0s - loss: 0.4215
124/124 [==============================] - 0s 1ms/step - loss: 0.4227
    724. 

  724. Epoch 6/10
    725. 

  725. 
  1/124 [..............................] - ETA: 0s - loss: 0.6116
 42/124 [=========>....................] - ETA: 0s - loss: 0.4020
 84/124 [===================>..........] - ETA: 0s - loss: 0.4126
124/124 [==============================] - 0s 1ms/step - loss: 0.4145
    726. 

  726. Epoch 7/10
    727. 

  727. 
  1/124 [..............................] - ETA: 0s - loss: 0.4667
 42/124 [=========>....................] - ETA: 0s - loss: 0.3734
 83/124 [===================>..........] - ETA: 0s - loss: 0.3929
124/124 [==============================] - 0s 1ms/step - loss: 0.4031
    728. 

  728. Epoch 8/10
    729. 

  729. 
  1/124 [..............................] - ETA: 0s - loss: 0.4228
 43/124 [=========>....................] - ETA: 0s - loss: 0.3916
 85/124 [===================>..........] - ETA: 0s - loss: 0.3981
124/124 [==============================] - ETA: 0s - loss: 0.4124
124/124 [==============================] - 0s 1ms/step - loss: 0.4124
    730. 

  730. Epoch 9/10
    731. 

  731. 
  1/124 [..............................] - ETA: 0s - loss: 0.3087
 41/124 [========>.....................] - ETA: 0s - loss: 0.4078
 81/124 [==================>...........] - ETA: 0s - loss: 0.4030
120/124 [============================>.] - ETA: 0s - loss: 0.3959
124/124 [==============================] - 0s 1ms/step - loss: 0.3973
    732. 

  732. Epoch 10/10
    733. 

  733. 
  1/124 [..............................] - ETA: 0s - loss: 0.2285
 40/124 [========>.....................] - ETA: 0s - loss: 0.3942
 82/124 [==================>...........] - ETA: 0s - loss: 0.3853
123/124 [============================>.] - ETA: 0s - loss: 0.3847
124/124 [==============================] - 0s 1ms/step - loss: 0.3840
    734. 

  734. -> test with GAN.predict
    735. 

  735. GAN tn, fp: 255, 55
    736. 

  736. GAN fn, tp: 5, 6
    737. 

  737. GAN f1 score: 0.167
    738. 

  738. GAN cohens kappa score: 0.115
    739. 

  739. 

  740. -> test with 'LR'
    741. 

  741. LR tn, fp: 216, 94
    742. 

  742. LR fn, tp: 4, 7
    743. 

  743. LR f1 score: 0.125
    744. 

  744. LR cohens kappa score: 0.067
    745. 

  745. LR average precision score: 0.069
    746. 

  746. 

  747. -> test with 'RF'
    748. 

  748. RF tn, fp: 304, 6
    749. 

  749. RF fn, tp: 11, 0
    750. 

  750. RF f1 score: 0.000
    751. 

  751. RF cohens kappa score: -0.025
    752. 

  752. 

  753. -> test with 'GB'
    754. 

  754. GB tn, fp: 285, 25
    755. 

  755. GB fn, tp: 6, 5
    756. 

  756. GB f1 score: 0.244
    757. 

  757. GB cohens kappa score: 0.204
    758. 

  758. 

  759. -> test with 'KNN'
    760. 

  760. KNN tn, fp: 215, 95
    761. 

  761. KNN fn, tp: 6, 5
    762. 

  762. KNN f1 score: 0.090
    763. 

  763. KNN cohens kappa score: 0.030
    764. 

  764. 

  765. 

  766. ------ Step 3/5: Slice 4/5 -------
    767. 

  767. -> Reset the GAN
    768. 

  768. -> Train generator for synthetic samples
    769. 

  769. -> create 1194 synthetic samples
    770. 

  770. -> retrain GAN for predict
    771. 

  771. Epoch 1/10
    772. 

  772. 
  1/124 [..............................] - ETA: 22s - loss: 0.5451
 39/124 [========>.....................] - ETA: 0s - loss: 0.5032 
 80/124 [==================>...........] - ETA: 0s - loss: 0.4945
120/124 [============================>.] - ETA: 0s - loss: 0.5020
124/124 [==============================] - 0s 1ms/step - loss: 0.5004
    773. 

  773. Epoch 2/10
    774. 

  774. 
  1/124 [..............................] - ETA: 0s - loss: 0.4651
 42/124 [=========>....................] - ETA: 0s - loss: 0.4873
 83/124 [===================>..........] - ETA: 0s - loss: 0.4928
124/124 [==============================] - 0s 1ms/step - loss: 0.4941
    775. 

  775. Epoch 3/10
    776. 

  776. 
  1/124 [..............................] - ETA: 0s - loss: 0.4342
 42/124 [=========>....................] - ETA: 0s - loss: 0.4825
 83/124 [===================>..........] - ETA: 0s - loss: 0.4858
122/124 [============================>.] - ETA: 0s - loss: 0.4811
124/124 [==============================] - 0s 1ms/step - loss: 0.4831
    777. 

  777. Epoch 4/10
    778. 

  778. 
  1/124 [..............................] - ETA: 0s - loss: 0.4544
 43/124 [=========>....................] - ETA: 0s - loss: 0.4678
 82/124 [==================>...........] - ETA: 0s - loss: 0.4816
118/124 [===========================>..] - ETA: 0s - loss: 0.4742
124/124 [==============================] - 0s 1ms/step - loss: 0.4779
    779. 

  779. Epoch 5/10
    780. 

  780. 
  1/124 [..............................] - ETA: 0s - loss: 0.4318
 42/124 [=========>....................] - ETA: 0s - loss: 0.4712
 83/124 [===================>..........] - ETA: 0s - loss: 0.4632
124/124 [==============================] - ETA: 0s - loss: 0.4703
124/124 [==============================] - 0s 1ms/step - loss: 0.4703
    781. 

  781. Epoch 6/10
    782. 

  782. 
  1/124 [..............................] - ETA: 0s - loss: 0.3656
 42/124 [=========>....................] - ETA: 0s - loss: 0.4664
 80/124 [==================>...........] - ETA: 0s - loss: 0.4705
119/124 [===========================>..] - ETA: 0s - loss: 0.4626
124/124 [==============================] - 0s 1ms/step - loss: 0.4623
    783. 

  783. Epoch 7/10
    784. 

  784. 
  1/124 [..............................] - ETA: 0s - loss: 0.5157
 39/124 [========>.....................] - ETA: 0s - loss: 0.4899
 78/124 [=================>............] - ETA: 0s - loss: 0.4710
119/124 [===========================>..] - ETA: 0s - loss: 0.4654
124/124 [==============================] - 0s 1ms/step - loss: 0.4631
    785. 

  785. Epoch 8/10
    786. 

  786. 
  1/124 [..............................] - ETA: 0s - loss: 0.4342
 42/124 [=========>....................] - ETA: 0s - loss: 0.4678
 82/124 [==================>...........] - ETA: 0s - loss: 0.4590
123/124 [============================>.] - ETA: 0s - loss: 0.4546
124/124 [==============================] - 0s 1ms/step - loss: 0.4547
    787. 

  787. Epoch 9/10
    788. 

  788. 
  1/124 [..............................] - ETA: 0s - loss: 0.2405
 42/124 [=========>....................] - ETA: 0s - loss: 0.4707
 82/124 [==================>...........] - ETA: 0s - loss: 0.4657
123/124 [============================>.] - ETA: 0s - loss: 0.4608
124/124 [==============================] - 0s 1ms/step - loss: 0.4605
    789. 

  789. Epoch 10/10
    790. 

  790. 
  1/124 [..............................] - ETA: 0s - loss: 0.5125
 38/124 [========>.....................] - ETA: 0s - loss: 0.4641
 77/124 [=================>............] - ETA: 0s - loss: 0.4590
116/124 [===========================>..] - ETA: 0s - loss: 0.4523
124/124 [==============================] - 0s 1ms/step - loss: 0.4470
    791. 

  791. -> test with GAN.predict
    792. 

  792. GAN tn, fp: 284, 26
    793. 

  793. GAN fn, tp: 8, 3
    794. 

  794. GAN f1 score: 0.150
    795. 

  795. GAN cohens kappa score: 0.106
    796. 

  796. 

  797. -> test with 'LR'
    798. 

  798. LR tn, fp: 201, 109
    799. 

  799. LR fn, tp: 2, 9
    800. 

  800. LR f1 score: 0.140
    801. 

  801. LR cohens kappa score: 0.082
    802. 

  802. LR average precision score: 0.175
    803. 

  803. 

  804. -> test with 'RF'
    805. 

  805. RF tn, fp: 304, 6
    806. 

  806. RF fn, tp: 10, 1
    807. 

  807. RF f1 score: 0.111
    808. 

  808. RF cohens kappa score: 0.087
    809. 

  809. 

  810. -> test with 'GB'
    811. 

  811. GB tn, fp: 287, 23
    812. 

  812. GB fn, tp: 8, 3
    813. 

  813. GB f1 score: 0.162
    814. 

  814. GB cohens kappa score: 0.120
    815. 

  815. 

  816. -> test with 'KNN'
    817. 

  817. KNN tn, fp: 226, 84
    818. 

  818. KNN fn, tp: 6, 5
    819. 

  819. KNN f1 score: 0.100
    820. 

  820. KNN cohens kappa score: 0.042
    821. 

  821. 

  822. 

  823. ------ Step 3/5: Slice 5/5 -------
    824. 

  824. -> Reset the GAN
    825. 

  825. -> Train generator for synthetic samples
    826. 

  826. -> create 1196 synthetic samples
    827. 

  827. -> retrain GAN for predict
    828. 

  828. Epoch 1/10
    829. 

  829. 
  1/124 [..............................] - ETA: 17s - loss: 0.3349
 45/124 [=========>....................] - ETA: 0s - loss: 0.4900 
 89/124 [====================>.........] - ETA: 0s - loss: 0.4795
124/124 [==============================] - 0s 1ms/step - loss: 0.4869
    830. 

  830. Epoch 2/10
    831. 

  831. 
  1/124 [..............................] - ETA: 0s - loss: 0.4777
 45/124 [=========>....................] - ETA: 0s - loss: 0.4872
 89/124 [====================>.........] - ETA: 0s - loss: 0.4825
124/124 [==============================] - 0s 1ms/step - loss: 0.4836
    832. 

  832. Epoch 3/10
    833. 

  833. 
  1/124 [..............................] - ETA: 0s - loss: 0.4119
 43/124 [=========>....................] - ETA: 0s - loss: 0.4672
 87/124 [====================>.........] - ETA: 0s - loss: 0.4668
124/124 [==============================] - 0s 1ms/step - loss: 0.4704
    834. 

  834. Epoch 4/10
    835. 

  835. 
  1/124 [..............................] - ETA: 0s - loss: 0.4512
 46/124 [==========>...................] - ETA: 0s - loss: 0.4587
 91/124 [=====================>........] - ETA: 0s - loss: 0.4624
124/124 [==============================] - 0s 1ms/step - loss: 0.4637
    836. 

  836. Epoch 5/10
    837. 

  837. 
  1/124 [..............................] - ETA: 0s - loss: 0.4339
 45/124 [=========>....................] - ETA: 0s - loss: 0.4720
 89/124 [====================>.........] - ETA: 0s - loss: 0.4593
124/124 [==============================] - 0s 1ms/step - loss: 0.4582
    838. 

  838. Epoch 6/10
    839. 

  839. 
  1/124 [..............................] - ETA: 0s - loss: 0.4705
 38/124 [========>.....................] - ETA: 0s - loss: 0.4535
 73/124 [================>.............] - ETA: 0s - loss: 0.4526
113/124 [==========================>...] - ETA: 0s - loss: 0.4478
124/124 [==============================] - 0s 1ms/step - loss: 0.4486
    840. 

  840. Epoch 7/10
    841. 

  841. 
  1/124 [..............................] - ETA: 0s - loss: 0.4236
 46/124 [==========>...................] - ETA: 0s - loss: 0.4461
 90/124 [====================>.........] - ETA: 0s - loss: 0.4313
124/124 [==============================] - 0s 1ms/step - loss: 0.4388
    842. 

  842. Epoch 8/10
    843. 

  843. 
  1/124 [..............................] - ETA: 0s - loss: 0.4850
 44/124 [=========>....................] - ETA: 0s - loss: 0.4440
 87/124 [====================>.........] - ETA: 0s - loss: 0.4448
124/124 [==============================] - 0s 1ms/step - loss: 0.4459
    844. 

  844. Epoch 9/10
    845. 

  845. 
  1/124 [..............................] - ETA: 0s - loss: 0.4687
 45/124 [=========>....................] - ETA: 0s - loss: 0.3923
 89/124 [====================>.........] - ETA: 0s - loss: 0.4217
124/124 [==============================] - 0s 1ms/step - loss: 0.4328
    846. 

  846. Epoch 10/10
    847. 

  847. 
  1/124 [..............................] - ETA: 0s - loss: 0.4399
 45/124 [=========>....................] - ETA: 0s - loss: 0.4181
 90/124 [====================>.........] - ETA: 0s - loss: 0.4198
124/124 [==============================] - 0s 1ms/step - loss: 0.4222
    848. 

  848. -> test with GAN.predict
    849. 

  849. GAN tn, fp: 223, 83
    850. 

  850. GAN fn, tp: 5, 4
    851. 

  851. GAN f1 score: 0.083
    852. 

  852. GAN cohens kappa score: 0.033
    853. 

  853. 

  854. -> test with 'LR'
    855. 

  855. LR tn, fp: 218, 88
    856. 

  856. LR fn, tp: 2, 7
    857. 

  857. LR f1 score: 0.135
    858. 

  858. LR cohens kappa score: 0.087
    859. 

  859. LR average precision score: 0.112
    860. 

  860. 

  861. -> test with 'RF'
    862. 

  862. RF tn, fp: 300, 6
    863. 

  863. RF fn, tp: 9, 0
    864. 

  864. RF f1 score: 0.000
    865. 

  865. RF cohens kappa score: -0.023
    866. 

  866. 

  867. -> test with 'GB'
    868. 

  868. GB tn, fp: 292, 14
    869. 

  869. GB fn, tp: 7, 2
    870. 

  870. GB f1 score: 0.160
    871. 

  871. GB cohens kappa score: 0.128
    872. 

  872. 

  873. -> test with 'KNN'
    874. 

  874. KNN tn, fp: 230, 76
    875. 

  875. KNN fn, tp: 4, 5
    876. 

  876. KNN f1 score: 0.111
    877. 

  877. KNN cohens kappa score: 0.063
    878. 

  878. 

  879. 

  880. ====== Step 4/5 =======
    881. 

  881. -> Shuffling data
    882. 

  882. -> Spliting data to slices
    883. 

  883. 

  884. ------ Step 4/5: Slice 1/5 -------
    885. 

  885. -> Reset the GAN
    886. 

  886. -> Train generator for synthetic samples
    887. 

  887. -> create 1194 synthetic samples
    888. 

  888. -> retrain GAN for predict
    889. 

  889. Epoch 1/10
    890. 

  890. 
  1/124 [..............................] - ETA: 19s - loss: 0.5251
 41/124 [========>.....................] - ETA: 0s - loss: 0.4714 
 80/124 [==================>...........] - ETA: 0s - loss: 0.4515
121/124 [============================>.] - ETA: 0s - loss: 0.4548
124/124 [==============================] - 0s 1ms/step - loss: 0.4532
    891. 

  891. Epoch 2/10
    892. 

  892. 
  1/124 [..............................] - ETA: 0s - loss: 0.3045
 39/124 [========>.....................] - ETA: 0s - loss: 0.4454
 79/124 [==================>...........] - ETA: 0s - loss: 0.4485
117/124 [===========================>..] - ETA: 0s - loss: 0.4436
124/124 [==============================] - 0s 1ms/step - loss: 0.4439
    893. 

  893. Epoch 3/10
    894. 

  894. 
  1/124 [..............................] - ETA: 0s - loss: 0.3686
 40/124 [========>.....................] - ETA: 0s - loss: 0.4593
 80/124 [==================>...........] - ETA: 0s - loss: 0.4475
120/124 [============================>.] - ETA: 0s - loss: 0.4425
124/124 [==============================] - 0s 1ms/step - loss: 0.4410
    895. 

  895. Epoch 4/10
    896. 

  896. 
  1/124 [..............................] - ETA: 0s - loss: 0.4364
 41/124 [========>.....................] - ETA: 0s - loss: 0.4257
 81/124 [==================>...........] - ETA: 0s - loss: 0.4301
121/124 [============================>.] - ETA: 0s - loss: 0.4331
124/124 [==============================] - 0s 1ms/step - loss: 0.4342
    897. 

  897. Epoch 5/10
    898. 

  898. 
  1/124 [..............................] - ETA: 0s - loss: 0.2828
 40/124 [========>.....................] - ETA: 0s - loss: 0.4254
 80/124 [==================>...........] - ETA: 0s - loss: 0.4238
115/124 [==========================>...] - ETA: 0s - loss: 0.4263
124/124 [==============================] - 0s 1ms/step - loss: 0.4263
    899. 

  899. Epoch 6/10
    900. 

  900. 
  1/124 [..............................] - ETA: 0s - loss: 0.4691
 42/124 [=========>....................] - ETA: 0s - loss: 0.4187
 83/124 [===================>..........] - ETA: 0s - loss: 0.4364
124/124 [==============================] - 0s 1ms/step - loss: 0.4279
    901. 

  901. Epoch 7/10
    902. 

  902. 
  1/124 [..............................] - ETA: 0s - loss: 0.4776
 39/124 [========>.....................] - ETA: 0s - loss: 0.4182
 78/124 [=================>............] - ETA: 0s - loss: 0.4214
120/124 [============================>.] - ETA: 0s - loss: 0.4190
124/124 [==============================] - 0s 1ms/step - loss: 0.4198
    903. 

  903. Epoch 8/10
    904. 

  904. 
  1/124 [..............................] - ETA: 0s - loss: 0.4313
 40/124 [========>.....................] - ETA: 0s - loss: 0.4214
 82/124 [==================>...........] - ETA: 0s - loss: 0.4082
122/124 [============================>.] - ETA: 0s - loss: 0.4079
124/124 [==============================] - 0s 1ms/step - loss: 0.4104
    905. 

  905. Epoch 9/10
    906. 

  906. 
  1/124 [..............................] - ETA: 0s - loss: 0.6001
 42/124 [=========>....................] - ETA: 0s - loss: 0.4051
 83/124 [===================>..........] - ETA: 0s - loss: 0.4122
124/124 [==============================] - 0s 1ms/step - loss: 0.4066
    907. 

  907. Epoch 10/10
    908. 

  908. 
  1/124 [..............................] - ETA: 0s - loss: 0.3171
 41/124 [========>.....................] - ETA: 0s - loss: 0.3820
 81/124 [==================>...........] - ETA: 0s - loss: 0.4042
121/124 [============================>.] - ETA: 0s - loss: 0.4024
124/124 [==============================] - 0s 1ms/step - loss: 0.4008
    909. 

  909. -> test with GAN.predict
    910. 

  910. GAN tn, fp: 213, 97
    911. 

  911. GAN fn, tp: 6, 5
    912. 

  912. GAN f1 score: 0.088
    913. 

  913. GAN cohens kappa score: 0.028
    914. 

  914. 

  915. -> test with 'LR'
    916. 

  916. LR tn, fp: 232, 78
    917. 

  917. LR fn, tp: 2, 9
    918. 

  918. LR f1 score: 0.184
    919. 

  919. LR cohens kappa score: 0.131
    920. 

  920. LR average precision score: 0.425
    921. 

  921. 

  922. -> test with 'RF'
    923. 

  923. RF tn, fp: 310, 0
    924. 

  924. RF fn, tp: 11, 0
    925. 

  925. RF f1 score: 0.000
    926. 

  926. RF cohens kappa score: 0.000
    927. 

  927. 

  928. -> test with 'GB'
    929. 

  929. GB tn, fp: 302, 8
    930. 

  930. GB fn, tp: 10, 1
    931. 

  931. GB f1 score: 0.100
    932. 

  932. GB cohens kappa score: 0.071
    933. 

  933. 

  934. -> test with 'KNN'
    935. 

  935. KNN tn, fp: 232, 78
    936. 

  936. KNN fn, tp: 10, 1
    937. 

  937. KNN f1 score: 0.022
    938. 

  938. KNN cohens kappa score: -0.040
    939. 

  939. 

  940. 

  941. ------ Step 4/5: Slice 2/5 -------
    942. 

  942. -> Reset the GAN
    943. 

  943. -> Train generator for synthetic samples
    944. 

  944. -> create 1194 synthetic samples
    945. 

  945. -> retrain GAN for predict
    946. 

  946. Epoch 1/10
    947. 

  947. 
  1/124 [..............................] - ETA: 21s - loss: 0.5463
 31/124 [======>.......................] - ETA: 0s - loss: 0.4928 
 59/124 [=============>................] - ETA: 0s - loss: 0.4697
 91/124 [=====================>........] - ETA: 0s - loss: 0.4757
124/124 [==============================] - 0s 2ms/step - loss: 0.4713
    948. 

  948. Epoch 2/10
    949. 

  949. 
  1/124 [..............................] - ETA: 0s - loss: 0.4108
 37/124 [=======>......................] - ETA: 0s - loss: 0.4654
 71/124 [================>.............] - ETA: 0s - loss: 0.4669
108/124 [=========================>....] - ETA: 0s - loss: 0.4605
124/124 [==============================] - 0s 1ms/step - loss: 0.4589
    950. 

  950. Epoch 3/10
    951. 

  951. 
  1/124 [..............................] - ETA: 0s - loss: 0.4128
 36/124 [=======>......................] - ETA: 0s - loss: 0.4363
 72/124 [================>.............] - ETA: 0s - loss: 0.4376
107/124 [========================>.....] - ETA: 0s - loss: 0.4489
124/124 [==============================] - 0s 1ms/step - loss: 0.4479
    952. 

  952. Epoch 4/10
    953. 

  953. 
  1/124 [..............................] - ETA: 0s - loss: 0.4766
 42/124 [=========>....................] - ETA: 0s - loss: 0.4304
 78/124 [=================>............] - ETA: 0s - loss: 0.4342
115/124 [==========================>...] - ETA: 0s - loss: 0.4407
124/124 [==============================] - 0s 1ms/step - loss: 0.4391
    954. 

  954. Epoch 5/10
    955. 

  955. 
  1/124 [..............................] - ETA: 0s - loss: 0.3944
 37/124 [=======>......................] - ETA: 0s - loss: 0.4170
 74/124 [================>.............] - ETA: 0s - loss: 0.4324
110/124 [=========================>....] - ETA: 0s - loss: 0.4236
124/124 [==============================] - 0s 1ms/step - loss: 0.4289
    956. 

  956. Epoch 6/10
    957. 

  957. 
  1/124 [..............................] - ETA: 0s - loss: 0.2762
 37/124 [=======>......................] - ETA: 0s - loss: 0.4368
 72/124 [================>.............] - ETA: 0s - loss: 0.4113
108/124 [=========================>....] - ETA: 0s - loss: 0.4178
124/124 [==============================] - 0s 1ms/step - loss: 0.4227
    958. 

  958. Epoch 7/10
    959. 

  959. 
  1/124 [..............................] - ETA: 0s - loss: 0.3356
 39/124 [========>.....................] - ETA: 0s - loss: 0.4145
 80/124 [==================>...........] - ETA: 0s - loss: 0.4180
116/124 [===========================>..] - ETA: 0s - loss: 0.4132
124/124 [==============================] - 0s 1ms/step - loss: 0.4138
    960. 

  960. Epoch 8/10
    961. 

  961. 
  1/124 [..............................] - ETA: 0s - loss: 0.4271
 34/124 [=======>......................] - ETA: 0s - loss: 0.4169
 70/124 [===============>..............] - ETA: 0s - loss: 0.4074
106/124 [========================>.....] - ETA: 0s - loss: 0.4080
124/124 [==============================] - 0s 1ms/step - loss: 0.4131
    962. 

  962. Epoch 9/10
    963. 

  963. 
  1/124 [..............................] - ETA: 0s - loss: 0.2345
 36/124 [=======>......................] - ETA: 0s - loss: 0.4035
 72/124 [================>.............] - ETA: 0s - loss: 0.4068
110/124 [=========================>....] - ETA: 0s - loss: 0.4150
124/124 [==============================] - 0s 1ms/step - loss: 0.4169
    964. 

  964. Epoch 10/10
    965. 

  965. 
  1/124 [..............................] - ETA: 0s - loss: 0.3635
 40/124 [========>.....................] - ETA: 0s - loss: 0.4030
 80/124 [==================>...........] - ETA: 0s - loss: 0.4166
121/124 [============================>.] - ETA: 0s - loss: 0.4047
124/124 [==============================] - 0s 1ms/step - loss: 0.4016
    966. 

  966. -> test with GAN.predict
    967. 

  967. GAN tn, fp: 221, 89
    968. 

  968. GAN fn, tp: 5, 6
    969. 

  969. GAN f1 score: 0.113
    970. 

  970. GAN cohens kappa score: 0.055
    971. 

  971. 

  972. -> test with 'LR'
    973. 

  973. LR tn, fp: 219, 91
    974. 

  974. LR fn, tp: 3, 8
    975. 

  975. LR f1 score: 0.145
    976. 

  976. LR cohens kappa score: 0.089
    977. 

  977. LR average precision score: 0.169
    978. 

  978. 

  979. -> test with 'RF'
    980. 

  980. RF tn, fp: 308, 2
    981. 

  981. RF fn, tp: 10, 1
    982. 

  982. RF f1 score: 0.143
    983. 

  983. RF cohens kappa score: 0.130
    984. 

  984. 

  985. -> test with 'GB'
    986. 

  986. GB tn, fp: 290, 20
    987. 

  987. GB fn, tp: 9, 2
    988. 

  988. GB f1 score: 0.121
    989. 

  989. GB cohens kappa score: 0.079
    990. 

  990. 

  991. -> test with 'KNN'
    992. 

  992. KNN tn, fp: 217, 93
    993. 

  993. KNN fn, tp: 6, 5
    994. 

  994. KNN f1 score: 0.092
    995. 

  995. KNN cohens kappa score: 0.032
    996. 

  996. 

  997. 

  998. ------ Step 4/5: Slice 3/5 -------
    999. 

  999. -> Reset the GAN
    1000. 

  1000. -> Train generator for synthetic samples
    1001. 

  1001. -> create 1194 synthetic samples
    1002. 

  1002. -> retrain GAN for predict
    1003. 

  1003. Epoch 1/10
    1004. 

  1004. 
  1/124 [..............................] - ETA: 19s - loss: 0.3159
 42/124 [=========>....................] - ETA: 0s - loss: 0.4546 
 83/124 [===================>..........] - ETA: 0s - loss: 0.4525
124/124 [==============================] - 0s 1ms/step - loss: 0.4483
    1005. 

  1005. Epoch 2/10
    1006. 

  1006. 
  1/124 [..............................] - ETA: 0s - loss: 0.4277
 41/124 [========>.....................] - ETA: 0s - loss: 0.4449
 75/124 [=================>............] - ETA: 0s - loss: 0.4478
114/124 [==========================>...] - ETA: 0s - loss: 0.4413
124/124 [==============================] - 0s 1ms/step - loss: 0.4384
    1007. 

  1007. Epoch 3/10
    1008. 

  1008. 
  1/124 [..............................] - ETA: 0s - loss: 0.5316
 42/124 [=========>....................] - ETA: 0s - loss: 0.4492
 81/124 [==================>...........] - ETA: 0s - loss: 0.4476
122/124 [============================>.] - ETA: 0s - loss: 0.4408
124/124 [==============================] - 0s 1ms/step - loss: 0.4410
    1009. 

  1009. Epoch 4/10
    1010. 

  1010. 
  1/124 [..............................] - ETA: 0s - loss: 0.3926
 42/124 [=========>....................] - ETA: 0s - loss: 0.4227
 81/124 [==================>...........] - ETA: 0s - loss: 0.4259
121/124 [============================>.] - ETA: 0s - loss: 0.4278
124/124 [==============================] - 0s 1ms/step - loss: 0.4297
    1011. 

  1011. Epoch 5/10
    1012. 

  1012. 
  1/124 [..............................] - ETA: 0s - loss: 0.5201
 42/124 [=========>....................] - ETA: 0s - loss: 0.3934
 83/124 [===================>..........] - ETA: 0s - loss: 0.4209
120/124 [============================>.] - ETA: 0s - loss: 0.4226
124/124 [==============================] - 0s 1ms/step - loss: 0.4231
    1013. 

  1013. Epoch 6/10
    1014. 

  1014. 
  1/124 [..............................] - ETA: 0s - loss: 0.2823
 42/124 [=========>....................] - ETA: 0s - loss: 0.4034
 77/124 [=================>............] - ETA: 0s - loss: 0.4297
109/124 [=========================>....] - ETA: 0s - loss: 0.4165
124/124 [==============================] - 0s 1ms/step - loss: 0.4149
    1015. 

  1015. Epoch 7/10
    1016. 

  1016. 
  1/124 [..............................] - ETA: 0s - loss: 0.4866
 37/124 [=======>......................] - ETA: 0s - loss: 0.4178
 76/124 [=================>............] - ETA: 0s - loss: 0.4160
116/124 [===========================>..] - ETA: 0s - loss: 0.4182
124/124 [==============================] - 0s 1ms/step - loss: 0.4166
    1017. 

  1017. Epoch 8/10
    1018. 

  1018. 
  1/124 [..............................] - ETA: 0s - loss: 0.3353
 40/124 [========>.....................] - ETA: 0s - loss: 0.4060
 79/124 [==================>...........] - ETA: 0s - loss: 0.4066
116/124 [===========================>..] - ETA: 0s - loss: 0.4103
124/124 [==============================] - 0s 1ms/step - loss: 0.4114
    1019. 

  1019. Epoch 9/10
    1020. 

  1020. 
  1/124 [..............................] - ETA: 0s - loss: 0.4455
 41/124 [========>.....................] - ETA: 0s - loss: 0.3867
 82/124 [==================>...........] - ETA: 0s - loss: 0.3983
124/124 [==============================] - ETA: 0s - loss: 0.4055
124/124 [==============================] - 0s 1ms/step - loss: 0.4055
    1021. 

  1021. Epoch 10/10
    1022. 

  1022. 
  1/124 [..............................] - ETA: 0s - loss: 0.3887
 41/124 [========>.....................] - ETA: 0s - loss: 0.4129
 82/124 [==================>...........] - ETA: 0s - loss: 0.3974
123/124 [============================>.] - ETA: 0s - loss: 0.3988
124/124 [==============================] - 0s 1ms/step - loss: 0.3992
    1023. 

  1023. -> test with GAN.predict
    1024. 

  1024. GAN tn, fp: 261, 49
    1025. 

  1025. GAN fn, tp: 8, 3
    1026. 

  1026. GAN f1 score: 0.095
    1027. 

  1027. GAN cohens kappa score: 0.041
    1028. 

  1028. 

  1029. -> test with 'LR'
    1030. 

  1030. LR tn, fp: 224, 86
    1031. 

  1031. LR fn, tp: 5, 6
    1032. 

  1032. LR f1 score: 0.117
    1033. 

  1033. LR cohens kappa score: 0.059
    1034. 

  1034. LR average precision score: 0.103
    1035. 

  1035. 

  1036. -> test with 'RF'
    1037. 

  1037. RF tn, fp: 306, 4
    1038. 

  1038. RF fn, tp: 10, 1
    1039. 

  1039. RF f1 score: 0.125
    1040. 

  1040. RF cohens kappa score: 0.106
    1041. 

  1041. 

  1042. -> test with 'GB'
    1043. 

  1043. GB tn, fp: 292, 18
    1044. 

  1044. GB fn, tp: 9, 2
    1045. 

  1045. GB f1 score: 0.129
    1046. 

  1046. GB cohens kappa score: 0.089
    1047. 

  1047. 

  1048. -> test with 'KNN'
    1049. 

  1049. KNN tn, fp: 235, 75
    1050. 

  1050. KNN fn, tp: 9, 2
    1051. 

  1051. KNN f1 score: 0.045
    1052. 

  1052. KNN cohens kappa score: -0.015
    1053. 

  1053. 

  1054. 

  1055. ------ Step 4/5: Slice 4/5 -------
    1056. 

  1056. -> Reset the GAN
    1057. 

  1057. -> Train generator for synthetic samples
    1058. 

  1058. -> create 1194 synthetic samples
    1059. 

  1059. -> retrain GAN for predict
    1060. 

  1060. Epoch 1/10
    1061. 

  1061. 
  1/124 [..............................] - ETA: 21s - loss: 0.6430
 38/124 [========>.....................] - ETA: 0s - loss: 0.4793 
 74/124 [================>.............] - ETA: 0s - loss: 0.4828
111/124 [=========================>....] - ETA: 0s - loss: 0.4825
124/124 [==============================] - 0s 1ms/step - loss: 0.4854
    1062. 

  1062. Epoch 2/10
    1063. 

  1063. 
  1/124 [..............................] - ETA: 0s - loss: 0.5221
 42/124 [=========>....................] - ETA: 0s - loss: 0.4736
 81/124 [==================>...........] - ETA: 0s - loss: 0.4824
118/124 [===========================>..] - ETA: 0s - loss: 0.4728
124/124 [==============================] - 0s 1ms/step - loss: 0.4724
    1064. 

  1064. Epoch 3/10
    1065. 

  1065. 
  1/124 [..............................] - ETA: 0s - loss: 0.4503
 41/124 [========>.....................] - ETA: 0s - loss: 0.4677
 83/124 [===================>..........] - ETA: 0s - loss: 0.4706
120/124 [============================>.] - ETA: 0s - loss: 0.4648
124/124 [==============================] - 0s 1ms/step - loss: 0.4642
    1066. 

  1066. Epoch 4/10
    1067. 

  1067. 
  1/124 [..............................] - ETA: 0s - loss: 0.4857
 39/124 [========>.....................] - ETA: 0s - loss: 0.4317
 80/124 [==================>...........] - ETA: 0s - loss: 0.4519
122/124 [============================>.] - ETA: 0s - loss: 0.4618
124/124 [==============================] - 0s 1ms/step - loss: 0.4623
    1068. 

  1068. Epoch 5/10
    1069. 

  1069. 
  1/124 [..............................] - ETA: 0s - loss: 0.4105
 40/124 [========>.....................] - ETA: 0s - loss: 0.4494
 82/124 [==================>...........] - ETA: 0s - loss: 0.4457
121/124 [============================>.] - ETA: 0s - loss: 0.4541
124/124 [==============================] - 0s 1ms/step - loss: 0.4550
    1070. 

  1070. Epoch 6/10
    1071. 

  1071. 
  1/124 [..............................] - ETA: 0s - loss: 0.3197
 41/124 [========>.....................] - ETA: 0s - loss: 0.4502
 84/124 [===================>..........] - ETA: 0s - loss: 0.4505
124/124 [==============================] - 0s 1ms/step - loss: 0.4489
    1072. 

  1072. Epoch 7/10
    1073. 

  1073. 
  1/124 [..............................] - ETA: 0s - loss: 0.4770
 39/124 [========>.....................] - ETA: 0s - loss: 0.4604
 81/124 [==================>...........] - ETA: 0s - loss: 0.4516
121/124 [============================>.] - ETA: 0s - loss: 0.4475
124/124 [==============================] - 0s 1ms/step - loss: 0.4469
    1074. 

  1074. Epoch 8/10
    1075. 

  1075. 
  1/124 [..............................] - ETA: 0s - loss: 0.4695
 41/124 [========>.....................] - ETA: 0s - loss: 0.4409
 81/124 [==================>...........] - ETA: 0s - loss: 0.4453
121/124 [============================>.] - ETA: 0s - loss: 0.4467
124/124 [==============================] - 0s 1ms/step - loss: 0.4456
    1076. 

  1076. Epoch 9/10
    1077. 

  1077. 
  1/124 [..............................] - ETA: 0s - loss: 0.5161
 41/124 [========>.....................] - ETA: 0s - loss: 0.4475
 81/124 [==================>...........] - ETA: 0s - loss: 0.4471
123/124 [============================>.] - ETA: 0s - loss: 0.4413
124/124 [==============================] - 0s 1ms/step - loss: 0.4407
    1078. 

  1078. Epoch 10/10
    1079. 

  1079. 
  1/124 [..............................] - ETA: 0s - loss: 0.5095
 43/124 [=========>....................] - ETA: 0s - loss: 0.4528
 84/124 [===================>..........] - ETA: 0s - loss: 0.4502
124/124 [==============================] - 0s 1ms/step - loss: 0.4420
    1080. 

  1080. -> test with GAN.predict
    1081. 

  1081. GAN tn, fp: 230, 80
    1082. 

  1082. GAN fn, tp: 4, 7
    1083. 

  1083. GAN f1 score: 0.143
    1084. 

  1084. GAN cohens kappa score: 0.087
    1085. 

  1085. 

  1086. -> test with 'LR'
    1087. 

  1087. LR tn, fp: 218, 92
    1088. 

  1088. LR fn, tp: 1, 10
    1089. 

  1089. LR f1 score: 0.177
    1090. 

  1090. LR cohens kappa score: 0.123
    1091. 

  1091. LR average precision score: 0.129
    1092. 

  1092. 

  1093. -> test with 'RF'
    1094. 

  1094. RF tn, fp: 307, 3
    1095. 

  1095. RF fn, tp: 9, 2
    1096. 

  1096. RF f1 score: 0.250
    1097. 

  1097. RF cohens kappa score: 0.234
    1098. 

  1098. 

  1099. -> test with 'GB'
    1100. 

  1100. GB tn, fp: 290, 20
    1101. 

  1101. GB fn, tp: 5, 6
    1102. 

  1102. GB f1 score: 0.324
    1103. 

  1103. GB cohens kappa score: 0.290
    1104. 

  1104. 

  1105. -> test with 'KNN'
    1106. 

  1106. KNN tn, fp: 226, 84
    1107. 

  1107. KNN fn, tp: 7, 4
    1108. 

  1108. KNN f1 score: 0.081
    1109. 

  1109. KNN cohens kappa score: 0.021
    1110. 

  1110. 

  1111. 

  1112. ------ Step 4/5: Slice 5/5 -------
    1113. 

  1113. -> Reset the GAN
    1114. 

  1114. -> Train generator for synthetic samples
    1115. 

  1115. -> create 1196 synthetic samples
    1116. 

  1116. -> retrain GAN for predict
    1117. 

  1117. Epoch 1/10
    1118. 

  1118. 
  1/124 [..............................] - ETA: 15s - loss: 0.3286
 44/124 [=========>....................] - ETA: 0s - loss: 0.4438 
 88/124 [====================>.........] - ETA: 0s - loss: 0.4568
124/124 [==============================] - 0s 1ms/step - loss: 0.4540
    1119. 

  1119. Epoch 2/10
    1120. 

  1120. 
  1/124 [..............................] - ETA: 0s - loss: 0.3396
 42/124 [=========>....................] - ETA: 0s - loss: 0.4382
 83/124 [===================>..........] - ETA: 0s - loss: 0.4422
124/124 [==============================] - 0s 1ms/step - loss: 0.4401
    1121. 

  1121. Epoch 3/10
    1122. 

  1122. 
  1/124 [..............................] - ETA: 0s - loss: 0.4587
 44/124 [=========>....................] - ETA: 0s - loss: 0.4369
 86/124 [===================>..........] - ETA: 0s - loss: 0.4306
124/124 [==============================] - 0s 1ms/step - loss: 0.4331
    1123. 

  1123. Epoch 4/10
    1124. 

  1124. 
  1/124 [..............................] - ETA: 0s - loss: 0.4076
 46/124 [==========>...................] - ETA: 0s - loss: 0.4265
 90/124 [====================>.........] - ETA: 0s - loss: 0.4172
124/124 [==============================] - 0s 1ms/step - loss: 0.4212
    1125. 

  1125. Epoch 5/10
    1126. 

  1126. 
  1/124 [..............................] - ETA: 0s - loss: 0.3678
 46/124 [==========>...................] - ETA: 0s - loss: 0.4101
 89/124 [====================>.........] - ETA: 0s - loss: 0.4107
124/124 [==============================] - 0s 1ms/step - loss: 0.4117
    1127. 

  1127. Epoch 6/10
    1128. 

  1128. 
  1/124 [..............................] - ETA: 0s - loss: 0.4722
 45/124 [=========>....................] - ETA: 0s - loss: 0.4299
 89/124 [====================>.........] - ETA: 0s - loss: 0.4163
124/124 [==============================] - 0s 1ms/step - loss: 0.4167
    1129. 

  1129. Epoch 7/10
    1130. 

  1130. 
  1/124 [..............................] - ETA: 0s - loss: 0.4754
 46/124 [==========>...................] - ETA: 0s - loss: 0.3970
 89/124 [====================>.........] - ETA: 0s - loss: 0.4068
124/124 [==============================] - 0s 1ms/step - loss: 0.3970
    1131. 

  1131. Epoch 8/10
    1132. 

  1132. 
  1/124 [..............................] - ETA: 0s - loss: 0.2678
 46/124 [==========>...................] - ETA: 0s - loss: 0.3783
 91/124 [=====================>........] - ETA: 0s - loss: 0.3874
124/124 [==============================] - 0s 1ms/step - loss: 0.3909
    1133. 

  1133. Epoch 9/10
    1134. 

  1134. 
  1/124 [..............................] - ETA: 0s - loss: 0.3500
 44/124 [=========>....................] - ETA: 0s - loss: 0.3837
 84/124 [===================>..........] - ETA: 0s - loss: 0.3770
124/124 [==============================] - 0s 1ms/step - loss: 0.3822
    1135. 

  1135. Epoch 10/10
    1136. 

  1136. 
  1/124 [..............................] - ETA: 0s - loss: 0.5491
 36/124 [=======>......................] - ETA: 0s - loss: 0.3768
 72/124 [================>.............] - ETA: 0s - loss: 0.3864
108/124 [=========================>....] - ETA: 0s - loss: 0.3771
124/124 [==============================] - 0s 1ms/step - loss: 0.3714
    1137. 

  1137. -> test with GAN.predict
    1138. 

  1138. GAN tn, fp: 254, 52
    1139. 

  1139. GAN fn, tp: 7, 2
    1140. 

  1140. GAN f1 score: 0.063
    1141. 

  1141. GAN cohens kappa score: 0.015
    1142. 

  1142. 

  1143. -> test with 'LR'
    1144. 

  1144. LR tn, fp: 207, 99
    1145. 

  1145. LR fn, tp: 5, 4
    1146. 

  1146. LR f1 score: 0.071
    1147. 

  1147. LR cohens kappa score: 0.020
    1148. 

  1148. LR average precision score: 0.058
    1149. 

  1149. 

  1150. -> test with 'RF'
    1151. 

  1151. RF tn, fp: 298, 8
    1152. 

  1152. RF fn, tp: 9, 0
    1153. 

  1153. RF f1 score: 0.000
    1154. 

  1154. RF cohens kappa score: -0.028
    1155. 

  1155. 

  1156. -> test with 'GB'
    1157. 

  1157. GB tn, fp: 277, 29
    1158. 

  1158. GB fn, tp: 8, 1
    1159. 

  1159. GB f1 score: 0.051
    1160. 

  1160. GB cohens kappa score: 0.008
    1161. 

  1161. 

  1162. -> test with 'KNN'
    1163. 

  1163. KNN tn, fp: 229, 77
    1164. 

  1164. KNN fn, tp: 7, 2
    1165. 

  1165. KNN f1 score: 0.045
    1166. 

  1166. KNN cohens kappa score: -0.006
    1167. 

  1167. 

  1168. 

  1169. ====== Step 5/5 =======
    1170. 

  1170. -> Shuffling data
    1171. 

  1171. -> Spliting data to slices
    1172. 

  1172. 

  1173. ------ Step 5/5: Slice 1/5 -------
    1174. 

  1174. -> Reset the GAN
    1175. 

  1175. -> Train generator for synthetic samples
    1176. 

  1176. -> create 1194 synthetic samples
    1177. 

  1177. -> retrain GAN for predict
    1178. 

  1178. Epoch 1/10
    1179. 

  1179. 
  1/124 [..............................] - ETA: 22s - loss: 0.3215
 42/124 [=========>....................] - ETA: 0s - loss: 0.4300 
 84/124 [===================>..........] - ETA: 0s - loss: 0.4363
124/124 [==============================] - ETA: 0s - loss: 0.4188
124/124 [==============================] - 0s 1ms/step - loss: 0.4188
    1180. 

  1180. Epoch 2/10
    1181. 

  1181. 
  1/124 [..............................] - ETA: 0s - loss: 0.3146
 43/124 [=========>....................] - ETA: 0s - loss: 0.4283
 84/124 [===================>..........] - ETA: 0s - loss: 0.4147
124/124 [==============================] - ETA: 0s - loss: 0.4063
124/124 [==============================] - 0s 1ms/step - loss: 0.4063
    1182. 

  1182. Epoch 3/10
    1183. 

  1183. 
  1/124 [..............................] - ETA: 0s - loss: 0.4156
 41/124 [========>.....................] - ETA: 0s - loss: 0.3940
 77/124 [=================>............] - ETA: 0s - loss: 0.3987
112/124 [==========================>...] - ETA: 0s - loss: 0.3983
124/124 [==============================] - 0s 1ms/step - loss: 0.3972
    1184. 

  1184. Epoch 4/10
    1185. 

  1185. 
  1/124 [..............................] - ETA: 0s - loss: 0.3600
 38/124 [========>.....................] - ETA: 0s - loss: 0.3929
 78/124 [=================>............] - ETA: 0s - loss: 0.3870
118/124 [===========================>..] - ETA: 0s - loss: 0.3919
124/124 [==============================] - 0s 1ms/step - loss: 0.3922
    1186. 

  1186. Epoch 5/10
    1187. 

  1187. 
  1/124 [..............................] - ETA: 0s - loss: 0.3682
 41/124 [========>.....................] - ETA: 0s - loss: 0.3950
 81/124 [==================>...........] - ETA: 0s - loss: 0.3899
122/124 [============================>.] - ETA: 0s - loss: 0.3830
124/124 [==============================] - 0s 1ms/step - loss: 0.3827
    1188. 

  1188. Epoch 6/10
    1189. 

  1189. 
  1/124 [..............................] - ETA: 0s - loss: 0.3401
 42/124 [=========>....................] - ETA: 0s - loss: 0.3741
 83/124 [===================>..........] - ETA: 0s - loss: 0.3669
124/124 [==============================] - ETA: 0s - loss: 0.3785
124/124 [==============================] - 0s 1ms/step - loss: 0.3785
    1190. 

  1190. Epoch 7/10
    1191. 

  1191. 
  1/124 [..............................] - ETA: 0s - loss: 0.3296
 39/124 [========>.....................] - ETA: 0s - loss: 0.3539
 81/124 [==================>...........] - ETA: 0s - loss: 0.3649
121/124 [============================>.] - ETA: 0s - loss: 0.3767
124/124 [==============================] - 0s 1ms/step - loss: 0.3772
    1192. 

  1192. Epoch 8/10
    1193. 

  1193. 
  1/124 [..............................] - ETA: 0s - loss: 0.3929
 42/124 [=========>....................] - ETA: 0s - loss: 0.3640
 84/124 [===================>..........] - ETA: 0s - loss: 0.3706
123/124 [============================>.] - ETA: 0s - loss: 0.3658
124/124 [==============================] - 0s 1ms/step - loss: 0.3652
    1194. 

  1194. Epoch 9/10
    1195. 

  1195. 
  1/124 [..............................] - ETA: 0s - loss: 0.3761
 43/124 [=========>....................] - ETA: 0s - loss: 0.3479
 85/124 [===================>..........] - ETA: 0s - loss: 0.3605
124/124 [==============================] - 0s 1ms/step - loss: 0.3588
    1196. 

  1196. Epoch 10/10
    1197. 

  1197. 
  1/124 [..............................] - ETA: 0s - loss: 0.2519
 40/124 [========>.....................] - ETA: 0s - loss: 0.3430
 81/124 [==================>...........] - ETA: 0s - loss: 0.3586
123/124 [============================>.] - ETA: 0s - loss: 0.3576
124/124 [==============================] - 0s 1ms/step - loss: 0.3581
    1198. 

  1198. -> test with GAN.predict
    1199. 

  1199. GAN tn, fp: 250, 60
    1200. 

  1200. GAN fn, tp: 8, 3
    1201. 

  1201. GAN f1 score: 0.081
    1202. 

  1202. GAN cohens kappa score: 0.024
    1203. 

  1203. 

  1204. -> test with 'LR'
    1205. 

  1205. LR tn, fp: 239, 71
    1206. 

  1206. LR fn, tp: 5, 6
    1207. 

  1207. LR f1 score: 0.136
    1208. 

  1208. LR cohens kappa score: 0.081
    1209. 

  1209. LR average precision score: 0.081
    1210. 

  1210. 

  1211. -> test with 'RF'
    1212. 

  1212. RF tn, fp: 306, 4
    1213. 

  1213. RF fn, tp: 11, 0
    1214. 

  1214. RF f1 score: 0.000
    1215. 

  1215. RF cohens kappa score: -0.019
    1216. 

  1216. 

  1217. -> test with 'GB'
    1218. 

  1218. GB tn, fp: 293, 17
    1219. 

  1219. GB fn, tp: 9, 2
    1220. 

  1220. GB f1 score: 0.133
    1221. 

  1221. GB cohens kappa score: 0.094
    1222. 

  1222. 

  1223. -> test with 'KNN'
    1224. 

  1224. KNN tn, fp: 237, 73
    1225. 

  1225. KNN fn, tp: 7, 4
    1226. 

  1226. KNN f1 score: 0.091
    1227. 

  1227. KNN cohens kappa score: 0.033
    1228. 

  1228. 

  1229. 

  1230. ------ Step 5/5: Slice 2/5 -------
    1231. 

  1231. -> Reset the GAN
    1232. 

  1232. -> Train generator for synthetic samples
    1233. 

  1233. -> create 1194 synthetic samples
    1234. 

  1234. -> retrain GAN for predict
    1235. 

  1235. Epoch 1/10
    1236. 

  1236. 
  1/124 [..............................] - ETA: 21s - loss: 0.5277
 37/124 [=======>......................] - ETA: 0s - loss: 0.4325 
 73/124 [================>.............] - ETA: 0s - loss: 0.4423
111/124 [=========================>....] - ETA: 0s - loss: 0.4367
124/124 [==============================] - 0s 1ms/step - loss: 0.4392
    1237. 

  1237. Epoch 2/10
    1238. 

  1238. 
  1/124 [..............................] - ETA: 0s - loss: 0.5615
 31/124 [======>.......................] - ETA: 0s - loss: 0.4341
 58/124 [=============>................] - ETA: 0s - loss: 0.4189
 87/124 [====================>.........] - ETA: 0s - loss: 0.4287
123/124 [============================>.] - ETA: 0s - loss: 0.4298
124/124 [==============================] - 0s 2ms/step - loss: 0.4294
    1239. 

  1239. Epoch 3/10
    1240. 

  1240. 
  1/124 [..............................] - ETA: 0s - loss: 0.5084
 37/124 [=======>......................] - ETA: 0s - loss: 0.4423
 73/124 [================>.............] - ETA: 0s - loss: 0.4253
109/124 [=========================>....] - ETA: 0s - loss: 0.4217
124/124 [==============================] - 0s 1ms/step - loss: 0.4241
    1241. 

  1241. Epoch 4/10
    1242. 

  1242. 
  1/124 [..............................] - ETA: 0s - loss: 0.3853
 37/124 [=======>......................] - ETA: 0s - loss: 0.4186
 70/124 [===============>..............] - ETA: 0s - loss: 0.4193
106/124 [========================>.....] - ETA: 0s - loss: 0.4182
124/124 [==============================] - 0s 1ms/step - loss: 0.4150
    1243. 

  1243. Epoch 5/10
    1244. 

  1244. 
  1/124 [..............................] - ETA: 0s - loss: 0.4326
 37/124 [=======>......................] - ETA: 0s - loss: 0.4141
 72/124 [================>.............] - ETA: 0s - loss: 0.4048
108/124 [=========================>....] - ETA: 0s - loss: 0.4049
124/124 [==============================] - 0s 1ms/step - loss: 0.4069
    1245. 

  1245. Epoch 6/10
    1246. 

  1246. 
  1/124 [..............................] - ETA: 0s - loss: 0.3504
 37/124 [=======>......................] - ETA: 0s - loss: 0.4209
 72/124 [================>.............] - ETA: 0s - loss: 0.4040
106/124 [========================>.....] - ETA: 0s - loss: 0.4068
124/124 [==============================] - 0s 1ms/step - loss: 0.4039
    1247. 

  1247. Epoch 7/10
    1248. 

  1248. 
  1/124 [..............................] - ETA: 0s - loss: 0.3872
 37/124 [=======>......................] - ETA: 0s - loss: 0.3952
 73/124 [================>.............] - ETA: 0s - loss: 0.3920
109/124 [=========================>....] - ETA: 0s - loss: 0.3962
124/124 [==============================] - 0s 1ms/step - loss: 0.4003
    1249. 

  1249. Epoch 8/10
    1250. 

  1250. 
  1/124 [..............................] - ETA: 0s - loss: 0.4001
 35/124 [=======>......................] - ETA: 0s - loss: 0.3819
 70/124 [===============>..............] - ETA: 0s - loss: 0.3839
106/124 [========================>.....] - ETA: 0s - loss: 0.3895
124/124 [==============================] - 0s 1ms/step - loss: 0.3879
    1251. 

  1251. Epoch 9/10
    1252. 

  1252. 
  1/124 [..............................] - ETA: 0s - loss: 0.2892
 36/124 [=======>......................] - ETA: 0s - loss: 0.3858
 71/124 [================>.............] - ETA: 0s - loss: 0.3864
108/124 [=========================>....] - ETA: 0s - loss: 0.3801
124/124 [==============================] - 0s 1ms/step - loss: 0.3822
    1253. 

  1253. Epoch 10/10
    1254. 

  1254. 
  1/124 [..............................] - ETA: 0s - loss: 0.4556
 35/124 [=======>......................] - ETA: 0s - loss: 0.4066
 70/124 [===============>..............] - ETA: 0s - loss: 0.3811
105/124 [========================>.....] - ETA: 0s - loss: 0.3834
124/124 [==============================] - 0s 1ms/step - loss: 0.3801
    1255. 

  1255. -> test with GAN.predict
    1256. 

  1256. GAN tn, fp: 217, 93
    1257. 

  1257. GAN fn, tp: 6, 5
    1258. 

  1258. GAN f1 score: 0.092
    1259. 

  1259. GAN cohens kappa score: 0.032
    1260. 

  1260. 

  1261. -> test with 'LR'
    1262. 

  1262. LR tn, fp: 217, 93
    1263. 

  1263. LR fn, tp: 5, 6
    1264. 

  1264. LR f1 score: 0.109
    1265. 

  1265. LR cohens kappa score: 0.051
    1266. 

  1266. LR average precision score: 0.102
    1267. 

  1267. 

  1268. -> test with 'RF'
    1269. 

  1269. RF tn, fp: 301, 9
    1270. 

  1270. RF fn, tp: 11, 0
    1271. 

  1271. RF f1 score: 0.000
    1272. 

  1272. RF cohens kappa score: -0.032
    1273. 

  1273. 

  1274. -> test with 'GB'
    1275. 

  1275. GB tn, fp: 287, 23
    1276. 

  1276. GB fn, tp: 9, 2
    1277. 

  1277. GB f1 score: 0.111
    1278. 

  1278. GB cohens kappa score: 0.067
    1279. 

  1279. 

  1280. -> test with 'KNN'
    1281. 

  1281. KNN tn, fp: 204, 106
    1282. 

  1282. KNN fn, tp: 7, 4
    1283. 

  1283. KNN f1 score: 0.066
    1284. 

  1284. KNN cohens kappa score: 0.004
    1285. 

  1285. 

  1286. 

  1287. ------ Step 5/5: Slice 3/5 -------
    1288. 

  1288. -> Reset the GAN
    1289. 

  1289. -> Train generator for synthetic samples
    1290. 

  1290. -> create 1194 synthetic samples
    1291. 

  1291. -> retrain GAN for predict
    1292. 

  1292. Epoch 1/10
    1293. 

  1293. 
  1/124 [..............................] - ETA: 19s - loss: 0.3672
 40/124 [========>.....................] - ETA: 0s - loss: 0.4563 
 81/124 [==================>...........] - ETA: 0s - loss: 0.4543
123/124 [============================>.] - ETA: 0s - loss: 0.4518
124/124 [==============================] - 0s 1ms/step - loss: 0.4515
    1294. 

  1294. Epoch 2/10
    1295. 

  1295. 
  1/124 [..............................] - ETA: 0s - loss: 0.3935
 41/124 [========>.....................] - ETA: 0s - loss: 0.4442
 76/124 [=================>............] - ETA: 0s - loss: 0.4410
109/124 [=========================>....] - ETA: 0s - loss: 0.4427
124/124 [==============================] - 0s 1ms/step - loss: 0.4438
    1296. 

  1296. Epoch 3/10
    1297. 

  1297. 
  1/124 [..............................] - ETA: 0s - loss: 0.5630
 39/124 [========>.....................] - ETA: 0s - loss: 0.4448
 73/124 [================>.............] - ETA: 0s - loss: 0.4338
113/124 [==========================>...] - ETA: 0s - loss: 0.4391
124/124 [==============================] - 0s 1ms/step - loss: 0.4341
    1298. 

  1298. Epoch 4/10
    1299. 

  1299. 
  1/124 [..............................] - ETA: 0s - loss: 0.4728
 39/124 [========>.....................] - ETA: 0s - loss: 0.4415
 79/124 [==================>...........] - ETA: 0s - loss: 0.4378
117/124 [===========================>..] - ETA: 0s - loss: 0.4302
124/124 [==============================] - 0s 1ms/step - loss: 0.4280
    1300. 

  1300. Epoch 5/10
    1301. 

  1301. 
  1/124 [..............................] - ETA: 0s - loss: 0.3828
 40/124 [========>.....................] - ETA: 0s - loss: 0.4197
 80/124 [==================>...........] - ETA: 0s - loss: 0.4230
122/124 [============================>.] - ETA: 0s - loss: 0.4240
124/124 [==============================] - 0s 1ms/step - loss: 0.4245
    1302. 

  1302. Epoch 6/10
    1303. 

  1303. 
  1/124 [..............................] - ETA: 0s - loss: 0.4473
 41/124 [========>.....................] - ETA: 0s - loss: 0.4242
 82/124 [==================>...........] - ETA: 0s - loss: 0.4173
119/124 [===========================>..] - ETA: 0s - loss: 0.4251
124/124 [==============================] - 0s 1ms/step - loss: 0.4268
    1304. 

  1304. Epoch 7/10
    1305. 

  1305. 
  1/124 [..............................] - ETA: 0s - loss: 0.3482
 41/124 [========>.....................] - ETA: 0s - loss: 0.4146
 81/124 [==================>...........] - ETA: 0s - loss: 0.4205
121/124 [============================>.] - ETA: 0s - loss: 0.4134
124/124 [==============================] - 0s 1ms/step - loss: 0.4131
    1306. 

  1306. Epoch 8/10
    1307. 

  1307. 
  1/124 [..............................] - ETA: 0s - loss: 0.4178
 42/124 [=========>....................] - ETA: 0s - loss: 0.4165
 83/124 [===================>..........] - ETA: 0s - loss: 0.4012
123/124 [============================>.] - ETA: 0s - loss: 0.4100
124/124 [==============================] - 0s 1ms/step - loss: 0.4102
    1308. 

  1308. Epoch 9/10
    1309. 

  1309. 
  1/124 [..............................] - ETA: 0s - loss: 0.4013
 42/124 [=========>....................] - ETA: 0s - loss: 0.3929
 81/124 [==================>...........] - ETA: 0s - loss: 0.4042
121/124 [============================>.] - ETA: 0s - loss: 0.4102
124/124 [==============================] - 0s 1ms/step - loss: 0.4109
    1310. 

  1310. Epoch 10/10
    1311. 

  1311. 
  1/124 [..............................] - ETA: 0s - loss: 0.4545
 38/124 [========>.....................] - ETA: 0s - loss: 0.4060
 78/124 [=================>............] - ETA: 0s - loss: 0.4041
119/124 [===========================>..] - ETA: 0s - loss: 0.3977
124/124 [==============================] - 0s 1ms/step - loss: 0.3986
    1312. 

  1312. -> test with GAN.predict
    1313. 

  1313. GAN tn, fp: 226, 84
    1314. 

  1314. GAN fn, tp: 6, 5
    1315. 

  1315. GAN f1 score: 0.100
    1316. 

  1316. GAN cohens kappa score: 0.042
    1317. 

  1317. 

  1318. -> test with 'LR'
    1319. 

  1319. LR tn, fp: 205, 105
    1320. 

  1320. LR fn, tp: 1, 10
    1321. 

  1321. LR f1 score: 0.159
    1322. 

  1322. LR cohens kappa score: 0.103
    1323. 

  1323. LR average precision score: 0.269
    1324. 

  1324. 

  1325. -> test with 'RF'
    1326. 

  1326. RF tn, fp: 308, 2
    1327. 

  1327. RF fn, tp: 11, 0
    1328. 

  1328. RF f1 score: 0.000
    1329. 

  1329. RF cohens kappa score: -0.011
    1330. 

  1330. 

  1331. -> test with 'GB'
    1332. 

  1332. GB tn, fp: 285, 25
    1333. 

  1333. GB fn, tp: 7, 4
    1334. 

  1334. GB f1 score: 0.200
    1335. 

  1335. GB cohens kappa score: 0.158
    1336. 

  1336. 

  1337. -> test with 'KNN'
    1338. 

  1338. KNN tn, fp: 253, 57
    1339. 

  1339. KNN fn, tp: 6, 5
    1340. 

  1340. KNN f1 score: 0.137
    1341. 

  1341. KNN cohens kappa score: 0.084
    1342. 

  1342. 

  1343. 

  1344. ------ Step 5/5: Slice 4/5 -------
    1345. 

  1345. -> Reset the GAN
    1346. 

  1346. -> Train generator for synthetic samples
    1347. 

  1347. -> create 1194 synthetic samples
    1348. 

  1348. -> retrain GAN for predict
    1349. 

  1349. Epoch 1/10
    1350. 

  1350. 
  1/124 [..............................] - ETA: 20s - loss: 0.4851
 40/124 [========>.....................] - ETA: 0s - loss: 0.5143 
 79/124 [==================>...........] - ETA: 0s - loss: 0.5082
120/124 [============================>.] - ETA: 0s - loss: 0.5126
124/124 [==============================] - 0s 1ms/step - loss: 0.5121
    1351. 

  1351. Epoch 2/10
    1352. 

  1352. 
  1/124 [..............................] - ETA: 0s - loss: 0.3673
 40/124 [========>.....................] - ETA: 0s - loss: 0.4993
 81/124 [==================>...........] - ETA: 0s - loss: 0.5013
120/124 [============================>.] - ETA: 0s - loss: 0.4997
124/124 [==============================] - 0s 1ms/step - loss: 0.4976
    1353. 

  1353. Epoch 3/10
    1354. 

  1354. 
  1/124 [..............................] - ETA: 0s - loss: 0.4838
 41/124 [========>.....................] - ETA: 0s - loss: 0.4777
 81/124 [==================>...........] - ETA: 0s - loss: 0.4967
121/124 [============================>.] - ETA: 0s - loss: 0.4934
124/124 [==============================] - 0s 1ms/step - loss: 0.4935
    1355. 

  1355. Epoch 4/10
    1356. 

  1356. 
  1/124 [..............................] - ETA: 0s - loss: 0.5666
 41/124 [========>.....................] - ETA: 0s - loss: 0.4841
 83/124 [===================>..........] - ETA: 0s - loss: 0.4817
123/124 [============================>.] - ETA: 0s - loss: 0.4757
124/124 [==============================] - 0s 1ms/step - loss: 0.4750
    1357. 

  1357. Epoch 5/10
    1358. 

  1358. 
  1/124 [..............................] - ETA: 0s - loss: 0.5313
 42/124 [=========>....................] - ETA: 0s - loss: 0.4670
 83/124 [===================>..........] - ETA: 0s - loss: 0.4657
124/124 [==============================] - ETA: 0s - loss: 0.4697
124/124 [==============================] - 0s 1ms/step - loss: 0.4697
    1359. 

  1359. Epoch 6/10
    1360. 

  1360. 
  1/124 [..............................] - ETA: 0s - loss: 0.4793
 41/124 [========>.....................] - ETA: 0s - loss: 0.4497
 82/124 [==================>...........] - ETA: 0s - loss: 0.4516
123/124 [============================>.] - ETA: 0s - loss: 0.4578
124/124 [==============================] - 0s 1ms/step - loss: 0.4565
    1361. 

  1361. Epoch 7/10
    1362. 

  1362. 
  1/124 [..............................] - ETA: 0s - loss: 0.4986
 40/124 [========>.....................] - ETA: 0s - loss: 0.4472
 81/124 [==================>...........] - ETA: 0s - loss: 0.4466
121/124 [============================>.] - ETA: 0s - loss: 0.4567
124/124 [==============================] - 0s 1ms/step - loss: 0.4557
    1363. 

  1363. Epoch 8/10
    1364. 

  1364. 
  1/124 [..............................] - ETA: 0s - loss: 0.4157
 42/124 [=========>....................] - ETA: 0s - loss: 0.4331
 83/124 [===================>..........] - ETA: 0s - loss: 0.4402
124/124 [==============================] - ETA: 0s - loss: 0.4414
124/124 [==============================] - 0s 1ms/step - loss: 0.4414
    1365. 

  1365. Epoch 9/10
    1366. 

  1366. 
  1/124 [..............................] - ETA: 0s - loss: 0.5629
 42/124 [=========>....................] - ETA: 0s - loss: 0.4530
 78/124 [=================>............] - ETA: 0s - loss: 0.4335
119/124 [===========================>..] - ETA: 0s - loss: 0.4332
124/124 [==============================] - 0s 1ms/step - loss: 0.4351
    1367. 

  1367. Epoch 10/10
    1368. 

  1368. 
  1/124 [..............................] - ETA: 0s - loss: 0.2800
 41/124 [========>.....................] - ETA: 0s - loss: 0.4425
 82/124 [==================>...........] - ETA: 0s - loss: 0.4314
121/124 [============================>.] - ETA: 0s - loss: 0.4216
124/124 [==============================] - 0s 1ms/step - loss: 0.4229
    1369. 

  1369. -> test with GAN.predict
    1370. 

  1370. GAN tn, fp: 268, 42
    1371. 

  1371. GAN fn, tp: 7, 4
    1372. 

  1372. GAN f1 score: 0.140
    1373. 

  1373. GAN cohens kappa score: 0.090
    1374. 

  1374. 

  1375. -> test with 'LR'
    1376. 

  1376. LR tn, fp: 213, 97
    1377. 

  1377. LR fn, tp: 4, 7
    1378. 

  1378. LR f1 score: 0.122
    1379. 

  1379. LR cohens kappa score: 0.064
    1380. 

  1380. LR average precision score: 0.221
    1381. 

  1381. 

  1382. -> test with 'RF'
    1383. 

  1383. RF tn, fp: 305, 5
    1384. 

  1384. RF fn, tp: 10, 1
    1385. 

  1385. RF f1 score: 0.118
    1386. 

  1386. RF cohens kappa score: 0.096
    1387. 

  1387. 

  1388. -> test with 'GB'
    1389. 

  1389. GB tn, fp: 296, 14
    1390. 

  1390. GB fn, tp: 8, 3
    1391. 

  1391. GB f1 score: 0.214
    1392. 

  1392. GB cohens kappa score: 0.180
    1393. 

  1393. 

  1394. -> test with 'KNN'
    1395. 

  1395. KNN tn, fp: 229, 81
    1396. 

  1396. KNN fn, tp: 8, 3
    1397. 

  1397. KNN f1 score: 0.063
    1398. 

  1398. KNN cohens kappa score: 0.003
    1399. 

  1399. 

  1400. 

  1401. ------ Step 5/5: Slice 5/5 -------
    1402. 

  1402. -> Reset the GAN
    1403. 

  1403. -> Train generator for synthetic samples
    1404. 

  1404. -> create 1196 synthetic samples
    1405. 

  1405. -> retrain GAN for predict
    1406. 

  1406. Epoch 1/10
    1407. 

  1407. 
  1/124 [..............................] - ETA: 21s - loss: 0.6464
 44/124 [=========>....................] - ETA: 0s - loss: 0.4833 
 87/124 [====================>.........] - ETA: 0s - loss: 0.4860
124/124 [==============================] - 0s 1ms/step - loss: 0.4778
    1408. 

  1408. Epoch 2/10
    1409. 

  1409. 
  1/124 [..............................] - ETA: 0s - loss: 0.5697
 45/124 [=========>....................] - ETA: 0s - loss: 0.4456
 89/124 [====================>.........] - ETA: 0s - loss: 0.4598
124/124 [==============================] - 0s 1ms/step - loss: 0.4625
    1410. 

  1410. Epoch 3/10
    1411. 

  1411. 
  1/124 [..............................] - ETA: 0s - loss: 0.3650
 45/124 [=========>....................] - ETA: 0s - loss: 0.4595
 90/124 [====================>.........] - ETA: 0s - loss: 0.4556
124/124 [==============================] - 0s 1ms/step - loss: 0.4542
    1412. 

  1412. Epoch 4/10
    1413. 

  1413. 
  1/124 [..............................] - ETA: 0s - loss: 0.3777
 43/124 [=========>....................] - ETA: 0s - loss: 0.4189
 84/124 [===================>..........] - ETA: 0s - loss: 0.4429
124/124 [==============================] - 0s 1ms/step - loss: 0.4432
    1414. 

  1414. Epoch 5/10
    1415. 

  1415. 
  1/124 [..............................] - ETA: 0s - loss: 0.4163
 43/124 [=========>....................] - ETA: 0s - loss: 0.4326
 87/124 [====================>.........] - ETA: 0s - loss: 0.4312
124/124 [==============================] - 0s 1ms/step - loss: 0.4333
    1416. 

  1416. Epoch 6/10
    1417. 

  1417. 
  1/124 [..............................] - ETA: 0s - loss: 0.6471
 46/124 [==========>...................] - ETA: 0s - loss: 0.4314
 86/124 [===================>..........] - ETA: 0s - loss: 0.4223
124/124 [==============================] - 0s 1ms/step - loss: 0.4237
    1418. 

  1418. Epoch 7/10
    1419. 

  1419. 
  1/124 [..............................] - ETA: 0s - loss: 0.5338
 44/124 [=========>....................] - ETA: 0s - loss: 0.4117
 87/124 [====================>.........] - ETA: 0s - loss: 0.4150
124/124 [==============================] - 0s 1ms/step - loss: 0.4147
    1420. 

  1420. Epoch 8/10
    1421. 

  1421. 
  1/124 [..............................] - ETA: 0s - loss: 0.4324
 44/124 [=========>....................] - ETA: 0s - loss: 0.4026
 87/124 [====================>.........] - ETA: 0s - loss: 0.4142
124/124 [==============================] - 0s 1ms/step - loss: 0.4096
    1422. 

  1422. Epoch 9/10
    1423. 

  1423. 
  1/124 [..............................] - ETA: 0s - loss: 0.4225
 46/124 [==========>...................] - ETA: 0s - loss: 0.4133
 89/124 [====================>.........] - ETA: 0s - loss: 0.4005
124/124 [==============================] - 0s 1ms/step - loss: 0.3993
    1424. 

  1424. Epoch 10/10
    1425. 

  1425. 
  1/124 [..............................] - ETA: 0s - loss: 0.4132
 39/124 [========>.....................] - ETA: 0s - loss: 0.3750
 80/124 [==================>...........] - ETA: 0s - loss: 0.3808
124/124 [==============================] - ETA: 0s - loss: 0.3907
124/124 [==============================] - 0s 1ms/step - loss: 0.3907
    1426. 

  1426. -> test with GAN.predict
    1427. 

  1427. GAN tn, fp: 236, 70
    1428. 

  1428. GAN fn, tp: 6, 3
    1429. 

  1429. GAN f1 score: 0.073
    1430. 

  1430. GAN cohens kappa score: 0.023
    1431. 

  1431. 

  1432. -> test with 'LR'
    1433. 

  1433. LR tn, fp: 231, 75
    1434. 

  1434. LR fn, tp: 3, 6
    1435. 

  1435. LR f1 score: 0.133
    1436. 

  1436. LR cohens kappa score: 0.086
    1437. 

  1437. LR average precision score: 0.141
    1438. 

  1438. 

  1439. -> test with 'RF'
    1440. 

  1440. RF tn, fp: 302, 4
    1441. 

  1441. RF fn, tp: 8, 1
    1442. 

  1442. RF f1 score: 0.143
    1443. 

  1443. RF cohens kappa score: 0.125
    1444. 

  1444. 

  1445. -> test with 'GB'
    1446. 

  1446. GB tn, fp: 289, 17
    1447. 

  1447. GB fn, tp: 8, 1
    1448. 

  1448. GB f1 score: 0.074
    1449. 

  1449. GB cohens kappa score: 0.037
    1450. 

  1450. 

  1451. -> test with 'KNN'
    1452. 

  1452. KNN tn, fp: 250, 56
    1453. 

  1453. KNN fn, tp: 8, 1
    1454. 

  1454. KNN f1 score: 0.030
    1455. 

  1455. KNN cohens kappa score: -0.020
    1456. 

  1456. 

  1457. ### Exercise is done.
    1458. 

  1458. 

  1459. -----[ LR ]-----
    1460. 

  1460. maximum:
    1461. 

  1461. LR tn, fp: 241, 122
    1462. 

  1462. LR fn, tp: 6, 10
    1463. 

  1463. LR f1 score: 0.184
    1464. 

  1464. LR cohens kappa score: 0.131
    1465. 

  1465. LR average precision score: 0.425
    1466. 

  1466. 

  1467. 

  1468. average:
    1469. 

  1469. LR tn, fp: 218.4, 90.8
    1470. 

  1470. LR fn, tp: 3.56, 7.04
    1471. 

  1471. LR f1 score: 0.130
    1472. 

  1472. LR cohens kappa score: 0.075
    1473. 

  1473. LR average precision score: 0.166
    1474. 

  1474. 

  1475. 

  1476. minimum:
    1477. 

  1477. LR tn, fp: 188, 69
    1478. 

  1478. LR fn, tp: 1, 4
    1479. 

  1479. LR f1 score: 0.071
    1480. 

  1480. LR cohens kappa score: 0.020
    1481. 

  1481. LR average precision score: 0.058
    1482. 

  1482. 

  1483. 

  1484. -----[ RF ]-----
    1485. 

  1485. maximum:
    1486. 

  1486. RF tn, fp: 310, 9
    1487. 

  1487. RF fn, tp: 11, 2
    1488. 

  1488. RF f1 score: 0.267
    1489. 

  1489. RF cohens kappa score: 0.253
    1490. 

  1490. 

  1491. 

  1492. average:
    1493. 

  1493. RF tn, fp: 305.04, 4.16
    1494. 

  1494. RF fn, tp: 9.96, 0.64
    1495. 

  1495. RF f1 score: 0.079
    1496. 

  1496. RF cohens kappa score: 0.062
    1497. 

  1497. 

  1498. 

  1499. minimum:
    1500. 

  1500. RF tn, fp: 298, 0
    1501. 

  1501. RF fn, tp: 8, 0
    1502. 

  1502. RF f1 score: 0.000
    1503. 

  1503. RF cohens kappa score: -0.032
    1504. 

  1504. 

  1505. 

  1506. -----[ GB ]-----
    1507. 

  1507. maximum:
    1508. 

  1508. GB tn, fp: 302, 29
    1509. 

  1509. GB fn, tp: 11, 6
    1510. 

  1510. GB f1 score: 0.324
    1511. 

  1511. GB cohens kappa score: 0.290
    1512. 

  1512. 

  1513. 

  1514. average:
    1515. 

  1515. GB tn, fp: 290.64, 18.56
    1516. 

  1516. GB fn, tp: 8.36, 2.24
    1517. 

  1517. GB f1 score: 0.133
    1518. 

  1518. GB cohens kappa score: 0.095
    1519. 

  1519. 

  1520. 

  1521. minimum:
    1522. 

  1522. GB tn, fp: 277, 8
    1523. 

  1523. GB fn, tp: 5, 0
    1524. 

  1524. GB f1 score: 0.000
    1525. 

  1525. GB cohens kappa score: -0.051
    1526. 

  1526. 

  1527. 

  1528. -----[ KNN ]-----
    1529. 

  1529. maximum:
    1530. 

  1530. KNN tn, fp: 253, 107
    1531. 

  1531. KNN fn, tp: 10, 6
    1532. 

  1532. KNN f1 score: 0.137
    1533. 

  1533. KNN cohens kappa score: 0.084
    1534. 

  1534. 

  1535. 

  1536. average:
    1537. 

  1537. KNN tn, fp: 227.68, 81.52
    1538. 

  1538. KNN fn, tp: 7.08, 3.52
    1539. 

  1539. KNN f1 score: 0.074
    1540. 

  1540. KNN cohens kappa score: 0.016
    1541. 

  1541. 

  1542. 

  1543. minimum:
    1544. 

  1544. KNN tn, fp: 203, 56
    1545. 

  1545. KNN fn, tp: 4, 1
    1546. 

  1546. KNN f1 score: 0.022
    1547. 

  1547. KNN cohens kappa score: -0.040
    1548. 

  1548. 

  1549. 

  1550. -----[ GAN ]-----
    1551. 

  1551. maximum:
    1552. 

  1552. GAN tn, fp: 284, 98
    1553. 

  1553. GAN fn, tp: 8, 8
    1554. 

  1554. GAN f1 score: 0.227
    1555. 

  1555. GAN cohens kappa score: 0.185
    1556. 

  1556. 

  1557. 

  1558. average:
    1559. 

  1559. GAN tn, fp: 243.36, 65.84
    1560. 

  1560. GAN fn, tp: 6.04, 4.56
    1561. 

  1561. GAN f1 score: 0.118
    1562. 

  1562. GAN cohens kappa score: 0.065
    1563. 

  1563. 

  1564. 

  1565. minimum:
    1566. 

  1566. GAN tn, fp: 212, 26
    1567. 

  1567. GAN fn, tp: 3, 2
    1568. 

  1568. GAN f1 score: 0.058
    1569. 

  1569. GAN cohens kappa score: 0.002
    1570. 

  1570.