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ConvGeNBenchmarkResults
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ConvGeNBench...
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convGAN-majority-full
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folding_yeast4.log

folding_yeast4.log 144 KB
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
  1. 

  2. 

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

  4. // Running convGAN-majority-full on folding_yeast4
    5. 

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

  6. 

  7. Load 'data_input/folding_yeast4'
    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 1106 synthetic samples
    21. 

  21. -> retrain GAN for predict
    22. 

  22. Epoch 1/10
    23. 

  23. 
  1/115 [..............................] - ETA: 18s - loss: 0.2124
 41/115 [=========>....................] - ETA: 0s - loss: 0.1608 
 81/115 [====================>.........] - ETA: 0s - loss: 0.1717
115/115 [==============================] - 0s 1ms/step - loss: 0.1759
    24. 

  24. Epoch 2/10
    25. 

  25. 
  1/115 [..............................] - ETA: 0s - loss: 0.1275
 42/115 [=========>....................] - ETA: 0s - loss: 0.1676
 82/115 [====================>.........] - ETA: 0s - loss: 0.1738
115/115 [==============================] - 0s 1ms/step - loss: 0.1741
    26. 

  26. Epoch 3/10
    27. 

  27. 
  1/115 [..............................] - ETA: 0s - loss: 0.1206
 41/115 [=========>....................] - ETA: 0s - loss: 0.1701
 82/115 [====================>.........] - ETA: 0s - loss: 0.1605
115/115 [==============================] - 0s 1ms/step - loss: 0.1682
    28. 

  28. Epoch 4/10
    29. 

  29. 
  1/115 [..............................] - ETA: 0s - loss: 0.1127
 42/115 [=========>....................] - ETA: 0s - loss: 0.1616
 83/115 [====================>.........] - ETA: 0s - loss: 0.1694
115/115 [==============================] - 0s 1ms/step - loss: 0.1677
    30. 

  30. Epoch 5/10
    31. 

  31. 
  1/115 [..............................] - ETA: 0s - loss: 0.1526
 42/115 [=========>....................] - ETA: 0s - loss: 0.1813
 81/115 [====================>.........] - ETA: 0s - loss: 0.1744
115/115 [==============================] - 0s 1ms/step - loss: 0.1679
    32. 

  32. Epoch 6/10
    33. 

  33. 
  1/115 [..............................] - ETA: 0s - loss: 0.2464
 42/115 [=========>....................] - ETA: 0s - loss: 0.1674
 83/115 [====================>.........] - ETA: 0s - loss: 0.1571
115/115 [==============================] - 0s 1ms/step - loss: 0.1640
    34. 

  34. Epoch 7/10
    35. 

  35. 
  1/115 [..............................] - ETA: 0s - loss: 0.1420
 42/115 [=========>....................] - ETA: 0s - loss: 0.1616
 82/115 [====================>.........] - ETA: 0s - loss: 0.1483
115/115 [==============================] - 0s 1ms/step - loss: 0.1630
    36. 

  36. Epoch 8/10
    37. 

  37. 
  1/115 [..............................] - ETA: 0s - loss: 0.0437
 38/115 [========>.....................] - ETA: 0s - loss: 0.1723
 76/115 [==================>...........] - ETA: 0s - loss: 0.1734
115/115 [==============================] - ETA: 0s - loss: 0.1654
115/115 [==============================] - 0s 1ms/step - loss: 0.1654
    38. 

  38. Epoch 9/10
    39. 

  39. 
  1/115 [..............................] - ETA: 0s - loss: 0.1017
 41/115 [=========>....................] - ETA: 0s - loss: 0.1661
 80/115 [===================>..........] - ETA: 0s - loss: 0.1633
115/115 [==============================] - 0s 1ms/step - loss: 0.1611
    40. 

  40. Epoch 10/10
    41. 

  41. 
  1/115 [..............................] - ETA: 0s - loss: 0.2900
 41/115 [=========>....................] - ETA: 0s - loss: 0.1689
 82/115 [====================>.........] - ETA: 0s - loss: 0.1646
115/115 [==============================] - 0s 1ms/step - loss: 0.1633
    42. 

  42. -> test with GAN.predict
    43. 

  43. GAN tn, fp: 261, 26
    44. 

  44. GAN fn, tp: 3, 8
    45. 

  45. GAN f1 score: 0.356
    46. 

  46. GAN cohens kappa score: 0.317
    47. 

  47. 

  48. -> test with 'LR'
    49. 

  49. LR tn, fp: 256, 31
    50. 

  50. LR fn, tp: 3, 8
    51. 

  51. LR f1 score: 0.320
    52. 

  52. LR cohens kappa score: 0.278
    53. 

  53. LR average precision score: 0.337
    54. 

  54. 

  55. -> test with 'RF'
    56. 

  56. RF tn, fp: 284, 3
    57. 

  57. RF fn, tp: 10, 1
    58. 

  58. RF f1 score: 0.133
    59. 

  59. RF cohens kappa score: 0.116
    60. 

  60. 

  61. -> test with 'GB'
    62. 

  62. GB tn, fp: 282, 5
    63. 

  63. GB fn, tp: 8, 3
    64. 

  64. GB f1 score: 0.316
    65. 

  65. GB cohens kappa score: 0.294
    66. 

  66. 

  67. -> test with 'KNN'
    68. 

  68. KNN tn, fp: 259, 28
    69. 

  69. KNN fn, tp: 2, 9
    70. 

  70. KNN f1 score: 0.375
    71. 

  71. KNN cohens kappa score: 0.337
    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 1106 synthetic samples
    78. 

  78. -> retrain GAN for predict
    79. 

  79. Epoch 1/10
    80. 

  80. 
  1/115 [..............................] - ETA: 17s - loss: 0.1872
 35/115 [========>.....................] - ETA: 0s - loss: 0.2271 
 72/115 [=================>............] - ETA: 0s - loss: 0.2156
107/115 [==========================>...] - ETA: 0s - loss: 0.2184
115/115 [==============================] - 0s 1ms/step - loss: 0.2113
    81. 

  81. Epoch 2/10
    82. 

  82. 
  1/115 [..............................] - ETA: 0s - loss: 0.5889
 41/115 [=========>....................] - ETA: 0s - loss: 0.2026
 82/115 [====================>.........] - ETA: 0s - loss: 0.2108
115/115 [==============================] - 0s 1ms/step - loss: 0.2208
    83. 

  83. Epoch 3/10
    84. 

  84. 
  1/115 [..............................] - ETA: 0s - loss: 0.0785
 39/115 [=========>....................] - ETA: 0s - loss: 0.2014
 80/115 [===================>..........] - ETA: 0s - loss: 0.2029
115/115 [==============================] - 0s 1ms/step - loss: 0.2152
    85. 

  85. Epoch 4/10
    86. 

  86. 
  1/115 [..............................] - ETA: 0s - loss: 0.1094
 42/115 [=========>....................] - ETA: 0s - loss: 0.1961
 82/115 [====================>.........] - ETA: 0s - loss: 0.2107
115/115 [==============================] - 0s 1ms/step - loss: 0.2083
    87. 

  87. Epoch 5/10
    88. 

  88. 
  1/115 [..............................] - ETA: 0s - loss: 0.2764
 42/115 [=========>....................] - ETA: 0s - loss: 0.1886
 82/115 [====================>.........] - ETA: 0s - loss: 0.2109
115/115 [==============================] - 0s 1ms/step - loss: 0.2063
    89. 

  89. Epoch 6/10
    90. 

  90. 
  1/115 [..............................] - ETA: 0s - loss: 0.4101
 41/115 [=========>....................] - ETA: 0s - loss: 0.2393
 80/115 [===================>..........] - ETA: 0s - loss: 0.2137
115/115 [==============================] - 0s 1ms/step - loss: 0.2040
    91. 

  91. Epoch 7/10
    92. 

  92. 
  1/115 [..............................] - ETA: 0s - loss: 0.1357
 42/115 [=========>....................] - ETA: 0s - loss: 0.2306
 83/115 [====================>.........] - ETA: 0s - loss: 0.2184
115/115 [==============================] - 0s 1ms/step - loss: 0.2044
    93. 

  93. Epoch 8/10
    94. 

  94. 
  1/115 [..............................] - ETA: 0s - loss: 0.4756
 41/115 [=========>....................] - ETA: 0s - loss: 0.2243
 78/115 [===================>..........] - ETA: 0s - loss: 0.2084
115/115 [==============================] - 0s 1ms/step - loss: 0.2070
    95. 

  95. Epoch 9/10
    96. 

  96. 
  1/115 [..............................] - ETA: 0s - loss: 0.2235
 41/115 [=========>....................] - ETA: 0s - loss: 0.2192
 82/115 [====================>.........] - ETA: 0s - loss: 0.2133
115/115 [==============================] - 0s 1ms/step - loss: 0.2037
    97. 

  97. Epoch 10/10
    98. 

  98. 
  1/115 [..............................] - ETA: 0s - loss: 0.2199
 42/115 [=========>....................] - ETA: 0s - loss: 0.2058
 83/115 [====================>.........] - ETA: 0s - loss: 0.2055
115/115 [==============================] - 0s 1ms/step - loss: 0.2024
    99. 

  99. -> test with GAN.predict
    100. 

  100. GAN tn, fp: 263, 24
    101. 

  101. GAN fn, tp: 3, 8
    102. 

  102. GAN f1 score: 0.372
    103. 

  103. GAN cohens kappa score: 0.336
    104. 

  104. 

  105. -> test with 'LR'
    106. 

  106. LR tn, fp: 245, 42
    107. 

  107. LR fn, tp: 2, 9
    108. 

  108. LR f1 score: 0.290
    109. 

  109. LR cohens kappa score: 0.244
    110. 

  110. LR average precision score: 0.613
    111. 

  111. 

  112. -> test with 'RF'
    113. 

  113. RF tn, fp: 286, 1
    114. 

  114. RF fn, tp: 8, 3
    115. 

  115. RF f1 score: 0.400
    116. 

  116. RF cohens kappa score: 0.388
    117. 

  117. 

  118. -> test with 'GB'
    119. 

  119. GB tn, fp: 284, 3
    120. 

  120. GB fn, tp: 7, 4
    121. 

  121. GB f1 score: 0.444
    122. 

  122. GB cohens kappa score: 0.428
    123. 

  123. 

  124. -> test with 'KNN'
    125. 

  125. KNN tn, fp: 255, 32
    126. 

  126. KNN fn, tp: 1, 10
    127. 

  127. KNN f1 score: 0.377
    128. 

  128. KNN cohens kappa score: 0.339
    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 1106 synthetic samples
    135. 

  135. -> retrain GAN for predict
    136. 

  136. Epoch 1/10
    137. 

  137. 
  1/115 [..............................] - ETA: 18s - loss: 0.3249
 42/115 [=========>....................] - ETA: 0s - loss: 0.1967 
 83/115 [====================>.........] - ETA: 0s - loss: 0.1862
115/115 [==============================] - 0s 1ms/step - loss: 0.1892
    138. 

  138. Epoch 2/10
    139. 

  139. 
  1/115 [..............................] - ETA: 0s - loss: 0.0836
 41/115 [=========>....................] - ETA: 0s - loss: 0.1881
 81/115 [====================>.........] - ETA: 0s - loss: 0.1698
115/115 [==============================] - 0s 1ms/step - loss: 0.1812
    140. 

  140. Epoch 3/10
    141. 

  141. 
  1/115 [..............................] - ETA: 0s - loss: 0.1491
 41/115 [=========>....................] - ETA: 0s - loss: 0.1536
 81/115 [====================>.........] - ETA: 0s - loss: 0.1790
115/115 [==============================] - 0s 1ms/step - loss: 0.1797
    142. 

  142. Epoch 4/10
    143. 

  143. 
  1/115 [..............................] - ETA: 0s - loss: 0.1988
 41/115 [=========>....................] - ETA: 0s - loss: 0.1787
 81/115 [====================>.........] - ETA: 0s - loss: 0.1760
115/115 [==============================] - 0s 1ms/step - loss: 0.1807
    144. 

  144. Epoch 5/10
    145. 

  145. 
  1/115 [..............................] - ETA: 0s - loss: 0.1821
 41/115 [=========>....................] - ETA: 0s - loss: 0.1779
 82/115 [====================>.........] - ETA: 0s - loss: 0.1789
115/115 [==============================] - 0s 1ms/step - loss: 0.1771
    146. 

  146. Epoch 6/10
    147. 

  147. 
  1/115 [..............................] - ETA: 0s - loss: 0.1867
 41/115 [=========>....................] - ETA: 0s - loss: 0.1603
 82/115 [====================>.........] - ETA: 0s - loss: 0.1692
115/115 [==============================] - 0s 1ms/step - loss: 0.1732
    148. 

  148. Epoch 7/10
    149. 

  149. 
  1/115 [..............................] - ETA: 0s - loss: 0.2466
 42/115 [=========>....................] - ETA: 0s - loss: 0.2011
 82/115 [====================>.........] - ETA: 0s - loss: 0.1697
115/115 [==============================] - 0s 1ms/step - loss: 0.1727
    150. 

  150. Epoch 8/10
    151. 

  151. 
  1/115 [..............................] - ETA: 0s - loss: 0.1712
 42/115 [=========>....................] - ETA: 0s - loss: 0.1696
 79/115 [===================>..........] - ETA: 0s - loss: 0.1706
112/115 [============================>.] - ETA: 0s - loss: 0.1793
115/115 [==============================] - 0s 1ms/step - loss: 0.1788
    152. 

  152. Epoch 9/10
    153. 

  153. 
  1/115 [..............................] - ETA: 0s - loss: 0.1313
 37/115 [========>.....................] - ETA: 0s - loss: 0.1546
 75/115 [==================>...........] - ETA: 0s - loss: 0.1712
115/115 [==============================] - 0s 1ms/step - loss: 0.1727
    154. 

  154. Epoch 10/10
    155. 

  155. 
  1/115 [..............................] - ETA: 0s - loss: 0.1461
 42/115 [=========>....................] - ETA: 0s - loss: 0.1540
 82/115 [====================>.........] - ETA: 0s - loss: 0.1597
115/115 [==============================] - 0s 1ms/step - loss: 0.1708
    156. 

  156. -> test with GAN.predict
    157. 

  157. GAN tn, fp: 259, 28
    158. 

  158. GAN fn, tp: 4, 7
    159. 

  159. GAN f1 score: 0.304
    160. 

  160. GAN cohens kappa score: 0.263
    161. 

  161. 

  162. -> test with 'LR'
    163. 

  163. LR tn, fp: 249, 38
    164. 

  164. LR fn, tp: 2, 9
    165. 

  165. LR f1 score: 0.310
    166. 

  166. LR cohens kappa score: 0.266
    167. 

  167. LR average precision score: 0.305
    168. 

  168. 

  169. -> test with 'RF'
    170. 

  170. RF tn, fp: 284, 3
    171. 

  171. RF fn, tp: 8, 3
    172. 

  172. RF f1 score: 0.353
    173. 

  173. RF cohens kappa score: 0.336
    174. 

  174. 

  175. -> test with 'GB'
    176. 

  176. GB tn, fp: 278, 9
    177. 

  177. GB fn, tp: 8, 3
    178. 

  178. GB f1 score: 0.261
    179. 

  179. GB cohens kappa score: 0.231
    180. 

  180. 

  181. -> test with 'KNN'
    182. 

  182. KNN tn, fp: 264, 23
    183. 

  183. KNN fn, tp: 4, 7
    184. 

  184. KNN f1 score: 0.341
    185. 

  185. KNN cohens kappa score: 0.304
    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 1106 synthetic samples
    192. 

  192. -> retrain GAN for predict
    193. 

  193. Epoch 1/10
    194. 

  194. 
  1/115 [..............................] - ETA: 18s - loss: 0.2231
 42/115 [=========>....................] - ETA: 0s - loss: 0.1736 
 83/115 [====================>.........] - ETA: 0s - loss: 0.1747
115/115 [==============================] - 0s 1ms/step - loss: 0.1791
    195. 

  195. Epoch 2/10
    196. 

  196. 
  1/115 [..............................] - ETA: 0s - loss: 0.1787
 41/115 [=========>....................] - ETA: 0s - loss: 0.1840
 80/115 [===================>..........] - ETA: 0s - loss: 0.1824
115/115 [==============================] - 0s 1ms/step - loss: 0.1739
    197. 

  197. Epoch 3/10
    198. 

  198. 
  1/115 [..............................] - ETA: 0s - loss: 0.2156
 41/115 [=========>....................] - ETA: 0s - loss: 0.1790
 80/115 [===================>..........] - ETA: 0s - loss: 0.1719
115/115 [==============================] - 0s 1ms/step - loss: 0.1752
    199. 

  199. Epoch 4/10
    200. 

  200. 
  1/115 [..............................] - ETA: 0s - loss: 0.2795
 39/115 [=========>....................] - ETA: 0s - loss: 0.1850
 78/115 [===================>..........] - ETA: 0s - loss: 0.1664
115/115 [==============================] - ETA: 0s - loss: 0.1704
115/115 [==============================] - 0s 1ms/step - loss: 0.1704
    201. 

  201. Epoch 5/10
    202. 

  202. 
  1/115 [..............................] - ETA: 0s - loss: 0.0948
 38/115 [========>.....................] - ETA: 0s - loss: 0.1670
 72/115 [=================>............] - ETA: 0s - loss: 0.1783
106/115 [==========================>...] - ETA: 0s - loss: 0.1686
115/115 [==============================] - 0s 1ms/step - loss: 0.1684
    203. 

  203. Epoch 6/10
    204. 

  204. 
  1/115 [..............................] - ETA: 0s - loss: 0.3254
 40/115 [=========>....................] - ETA: 0s - loss: 0.1657
 78/115 [===================>..........] - ETA: 0s - loss: 0.1669
115/115 [==============================] - 0s 1ms/step - loss: 0.1678
    205. 

  205. Epoch 7/10
    206. 

  206. 
  1/115 [..............................] - ETA: 0s - loss: 0.1806
 39/115 [=========>....................] - ETA: 0s - loss: 0.1942
 80/115 [===================>..........] - ETA: 0s - loss: 0.1752
115/115 [==============================] - 0s 1ms/step - loss: 0.1726
    207. 

  207. Epoch 8/10
    208. 

  208. 
  1/115 [..............................] - ETA: 0s - loss: 0.1735
 40/115 [=========>....................] - ETA: 0s - loss: 0.1967
 80/115 [===================>..........] - ETA: 0s - loss: 0.1748
115/115 [==============================] - 0s 1ms/step - loss: 0.1751
    209. 

  209. Epoch 9/10
    210. 

  210. 
  1/115 [..............................] - ETA: 0s - loss: 0.2037
 40/115 [=========>....................] - ETA: 0s - loss: 0.1557
 79/115 [===================>..........] - ETA: 0s - loss: 0.1699
115/115 [==============================] - 0s 1ms/step - loss: 0.1700
    211. 

  211. Epoch 10/10
    212. 

  212. 
  1/115 [..............................] - ETA: 0s - loss: 0.1053
 42/115 [=========>....................] - ETA: 0s - loss: 0.1571
 82/115 [====================>.........] - ETA: 0s - loss: 0.1679
115/115 [==============================] - 0s 1ms/step - loss: 0.1699
    213. 

  213. -> test with GAN.predict
    214. 

  214. GAN tn, fp: 264, 23
    215. 

  215. GAN fn, tp: 7, 4
    216. 

  216. GAN f1 score: 0.211
    217. 

  217. GAN cohens kappa score: 0.167
    218. 

  218. 

  219. -> test with 'LR'
    220. 

  220. LR tn, fp: 255, 32
    221. 

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

  222. LR f1 score: 0.208
    223. 

  223. LR cohens kappa score: 0.161
    224. 

  224. LR average precision score: 0.221
    225. 

  225. 

  226. -> test with 'RF'
    227. 

  227. RF tn, fp: 281, 6
    228. 

  228. RF fn, tp: 8, 3
    229. 

  229. RF f1 score: 0.300
    230. 

  230. RF cohens kappa score: 0.276
    231. 

  231. 

  232. -> test with 'GB'
    233. 

  233. GB tn, fp: 278, 9
    234. 

  234. GB fn, tp: 8, 3
    235. 

  235. GB f1 score: 0.261
    236. 

  236. GB cohens kappa score: 0.231
    237. 

  237. 

  238. -> test with 'KNN'
    239. 

  239. KNN tn, fp: 263, 24
    240. 

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

  241. KNN f1 score: 0.293
    242. 

  242. KNN cohens kappa score: 0.252
    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 1104 synthetic samples
    249. 

  249. -> retrain GAN for predict
    250. 

  250. Epoch 1/10
    251. 

  251. 
  1/115 [..............................] - ETA: 18s - loss: 0.1911
 40/115 [=========>....................] - ETA: 0s - loss: 0.2225 
 80/115 [===================>..........] - ETA: 0s - loss: 0.2099
115/115 [==============================] - 0s 1ms/step - loss: 0.2047
    252. 

  252. Epoch 2/10
    253. 

  253. 
  1/115 [..............................] - ETA: 0s - loss: 0.3832
 40/115 [=========>....................] - ETA: 0s - loss: 0.1917
 80/115 [===================>..........] - ETA: 0s - loss: 0.2101
115/115 [==============================] - 0s 1ms/step - loss: 0.2043
    254. 

  254. Epoch 3/10
    255. 

  255. 
  1/115 [..............................] - ETA: 0s - loss: 0.1352
 41/115 [=========>....................] - ETA: 0s - loss: 0.2108
 80/115 [===================>..........] - ETA: 0s - loss: 0.2066
115/115 [==============================] - 0s 1ms/step - loss: 0.2035
    256. 

  256. Epoch 4/10
    257. 

  257. 
  1/115 [..............................] - ETA: 0s - loss: 0.0686
 42/115 [=========>....................] - ETA: 0s - loss: 0.2126
 68/115 [================>.............] - ETA: 0s - loss: 0.1969
107/115 [==========================>...] - ETA: 0s - loss: 0.2012
115/115 [==============================] - 0s 1ms/step - loss: 0.1985
    258. 

  258. Epoch 5/10
    259. 

  259. 
  1/115 [..............................] - ETA: 0s - loss: 0.2547
 41/115 [=========>....................] - ETA: 0s - loss: 0.1927
 74/115 [==================>...........] - ETA: 0s - loss: 0.1908
108/115 [===========================>..] - ETA: 0s - loss: 0.1915
115/115 [==============================] - 0s 1ms/step - loss: 0.1974
    260. 

  260. Epoch 6/10
    261. 

  261. 
  1/115 [..............................] - ETA: 0s - loss: 0.3245
 34/115 [=======>......................] - ETA: 0s - loss: 0.1972
 70/115 [=================>............] - ETA: 0s - loss: 0.1956
108/115 [===========================>..] - ETA: 0s - loss: 0.1948
115/115 [==============================] - 0s 1ms/step - loss: 0.1982
    262. 

  262. Epoch 7/10
    263. 

  263. 
  1/115 [..............................] - ETA: 0s - loss: 0.1368
 32/115 [=======>......................] - ETA: 0s - loss: 0.1810
 66/115 [================>.............] - ETA: 0s - loss: 0.2119
103/115 [=========================>....] - ETA: 0s - loss: 0.1946
115/115 [==============================] - 0s 1ms/step - loss: 0.1997
    264. 

  264. Epoch 8/10
    265. 

  265. 
  1/115 [..............................] - ETA: 0s - loss: 0.2637
 34/115 [=======>......................] - ETA: 0s - loss: 0.1936
 64/115 [===============>..............] - ETA: 0s - loss: 0.1829
102/115 [=========================>....] - ETA: 0s - loss: 0.1917
115/115 [==============================] - 0s 2ms/step - loss: 0.1976
    266. 

  266. Epoch 9/10
    267. 

  267. 
  1/115 [..............................] - ETA: 0s - loss: 0.1689
 35/115 [========>.....................] - ETA: 0s - loss: 0.2036
 65/115 [===============>..............] - ETA: 0s - loss: 0.1873
 95/115 [=======================>......] - ETA: 0s - loss: 0.1967
115/115 [==============================] - 0s 2ms/step - loss: 0.1959
    268. 

  268. Epoch 10/10
    269. 

  269. 
  1/115 [..............................] - ETA: 0s - loss: 0.0371
 34/115 [=======>......................] - ETA: 0s - loss: 0.1780
 69/115 [=================>............] - ETA: 0s - loss: 0.2021
107/115 [==========================>...] - ETA: 0s - loss: 0.1986
115/115 [==============================] - 0s 1ms/step - loss: 0.1990
    270. 

  270. -> test with GAN.predict
    271. 

  271. GAN tn, fp: 250, 35
    272. 

  272. GAN fn, tp: 2, 5
    273. 

  273. GAN f1 score: 0.213
    274. 

  274. GAN cohens kappa score: 0.179
    275. 

  275. 

  276. -> test with 'LR'
    277. 

  277. LR tn, fp: 248, 37
    278. 

  278. LR fn, tp: 1, 6
    279. 

  279. LR f1 score: 0.240
    280. 

  280. LR cohens kappa score: 0.207
    281. 

  281. LR average precision score: 0.473
    282. 

  282. 

  283. -> test with 'RF'
    284. 

  284. RF tn, fp: 283, 2
    285. 

  285. RF fn, tp: 5, 2
    286. 

  286. RF f1 score: 0.364
    287. 

  287. RF cohens kappa score: 0.352
    288. 

  288. 

  289. -> test with 'GB'
    290. 

  290. GB tn, fp: 281, 4
    291. 

  291. GB fn, tp: 4, 3
    292. 

  292. GB f1 score: 0.429
    293. 

  293. GB cohens kappa score: 0.415
    294. 

  294. 

  295. -> test with 'KNN'
    296. 

  296. KNN tn, fp: 260, 25
    297. 

  297. KNN fn, tp: 1, 6
    298. 

  298. KNN f1 score: 0.316
    299. 

  299. KNN cohens kappa score: 0.288
    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 1106 synthetic samples
    310. 

  310. -> retrain GAN for predict
    311. 

  311. Epoch 1/10
    312. 

  312. 
  1/115 [..............................] - ETA: 17s - loss: 0.2548
 42/115 [=========>....................] - ETA: 0s - loss: 0.2501 
 83/115 [====================>.........] - ETA: 0s - loss: 0.2317
115/115 [==============================] - 0s 1ms/step - loss: 0.2229
    313. 

  313. Epoch 2/10
    314. 

  314. 
  1/115 [..............................] - ETA: 0s - loss: 0.2089
 41/115 [=========>....................] - ETA: 0s - loss: 0.2306
 81/115 [====================>.........] - ETA: 0s - loss: 0.2269
115/115 [==============================] - 0s 1ms/step - loss: 0.2202
    315. 

  315. Epoch 3/10
    316. 

  316. 
  1/115 [..............................] - ETA: 0s - loss: 0.1395
 38/115 [========>.....................] - ETA: 0s - loss: 0.2034
 79/115 [===================>..........] - ETA: 0s - loss: 0.2234
115/115 [==============================] - 0s 1ms/step - loss: 0.2164
    317. 

  317. Epoch 4/10
    318. 

  318. 
  1/115 [..............................] - ETA: 0s - loss: 0.1460
 42/115 [=========>....................] - ETA: 0s - loss: 0.2090
 84/115 [====================>.........] - ETA: 0s - loss: 0.2133
115/115 [==============================] - 0s 1ms/step - loss: 0.2189
    319. 

  319. Epoch 5/10
    320. 

  320. 
  1/115 [..............................] - ETA: 0s - loss: 0.1581
 42/115 [=========>....................] - ETA: 0s - loss: 0.2067
 83/115 [====================>.........] - ETA: 0s - loss: 0.2015
115/115 [==============================] - 0s 1ms/step - loss: 0.2124
    321. 

  321. Epoch 6/10
    322. 

  322. 
  1/115 [..............................] - ETA: 0s - loss: 0.1815
 42/115 [=========>....................] - ETA: 0s - loss: 0.2354
 83/115 [====================>.........] - ETA: 0s - loss: 0.2245
115/115 [==============================] - 0s 1ms/step - loss: 0.2168
    323. 

  323. Epoch 7/10
    324. 

  324. 
  1/115 [..............................] - ETA: 0s - loss: 0.1166
 40/115 [=========>....................] - ETA: 0s - loss: 0.2135
 81/115 [====================>.........] - ETA: 0s - loss: 0.2152
 88/115 [=====================>........] - ETA: 0s - loss: 0.2181
115/115 [==============================] - 0s 3ms/step - loss: 0.2176
    325. 

  325. Epoch 8/10
    326. 

  326. 
  1/115 [..............................] - ETA: 0s - loss: 0.0993
 40/115 [=========>....................] - ETA: 0s - loss: 0.2101
 80/115 [===================>..........] - ETA: 0s - loss: 0.2118
115/115 [==============================] - 0s 1ms/step - loss: 0.2107
    327. 

  327. Epoch 9/10
    328. 

  328. 
  1/115 [..............................] - ETA: 0s - loss: 0.2400
 40/115 [=========>....................] - ETA: 0s - loss: 0.2045
 79/115 [===================>..........] - ETA: 0s - loss: 0.2107
115/115 [==============================] - 0s 1ms/step - loss: 0.2146
    329. 

  329. Epoch 10/10
    330. 

  330. 
  1/115 [..............................] - ETA: 0s - loss: 0.1427
 41/115 [=========>....................] - ETA: 0s - loss: 0.2336
 75/115 [==================>...........] - ETA: 0s - loss: 0.2195
110/115 [===========================>..] - ETA: 0s - loss: 0.2110
115/115 [==============================] - 0s 1ms/step - loss: 0.2117
    331. 

  331. -> test with GAN.predict
    332. 

  332. GAN tn, fp: 270, 17
    333. 

  333. GAN fn, tp: 4, 7
    334. 

  334. GAN f1 score: 0.400
    335. 

  335. GAN cohens kappa score: 0.368
    336. 

  336. 

  337. -> test with 'LR'
    338. 

  338. LR tn, fp: 252, 35
    339. 

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

  340. LR f1 score: 0.296
    341. 

  341. LR cohens kappa score: 0.252
    342. 

  342. LR average precision score: 0.336
    343. 

  343. 

  344. -> test with 'RF'
    345. 

  345. RF tn, fp: 286, 1
    346. 

  346. RF fn, tp: 9, 2
    347. 

  347. RF f1 score: 0.286
    348. 

  348. RF cohens kappa score: 0.274
    349. 

  349. 

  350. -> test with 'GB'
    351. 

  351. GB tn, fp: 284, 3
    352. 

  352. GB fn, tp: 9, 2
    353. 

  353. GB f1 score: 0.250
    354. 

  354. GB cohens kappa score: 0.232
    355. 

  355. 

  356. -> test with 'KNN'
    357. 

  357. KNN tn, fp: 264, 23
    358. 

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

  359. KNN f1 score: 0.381
    360. 

  360. KNN cohens kappa score: 0.345
    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 1106 synthetic samples
    367. 

  367. -> retrain GAN for predict
    368. 

  368. Epoch 1/10
    369. 

  369. 
  1/115 [..............................] - ETA: 21s - loss: 0.1241
 37/115 [========>.....................] - ETA: 0s - loss: 0.1690 
 74/115 [==================>...........] - ETA: 0s - loss: 0.1661
108/115 [===========================>..] - ETA: 0s - loss: 0.1764
115/115 [==============================] - 0s 1ms/step - loss: 0.1729
    370. 

  370. Epoch 2/10
    371. 

  371. 
  1/115 [..............................] - ETA: 0s - loss: 0.1104
 36/115 [========>.....................] - ETA: 0s - loss: 0.1467
 70/115 [=================>............] - ETA: 0s - loss: 0.1749
106/115 [==========================>...] - ETA: 0s - loss: 0.1672
115/115 [==============================] - 0s 1ms/step - loss: 0.1701
    372. 

  372. Epoch 3/10
    373. 

  373. 
  1/115 [..............................] - ETA: 0s - loss: 0.1537
 40/115 [=========>....................] - ETA: 0s - loss: 0.2118
 76/115 [==================>...........] - ETA: 0s - loss: 0.1821
110/115 [===========================>..] - ETA: 0s - loss: 0.1731
115/115 [==============================] - 0s 1ms/step - loss: 0.1745
    374. 

  374. Epoch 4/10
    375. 

  375. 
  1/115 [..............................] - ETA: 0s - loss: 0.3667
 35/115 [========>.....................] - ETA: 0s - loss: 0.1729
 68/115 [================>.............] - ETA: 0s - loss: 0.1678
101/115 [=========================>....] - ETA: 0s - loss: 0.1649
115/115 [==============================] - 0s 2ms/step - loss: 0.1674
    376. 

  376. Epoch 5/10
    377. 

  377. 
  1/115 [..............................] - ETA: 0s - loss: 0.0645
 39/115 [=========>....................] - ETA: 0s - loss: 0.1675
 74/115 [==================>...........] - ETA: 0s - loss: 0.1688
110/115 [===========================>..] - ETA: 0s - loss: 0.1688
115/115 [==============================] - 0s 1ms/step - loss: 0.1674
    378. 

  378. Epoch 6/10
    379. 

  379. 
  1/115 [..............................] - ETA: 0s - loss: 0.0836
 33/115 [=======>......................] - ETA: 0s - loss: 0.1496
 69/115 [=================>............] - ETA: 0s - loss: 0.1553
 98/115 [========================>.....] - ETA: 0s - loss: 0.1661
115/115 [==============================] - 0s 2ms/step - loss: 0.1647
    380. 

  380. Epoch 7/10
    381. 

  381. 
  1/115 [..............................] - ETA: 0s - loss: 0.0380
 37/115 [========>.....................] - ETA: 0s - loss: 0.1743
 69/115 [=================>............] - ETA: 0s - loss: 0.1658
103/115 [=========================>....] - ETA: 0s - loss: 0.1678
115/115 [==============================] - 0s 1ms/step - loss: 0.1666
    382. 

  382. Epoch 8/10
    383. 

  383. 
  1/115 [..............................] - ETA: 0s - loss: 0.1901
 33/115 [=======>......................] - ETA: 0s - loss: 0.1591
 69/115 [=================>............] - ETA: 0s - loss: 0.1521
107/115 [==========================>...] - ETA: 0s - loss: 0.1622
115/115 [==============================] - 0s 1ms/step - loss: 0.1624
    384. 

  384. Epoch 9/10
    385. 

  385. 
  1/115 [..............................] - ETA: 0s - loss: 0.0560
 36/115 [========>.....................] - ETA: 0s - loss: 0.1660
 72/115 [=================>............] - ETA: 0s - loss: 0.1635
111/115 [===========================>..] - ETA: 0s - loss: 0.1605
115/115 [==============================] - 0s 1ms/step - loss: 0.1589
    386. 

  386. Epoch 10/10
    387. 

  387. 
  1/115 [..............................] - ETA: 0s - loss: 0.2369
 40/115 [=========>....................] - ETA: 0s - loss: 0.1598
 76/115 [==================>...........] - ETA: 0s - loss: 0.1610
111/115 [===========================>..] - ETA: 0s - loss: 0.1615
115/115 [==============================] - 0s 1ms/step - loss: 0.1636
    388. 

  388. -> test with GAN.predict
    389. 

  389. GAN tn, fp: 262, 25
    390. 

  390. GAN fn, tp: 4, 7
    391. 

  391. GAN f1 score: 0.326
    392. 

  392. GAN cohens kappa score: 0.286
    393. 

  393. 

  394. -> test with 'LR'
    395. 

  395. LR tn, fp: 250, 37
    396. 

  396. LR fn, tp: 3, 8
    397. 

  397. LR f1 score: 0.286
    398. 

  398. LR cohens kappa score: 0.241
    399. 

  399. LR average precision score: 0.453
    400. 

  400. 

  401. -> test with 'RF'
    402. 

  402. RF tn, fp: 282, 5
    403. 

  403. RF fn, tp: 6, 5
    404. 

  404. RF f1 score: 0.476
    405. 

  405. RF cohens kappa score: 0.457
    406. 

  406. 

  407. -> test with 'GB'
    408. 

  408. GB tn, fp: 278, 9
    409. 

  409. GB fn, tp: 7, 4
    410. 

  410. GB f1 score: 0.333
    411. 

  411. GB cohens kappa score: 0.306
    412. 

  412. 

  413. -> test with 'KNN'
    414. 

  414. KNN tn, fp: 253, 34
    415. 

  415. KNN fn, tp: 3, 8
    416. 

  416. KNN f1 score: 0.302
    417. 

  417. KNN cohens kappa score: 0.259
    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 1106 synthetic samples
    424. 

  424. -> retrain GAN for predict
    425. 

  425. Epoch 1/10
    426. 

  426. 
  1/115 [..............................] - ETA: 17s - loss: 0.2098
 42/115 [=========>....................] - ETA: 0s - loss: 0.1703 
 80/115 [===================>..........] - ETA: 0s - loss: 0.1803
115/115 [==============================] - 0s 1ms/step - loss: 0.1853
    427. 

  427. Epoch 2/10
    428. 

  428. 
  1/115 [..............................] - ETA: 0s - loss: 0.1948
 42/115 [=========>....................] - ETA: 0s - loss: 0.1794
 81/115 [====================>.........] - ETA: 0s - loss: 0.1761
115/115 [==============================] - 0s 1ms/step - loss: 0.1791
    429. 

  429. Epoch 3/10
    430. 

  430. 
  1/115 [..............................] - ETA: 0s - loss: 0.3270
 40/115 [=========>....................] - ETA: 0s - loss: 0.1840
 79/115 [===================>..........] - ETA: 0s - loss: 0.1882
115/115 [==============================] - 0s 1ms/step - loss: 0.1788
    431. 

  431. Epoch 4/10
    432. 

  432. 
  1/115 [..............................] - ETA: 0s - loss: 0.0890
 39/115 [=========>....................] - ETA: 0s - loss: 0.1775
 77/115 [===================>..........] - ETA: 0s - loss: 0.1741
115/115 [==============================] - 0s 1ms/step - loss: 0.1779
    433. 

  433. Epoch 5/10
    434. 

  434. 
  1/115 [..............................] - ETA: 0s - loss: 0.0406
 41/115 [=========>....................] - ETA: 0s - loss: 0.1350
 81/115 [====================>.........] - ETA: 0s - loss: 0.1594
115/115 [==============================] - 0s 1ms/step - loss: 0.1723
    435. 

  435. Epoch 6/10
    436. 

  436. 
  1/115 [..............................] - ETA: 0s - loss: 0.3309
 40/115 [=========>....................] - ETA: 0s - loss: 0.1562
 79/115 [===================>..........] - ETA: 0s - loss: 0.1725
115/115 [==============================] - 0s 1ms/step - loss: 0.1719
    437. 

  437. Epoch 7/10
    438. 

  438. 
  1/115 [..............................] - ETA: 0s - loss: 0.0647
 42/115 [=========>....................] - ETA: 0s - loss: 0.1551
 80/115 [===================>..........] - ETA: 0s - loss: 0.1613
115/115 [==============================] - 0s 1ms/step - loss: 0.1715
    439. 

  439. Epoch 8/10
    440. 

  440. 
  1/115 [..............................] - ETA: 0s - loss: 0.1300
 42/115 [=========>....................] - ETA: 0s - loss: 0.1704
 82/115 [====================>.........] - ETA: 0s - loss: 0.1689
115/115 [==============================] - 0s 1ms/step - loss: 0.1702
    441. 

  441. Epoch 9/10
    442. 

  442. 
  1/115 [..............................] - ETA: 0s - loss: 0.0931
 34/115 [=======>......................] - ETA: 0s - loss: 0.1894
 70/115 [=================>............] - ETA: 0s - loss: 0.1773
106/115 [==========================>...] - ETA: 0s - loss: 0.1763
115/115 [==============================] - 0s 1ms/step - loss: 0.1749
    443. 

  443. Epoch 10/10
    444. 

  444. 
  1/115 [..............................] - ETA: 0s - loss: 0.0510
 39/115 [=========>....................] - ETA: 0s - loss: 0.1673
 78/115 [===================>..........] - ETA: 0s - loss: 0.1736
115/115 [==============================] - 0s 1ms/step - loss: 0.1770
    445. 

  445. -> test with GAN.predict
    446. 

  446. GAN tn, fp: 262, 25
    447. 

  447. GAN fn, tp: 6, 5
    448. 

  448. GAN f1 score: 0.244
    449. 

  449. GAN cohens kappa score: 0.201
    450. 

  450. 

  451. -> test with 'LR'
    452. 

  452. LR tn, fp: 252, 35
    453. 

  453. LR fn, tp: 4, 7
    454. 

  454. LR f1 score: 0.264
    455. 

  455. LR cohens kappa score: 0.218
    456. 

  456. LR average precision score: 0.355
    457. 

  457. 

  458. -> test with 'RF'
    459. 

  459. RF tn, fp: 283, 4
    460. 

  460. RF fn, tp: 7, 4
    461. 

  461. RF f1 score: 0.421
    462. 

  462. RF cohens kappa score: 0.402
    463. 

  463. 

  464. -> test with 'GB'
    465. 

  465. GB tn, fp: 280, 7
    466. 

  466. GB fn, tp: 7, 4
    467. 

  467. GB f1 score: 0.364
    468. 

  468. GB cohens kappa score: 0.339
    469. 

  469. 

  470. -> test with 'KNN'
    471. 

  471. KNN tn, fp: 257, 30
    472. 

  472. KNN fn, tp: 3, 8
    473. 

  473. KNN f1 score: 0.327
    474. 

  474. KNN cohens kappa score: 0.286
    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 1106 synthetic samples
    481. 

  481. -> retrain GAN for predict
    482. 

  482. Epoch 1/10
    483. 

  483. 
  1/115 [..............................] - ETA: 47s - loss: 0.2700
 38/115 [========>.....................] - ETA: 0s - loss: 0.1535 
 77/115 [===================>..........] - ETA: 0s - loss: 0.1577
115/115 [==============================] - 1s 1ms/step - loss: 0.1650
    484. 

  484. Epoch 2/10
    485. 

  485. 
  1/115 [..............................] - ETA: 0s - loss: 0.1856
 33/115 [=======>......................] - ETA: 0s - loss: 0.1424
 72/115 [=================>............] - ETA: 0s - loss: 0.1554
112/115 [============================>.] - ETA: 0s - loss: 0.1583
115/115 [==============================] - 0s 1ms/step - loss: 0.1620
    486. 

  486. Epoch 3/10
    487. 

  487. 
  1/115 [..............................] - ETA: 0s - loss: 0.3295
 42/115 [=========>....................] - ETA: 0s - loss: 0.1554
 82/115 [====================>.........] - ETA: 0s - loss: 0.1683
115/115 [==============================] - 0s 1ms/step - loss: 0.1691
    488. 

  488. Epoch 4/10
    489. 

  489. 
  1/115 [..............................] - ETA: 0s - loss: 0.1819
 40/115 [=========>....................] - ETA: 0s - loss: 0.1890
 80/115 [===================>..........] - ETA: 0s - loss: 0.1820
115/115 [==============================] - 0s 1ms/step - loss: 0.1706
    490. 

  490. Epoch 5/10
    491. 

  491. 
  1/115 [..............................] - ETA: 0s - loss: 0.1509
 41/115 [=========>....................] - ETA: 0s - loss: 0.1492
 79/115 [===================>..........] - ETA: 0s - loss: 0.1610
115/115 [==============================] - 0s 1ms/step - loss: 0.1584
    492. 

  492. Epoch 6/10
    493. 

  493. 
  1/115 [..............................] - ETA: 0s - loss: 0.1113
 39/115 [=========>....................] - ETA: 0s - loss: 0.1592
 81/115 [====================>.........] - ETA: 0s - loss: 0.1657
115/115 [==============================] - 0s 1ms/step - loss: 0.1631
    494. 

  494. Epoch 7/10
    495. 

  495. 
  1/115 [..............................] - ETA: 0s - loss: 0.2094
 42/115 [=========>....................] - ETA: 0s - loss: 0.1760
 82/115 [====================>.........] - ETA: 0s - loss: 0.1721
115/115 [==============================] - 0s 1ms/step - loss: 0.1603
    496. 

  496. Epoch 8/10
    497. 

  497. 
  1/115 [..............................] - ETA: 0s - loss: 0.1029
 41/115 [=========>....................] - ETA: 0s - loss: 0.1747
 82/115 [====================>.........] - ETA: 0s - loss: 0.1616
115/115 [==============================] - 0s 1ms/step - loss: 0.1575
    498. 

  498. Epoch 9/10
    499. 

  499. 
  1/115 [..............................] - ETA: 0s - loss: 0.5751
 41/115 [=========>....................] - ETA: 0s - loss: 0.1769
 81/115 [====================>.........] - ETA: 0s - loss: 0.1640
115/115 [==============================] - 0s 1ms/step - loss: 0.1599
    500. 

  500. Epoch 10/10
    501. 

  501. 
  1/115 [..............................] - ETA: 0s - loss: 0.2062
 40/115 [=========>....................] - ETA: 0s - loss: 0.1552
 78/115 [===================>..........] - ETA: 0s - loss: 0.1567
115/115 [==============================] - 0s 1ms/step - loss: 0.1571
    502. 

  502. -> test with GAN.predict
    503. 

  503. GAN tn, fp: 263, 24
    504. 

  504. GAN fn, tp: 4, 7
    505. 

  505. GAN f1 score: 0.333
    506. 

  506. GAN cohens kappa score: 0.295
    507. 

  507. 

  508. -> test with 'LR'
    509. 

  509. LR tn, fp: 255, 32
    510. 

  510. LR fn, tp: 3, 8
    511. 

  511. LR f1 score: 0.314
    512. 

  512. LR cohens kappa score: 0.272
    513. 

  513. LR average precision score: 0.310
    514. 

  514. 

  515. -> test with 'RF'
    516. 

  516. RF tn, fp: 284, 3
    517. 

  517. RF fn, tp: 7, 4
    518. 

  518. RF f1 score: 0.444
    519. 

  519. RF cohens kappa score: 0.428
    520. 

  520. 

  521. -> test with 'GB'
    522. 

  522. GB tn, fp: 279, 8
    523. 

  523. GB fn, tp: 5, 6
    524. 

  524. GB f1 score: 0.480
    525. 

  525. GB cohens kappa score: 0.458
    526. 

  526. 

  527. -> test with 'KNN'
    528. 

  528. KNN tn, fp: 267, 20
    529. 

  529. KNN fn, tp: 3, 8
    530. 

  530. KNN f1 score: 0.410
    531. 

  531. KNN cohens kappa score: 0.377
    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 1104 synthetic samples
    538. 

  538. -> retrain GAN for predict
    539. 

  539. Epoch 1/10
    540. 

  540. 
  1/115 [..............................] - ETA: 21s - loss: 0.3003
 40/115 [=========>....................] - ETA: 0s - loss: 0.2256 
 80/115 [===================>..........] - ETA: 0s - loss: 0.2197
115/115 [==============================] - 0s 1ms/step - loss: 0.2126
    541. 

  541. Epoch 2/10
    542. 

  542. 
  1/115 [..............................] - ETA: 0s - loss: 0.3454
 41/115 [=========>....................] - ETA: 0s - loss: 0.1922
 82/115 [====================>.........] - ETA: 0s - loss: 0.1889
115/115 [==============================] - 0s 1ms/step - loss: 0.2013
    543. 

  543. Epoch 3/10
    544. 

  544. 
  1/115 [..............................] - ETA: 0s - loss: 0.1420
 41/115 [=========>....................] - ETA: 0s - loss: 0.1707
 82/115 [====================>.........] - ETA: 0s - loss: 0.2010
115/115 [==============================] - 0s 1ms/step - loss: 0.1997
    545. 

  545. Epoch 4/10
    546. 

  546. 
  1/115 [..............................] - ETA: 0s - loss: 0.1951
 41/115 [=========>....................] - ETA: 0s - loss: 0.2251
 82/115 [====================>.........] - ETA: 0s - loss: 0.2094
115/115 [==============================] - 0s 1ms/step - loss: 0.1992
    547. 

  547. Epoch 5/10
    548. 

  548. 
  1/115 [..............................] - ETA: 0s - loss: 0.2690
 39/115 [=========>....................] - ETA: 0s - loss: 0.1996
 79/115 [===================>..........] - ETA: 0s - loss: 0.1931
115/115 [==============================] - 0s 1ms/step - loss: 0.2000
    549. 

  549. Epoch 6/10
    550. 

  550. 
  1/115 [..............................] - ETA: 0s - loss: 0.0417
 41/115 [=========>....................] - ETA: 0s - loss: 0.2021
 81/115 [====================>.........] - ETA: 0s - loss: 0.1935
115/115 [==============================] - 0s 1ms/step - loss: 0.1974
    551. 

  551. Epoch 7/10
    552. 

  552. 
  1/115 [..............................] - ETA: 0s - loss: 0.2230
 38/115 [========>.....................] - ETA: 0s - loss: 0.1715
 78/115 [===================>..........] - ETA: 0s - loss: 0.1987
115/115 [==============================] - 0s 1ms/step - loss: 0.1985
    553. 

  553. Epoch 8/10
    554. 

  554. 
  1/115 [..............................] - ETA: 0s - loss: 0.1704
 41/115 [=========>....................] - ETA: 0s - loss: 0.2054
 82/115 [====================>.........] - ETA: 0s - loss: 0.1896
115/115 [==============================] - 0s 1ms/step - loss: 0.1996
    555. 

  555. Epoch 9/10
    556. 

  556. 
  1/115 [..............................] - ETA: 0s - loss: 0.0661
 42/115 [=========>....................] - ETA: 0s - loss: 0.1782
 82/115 [====================>.........] - ETA: 0s - loss: 0.2000
115/115 [==============================] - 0s 1ms/step - loss: 0.1955
    557. 

  557. Epoch 10/10
    558. 

  558. 
  1/115 [..............................] - ETA: 0s - loss: 0.1630
 40/115 [=========>....................] - ETA: 0s - loss: 0.1998
 80/115 [===================>..........] - ETA: 0s - loss: 0.1899
115/115 [==============================] - 0s 1ms/step - loss: 0.1948
    559. 

  559. -> test with GAN.predict
    560. 

  560. GAN tn, fp: 268, 17
    561. 

  561. GAN fn, tp: 2, 5
    562. 

  562. GAN f1 score: 0.345
    563. 

  563. GAN cohens kappa score: 0.320
    564. 

  564. 

  565. -> test with 'LR'
    566. 

  566. LR tn, fp: 248, 37
    567. 

  567. LR fn, tp: 1, 6
    568. 

  568. LR f1 score: 0.240
    569. 

  569. LR cohens kappa score: 0.207
    570. 

  570. LR average precision score: 0.411
    571. 

  571. 

  572. -> test with 'RF'
    573. 

  573. RF tn, fp: 281, 4
    574. 

  574. RF fn, tp: 5, 2
    575. 

  575. RF f1 score: 0.308
    576. 

  576. RF cohens kappa score: 0.292
    577. 

  577. 

  578. -> test with 'GB'
    579. 

  579. GB tn, fp: 279, 6
    580. 

  580. GB fn, tp: 6, 1
    581. 

  581. GB f1 score: 0.143
    582. 

  582. GB cohens kappa score: 0.122
    583. 

  583. 

  584. -> test with 'KNN'
    585. 

  585. KNN tn, fp: 265, 20
    586. 

  586. KNN fn, tp: 2, 5
    587. 

  587. KNN f1 score: 0.312
    588. 

  588. KNN cohens kappa score: 0.286
    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 1106 synthetic samples
    599. 

  599. -> retrain GAN for predict
    600. 

  600. Epoch 1/10
    601. 

  601. 
  1/115 [..............................] - ETA: 23s - loss: 0.1778
 42/115 [=========>....................] - ETA: 0s - loss: 0.2121 
 82/115 [====================>.........] - ETA: 0s - loss: 0.1995
115/115 [==============================] - 0s 1ms/step - loss: 0.2036
    602. 

  602. Epoch 2/10
    603. 

  603. 
  1/115 [..............................] - ETA: 0s - loss: 0.1246
 41/115 [=========>....................] - ETA: 0s - loss: 0.1831
 80/115 [===================>..........] - ETA: 0s - loss: 0.1978
115/115 [==============================] - 0s 1ms/step - loss: 0.2015
    604. 

  604. Epoch 3/10
    605. 

  605. 
  1/115 [..............................] - ETA: 0s - loss: 0.0778
 38/115 [========>.....................] - ETA: 0s - loss: 0.2139
 75/115 [==================>...........] - ETA: 0s - loss: 0.2148
115/115 [==============================] - ETA: 0s - loss: 0.2036
115/115 [==============================] - 0s 1ms/step - loss: 0.2036
    606. 

  606. Epoch 4/10
    607. 

  607. 
  1/115 [..............................] - ETA: 0s - loss: 0.0367
 42/115 [=========>....................] - ETA: 0s - loss: 0.1887
 83/115 [====================>.........] - ETA: 0s - loss: 0.1837
115/115 [==============================] - 0s 1ms/step - loss: 0.2025
    608. 

  608. Epoch 5/10
    609. 

  609. 
  1/115 [..............................] - ETA: 0s - loss: 0.2089
 40/115 [=========>....................] - ETA: 0s - loss: 0.1929
 80/115 [===================>..........] - ETA: 0s - loss: 0.1982
115/115 [==============================] - 0s 1ms/step - loss: 0.1993
    610. 

  610. Epoch 6/10
    611. 

  611. 
  1/115 [..............................] - ETA: 0s - loss: 0.2134
 39/115 [=========>....................] - ETA: 0s - loss: 0.2011
 79/115 [===================>..........] - ETA: 0s - loss: 0.1954
115/115 [==============================] - 0s 1ms/step - loss: 0.1995
    612. 

  612. Epoch 7/10
    613. 

  613. 
  1/115 [..............................] - ETA: 0s - loss: 0.1244
 42/115 [=========>....................] - ETA: 0s - loss: 0.1926
 83/115 [====================>.........] - ETA: 0s - loss: 0.1948
115/115 [==============================] - 0s 1ms/step - loss: 0.2012
    614. 

  614. Epoch 8/10
    615. 

  615. 
  1/115 [..............................] - ETA: 0s - loss: 0.0358
 42/115 [=========>....................] - ETA: 0s - loss: 0.1867
 82/115 [====================>.........] - ETA: 0s - loss: 0.2010
115/115 [==============================] - 0s 1ms/step - loss: 0.2005
    616. 

  616. Epoch 9/10
    617. 

  617. 
  1/115 [..............................] - ETA: 0s - loss: 0.3690
 41/115 [=========>....................] - ETA: 0s - loss: 0.2124
 76/115 [==================>...........] - ETA: 0s - loss: 0.1928
115/115 [==============================] - 0s 1ms/step - loss: 0.1986
    618. 

  618. Epoch 10/10
    619. 

  619. 
  1/115 [..............................] - ETA: 0s - loss: 0.3767
 40/115 [=========>....................] - ETA: 0s - loss: 0.1930
 80/115 [===================>..........] - ETA: 0s - loss: 0.1858
115/115 [==============================] - 0s 1ms/step - loss: 0.1944
    620. 

  620. -> test with GAN.predict
    621. 

  621. GAN tn, fp: 243, 44
    622. 

  622. GAN fn, tp: 2, 9
    623. 

  623. GAN f1 score: 0.281
    624. 

  624. GAN cohens kappa score: 0.234
    625. 

  625. 

  626. -> test with 'LR'
    627. 

  627. LR tn, fp: 250, 37
    628. 

  628. LR fn, tp: 2, 9
    629. 

  629. LR f1 score: 0.316
    630. 

  630. LR cohens kappa score: 0.272
    631. 

  631. LR average precision score: 0.417
    632. 

  632. 

  633. -> test with 'RF'
    634. 

  634. RF tn, fp: 283, 4
    635. 

  635. RF fn, tp: 7, 4
    636. 

  636. RF f1 score: 0.421
    637. 

  637. RF cohens kappa score: 0.402
    638. 

  638. 

  639. -> test with 'GB'
    640. 

  640. GB tn, fp: 280, 7
    641. 

  641. GB fn, tp: 9, 2
    642. 

  642. GB f1 score: 0.200
    643. 

  643. GB cohens kappa score: 0.173
    644. 

  644. 

  645. -> test with 'KNN'
    646. 

  646. KNN tn, fp: 267, 20
    647. 

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

  648. KNN f1 score: 0.410
    649. 

  649. KNN cohens kappa score: 0.377
    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 1106 synthetic samples
    656. 

  656. -> retrain GAN for predict
    657. 

  657. Epoch 1/10
    658. 

  658. 
  1/115 [..............................] - ETA: 21s - loss: 0.2093
 39/115 [=========>....................] - ETA: 0s - loss: 0.2060 
 73/115 [==================>...........] - ETA: 0s - loss: 0.2098
111/115 [===========================>..] - ETA: 0s - loss: 0.2023
115/115 [==============================] - 0s 1ms/step - loss: 0.2011
    659. 

  659. Epoch 2/10
    660. 

  660. 
  1/115 [..............................] - ETA: 0s - loss: 0.2743
 40/115 [=========>....................] - ETA: 0s - loss: 0.1833
 78/115 [===================>..........] - ETA: 0s - loss: 0.1903
115/115 [==============================] - 0s 1ms/step - loss: 0.1979
    661. 

  661. Epoch 3/10
    662. 

  662. 
  1/115 [..............................] - ETA: 0s - loss: 0.2375
 36/115 [========>.....................] - ETA: 0s - loss: 0.2011
 76/115 [==================>...........] - ETA: 0s - loss: 0.1946
115/115 [==============================] - 0s 1ms/step - loss: 0.1975
    663. 

  663. Epoch 4/10
    664. 

  664. 
  1/115 [..............................] - ETA: 0s - loss: 0.2613
 41/115 [=========>....................] - ETA: 0s - loss: 0.1888
 80/115 [===================>..........] - ETA: 0s - loss: 0.1883
115/115 [==============================] - 0s 1ms/step - loss: 0.1955
    665. 

  665. Epoch 5/10
    666. 

  666. 
  1/115 [..............................] - ETA: 0s - loss: 0.1052
 41/115 [=========>....................] - ETA: 0s - loss: 0.1840
 82/115 [====================>.........] - ETA: 0s - loss: 0.1861
115/115 [==============================] - 0s 1ms/step - loss: 0.1965
    667. 

  667. Epoch 6/10
    668. 

  668. 
  1/115 [..............................] - ETA: 0s - loss: 0.5679
 41/115 [=========>....................] - ETA: 0s - loss: 0.2049
 78/115 [===================>..........] - ETA: 0s - loss: 0.1982
112/115 [============================>.] - ETA: 0s - loss: 0.1970
115/115 [==============================] - 0s 1ms/step - loss: 0.1975
    669. 

  669. Epoch 7/10
    670. 

  670. 
  1/115 [..............................] - ETA: 0s - loss: 0.0793
 36/115 [========>.....................] - ETA: 0s - loss: 0.1973
 76/115 [==================>...........] - ETA: 0s - loss: 0.1883
114/115 [============================>.] - ETA: 0s - loss: 0.1902
115/115 [==============================] - 0s 1ms/step - loss: 0.1901
    671. 

  671. Epoch 8/10
    672. 

  672. 
  1/115 [..............................] - ETA: 0s - loss: 0.2365
 40/115 [=========>....................] - ETA: 0s - loss: 0.1936
 80/115 [===================>..........] - ETA: 0s - loss: 0.2023
115/115 [==============================] - 0s 1ms/step - loss: 0.1956
    673. 

  673. Epoch 9/10
    674. 

  674. 
  1/115 [..............................] - ETA: 0s - loss: 0.2027
 42/115 [=========>....................] - ETA: 0s - loss: 0.2072
 83/115 [====================>.........] - ETA: 0s - loss: 0.1926
115/115 [==============================] - 0s 1ms/step - loss: 0.1902
    675. 

  675. Epoch 10/10
    676. 

  676. 
  1/115 [..............................] - ETA: 0s - loss: 0.1261
 41/115 [=========>....................] - ETA: 0s - loss: 0.1830
 76/115 [==================>...........] - ETA: 0s - loss: 0.1751
115/115 [==============================] - ETA: 0s - loss: 0.1904
115/115 [==============================] - 0s 1ms/step - loss: 0.1904
    677. 

  677. -> test with GAN.predict
    678. 

  678. GAN tn, fp: 262, 25
    679. 

  679. GAN fn, tp: 4, 7
    680. 

  680. GAN f1 score: 0.326
    681. 

  681. GAN cohens kappa score: 0.286
    682. 

  682. 

  683. -> test with 'LR'
    684. 

  684. LR tn, fp: 251, 36
    685. 

  685. LR fn, tp: 2, 9
    686. 

  686. LR f1 score: 0.321
    687. 

  687. LR cohens kappa score: 0.279
    688. 

  688. LR average precision score: 0.394
    689. 

  689. 

  690. -> test with 'RF'
    691. 

  691. RF tn, fp: 284, 3
    692. 

  692. RF fn, tp: 8, 3
    693. 

  693. RF f1 score: 0.353
    694. 

  694. RF cohens kappa score: 0.336
    695. 

  695. 

  696. -> test with 'GB'
    697. 

  697. GB tn, fp: 282, 5
    698. 

  698. GB fn, tp: 6, 5
    699. 

  699. GB f1 score: 0.476
    700. 

  700. GB cohens kappa score: 0.457
    701. 

  701. 

  702. -> test with 'KNN'
    703. 

  703. KNN tn, fp: 260, 27
    704. 

  704. KNN fn, tp: 1, 10
    705. 

  705. KNN f1 score: 0.417
    706. 

  706. KNN cohens kappa score: 0.381
    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 1106 synthetic samples
    713. 

  713. -> retrain GAN for predict
    714. 

  714. Epoch 1/10
    715. 

  715. 
  1/115 [..............................] - ETA: 20s - loss: 0.2439
 40/115 [=========>....................] - ETA: 0s - loss: 0.1874 
 81/115 [====================>.........] - ETA: 0s - loss: 0.1680
115/115 [==============================] - 0s 1ms/step - loss: 0.1710
    716. 

  716. Epoch 2/10
    717. 

  717. 
  1/115 [..............................] - ETA: 0s - loss: 0.1797
 37/115 [========>.....................] - ETA: 0s - loss: 0.1769
 77/115 [===================>..........] - ETA: 0s - loss: 0.1731
115/115 [==============================] - 0s 1ms/step - loss: 0.1748
    718. 

  718. Epoch 3/10
    719. 

  719. 
  1/115 [..............................] - ETA: 0s - loss: 0.0414
 41/115 [=========>....................] - ETA: 0s - loss: 0.1901
 79/115 [===================>..........] - ETA: 0s - loss: 0.1801
115/115 [==============================] - 0s 1ms/step - loss: 0.1708
    720. 

  720. Epoch 4/10
    721. 

  721. 
  1/115 [..............................] - ETA: 0s - loss: 0.0624
 42/115 [=========>....................] - ETA: 0s - loss: 0.1793
 82/115 [====================>.........] - ETA: 0s - loss: 0.1756
115/115 [==============================] - 0s 1ms/step - loss: 0.1713
    722. 

  722. Epoch 5/10
    723. 

  723. 
  1/115 [..............................] - ETA: 0s - loss: 0.2433
 40/115 [=========>....................] - ETA: 0s - loss: 0.1828
 79/115 [===================>..........] - ETA: 0s - loss: 0.1747
115/115 [==============================] - 0s 1ms/step - loss: 0.1685
    724. 

  724. Epoch 6/10
    725. 

  725. 
  1/115 [..............................] - ETA: 0s - loss: 0.3541
 41/115 [=========>....................] - ETA: 0s - loss: 0.1751
 83/115 [====================>.........] - ETA: 0s - loss: 0.1746
115/115 [==============================] - 0s 1ms/step - loss: 0.1733
    726. 

  726. Epoch 7/10
    727. 

  727. 
  1/115 [..............................] - ETA: 0s - loss: 0.1641
 38/115 [========>.....................] - ETA: 0s - loss: 0.1651
 78/115 [===================>..........] - ETA: 0s - loss: 0.1574
115/115 [==============================] - 0s 1ms/step - loss: 0.1668
    728. 

  728. Epoch 8/10
    729. 

  729. 
  1/115 [..............................] - ETA: 0s - loss: 0.3345
 40/115 [=========>....................] - ETA: 0s - loss: 0.1875
 80/115 [===================>..........] - ETA: 0s - loss: 0.1746
115/115 [==============================] - 0s 1ms/step - loss: 0.1681
    730. 

  730. Epoch 9/10
    731. 

  731. 
  1/115 [..............................] - ETA: 0s - loss: 0.0982
 42/115 [=========>....................] - ETA: 0s - loss: 0.1352
 81/115 [====================>.........] - ETA: 0s - loss: 0.1544
115/115 [==============================] - 0s 1ms/step - loss: 0.1639
    732. 

  732. Epoch 10/10
    733. 

  733. 
  1/115 [..............................] - ETA: 0s - loss: 0.2649
 41/115 [=========>....................] - ETA: 0s - loss: 0.1646
 81/115 [====================>.........] - ETA: 0s - loss: 0.1753
115/115 [==============================] - 0s 1ms/step - loss: 0.1660
    734. 

  734. -> test with GAN.predict
    735. 

  735. GAN tn, fp: 261, 26
    736. 

  736. GAN fn, tp: 4, 7
    737. 

  737. GAN f1 score: 0.318
    738. 

  738. GAN cohens kappa score: 0.278
    739. 

  739. 

  740. -> test with 'LR'
    741. 

  741. LR tn, fp: 251, 36
    742. 

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

  743. LR f1 score: 0.259
    744. 

  744. LR cohens kappa score: 0.213
    745. 

  745. LR average precision score: 0.227
    746. 

  746. 

  747. -> test with 'RF'
    748. 

  748. RF tn, fp: 281, 6
    749. 

  749. RF fn, tp: 8, 3
    750. 

  750. RF f1 score: 0.300
    751. 

  751. RF cohens kappa score: 0.276
    752. 

  752. 

  753. -> test with 'GB'
    754. 

  754. GB tn, fp: 279, 8
    755. 

  755. GB fn, tp: 8, 3
    756. 

  756. GB f1 score: 0.273
    757. 

  757. GB cohens kappa score: 0.245
    758. 

  758. 

  759. -> test with 'KNN'
    760. 

  760. KNN tn, fp: 260, 27
    761. 

  761. KNN fn, tp: 3, 8
    762. 

  762. KNN f1 score: 0.348
    763. 

  763. KNN cohens kappa score: 0.309
    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 1106 synthetic samples
    770. 

  770. -> retrain GAN for predict
    771. 

  771. Epoch 1/10
    772. 

  772. 
  1/115 [..............................] - ETA: 22s - loss: 0.2321
 37/115 [========>.....................] - ETA: 0s - loss: 0.1726 
 74/115 [==================>...........] - ETA: 0s - loss: 0.1559
112/115 [============================>.] - ETA: 0s - loss: 0.1618
115/115 [==============================] - 0s 1ms/step - loss: 0.1625
    773. 

  773. Epoch 2/10
    774. 

  774. 
  1/115 [..............................] - ETA: 0s - loss: 0.1922
 34/115 [=======>......................] - ETA: 0s - loss: 0.1726
 69/115 [=================>............] - ETA: 0s - loss: 0.1663
102/115 [=========================>....] - ETA: 0s - loss: 0.1580
115/115 [==============================] - 0s 1ms/step - loss: 0.1656
    775. 

  775. Epoch 3/10
    776. 

  776. 
  1/115 [..............................] - ETA: 0s - loss: 0.1303
 35/115 [========>.....................] - ETA: 0s - loss: 0.1518
 70/115 [=================>............] - ETA: 0s - loss: 0.1654
106/115 [==========================>...] - ETA: 0s - loss: 0.1626
115/115 [==============================] - 0s 1ms/step - loss: 0.1645
    777. 

  777. Epoch 4/10
    778. 

  778. 
  1/115 [..............................] - ETA: 0s - loss: 0.2516
 35/115 [========>.....................] - ETA: 0s - loss: 0.1543
 68/115 [================>.............] - ETA: 0s - loss: 0.1678
100/115 [=========================>....] - ETA: 0s - loss: 0.1602
115/115 [==============================] - 0s 2ms/step - loss: 0.1608
    779. 

  779. Epoch 5/10
    780. 

  780. 
  1/115 [..............................] - ETA: 0s - loss: 0.2231
 36/115 [========>.....................] - ETA: 0s - loss: 0.1350
 72/115 [=================>............] - ETA: 0s - loss: 0.1592
107/115 [==========================>...] - ETA: 0s - loss: 0.1551
115/115 [==============================] - 0s 1ms/step - loss: 0.1586
    781. 

  781. Epoch 6/10
    782. 

  782. 
  1/115 [..............................] - ETA: 0s - loss: 0.4055
 40/115 [=========>....................] - ETA: 0s - loss: 0.1558
 75/115 [==================>...........] - ETA: 0s - loss: 0.1634
111/115 [===========================>..] - ETA: 0s - loss: 0.1610
115/115 [==============================] - 0s 1ms/step - loss: 0.1608
    783. 

  783. Epoch 7/10
    784. 

  784. 
  1/115 [..............................] - ETA: 0s - loss: 0.1155
 38/115 [========>.....................] - ETA: 0s - loss: 0.1721
 68/115 [================>.............] - ETA: 0s - loss: 0.1736
101/115 [=========================>....] - ETA: 0s - loss: 0.1596
115/115 [==============================] - 0s 2ms/step - loss: 0.1572
    785. 

  785. Epoch 8/10
    786. 

  786. 
  1/115 [..............................] - ETA: 0s - loss: 0.1256
 35/115 [========>.....................] - ETA: 0s - loss: 0.1591
 70/115 [=================>............] - ETA: 0s - loss: 0.1665
106/115 [==========================>...] - ETA: 0s - loss: 0.1620
115/115 [==============================] - 0s 1ms/step - loss: 0.1590
    787. 

  787. Epoch 9/10
    788. 

  788. 
  1/115 [..............................] - ETA: 0s - loss: 0.1149
 32/115 [=======>......................] - ETA: 0s - loss: 0.1634
 64/115 [===============>..............] - ETA: 0s - loss: 0.1729
 99/115 [========================>.....] - ETA: 0s - loss: 0.1740
115/115 [==============================] - 0s 2ms/step - loss: 0.1590
    789. 

  789. Epoch 10/10
    790. 

  790. 
  1/115 [..............................] - ETA: 0s - loss: 0.2100
 34/115 [=======>......................] - ETA: 0s - loss: 0.1581
 68/115 [================>.............] - ETA: 0s - loss: 0.1510
104/115 [==========================>...] - ETA: 0s - loss: 0.1588
115/115 [==============================] - 0s 1ms/step - loss: 0.1559
    791. 

  791. -> test with GAN.predict
    792. 

  792. GAN tn, fp: 269, 18
    793. 

  793. GAN fn, tp: 4, 7
    794. 

  794. GAN f1 score: 0.389
    795. 

  795. GAN cohens kappa score: 0.356
    796. 

  796. 

  797. -> test with 'LR'
    798. 

  798. LR tn, fp: 254, 33
    799. 

  799. LR fn, tp: 3, 8
    800. 

  800. LR f1 score: 0.308
    801. 

  801. LR cohens kappa score: 0.265
    802. 

  802. LR average precision score: 0.444
    803. 

  803. 

  804. -> test with 'RF'
    805. 

  805. RF tn, fp: 280, 7
    806. 

  806. RF fn, tp: 7, 4
    807. 

  807. RF f1 score: 0.364
    808. 

  808. RF cohens kappa score: 0.339
    809. 

  809. 

  810. -> test with 'GB'
    811. 

  811. GB tn, fp: 277, 10
    812. 

  812. GB fn, tp: 5, 6
    813. 

  813. GB f1 score: 0.444
    814. 

  814. GB cohens kappa score: 0.419
    815. 

  815. 

  816. -> test with 'KNN'
    817. 

  817. KNN tn, fp: 269, 18
    818. 

  818. KNN fn, tp: 4, 7
    819. 

  819. KNN f1 score: 0.389
    820. 

  820. KNN cohens kappa score: 0.356
    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 1104 synthetic samples
    827. 

  827. -> retrain GAN for predict
    828. 

  828. Epoch 1/10
    829. 

  829. 
  1/115 [..............................] - ETA: 20s - loss: 0.2777
 38/115 [========>.....................] - ETA: 0s - loss: 0.1871 
 73/115 [==================>...........] - ETA: 0s - loss: 0.1893
106/115 [==========================>...] - ETA: 0s - loss: 0.1831
115/115 [==============================] - 0s 1ms/step - loss: 0.1849
    830. 

  830. Epoch 2/10
    831. 

  831. 
  1/115 [..............................] - ETA: 0s - loss: 0.2044
 39/115 [=========>....................] - ETA: 0s - loss: 0.1901
 76/115 [==================>...........] - ETA: 0s - loss: 0.1860
115/115 [==============================] - ETA: 0s - loss: 0.1809
115/115 [==============================] - 0s 1ms/step - loss: 0.1809
    832. 

  832. Epoch 3/10
    833. 

  833. 
  1/115 [..............................] - ETA: 0s - loss: 0.0613
 40/115 [=========>....................] - ETA: 0s - loss: 0.1773
 79/115 [===================>..........] - ETA: 0s - loss: 0.1802
115/115 [==============================] - 0s 1ms/step - loss: 0.1729
    834. 

  834. Epoch 4/10
    835. 

  835. 
  1/115 [..............................] - ETA: 0s - loss: 0.1221
 40/115 [=========>....................] - ETA: 0s - loss: 0.1602
 81/115 [====================>.........] - ETA: 0s - loss: 0.1670
115/115 [==============================] - 0s 1ms/step - loss: 0.1722
    836. 

  836. Epoch 5/10
    837. 

  837. 
  1/115 [..............................] - ETA: 0s - loss: 0.0648
 42/115 [=========>....................] - ETA: 0s - loss: 0.1627
 83/115 [====================>.........] - ETA: 0s - loss: 0.1571
115/115 [==============================] - 0s 1ms/step - loss: 0.1750
    838. 

  838. Epoch 6/10
    839. 

  839. 
  1/115 [..............................] - ETA: 0s - loss: 0.2864
 41/115 [=========>....................] - ETA: 0s - loss: 0.1719
 81/115 [====================>.........] - ETA: 0s - loss: 0.1637
115/115 [==============================] - 0s 1ms/step - loss: 0.1716
    840. 

  840. Epoch 7/10
    841. 

  841. 
  1/115 [..............................] - ETA: 0s - loss: 0.1152
 42/115 [=========>....................] - ETA: 0s - loss: 0.2003
 82/115 [====================>.........] - ETA: 0s - loss: 0.1722
115/115 [==============================] - 0s 1ms/step - loss: 0.1717
    842. 

  842. Epoch 8/10
    843. 

  843. 
  1/115 [..............................] - ETA: 0s - loss: 0.0696
 41/115 [=========>....................] - ETA: 0s - loss: 0.1746
 81/115 [====================>.........] - ETA: 0s - loss: 0.1695
115/115 [==============================] - 0s 1ms/step - loss: 0.1709
    844. 

  844. Epoch 9/10
    845. 

  845. 
  1/115 [..............................] - ETA: 0s - loss: 0.1466
 41/115 [=========>....................] - ETA: 0s - loss: 0.2006
 82/115 [====================>.........] - ETA: 0s - loss: 0.1714
115/115 [==============================] - 0s 1ms/step - loss: 0.1729
    846. 

  846. Epoch 10/10
    847. 

  847. 
  1/115 [..............................] - ETA: 0s - loss: 0.0536
 34/115 [=======>......................] - ETA: 0s - loss: 0.1821
 62/115 [===============>..............] - ETA: 0s - loss: 0.1847
 92/115 [=======================>......] - ETA: 0s - loss: 0.1794
115/115 [==============================] - 0s 2ms/step - loss: 0.1719
    848. 

  848. -> test with GAN.predict
    849. 

  849. GAN tn, fp: 263, 22
    850. 

  850. GAN fn, tp: 5, 2
    851. 

  851. GAN f1 score: 0.129
    852. 

  852. GAN cohens kappa score: 0.095
    853. 

  853. 

  854. -> test with 'LR'
    855. 

  855. LR tn, fp: 251, 34
    856. 

  856. LR fn, tp: 2, 5
    857. 

  857. LR f1 score: 0.217
    858. 

  858. LR cohens kappa score: 0.184
    859. 

  859. LR average precision score: 0.427
    860. 

  860. 

  861. -> test with 'RF'
    862. 

  862. RF tn, fp: 281, 4
    863. 

  863. RF fn, tp: 5, 2
    864. 

  864. RF f1 score: 0.308
    865. 

  865. RF cohens kappa score: 0.292
    866. 

  866. 

  867. -> test with 'GB'
    868. 

  868. GB tn, fp: 279, 6
    869. 

  869. GB fn, tp: 4, 3
    870. 

  870. GB f1 score: 0.375
    871. 

  871. GB cohens kappa score: 0.358
    872. 

  872. 

  873. -> test with 'KNN'
    874. 

  874. KNN tn, fp: 259, 26
    875. 

  875. KNN fn, tp: 2, 5
    876. 

  876. KNN f1 score: 0.263
    877. 

  877. KNN cohens kappa score: 0.233
    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 1106 synthetic samples
    888. 

  888. -> retrain GAN for predict
    889. 

  889. Epoch 1/10
    890. 

  890. 
  1/115 [..............................] - ETA: 19s - loss: 0.1528
 39/115 [=========>....................] - ETA: 0s - loss: 0.1515 
 79/115 [===================>..........] - ETA: 0s - loss: 0.1534
115/115 [==============================] - 0s 1ms/step - loss: 0.1601
    891. 

  891. Epoch 2/10
    892. 

  892. 
  1/115 [..............................] - ETA: 0s - loss: 0.2879
 41/115 [=========>....................] - ETA: 0s - loss: 0.1501
 81/115 [====================>.........] - ETA: 0s - loss: 0.1586
115/115 [==============================] - 0s 1ms/step - loss: 0.1587
    893. 

  893. Epoch 3/10
    894. 

  894. 
  1/115 [..............................] - ETA: 0s - loss: 0.1684
 42/115 [=========>....................] - ETA: 0s - loss: 0.1376
 80/115 [===================>..........] - ETA: 0s - loss: 0.1503
115/115 [==============================] - 0s 1ms/step - loss: 0.1548
    895. 

  895. Epoch 4/10
    896. 

  896. 
  1/115 [..............................] - ETA: 0s - loss: 0.1316
 40/115 [=========>....................] - ETA: 0s - loss: 0.1659
 80/115 [===================>..........] - ETA: 0s - loss: 0.1544
115/115 [==============================] - 0s 1ms/step - loss: 0.1568
    897. 

  897. Epoch 5/10
    898. 

  898. 
  1/115 [..............................] - ETA: 0s - loss: 0.2023
 40/115 [=========>....................] - ETA: 0s - loss: 0.1509
 80/115 [===================>..........] - ETA: 0s - loss: 0.1616
115/115 [==============================] - 0s 1ms/step - loss: 0.1590
    899. 

  899. Epoch 6/10
    900. 

  900. 
  1/115 [..............................] - ETA: 0s - loss: 0.0983
 39/115 [=========>....................] - ETA: 0s - loss: 0.1430
 79/115 [===================>..........] - ETA: 0s - loss: 0.1594
115/115 [==============================] - 0s 1ms/step - loss: 0.1514
    901. 

  901. Epoch 7/10
    902. 

  902. 
  1/115 [..............................] - ETA: 0s - loss: 0.1212
 37/115 [========>.....................] - ETA: 0s - loss: 0.1625
 70/115 [=================>............] - ETA: 0s - loss: 0.1450
102/115 [=========================>....] - ETA: 0s - loss: 0.1549
115/115 [==============================] - 0s 1ms/step - loss: 0.1530
    903. 

  903. Epoch 8/10
    904. 

  904. 
  1/115 [..............................] - ETA: 0s - loss: 0.1013
 40/115 [=========>....................] - ETA: 0s - loss: 0.1456
 79/115 [===================>..........] - ETA: 0s - loss: 0.1521
115/115 [==============================] - 0s 1ms/step - loss: 0.1512
    905. 

  905. Epoch 9/10
    906. 

  906. 
  1/115 [..............................] - ETA: 0s - loss: 0.0759
 40/115 [=========>....................] - ETA: 0s - loss: 0.1302
 81/115 [====================>.........] - ETA: 0s - loss: 0.1447
115/115 [==============================] - 0s 1ms/step - loss: 0.1549
    907. 

  907. Epoch 10/10
    908. 

  908. 
  1/115 [..............................] - ETA: 0s - loss: 0.1134
 41/115 [=========>....................] - ETA: 0s - loss: 0.1649
 81/115 [====================>.........] - ETA: 0s - loss: 0.1551
115/115 [==============================] - 0s 1ms/step - loss: 0.1537
    909. 

  909. -> test with GAN.predict
    910. 

  910. GAN tn, fp: 274, 13
    911. 

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

  912. GAN f1 score: 0.400
    913. 

  913. GAN cohens kappa score: 0.371
    914. 

  914. 

  915. -> test with 'LR'
    916. 

  916. LR tn, fp: 262, 25
    917. 

  917. LR fn, tp: 5, 6
    918. 

  918. LR f1 score: 0.286
    919. 

  919. LR cohens kappa score: 0.245
    920. 

  920. LR average precision score: 0.449
    921. 

  921. 

  922. -> test with 'RF'
    923. 

  923. RF tn, fp: 286, 1
    924. 

  924. RF fn, tp: 8, 3
    925. 

  925. RF f1 score: 0.400
    926. 

  926. RF cohens kappa score: 0.388
    927. 

  927. 

  928. -> test with 'GB'
    929. 

  929. GB tn, fp: 282, 5
    930. 

  930. GB fn, tp: 6, 5
    931. 

  931. GB f1 score: 0.476
    932. 

  932. GB cohens kappa score: 0.457
    933. 

  933. 

  934. -> test with 'KNN'
    935. 

  935. KNN tn, fp: 274, 13
    936. 

  936. KNN fn, tp: 6, 5
    937. 

  937. KNN f1 score: 0.345
    938. 

  938. KNN cohens kappa score: 0.313
    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 1106 synthetic samples
    945. 

  945. -> retrain GAN for predict
    946. 

  946. Epoch 1/10
    947. 

  947. 
  1/115 [..............................] - ETA: 18s - loss: 0.2011
 42/115 [=========>....................] - ETA: 0s - loss: 0.2123 
 84/115 [====================>.........] - ETA: 0s - loss: 0.2070
115/115 [==============================] - 0s 1ms/step - loss: 0.1951
    948. 

  948. Epoch 2/10
    949. 

  949. 
  1/115 [..............................] - ETA: 0s - loss: 0.0886
 42/115 [=========>....................] - ETA: 0s - loss: 0.1897
 84/115 [====================>.........] - ETA: 0s - loss: 0.1870
115/115 [==============================] - 0s 1ms/step - loss: 0.1957
    950. 

  950. Epoch 3/10
    951. 

  951. 
  1/115 [..............................] - ETA: 0s - loss: 0.1696
 42/115 [=========>....................] - ETA: 0s - loss: 0.2151
 82/115 [====================>.........] - ETA: 0s - loss: 0.1970
115/115 [==============================] - 0s 1ms/step - loss: 0.1972
    952. 

  952. Epoch 4/10
    953. 

  953. 
  1/115 [..............................] - ETA: 0s - loss: 0.5208
 42/115 [=========>....................] - ETA: 0s - loss: 0.2355
 83/115 [====================>.........] - ETA: 0s - loss: 0.1980
115/115 [==============================] - 0s 1ms/step - loss: 0.1906
    954. 

  954. Epoch 5/10
    955. 

  955. 
  1/115 [..............................] - ETA: 0s - loss: 0.0221
 41/115 [=========>....................] - ETA: 0s - loss: 0.1580
 80/115 [===================>..........] - ETA: 0s - loss: 0.1761
115/115 [==============================] - 0s 1ms/step - loss: 0.1904
    956. 

  956. Epoch 6/10
    957. 

  957. 
  1/115 [..............................] - ETA: 0s - loss: 0.1375
 42/115 [=========>....................] - ETA: 0s - loss: 0.1879
 82/115 [====================>.........] - ETA: 0s - loss: 0.1861
115/115 [==============================] - 0s 1ms/step - loss: 0.1923
    958. 

  958. Epoch 7/10
    959. 

  959. 
  1/115 [..............................] - ETA: 0s - loss: 0.1185
 40/115 [=========>....................] - ETA: 0s - loss: 0.2072
 79/115 [===================>..........] - ETA: 0s - loss: 0.1932
115/115 [==============================] - 0s 1ms/step - loss: 0.1918
    960. 

  960. Epoch 8/10
    961. 

  961. 
  1/115 [..............................] - ETA: 0s - loss: 0.2248
 34/115 [=======>......................] - ETA: 0s - loss: 0.1854
 69/115 [=================>............] - ETA: 0s - loss: 0.1891
103/115 [=========================>....] - ETA: 0s - loss: 0.1928
115/115 [==============================] - 0s 1ms/step - loss: 0.1891
    962. 

  962. Epoch 9/10
    963. 

  963. 
  1/115 [..............................] - ETA: 0s - loss: 0.2268
 41/115 [=========>....................] - ETA: 0s - loss: 0.1940
 80/115 [===================>..........] - ETA: 0s - loss: 0.1941
115/115 [==============================] - 0s 1ms/step - loss: 0.1896
    964. 

  964. Epoch 10/10
    965. 

  965. 
  1/115 [..............................] - ETA: 0s - loss: 0.1440
 40/115 [=========>....................] - ETA: 0s - loss: 0.1593
 80/115 [===================>..........] - ETA: 0s - loss: 0.1899
115/115 [==============================] - 0s 1ms/step - loss: 0.1849
    966. 

  966. -> test with GAN.predict
    967. 

  967. GAN tn, fp: 248, 39
    968. 

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

  969. GAN f1 score: 0.214
    970. 

  970. GAN cohens kappa score: 0.165
    971. 

  971. 

  972. -> test with 'LR'
    973. 

  973. LR tn, fp: 252, 35
    974. 

  974. LR fn, tp: 2, 9
    975. 

  975. LR f1 score: 0.327
    976. 

  976. LR cohens kappa score: 0.285
    977. 

  977. LR average precision score: 0.377
    978. 

  978. 

  979. -> test with 'RF'
    980. 

  980. RF tn, fp: 285, 2
    981. 

  981. RF fn, tp: 7, 4
    982. 

  982. RF f1 score: 0.471
    983. 

  983. RF cohens kappa score: 0.456
    984. 

  984. 

  985. -> test with 'GB'
    986. 

  986. GB tn, fp: 281, 6
    987. 

  987. GB fn, tp: 8, 3
    988. 

  988. GB f1 score: 0.300
    989. 

  989. GB cohens kappa score: 0.276
    990. 

  990. 

  991. -> test with 'KNN'
    992. 

  992. KNN tn, fp: 260, 27
    993. 

  993. KNN fn, tp: 4, 7
    994. 

  994. KNN f1 score: 0.311
    995. 

  995. KNN cohens kappa score: 0.270
    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 1106 synthetic samples
    1002. 

  1002. -> retrain GAN for predict
    1003. 

  1003. Epoch 1/10
    1004. 

  1004. 
  1/115 [..............................] - ETA: 20s - loss: 0.1318
 40/115 [=========>....................] - ETA: 0s - loss: 0.1719 
 79/115 [===================>..........] - ETA: 0s - loss: 0.1776
115/115 [==============================] - 0s 1ms/step - loss: 0.1828
    1005. 

  1005. Epoch 2/10
    1006. 

  1006. 
  1/115 [..............................] - ETA: 0s - loss: 0.1919
 42/115 [=========>....................] - ETA: 0s - loss: 0.1784
 80/115 [===================>..........] - ETA: 0s - loss: 0.1795
115/115 [==============================] - 0s 1ms/step - loss: 0.1839
    1007. 

  1007. Epoch 3/10
    1008. 

  1008. 
  1/115 [..............................] - ETA: 0s - loss: 0.1370
 41/115 [=========>....................] - ETA: 0s - loss: 0.1663
 81/115 [====================>.........] - ETA: 0s - loss: 0.1720
115/115 [==============================] - 0s 1ms/step - loss: 0.1798
    1009. 

  1009. Epoch 4/10
    1010. 

  1010. 
  1/115 [..............................] - ETA: 0s - loss: 0.2946
 39/115 [=========>....................] - ETA: 0s - loss: 0.1792
 80/115 [===================>..........] - ETA: 0s - loss: 0.1730
115/115 [==============================] - 0s 1ms/step - loss: 0.1806
    1011. 

  1011. Epoch 5/10
    1012. 

  1012. 
  1/115 [..............................] - ETA: 0s - loss: 0.0510
 43/115 [==========>...................] - ETA: 0s - loss: 0.1428
 83/115 [====================>.........] - ETA: 0s - loss: 0.1607
115/115 [==============================] - 0s 1ms/step - loss: 0.1778
    1013. 

  1013. Epoch 6/10
    1014. 

  1014. 
  1/115 [..............................] - ETA: 0s - loss: 0.4117
 37/115 [========>.....................] - ETA: 0s - loss: 0.1550
 72/115 [=================>............] - ETA: 0s - loss: 0.1794
111/115 [===========================>..] - ETA: 0s - loss: 0.1748
115/115 [==============================] - 0s 1ms/step - loss: 0.1742
    1015. 

  1015. Epoch 7/10
    1016. 

  1016. 
  1/115 [..............................] - ETA: 0s - loss: 0.2667
 42/115 [=========>....................] - ETA: 0s - loss: 0.1654
 82/115 [====================>.........] - ETA: 0s - loss: 0.1652
115/115 [==============================] - 0s 1ms/step - loss: 0.1724
    1017. 

  1017. Epoch 8/10
    1018. 

  1018. 
  1/115 [..............................] - ETA: 0s - loss: 0.3016
 40/115 [=========>....................] - ETA: 0s - loss: 0.1691
 80/115 [===================>..........] - ETA: 0s - loss: 0.1789
115/115 [==============================] - 0s 1ms/step - loss: 0.1756
    1019. 

  1019. Epoch 9/10
    1020. 

  1020. 
  1/115 [..............................] - ETA: 0s - loss: 0.0390
 35/115 [========>.....................] - ETA: 0s - loss: 0.1893
 68/115 [================>.............] - ETA: 0s - loss: 0.1778
105/115 [==========================>...] - ETA: 0s - loss: 0.1728
115/115 [==============================] - 0s 1ms/step - loss: 0.1713
    1021. 

  1021. Epoch 10/10
    1022. 

  1022. 
  1/115 [..............................] - ETA: 0s - loss: 0.0529
 42/115 [=========>....................] - ETA: 0s - loss: 0.1799
 82/115 [====================>.........] - ETA: 0s - loss: 0.1804
115/115 [==============================] - 0s 1ms/step - loss: 0.1705
    1023. 

  1023. -> test with GAN.predict
    1024. 

  1024. GAN tn, fp: 268, 19
    1025. 

  1025. GAN fn, tp: 5, 6
    1026. 

  1026. GAN f1 score: 0.333
    1027. 

  1027. GAN cohens kappa score: 0.297
    1028. 

  1028. 

  1029. -> test with 'LR'
    1030. 

  1030. LR tn, fp: 246, 41
    1031. 

  1031. LR fn, tp: 2, 9
    1032. 

  1032. LR f1 score: 0.295
    1033. 

  1033. LR cohens kappa score: 0.250
    1034. 

  1034. LR average precision score: 0.245
    1035. 

  1035. 

  1036. -> test with 'RF'
    1037. 

  1037. RF tn, fp: 283, 4
    1038. 

  1038. RF fn, tp: 11, 0
    1039. 

  1039. RF f1 score: 0.000
    1040. 

  1040. RF cohens kappa score: -0.020
    1041. 

  1041. 

  1042. -> test with 'GB'
    1043. 

  1043. GB tn, fp: 283, 4
    1044. 

  1044. GB fn, tp: 8, 3
    1045. 

  1045. GB f1 score: 0.333
    1046. 

  1046. GB cohens kappa score: 0.314
    1047. 

  1047. 

  1048. -> test with 'KNN'
    1049. 

  1049. KNN tn, fp: 260, 27
    1050. 

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

  1051. KNN f1 score: 0.383
    1052. 

  1052. KNN cohens kappa score: 0.346
    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 1106 synthetic samples
    1059. 

  1059. -> retrain GAN for predict
    1060. 

  1060. Epoch 1/10
    1061. 

  1061. 
  1/115 [..............................] - ETA: 17s - loss: 0.1409
 42/115 [=========>....................] - ETA: 0s - loss: 0.1675 
 80/115 [===================>..........] - ETA: 0s - loss: 0.1678
115/115 [==============================] - 0s 1ms/step - loss: 0.1665
    1062. 

  1062. Epoch 2/10
    1063. 

  1063. 
  1/115 [..............................] - ETA: 0s - loss: 0.0255
 42/115 [=========>....................] - ETA: 0s - loss: 0.1627
 82/115 [====================>.........] - ETA: 0s - loss: 0.1659
115/115 [==============================] - 0s 1ms/step - loss: 0.1625
    1064. 

  1064. Epoch 3/10
    1065. 

  1065. 
  1/115 [..............................] - ETA: 0s - loss: 0.1608
 41/115 [=========>....................] - ETA: 0s - loss: 0.1601
 82/115 [====================>.........] - ETA: 0s - loss: 0.1597
115/115 [==============================] - 0s 1ms/step - loss: 0.1610
    1066. 

  1066. Epoch 4/10
    1067. 

  1067. 
  1/115 [..............................] - ETA: 0s - loss: 0.0714
 41/115 [=========>....................] - ETA: 0s - loss: 0.1609
 83/115 [====================>.........] - ETA: 0s - loss: 0.1562
115/115 [==============================] - 0s 1ms/step - loss: 0.1601
    1068. 

  1068. Epoch 5/10
    1069. 

  1069. 
  1/115 [..............................] - ETA: 0s - loss: 0.1351
 41/115 [=========>....................] - ETA: 0s - loss: 0.1252
 82/115 [====================>.........] - ETA: 0s - loss: 0.1494
115/115 [==============================] - 0s 1ms/step - loss: 0.1589
    1070. 

  1070. Epoch 6/10
    1071. 

  1071. 
  1/115 [..............................] - ETA: 0s - loss: 0.2603
 42/115 [=========>....................] - ETA: 0s - loss: 0.1416
 82/115 [====================>.........] - ETA: 0s - loss: 0.1566
115/115 [==============================] - 0s 1ms/step - loss: 0.1602
    1072. 

  1072. Epoch 7/10
    1073. 

  1073. 
  1/115 [..............................] - ETA: 0s - loss: 0.2105
 41/115 [=========>....................] - ETA: 0s - loss: 0.1738
 82/115 [====================>.........] - ETA: 0s - loss: 0.1599
115/115 [==============================] - 0s 1ms/step - loss: 0.1603
    1074. 

  1074. Epoch 8/10
    1075. 

  1075. 
  1/115 [..............................] - ETA: 0s - loss: 0.1206
 39/115 [=========>....................] - ETA: 0s - loss: 0.1349
 78/115 [===================>..........] - ETA: 0s - loss: 0.1495
115/115 [==============================] - 0s 1ms/step - loss: 0.1560
    1076. 

  1076. Epoch 9/10
    1077. 

  1077. 
  1/115 [..............................] - ETA: 0s - loss: 0.1735
 38/115 [========>.....................] - ETA: 0s - loss: 0.1637
 79/115 [===================>..........] - ETA: 0s - loss: 0.1629
115/115 [==============================] - 0s 1ms/step - loss: 0.1563
    1078. 

  1078. Epoch 10/10
    1079. 

  1079. 
  1/115 [..............................] - ETA: 0s - loss: 0.1338
 42/115 [=========>....................] - ETA: 0s - loss: 0.1463
 83/115 [====================>.........] - ETA: 0s - loss: 0.1517
115/115 [==============================] - 0s 1ms/step - loss: 0.1544
    1080. 

  1080. -> test with GAN.predict
    1081. 

  1081. GAN tn, fp: 264, 23
    1082. 

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

  1083. GAN f1 score: 0.341
    1084. 

  1084. GAN cohens kappa score: 0.304
    1085. 

  1085. 

  1086. -> test with 'LR'
    1087. 

  1087. LR tn, fp: 247, 40
    1088. 

  1088. LR fn, tp: 3, 8
    1089. 

  1089. LR f1 score: 0.271
    1090. 

  1090. LR cohens kappa score: 0.225
    1091. 

  1091. LR average precision score: 0.293
    1092. 

  1092. 

  1093. -> test with 'RF'
    1094. 

  1094. RF tn, fp: 280, 7
    1095. 

  1095. RF fn, tp: 6, 5
    1096. 

  1096. RF f1 score: 0.435
    1097. 

  1097. RF cohens kappa score: 0.412
    1098. 

  1098. 

  1099. -> test with 'GB'
    1100. 

  1100. GB tn, fp: 274, 13
    1101. 

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

  1102. GB f1 score: 0.345
    1103. 

  1103. GB cohens kappa score: 0.313
    1104. 

  1104. 

  1105. -> test with 'KNN'
    1106. 

  1106. KNN tn, fp: 261, 26
    1107. 

  1107. KNN fn, tp: 3, 8
    1108. 

  1108. KNN f1 score: 0.356
    1109. 

  1109. KNN cohens kappa score: 0.317
    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 1104 synthetic samples
    1116. 

  1116. -> retrain GAN for predict
    1117. 

  1117. Epoch 1/10
    1118. 

  1118. 
  1/115 [..............................] - ETA: 20s - loss: 0.2141
 42/115 [=========>....................] - ETA: 0s - loss: 0.2116 
 82/115 [====================>.........] - ETA: 0s - loss: 0.2034
115/115 [==============================] - 0s 1ms/step - loss: 0.2087
    1119. 

  1119. Epoch 2/10
    1120. 

  1120. 
  1/115 [..............................] - ETA: 0s - loss: 0.6608
 39/115 [=========>....................] - ETA: 0s - loss: 0.2280
 79/115 [===================>..........] - ETA: 0s - loss: 0.2155
115/115 [==============================] - 0s 1ms/step - loss: 0.2097
    1121. 

  1121. Epoch 3/10
    1122. 

  1122. 
  1/115 [..............................] - ETA: 0s - loss: 0.0412
 42/115 [=========>....................] - ETA: 0s - loss: 0.2119
 82/115 [====================>.........] - ETA: 0s - loss: 0.2081
115/115 [==============================] - 0s 1ms/step - loss: 0.2018
    1123. 

  1123. Epoch 4/10
    1124. 

  1124. 
  1/115 [..............................] - ETA: 0s - loss: 0.1700
 42/115 [=========>....................] - ETA: 0s - loss: 0.1927
 82/115 [====================>.........] - ETA: 0s - loss: 0.2033
115/115 [==============================] - 0s 1ms/step - loss: 0.1990
    1125. 

  1125. Epoch 5/10
    1126. 

  1126. 
  1/115 [..............................] - ETA: 0s - loss: 0.0497
 41/115 [=========>....................] - ETA: 0s - loss: 0.2064
 81/115 [====================>.........] - ETA: 0s - loss: 0.1879
115/115 [==============================] - 0s 1ms/step - loss: 0.2029
    1127. 

  1127. Epoch 6/10
    1128. 

  1128. 
  1/115 [..............................] - ETA: 0s - loss: 0.2349
 41/115 [=========>....................] - ETA: 0s - loss: 0.2178
 80/115 [===================>..........] - ETA: 0s - loss: 0.2104
114/115 [============================>.] - ETA: 0s - loss: 0.2002
115/115 [==============================] - 0s 1ms/step - loss: 0.1994
    1129. 

  1129. Epoch 7/10
    1130. 

  1130. 
  1/115 [..............................] - ETA: 0s - loss: 0.1337
 38/115 [========>.....................] - ETA: 0s - loss: 0.1858
 78/115 [===================>..........] - ETA: 0s - loss: 0.1874
115/115 [==============================] - 0s 1ms/step - loss: 0.1990
    1131. 

  1131. Epoch 8/10
    1132. 

  1132. 
  1/115 [..............................] - ETA: 0s - loss: 0.1225
 33/115 [=======>......................] - ETA: 0s - loss: 0.2083
 68/115 [================>.............] - ETA: 0s - loss: 0.2005
103/115 [=========================>....] - ETA: 0s - loss: 0.1902
115/115 [==============================] - 0s 1ms/step - loss: 0.1964
    1133. 

  1133. Epoch 9/10
    1134. 

  1134. 
  1/115 [..............................] - ETA: 0s - loss: 0.0938
 39/115 [=========>....................] - ETA: 0s - loss: 0.2024
 78/115 [===================>..........] - ETA: 0s - loss: 0.1999
115/115 [==============================] - 0s 1ms/step - loss: 0.1965
    1135. 

  1135. Epoch 10/10
    1136. 

  1136. 
  1/115 [..............................] - ETA: 0s - loss: 0.2296
 41/115 [=========>....................] - ETA: 0s - loss: 0.1879
 81/115 [====================>.........] - ETA: 0s - loss: 0.2022
115/115 [==============================] - 0s 1ms/step - loss: 0.1952
    1137. 

  1137. -> test with GAN.predict
    1138. 

  1138. GAN tn, fp: 257, 28
    1139. 

  1139. GAN fn, tp: 2, 5
    1140. 

  1140. GAN f1 score: 0.250
    1141. 

  1141. GAN cohens kappa score: 0.219
    1142. 

  1142. 

  1143. -> test with 'LR'
    1144. 

  1144. LR tn, fp: 249, 36
    1145. 

  1145. LR fn, tp: 2, 5
    1146. 

  1146. LR f1 score: 0.208
    1147. 

  1147. LR cohens kappa score: 0.175
    1148. 

  1148. LR average precision score: 0.436
    1149. 

  1149. 

  1150. -> test with 'RF'
    1151. 

  1151. RF tn, fp: 280, 5
    1152. 

  1152. RF fn, tp: 3, 4
    1153. 

  1153. RF f1 score: 0.500
    1154. 

  1154. RF cohens kappa score: 0.486
    1155. 

  1155. 

  1156. -> test with 'GB'
    1157. 

  1157. GB tn, fp: 279, 6
    1158. 

  1158. GB fn, tp: 4, 3
    1159. 

  1159. GB f1 score: 0.375
    1160. 

  1160. GB cohens kappa score: 0.358
    1161. 

  1161. 

  1162. -> test with 'KNN'
    1163. 

  1163. KNN tn, fp: 260, 25
    1164. 

  1164. KNN fn, tp: 2, 5
    1165. 

  1165. KNN f1 score: 0.270
    1166. 

  1166. KNN cohens kappa score: 0.241
    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 1106 synthetic samples
    1177. 

  1177. -> retrain GAN for predict
    1178. 

  1178. Epoch 1/10
    1179. 

  1179. 
  1/115 [..............................] - ETA: 18s - loss: 0.2423
 42/115 [=========>....................] - ETA: 0s - loss: 0.1934 
 84/115 [====================>.........] - ETA: 0s - loss: 0.1983
115/115 [==============================] - 0s 1ms/step - loss: 0.1986
    1180. 

  1180. Epoch 2/10
    1181. 

  1181. 
  1/115 [..............................] - ETA: 0s - loss: 0.2247
 22/115 [====>.........................] - ETA: 1s - loss: 0.2018
 48/115 [===========>..................] - ETA: 0s - loss: 0.2032
 89/115 [======================>.......] - ETA: 0s - loss: 0.1967
115/115 [==============================] - 0s 3ms/step - loss: 0.1957
    1182. 

  1182. Epoch 3/10
    1183. 

  1183. 
  1/115 [..............................] - ETA: 0s - loss: 0.2477
 41/115 [=========>....................] - ETA: 0s - loss: 0.1890
 81/115 [====================>.........] - ETA: 0s - loss: 0.2012
115/115 [==============================] - 0s 1ms/step - loss: 0.1960
    1184. 

  1184. Epoch 4/10
    1185. 

  1185. 
  1/115 [..............................] - ETA: 0s - loss: 0.2355
 41/115 [=========>....................] - ETA: 0s - loss: 0.1844
 82/115 [====================>.........] - ETA: 0s - loss: 0.1912
115/115 [==============================] - 0s 1ms/step - loss: 0.1908
    1186. 

  1186. Epoch 5/10
    1187. 

  1187. 
  1/115 [..............................] - ETA: 0s - loss: 0.3253
 41/115 [=========>....................] - ETA: 0s - loss: 0.1830
 81/115 [====================>.........] - ETA: 0s - loss: 0.2012
115/115 [==============================] - 0s 1ms/step - loss: 0.1943
    1188. 

  1188. Epoch 6/10
    1189. 

  1189. 
  1/115 [..............................] - ETA: 0s - loss: 0.4051
 40/115 [=========>....................] - ETA: 0s - loss: 0.1780
 79/115 [===================>..........] - ETA: 0s - loss: 0.1900
115/115 [==============================] - 0s 1ms/step - loss: 0.1886
    1190. 

  1190. Epoch 7/10
    1191. 

  1191. 
  1/115 [..............................] - ETA: 0s - loss: 0.0891
 41/115 [=========>....................] - ETA: 0s - loss: 0.1935
 81/115 [====================>.........] - ETA: 0s - loss: 0.1870
115/115 [==============================] - 0s 1ms/step - loss: 0.1904
    1192. 

  1192. Epoch 8/10
    1193. 

  1193. 
  1/115 [..............................] - ETA: 0s - loss: 0.0790
 37/115 [========>.....................] - ETA: 0s - loss: 0.1608
 75/115 [==================>...........] - ETA: 0s - loss: 0.1809
114/115 [============================>.] - ETA: 0s - loss: 0.1892
115/115 [==============================] - 0s 1ms/step - loss: 0.1891
    1194. 

  1194. Epoch 9/10
    1195. 

  1195. 
  1/115 [..............................] - ETA: 0s - loss: 0.0940
 39/115 [=========>....................] - ETA: 0s - loss: 0.1937
 76/115 [==================>...........] - ETA: 0s - loss: 0.1886
115/115 [==============================] - 0s 1ms/step - loss: 0.1870
    1196. 

  1196. Epoch 10/10
    1197. 

  1197. 
  1/115 [..............................] - ETA: 0s - loss: 0.4806
 41/115 [=========>....................] - ETA: 0s - loss: 0.1734
 82/115 [====================>.........] - ETA: 0s - loss: 0.1815
115/115 [==============================] - 0s 1ms/step - loss: 0.1850
    1198. 

  1198. -> test with GAN.predict
    1199. 

  1199. GAN tn, fp: 261, 26
    1200. 

  1200. GAN fn, tp: 4, 7
    1201. 

  1201. GAN f1 score: 0.318
    1202. 

  1202. GAN cohens kappa score: 0.278
    1203. 

  1203. 

  1204. -> test with 'LR'
    1205. 

  1205. LR tn, fp: 254, 33
    1206. 

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

  1207. LR f1 score: 0.240
    1208. 

  1208. LR cohens kappa score: 0.194
    1209. 

  1209. LR average precision score: 0.244
    1210. 

  1210. 

  1211. -> test with 'RF'
    1212. 

  1212. RF tn, fp: 285, 2
    1213. 

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

  1214. RF f1 score: 0.000
    1215. 

  1215. RF cohens kappa score: -0.011
    1216. 

  1216. 

  1217. -> test with 'GB'
    1218. 

  1218. GB tn, fp: 280, 7
    1219. 

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

  1220. GB f1 score: 0.200
    1221. 

  1221. GB cohens kappa score: 0.173
    1222. 

  1222. 

  1223. -> test with 'KNN'
    1224. 

  1224. KNN tn, fp: 267, 20
    1225. 

  1225. KNN fn, tp: 3, 8
    1226. 

  1226. KNN f1 score: 0.410
    1227. 

  1227. KNN cohens kappa score: 0.377
    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 1106 synthetic samples
    1234. 

  1234. -> retrain GAN for predict
    1235. 

  1235. Epoch 1/10
    1236. 

  1236. 
  1/115 [..............................] - ETA: 22s - loss: 0.2529
 42/115 [=========>....................] - ETA: 0s - loss: 0.2023 
 83/115 [====================>.........] - ETA: 0s - loss: 0.1823
115/115 [==============================] - 0s 1ms/step - loss: 0.1721
    1237. 

  1237. Epoch 2/10
    1238. 

  1238. 
  1/115 [..............................] - ETA: 0s - loss: 0.2589
 40/115 [=========>....................] - ETA: 0s - loss: 0.1567
 80/115 [===================>..........] - ETA: 0s - loss: 0.1696
115/115 [==============================] - 0s 1ms/step - loss: 0.1778
    1239. 

  1239. Epoch 3/10
    1240. 

  1240. 
  1/115 [..............................] - ETA: 0s - loss: 0.1110
 41/115 [=========>....................] - ETA: 0s - loss: 0.1382
 79/115 [===================>..........] - ETA: 0s - loss: 0.1540
115/115 [==============================] - ETA: 0s - loss: 0.1711
115/115 [==============================] - 0s 1ms/step - loss: 0.1711
    1241. 

  1241. Epoch 4/10
    1242. 

  1242. 
  1/115 [..............................] - ETA: 0s - loss: 0.1591
 40/115 [=========>....................] - ETA: 0s - loss: 0.1812
 78/115 [===================>..........] - ETA: 0s - loss: 0.1775
115/115 [==============================] - 0s 1ms/step - loss: 0.1734
    1243. 

  1243. Epoch 5/10
    1244. 

  1244. 
  1/115 [..............................] - ETA: 0s - loss: 0.0661
 41/115 [=========>....................] - ETA: 0s - loss: 0.1757
 81/115 [====================>.........] - ETA: 0s - loss: 0.1664
115/115 [==============================] - 0s 1ms/step - loss: 0.1666
    1245. 

  1245. Epoch 6/10
    1246. 

  1246. 
  1/115 [..............................] - ETA: 0s - loss: 0.0660
 40/115 [=========>....................] - ETA: 0s - loss: 0.1817
 80/115 [===================>..........] - ETA: 0s - loss: 0.1749
115/115 [==============================] - 0s 1ms/step - loss: 0.1686
    1247. 

  1247. Epoch 7/10
    1248. 

  1248. 
  1/115 [..............................] - ETA: 0s - loss: 0.2413
 40/115 [=========>....................] - ETA: 0s - loss: 0.1442
 80/115 [===================>..........] - ETA: 0s - loss: 0.1515
115/115 [==============================] - 0s 1ms/step - loss: 0.1666
    1249. 

  1249. Epoch 8/10
    1250. 

  1250. 
  1/115 [..............................] - ETA: 0s - loss: 0.3588
 41/115 [=========>....................] - ETA: 0s - loss: 0.1655
 80/115 [===================>..........] - ETA: 0s - loss: 0.1687
115/115 [==============================] - 0s 1ms/step - loss: 0.1660
    1251. 

  1251. Epoch 9/10
    1252. 

  1252. 
  1/115 [..............................] - ETA: 0s - loss: 0.1238
 41/115 [=========>....................] - ETA: 0s - loss: 0.1855
 79/115 [===================>..........] - ETA: 0s - loss: 0.1750
112/115 [============================>.] - ETA: 0s - loss: 0.1651
115/115 [==============================] - 0s 1ms/step - loss: 0.1643
    1253. 

  1253. Epoch 10/10
    1254. 

  1254. 
  1/115 [..............................] - ETA: 0s - loss: 0.0557
 37/115 [========>.....................] - ETA: 0s - loss: 0.1419
 73/115 [==================>...........] - ETA: 0s - loss: 0.1627
112/115 [============================>.] - ETA: 0s - loss: 0.1683
115/115 [==============================] - 0s 1ms/step - loss: 0.1685
    1255. 

  1255. -> test with GAN.predict
    1256. 

  1256. GAN tn, fp: 256, 31
    1257. 

  1257. GAN fn, tp: 3, 8
    1258. 

  1258. GAN f1 score: 0.320
    1259. 

  1259. GAN cohens kappa score: 0.278
    1260. 

  1260. 

  1261. -> test with 'LR'
    1262. 

  1262. LR tn, fp: 241, 46
    1263. 

  1263. LR fn, tp: 2, 9
    1264. 

  1264. LR f1 score: 0.273
    1265. 

  1265. LR cohens kappa score: 0.225
    1266. 

  1266. LR average precision score: 0.513
    1267. 

  1267. 

  1268. -> test with 'RF'
    1269. 

  1269. RF tn, fp: 281, 6
    1270. 

  1270. RF fn, tp: 8, 3
    1271. 

  1271. RF f1 score: 0.300
    1272. 

  1272. RF cohens kappa score: 0.276
    1273. 

  1273. 

  1274. -> test with 'GB'
    1275. 

  1275. GB tn, fp: 280, 7
    1276. 

  1276. GB fn, tp: 5, 6
    1277. 

  1277. GB f1 score: 0.500
    1278. 

  1278. GB cohens kappa score: 0.479
    1279. 

  1279. 

  1280. -> test with 'KNN'
    1281. 

  1281. KNN tn, fp: 260, 27
    1282. 

  1282. KNN fn, tp: 1, 10
    1283. 

  1283. KNN f1 score: 0.417
    1284. 

  1284. KNN cohens kappa score: 0.381
    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 1106 synthetic samples
    1291. 

  1291. -> retrain GAN for predict
    1292. 

  1292. Epoch 1/10
    1293. 

  1293. 
  1/115 [..............................] - ETA: 19s - loss: 0.2144
 34/115 [=======>......................] - ETA: 0s - loss: 0.1983 
 73/115 [==================>...........] - ETA: 0s - loss: 0.1962
111/115 [===========================>..] - ETA: 0s - loss: 0.2025
115/115 [==============================] - 0s 1ms/step - loss: 0.2004
    1294. 

  1294. Epoch 2/10
    1295. 

  1295. 
  1/115 [..............................] - ETA: 0s - loss: 0.2432
 39/115 [=========>....................] - ETA: 0s - loss: 0.2219
 78/115 [===================>..........] - ETA: 0s - loss: 0.2072
115/115 [==============================] - 0s 1ms/step - loss: 0.2022
    1296. 

  1296. Epoch 3/10
    1297. 

  1297. 
  1/115 [..............................] - ETA: 0s - loss: 0.3899
 40/115 [=========>....................] - ETA: 0s - loss: 0.1930
 80/115 [===================>..........] - ETA: 0s - loss: 0.1909
115/115 [==============================] - 0s 1ms/step - loss: 0.1936
    1298. 

  1298. Epoch 4/10
    1299. 

  1299. 
  1/115 [..............................] - ETA: 0s - loss: 0.1229
 41/115 [=========>....................] - ETA: 0s - loss: 0.2142
 80/115 [===================>..........] - ETA: 0s - loss: 0.1939
115/115 [==============================] - 0s 1ms/step - loss: 0.1946
    1300. 

  1300. Epoch 5/10
    1301. 

  1301. 
  1/115 [..............................] - ETA: 0s - loss: 0.0993
 42/115 [=========>....................] - ETA: 0s - loss: 0.1674
 79/115 [===================>..........] - ETA: 0s - loss: 0.1880
115/115 [==============================] - 0s 1ms/step - loss: 0.1942
    1302. 

  1302. Epoch 6/10
    1303. 

  1303. 
  1/115 [..............................] - ETA: 0s - loss: 0.2643
 40/115 [=========>....................] - ETA: 0s - loss: 0.2028
 80/115 [===================>..........] - ETA: 0s - loss: 0.1929
115/115 [==============================] - 0s 1ms/step - loss: 0.1928
    1304. 

  1304. Epoch 7/10
    1305. 

  1305. 
  1/115 [..............................] - ETA: 0s - loss: 0.1168
 42/115 [=========>....................] - ETA: 0s - loss: 0.1815
 82/115 [====================>.........] - ETA: 0s - loss: 0.1812
115/115 [==============================] - 0s 1ms/step - loss: 0.1920
    1306. 

  1306. Epoch 8/10
    1307. 

  1307. 
  1/115 [..............................] - ETA: 0s - loss: 0.0890
 37/115 [========>.....................] - ETA: 0s - loss: 0.1600
 77/115 [===================>..........] - ETA: 0s - loss: 0.1835
115/115 [==============================] - 0s 1ms/step - loss: 0.1918
    1308. 

  1308. Epoch 9/10
    1309. 

  1309. 
  1/115 [..............................] - ETA: 0s - loss: 0.2180
 41/115 [=========>....................] - ETA: 0s - loss: 0.1894
 79/115 [===================>..........] - ETA: 0s - loss: 0.1771
115/115 [==============================] - 0s 1ms/step - loss: 0.1901
    1310. 

  1310. Epoch 10/10
    1311. 

  1311. 
  1/115 [..............................] - ETA: 0s - loss: 0.3356
 40/115 [=========>....................] - ETA: 0s - loss: 0.2400
 81/115 [====================>.........] - ETA: 0s - loss: 0.2184
115/115 [==============================] - 0s 1ms/step - loss: 0.1987
    1312. 

  1312. -> test with GAN.predict
    1313. 

  1313. GAN tn, fp: 264, 23
    1314. 

  1314. GAN fn, tp: 4, 7
    1315. 

  1315. GAN f1 score: 0.341
    1316. 

  1316. GAN cohens kappa score: 0.304
    1317. 

  1317. 

  1318. -> test with 'LR'
    1319. 

  1319. LR tn, fp: 251, 36
    1320. 

  1320. LR fn, tp: 3, 8
    1321. 

  1321. LR f1 score: 0.291
    1322. 

  1322. LR cohens kappa score: 0.246
    1323. 

  1323. LR average precision score: 0.445
    1324. 

  1324. 

  1325. -> test with 'RF'
    1326. 

  1326. RF tn, fp: 286, 1
    1327. 

  1327. RF fn, tp: 10, 1
    1328. 

  1328. RF f1 score: 0.154
    1329. 

  1329. RF cohens kappa score: 0.144
    1330. 

  1330. 

  1331. -> test with 'GB'
    1332. 

  1332. GB tn, fp: 284, 3
    1333. 

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

  1334. GB f1 score: 0.444
    1335. 

  1335. GB cohens kappa score: 0.428
    1336. 

  1336. 

  1337. -> test with 'KNN'
    1338. 

  1338. KNN tn, fp: 260, 27
    1339. 

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

  1340. KNN f1 score: 0.273
    1341. 

  1341. KNN cohens kappa score: 0.230
    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 1106 synthetic samples
    1348. 

  1348. -> retrain GAN for predict
    1349. 

  1349. Epoch 1/10
    1350. 

  1350. 
  1/115 [..............................] - ETA: 21s - loss: 0.2077
 38/115 [========>.....................] - ETA: 0s - loss: 0.1472 
 69/115 [=================>............] - ETA: 0s - loss: 0.1584
101/115 [=========================>....] - ETA: 0s - loss: 0.1615
115/115 [==============================] - 0s 2ms/step - loss: 0.1541
    1351. 

  1351. Epoch 2/10
    1352. 

  1352. 
  1/115 [..............................] - ETA: 0s - loss: 0.1701
 33/115 [=======>......................] - ETA: 0s - loss: 0.1356
 70/115 [=================>............] - ETA: 0s - loss: 0.1545
105/115 [==========================>...] - ETA: 0s - loss: 0.1568
115/115 [==============================] - 0s 1ms/step - loss: 0.1551
    1353. 

  1353. Epoch 3/10
    1354. 

  1354. 
  1/115 [..............................] - ETA: 0s - loss: 0.3318
 38/115 [========>.....................] - ETA: 0s - loss: 0.1658
 76/115 [==================>...........] - ETA: 0s - loss: 0.1498
115/115 [==============================] - 0s 1ms/step - loss: 0.1519
    1355. 

  1355. Epoch 4/10
    1356. 

  1356. 
  1/115 [..............................] - ETA: 0s - loss: 0.0944
 38/115 [========>.....................] - ETA: 0s - loss: 0.1479
 71/115 [=================>............] - ETA: 0s - loss: 0.1433
109/115 [===========================>..] - ETA: 0s - loss: 0.1499
115/115 [==============================] - 0s 1ms/step - loss: 0.1496
    1357. 

  1357. Epoch 5/10
    1358. 

  1358. 
  1/115 [..............................] - ETA: 0s - loss: 0.1026
 39/115 [=========>....................] - ETA: 0s - loss: 0.1722
 80/115 [===================>..........] - ETA: 0s - loss: 0.1509
113/115 [============================>.] - ETA: 0s - loss: 0.1484
115/115 [==============================] - 0s 1ms/step - loss: 0.1472
    1359. 

  1359. Epoch 6/10
    1360. 

  1360. 
  1/115 [..............................] - ETA: 0s - loss: 0.0635
 37/115 [========>.....................] - ETA: 0s - loss: 0.1421
 72/115 [=================>............] - ETA: 0s - loss: 0.1547
109/115 [===========================>..] - ETA: 0s - loss: 0.1526
115/115 [==============================] - 0s 1ms/step - loss: 0.1502
    1361. 

  1361. Epoch 7/10
    1362. 

  1362. 
  1/115 [..............................] - ETA: 0s - loss: 0.1549
 31/115 [=======>......................] - ETA: 0s - loss: 0.1663
 63/115 [===============>..............] - ETA: 0s - loss: 0.1470
 98/115 [========================>.....] - ETA: 0s - loss: 0.1392
115/115 [==============================] - 0s 2ms/step - loss: 0.1490
    1363. 

  1363. Epoch 8/10
    1364. 

  1364. 
  1/115 [..............................] - ETA: 0s - loss: 0.2034
 36/115 [========>.....................] - ETA: 0s - loss: 0.1504
 77/115 [===================>..........] - ETA: 0s - loss: 0.1547
115/115 [==============================] - 0s 1ms/step - loss: 0.1517
    1365. 

  1365. Epoch 9/10
    1366. 

  1366. 
  1/115 [..............................] - ETA: 0s - loss: 0.0676
 41/115 [=========>....................] - ETA: 0s - loss: 0.1421
 77/115 [===================>..........] - ETA: 0s - loss: 0.1605
113/115 [============================>.] - ETA: 0s - loss: 0.1466
115/115 [==============================] - 0s 1ms/step - loss: 0.1471
    1367. 

  1367. Epoch 10/10
    1368. 

  1368. 
  1/115 [..............................] - ETA: 0s - loss: 0.1798
 39/115 [=========>....................] - ETA: 0s - loss: 0.1741
 78/115 [===================>..........] - ETA: 0s - loss: 0.1671
115/115 [==============================] - 0s 1ms/step - loss: 0.1510
    1369. 

  1369. -> test with GAN.predict
    1370. 

  1370. GAN tn, fp: 271, 16
    1371. 

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

  1372. GAN f1 score: 0.412
    1373. 

  1373. GAN cohens kappa score: 0.381
    1374. 

  1374. 

  1375. -> test with 'LR'
    1376. 

  1376. LR tn, fp: 253, 34
    1377. 

  1377. LR fn, tp: 1, 10
    1378. 

  1378. LR f1 score: 0.364
    1379. 

  1379. LR cohens kappa score: 0.324
    1380. 

  1380. LR average precision score: 0.475
    1381. 

  1381. 

  1382. -> test with 'RF'
    1383. 

  1383. RF tn, fp: 283, 4
    1384. 

  1384. RF fn, tp: 8, 3
    1385. 

  1385. RF f1 score: 0.333
    1386. 

  1386. RF cohens kappa score: 0.314
    1387. 

  1387. 

  1388. -> test with 'GB'
    1389. 

  1389. GB tn, fp: 284, 3
    1390. 

  1390. GB fn, tp: 7, 4
    1391. 

  1391. GB f1 score: 0.444
    1392. 

  1392. GB cohens kappa score: 0.428
    1393. 

  1393. 

  1394. -> test with 'KNN'
    1395. 

  1395. KNN tn, fp: 264, 23
    1396. 

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

  1397. KNN f1 score: 0.381
    1398. 

  1398. KNN cohens kappa score: 0.345
    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 1104 synthetic samples
    1405. 

  1405. -> retrain GAN for predict
    1406. 

  1406. Epoch 1/10
    1407. 

  1407. 
  1/115 [..............................] - ETA: 22s - loss: 0.1027
 43/115 [==========>...................] - ETA: 0s - loss: 0.1839 
 84/115 [====================>.........] - ETA: 0s - loss: 0.2023
115/115 [==============================] - 0s 1ms/step - loss: 0.1921
    1408. 

  1408. Epoch 2/10
    1409. 

  1409. 
  1/115 [..............................] - ETA: 0s - loss: 0.2899
 41/115 [=========>....................] - ETA: 0s - loss: 0.1862
 82/115 [====================>.........] - ETA: 0s - loss: 0.1823
115/115 [==============================] - 0s 1ms/step - loss: 0.1884
    1410. 

  1410. Epoch 3/10
    1411. 

  1411. 
  1/115 [..............................] - ETA: 0s - loss: 0.2253
 39/115 [=========>....................] - ETA: 0s - loss: 0.1927
 78/115 [===================>..........] - ETA: 0s - loss: 0.1927
115/115 [==============================] - 0s 1ms/step - loss: 0.1888
    1412. 

  1412. Epoch 4/10
    1413. 

  1413. 
  1/115 [..............................] - ETA: 0s - loss: 0.2652
 42/115 [=========>....................] - ETA: 0s - loss: 0.1925
 81/115 [====================>.........] - ETA: 0s - loss: 0.1780
115/115 [==============================] - 0s 1ms/step - loss: 0.1859
    1414. 

  1414. Epoch 5/10
    1415. 

  1415. 
  1/115 [..............................] - ETA: 0s - loss: 0.0997
 40/115 [=========>....................] - ETA: 0s - loss: 0.1737
 81/115 [====================>.........] - ETA: 0s - loss: 0.1850
115/115 [==============================] - 0s 1ms/step - loss: 0.1881
    1416. 

  1416. Epoch 6/10
    1417. 

  1417. 
  1/115 [..............................] - ETA: 0s - loss: 0.1106
 42/115 [=========>....................] - ETA: 0s - loss: 0.1866
 76/115 [==================>...........] - ETA: 0s - loss: 0.1894
115/115 [==============================] - ETA: 0s - loss: 0.1858
115/115 [==============================] - 0s 1ms/step - loss: 0.1858
    1418. 

  1418. Epoch 7/10
    1419. 

  1419. 
  1/115 [..............................] - ETA: 0s - loss: 0.1879
 40/115 [=========>....................] - ETA: 0s - loss: 0.1676
 80/115 [===================>..........] - ETA: 0s - loss: 0.1860
115/115 [==============================] - 0s 1ms/step - loss: 0.1849
    1420. 

  1420. Epoch 8/10
    1421. 

  1421. 
  1/115 [..............................] - ETA: 0s - loss: 0.2020
 37/115 [========>.....................] - ETA: 0s - loss: 0.1588
 73/115 [==================>...........] - ETA: 0s - loss: 0.1705
108/115 [===========================>..] - ETA: 0s - loss: 0.1825
115/115 [==============================] - 0s 1ms/step - loss: 0.1838
    1422. 

  1422. Epoch 9/10
    1423. 

  1423. 
  1/115 [..............................] - ETA: 0s - loss: 0.3628
 40/115 [=========>....................] - ETA: 0s - loss: 0.1718
 79/115 [===================>..........] - ETA: 0s - loss: 0.1885
115/115 [==============================] - 0s 1ms/step - loss: 0.1838
    1424. 

  1424. Epoch 10/10
    1425. 

  1425. 
  1/115 [..............................] - ETA: 0s - loss: 0.1529
 41/115 [=========>....................] - ETA: 0s - loss: 0.1770
 80/115 [===================>..........] - ETA: 0s - loss: 0.1820
115/115 [==============================] - 0s 1ms/step - loss: 0.1852
    1426. 

  1426. -> test with GAN.predict
    1427. 

  1427. GAN tn, fp: 259, 26
    1428. 

  1428. GAN fn, tp: 3, 4
    1429. 

  1429. GAN f1 score: 0.216
    1430. 

  1430. GAN cohens kappa score: 0.185
    1431. 

  1431. 

  1432. -> test with 'LR'
    1433. 

  1433. LR tn, fp: 249, 36
    1434. 

  1434. LR fn, tp: 3, 4
    1435. 

  1435. LR f1 score: 0.170
    1436. 

  1436. LR cohens kappa score: 0.135
    1437. 

  1437. LR average precision score: 0.160
    1438. 

  1438. 

  1439. -> test with 'RF'
    1440. 

  1440. RF tn, fp: 283, 2
    1441. 

  1441. RF fn, tp: 6, 1
    1442. 

  1442. RF f1 score: 0.200
    1443. 

  1443. RF cohens kappa score: 0.188
    1444. 

  1444. 

  1445. -> test with 'GB'
    1446. 

  1446. GB tn, fp: 281, 4
    1447. 

  1447. GB fn, tp: 5, 2
    1448. 

  1448. GB f1 score: 0.308
    1449. 

  1449. GB cohens kappa score: 0.292
    1450. 

  1450. 

  1451. -> test with 'KNN'
    1452. 

  1452. KNN tn, fp: 264, 21
    1453. 

  1453. KNN fn, tp: 2, 5
    1454. 

  1454. KNN f1 score: 0.303
    1455. 

  1455. KNN cohens kappa score: 0.276
    1456. 

  1456. 

  1457. ### Exercise is done.
    1458. 

  1458. 

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

  1460. maximum:
    1461. 

  1461. LR tn, fp: 262, 46
    1462. 

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

  1463. LR f1 score: 0.364
    1464. 

  1464. LR cohens kappa score: 0.324
    1465. 

  1465. LR average precision score: 0.613
    1466. 

  1466. 

  1467. 

  1468. average:
    1469. 

  1469. LR tn, fp: 250.84, 35.76
    1470. 

  1470. LR fn, tp: 2.76, 7.44
    1471. 

  1471. LR f1 score: 0.277
    1472. 

  1472. LR cohens kappa score: 0.235
    1473. 

  1473. LR average precision score: 0.374
    1474. 

  1474. 

  1475. 

  1476. minimum:
    1477. 

  1477. LR tn, fp: 241, 25
    1478. 

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

  1479. LR f1 score: 0.170
    1480. 

  1480. LR cohens kappa score: 0.135
    1481. 

  1481. LR average precision score: 0.160
    1482. 

  1482. 

  1483. 

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

  1485. maximum:
    1486. 

  1486. RF tn, fp: 286, 7
    1487. 

  1487. RF fn, tp: 11, 5
    1488. 

  1488. RF f1 score: 0.500
    1489. 

  1489. RF cohens kappa score: 0.486
    1490. 

  1490. 

  1491. 

  1492. average:
    1493. 

  1493. RF tn, fp: 283.0, 3.6
    1494. 

  1494. RF fn, tp: 7.44, 2.76
    1495. 

  1495. RF f1 score: 0.321
    1496. 

  1496. RF cohens kappa score: 0.304
    1497. 

  1497. 

  1498. 

  1499. minimum:
    1500. 

  1500. RF tn, fp: 280, 1
    1501. 

  1501. RF fn, tp: 3, 0
    1502. 

  1502. RF f1 score: 0.000
    1503. 

  1503. RF cohens kappa score: -0.020
    1504. 

  1504. 

  1505. 

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

  1507. maximum:
    1508. 

  1508. GB tn, fp: 284, 13
    1509. 

  1509. GB fn, tp: 9, 6
    1510. 

  1510. GB f1 score: 0.500
    1511. 

  1511. GB cohens kappa score: 0.479
    1512. 

  1512. 

  1513. 

  1514. average:
    1515. 

  1515. GB tn, fp: 280.32, 6.28
    1516. 

  1516. GB fn, tp: 6.64, 3.56
    1517. 

  1517. GB f1 score: 0.351
    1518. 

  1518. GB cohens kappa score: 0.329
    1519. 

  1519. 

  1520. 

  1521. minimum:
    1522. 

  1522. GB tn, fp: 274, 3
    1523. 

  1523. GB fn, tp: 4, 1
    1524. 

  1524. GB f1 score: 0.143
    1525. 

  1525. GB cohens kappa score: 0.122
    1526. 

  1526. 

  1527. 

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

  1529. maximum:
    1530. 

  1530. KNN tn, fp: 274, 34
    1531. 

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

  1532. KNN f1 score: 0.417
    1533. 

  1533. KNN cohens kappa score: 0.381
    1534. 

  1534. 

  1535. 

  1536. average:
    1537. 

  1537. KNN tn, fp: 262.08, 24.52
    1538. 

  1538. KNN fn, tp: 2.84, 7.36
    1539. 

  1539. KNN f1 score: 0.348
    1540. 

  1540. KNN cohens kappa score: 0.313
    1541. 

  1541. 

  1542. 

  1543. minimum:
    1544. 

  1544. KNN tn, fp: 253, 13
    1545. 

  1545. KNN fn, tp: 1, 5
    1546. 

  1546. KNN f1 score: 0.263
    1547. 

  1547. KNN cohens kappa score: 0.230
    1548. 

  1548. 

  1549. 

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

  1551. maximum:
    1552. 

  1552. GAN tn, fp: 274, 44
    1553. 

  1553. GAN fn, tp: 7, 9
    1554. 

  1554. GAN f1 score: 0.412
    1555. 

  1555. GAN cohens kappa score: 0.381
    1556. 

  1556. 

  1557. 

  1558. average:
    1559. 

  1559. GAN tn, fp: 261.68, 24.92
    1560. 

  1560. GAN fn, tp: 3.88, 6.32
    1561. 

  1561. GAN f1 score: 0.308
    1562. 

  1562. GAN cohens kappa score: 0.271
    1563. 

  1563. 

  1564. 

  1565. minimum:
    1566. 

  1566. GAN tn, fp: 243, 13
    1567. 

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

  1568. GAN f1 score: 0.129
    1569. 

  1569. GAN cohens kappa score: 0.095
    1570. 

  1570.