ConvGeNBenchmarkResults/data_result/ConvGeN-majority-5/folding_kddcup-guess_passwd_vs_satan.log

///////////////////////////////////////////
// Running convGAN-majority-5 on folding_kddcup-guess_passwd_vs_satan
///////////////////////////////////////////

Load 'data_input/folding_kddcup-guess_passwd_vs_satan'
from pickle file
Data loaded.
-> Shuffling data
### Start exercise for synthetic point generator

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

------ Step 1/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 21s - loss: 5.7494e-06
 37/128 [=======>......................] - ETA: 0s - loss: 6.3475e-06 
 70/128 [===============>..............] - ETA: 0s - loss: 6.4046e-06
105/128 [=======================>......] - ETA: 0s - loss: 1.2190e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.1174e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 8.9000e-06
 37/128 [=======>......................] - ETA: 0s - loss: 5.8282e-06
 70/128 [===============>..............] - ETA: 0s - loss: 1.3665e-05
107/128 [========================>.....] - ETA: 0s - loss: 1.0796e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.0016e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 4.9194e-06
 35/128 [=======>......................] - ETA: 0s - loss: 5.3844e-06
 70/128 [===============>..............] - ETA: 0s - loss: 5.2432e-06
104/128 [=======================>......] - ETA: 0s - loss: 5.0827e-06
128/128 [==============================] - 0s 2ms/step - loss: 9.0270e-06
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 5.1384e-06
 32/128 [======>.......................] - ETA: 0s - loss: 4.8176e-06
 66/128 [==============>...............] - ETA: 0s - loss: 4.6396e-06
 99/128 [======================>.......] - ETA: 0s - loss: 4.5274e-06
128/128 [==============================] - 0s 2ms/step - loss: 8.1502e-06
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 5.2006e-06
 33/128 [======>.......................] - ETA: 0s - loss: 4.2861e-06
 67/128 [==============>...............] - ETA: 0s - loss: 4.1234e-06
102/128 [======================>.......] - ETA: 0s - loss: 4.0821e-06
128/128 [==============================] - 0s 1ms/step - loss: 7.3880e-06
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 4.5961e-06
 32/128 [======>.......................] - ETA: 0s - loss: 3.8864e-06
 67/128 [==============>...............] - ETA: 0s - loss: 3.7921e-06
101/128 [======================>.......] - ETA: 0s - loss: 7.5405e-06
128/128 [==============================] - 0s 2ms/step - loss: 6.7157e-06
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 5.3358e-06
 31/128 [======>.......................] - ETA: 0s - loss: 3.4671e-06
 62/128 [=============>................] - ETA: 0s - loss: 9.2394e-06
 94/128 [=====================>........] - ETA: 0s - loss: 7.2183e-06
127/128 [============================>.] - ETA: 0s - loss: 6.1355e-06
128/128 [==============================] - 0s 2ms/step - loss: 6.1328e-06
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 2.2450e-06
 34/128 [======>.......................] - ETA: 0s - loss: 3.3399e-06
 67/128 [==============>...............] - ETA: 0s - loss: 3.0969e-06
101/128 [======================>.......] - ETA: 0s - loss: 3.0015e-06
128/128 [==============================] - 0s 2ms/step - loss: 5.6192e-06
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 2.1995e-06
 35/128 [=======>......................] - ETA: 0s - loss: 1.1808e-05
 70/128 [===============>..............] - ETA: 0s - loss: 7.2517e-06
 99/128 [======================>.......] - ETA: 0s - loss: 5.8699e-06
128/128 [==============================] - ETA: 0s - loss: 5.1673e-06
128/128 [==============================] - 0s 2ms/step - loss: 5.1673e-06
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 3.7780e-06
 32/128 [======>.......................] - ETA: 0s - loss: 2.4246e-06
 68/128 [==============>...............] - ETA: 0s - loss: 6.7886e-06
101/128 [======================>.......] - ETA: 0s - loss: 5.3704e-06
128/128 [==============================] - 0s 1ms/step - loss: 4.7438e-06
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 1/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 21s - loss: 3.4560e-07
 39/128 [========>.....................] - ETA: 0s - loss: 5.6879e-07 
 77/128 [=================>............] - ETA: 0s - loss: 3.9316e-06
111/128 [=========================>....] - ETA: 0s - loss: 6.5588e-05
128/128 [==============================] - 0s 1ms/step - loss: 5.7403e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 4.7907e-07
 36/128 [=======>......................] - ETA: 0s - loss: 6.7542e-07
 68/128 [==============>...............] - ETA: 0s - loss: 9.1382e-05
103/128 [=======================>......] - ETA: 0s - loss: 6.0549e-05
128/128 [==============================] - 0s 2ms/step - loss: 5.0587e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 6.7880e-07
 36/128 [=======>......................] - ETA: 0s - loss: 5.3532e-06
 71/128 [===============>..............] - ETA: 0s - loss: 2.9624e-06
104/128 [=======================>......] - ETA: 0s - loss: 2.2853e-06
128/128 [==============================] - 0s 1ms/step - loss: 4.5091e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 3.2641e-07
 34/128 [======>.......................] - ETA: 0s - loss: 4.9954e-06
 66/128 [==============>...............] - ETA: 0s - loss: 5.0905e-05
104/128 [=======================>......] - ETA: 0s - loss: 3.2529e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.9842e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 4.0673e-07
 36/128 [=======>......................] - ETA: 0s - loss: 3.9864e-06
 70/128 [===============>..............] - ETA: 0s - loss: 4.3123e-05
103/128 [=======================>......] - ETA: 0s - loss: 4.3841e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.5696e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 8.0692e-07
 32/128 [======>.......................] - ETA: 0s - loss: 4.0327e-06
 64/128 [==============>...............] - ETA: 0s - loss: 6.2739e-05
 99/128 [======================>.......] - ETA: 0s - loss: 4.0751e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.1915e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 8.7666e-07
 35/128 [=======>......................] - ETA: 0s - loss: 4.9622e-07
 71/128 [===============>..............] - ETA: 0s - loss: 4.7321e-07
105/128 [=======================>......] - ETA: 0s - loss: 3.4637e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.8701e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 5.6315e-07
 38/128 [=======>......................] - ETA: 0s - loss: 5.6850e-05
 74/128 [================>.............] - ETA: 0s - loss: 2.9501e-05
108/128 [========================>.....] - ETA: 0s - loss: 2.0353e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.5498e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 4.8224e-07
 38/128 [=======>......................] - ETA: 0s - loss: 5.7332e-07
 78/128 [=================>............] - ETA: 0s - loss: 1.2719e-05
112/128 [=========================>....] - ETA: 0s - loss: 9.6113e-06
128/128 [==============================] - 0s 1ms/step - loss: 2.2805e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 3.6669e-07
 41/128 [========>.....................] - ETA: 0s - loss: 4.0738e-05
 80/128 [=================>............] - ETA: 0s - loss: 2.1070e-05
115/128 [=========================>....] - ETA: 0s - loss: 2.2524e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.0438e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 1/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 24s - loss: 4.2643e-07
 42/128 [========>.....................] - ETA: 0s - loss: 5.4620e-07 
 80/128 [=================>............] - ETA: 0s - loss: 7.1674e-07
115/128 [=========================>....] - ETA: 0s - loss: 2.6906e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.4544e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 5.0652e-07
 26/128 [=====>........................] - ETA: 0s - loss: 7.1553e-07
 47/128 [==========>...................] - ETA: 0s - loss: 6.4455e-07
 85/128 [==================>...........] - ETA: 0s - loss: 8.2295e-07
124/128 [============================>.] - ETA: 0s - loss: 2.1976e-05
128/128 [==============================] - 0s 2ms/step - loss: 2.1451e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 3.5124e-07
 36/128 [=======>......................] - ETA: 0s - loss: 6.3696e-07
 57/128 [============>.................] - ETA: 0s - loss: 5.5692e-07
 81/128 [=================>............] - ETA: 0s - loss: 7.0223e-07
118/128 [==========================>...] - ETA: 0s - loss: 2.0267e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.8850e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 3.1672e-07
 39/128 [========>.....................] - ETA: 0s - loss: 4.1706e-07
 73/128 [================>.............] - ETA: 0s - loss: 6.6956e-06
 99/128 [======================>.......] - ETA: 0s - loss: 2.1151e-05
119/128 [==========================>...] - ETA: 0s - loss: 1.7715e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.6610e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 3.3973e-07
 37/128 [=======>......................] - ETA: 0s - loss: 7.5012e-07
 75/128 [================>.............] - ETA: 0s - loss: 1.9478e-05
110/128 [========================>.....] - ETA: 0s - loss: 1.6834e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.4634e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 0.0013
  4/128 [..............................] - ETA: 2s - loss: 3.1656e-04
 35/128 [=======>......................] - ETA: 0s - loss: 3.6668e-05
 73/128 [================>.............] - ETA: 0s - loss: 2.2233e-05
112/128 [=========================>....] - ETA: 0s - loss: 1.4604e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.2902e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 3.2034e-07
 26/128 [=====>........................] - ETA: 0s - loss: 3.8198e-07
 47/128 [==========>...................] - ETA: 0s - loss: 2.4517e-05
 86/128 [===================>..........] - ETA: 0s - loss: 1.6890e-05
125/128 [============================>.] - ETA: 0s - loss: 1.1706e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.1517e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 2.3214e-07
 37/128 [=======>......................] - ETA: 0s - loss: 2.7855e-05
 71/128 [===============>..............] - ETA: 0s - loss: 1.4630e-05
 86/128 [===================>..........] - ETA: 0s - loss: 1.2121e-05
118/128 [==========================>...] - ETA: 0s - loss: 1.1056e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.0281e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 2.8316e-07
 34/128 [======>.......................] - ETA: 0s - loss: 4.0559e-07
 69/128 [===============>..............] - ETA: 0s - loss: 3.6740e-07
102/128 [======================>.......] - ETA: 0s - loss: 1.1402e-05
110/128 [========================>.....] - ETA: 0s - loss: 1.0588e-05
128/128 [==============================] - 0s 2ms/step - loss: 9.1901e-06
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 1.7352e-07
 39/128 [========>.....................] - ETA: 0s - loss: 5.5969e-06
 76/128 [================>.............] - ETA: 0s - loss: 1.3639e-05
110/128 [========================>.....] - ETA: 0s - loss: 9.4809e-06
128/128 [==============================] - 0s 1ms/step - loss: 8.2285e-06
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 1
KNN fn, tp: 0, 11
KNN f1 score: 0.957
KNN cohens kappa score: 0.955


------ Step 1/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 23s - loss: 4.9093e-04
 35/128 [=======>......................] - ETA: 0s - loss: 4.9437e-04 
 72/128 [===============>..............] - ETA: 0s - loss: 4.4802e-04
104/128 [=======================>......] - ETA: 0s - loss: 4.3590e-04
128/128 [==============================] - 0s 1ms/step - loss: 4.5831e-04
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 4.7742e-09
 35/128 [=======>......................] - ETA: 0s - loss: 3.5218e-04
 69/128 [===============>..............] - ETA: 0s - loss: 3.9199e-04
103/128 [=======================>......] - ETA: 0s - loss: 3.8094e-04
128/128 [==============================] - 0s 1ms/step - loss: 3.9735e-04
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 3.6939e-04
 35/128 [=======>......................] - ETA: 0s - loss: 3.1224e-04
 67/128 [==============>...............] - ETA: 0s - loss: 3.1046e-04
101/128 [======================>.......] - ETA: 0s - loss: 3.4528e-04
128/128 [==============================] - 0s 2ms/step - loss: 3.4705e-04
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 3.2489e-04
 35/128 [=======>......................] - ETA: 0s - loss: 2.5516e-04
 70/128 [===============>..............] - ETA: 0s - loss: 3.5410e-04
104/128 [=======================>......] - ETA: 0s - loss: 3.2342e-04
128/128 [==============================] - 0s 1ms/step - loss: 3.0531e-04
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 1.4188e-04
 32/128 [======>.......................] - ETA: 0s - loss: 2.8290e-04
 64/128 [==============>...............] - ETA: 0s - loss: 2.8828e-04
 96/128 [=====================>........] - ETA: 0s - loss: 2.7575e-04
128/128 [==============================] - 0s 2ms/step - loss: 2.6935e-04
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 3.7498e-04
 34/128 [======>.......................] - ETA: 0s - loss: 2.4229e-04
 68/128 [==============>...............] - ETA: 0s - loss: 2.2951e-04
101/128 [======================>.......] - ETA: 0s - loss: 2.0705e-04
128/128 [==============================] - 0s 2ms/step - loss: 2.3864e-04
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 1.1070e-04
 34/128 [======>.......................] - ETA: 0s - loss: 1.6984e-04
 68/128 [==============>...............] - ETA: 0s - loss: 1.9075e-04
 99/128 [======================>.......] - ETA: 0s - loss: 2.0015e-04
128/128 [==============================] - 0s 2ms/step - loss: 2.1206e-04
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 9.7673e-05
 33/128 [======>.......................] - ETA: 0s - loss: 2.0126e-04
 65/128 [==============>...............] - ETA: 0s - loss: 2.1224e-04
 99/128 [======================>.......] - ETA: 0s - loss: 2.0246e-04
128/128 [==============================] - 0s 2ms/step - loss: 1.8885e-04
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 2.6092e-04
 38/128 [=======>......................] - ETA: 0s - loss: 1.3990e-04
 72/128 [===============>..............] - ETA: 0s - loss: 1.4882e-04
105/128 [=======================>......] - ETA: 0s - loss: 1.5498e-04
128/128 [==============================] - 0s 1ms/step - loss: 1.6895e-04
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 1.5492e-04
 37/128 [=======>......................] - ETA: 0s - loss: 1.5664e-04
 72/128 [===============>..............] - ETA: 0s - loss: 1.4295e-04
103/128 [=======================>......] - ETA: 0s - loss: 1.5894e-04
128/128 [==============================] - 0s 2ms/step - loss: 1.5139e-04
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 1
KNN fn, tp: 0, 11
KNN f1 score: 0.957
KNN cohens kappa score: 0.955


------ Step 1/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1228 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 22s - loss: 6.9627e-04
 36/128 [=======>......................] - ETA: 0s - loss: 2.1375e-05 
 71/128 [===============>..............] - ETA: 0s - loss: 1.3370e-05
105/128 [=======================>......] - ETA: 0s - loss: 6.7273e-05
128/128 [==============================] - 0s 1ms/step - loss: 7.4383e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 1.2404e-06
 33/128 [======>.......................] - ETA: 0s - loss: 2.2566e-04
 69/128 [===============>..............] - ETA: 0s - loss: 1.1017e-04
103/128 [=======================>......] - ETA: 0s - loss: 8.0251e-05
128/128 [==============================] - 0s 1ms/step - loss: 6.5821e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 9.2934e-07
 37/128 [=======>......................] - ETA: 0s - loss: 4.7460e-05
 72/128 [===============>..............] - ETA: 0s - loss: 3.3912e-05
106/128 [=======================>......] - ETA: 0s - loss: 6.9745e-05
128/128 [==============================] - 0s 1ms/step - loss: 5.8358e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 7.2964e-07
 36/128 [=======>......................] - ETA: 0s - loss: 1.2649e-04
 73/128 [================>.............] - ETA: 0s - loss: 7.0538e-05
110/128 [========================>.....] - ETA: 0s - loss: 5.9959e-05
128/128 [==============================] - 0s 1ms/step - loss: 5.1979e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 8.9219e-07
 37/128 [=======>......................] - ETA: 0s - loss: 3.4264e-05
 71/128 [===============>..............] - ETA: 0s - loss: 1.8463e-05
107/128 [========================>.....] - ETA: 0s - loss: 5.4333e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.6461e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 3.5158e-07
 38/128 [=======>......................] - ETA: 0s - loss: 3.8541e-06
 76/128 [================>.............] - ETA: 0s - loss: 2.5524e-06
113/128 [=========================>....] - ETA: 0s - loss: 4.6748e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.1592e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 3.9188e-07
 37/128 [=======>......................] - ETA: 0s - loss: 1.0811e-05
 71/128 [===============>..............] - ETA: 0s - loss: 1.8774e-05
102/128 [======================>.......] - ETA: 0s - loss: 4.6292e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.7322e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 4.1669e-07
 32/128 [======>.......................] - ETA: 0s - loss: 2.1383e-06
 68/128 [==============>...............] - ETA: 0s - loss: 6.2328e-05
107/128 [========================>.....] - ETA: 0s - loss: 4.0084e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.3826e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 4.3142e-07
 40/128 [========>.....................] - ETA: 0s - loss: 8.6649e-05
 77/128 [=================>............] - ETA: 0s - loss: 4.9360e-05
113/128 [=========================>....] - ETA: 0s - loss: 3.4340e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.0551e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 4.8197e-07
 36/128 [=======>......................] - ETA: 0s - loss: 1.9091e-05
 72/128 [===============>..............] - ETA: 0s - loss: 9.8778e-06
110/128 [========================>.....] - ETA: 0s - loss: 9.1965e-06
128/128 [==============================] - 0s 1ms/step - loss: 2.7694e-05
-> test with GAN.predict
GAN tn, fp: 317, 0
GAN fn, tp: 0, 9
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 317, 0
LR fn, tp: 0, 9
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 317, 0
RF fn, tp: 0, 9
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 317, 0
GB fn, tp: 0, 9
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 0
KNN fn, tp: 0, 9
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


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

------ Step 2/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 20s - loss: 5.2786e-07
 14/128 [==>...........................] - ETA: 0s - loss: 2.1841e-06 
 47/128 [==========>...................] - ETA: 0s - loss: 1.1741e-06
 85/128 [==================>...........] - ETA: 0s - loss: 8.6378e-06
119/128 [==========================>...] - ETA: 0s - loss: 6.3993e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.1183e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 2.5614e-07
 30/128 [======>.......................] - ETA: 0s - loss: 1.9369e-05
 41/128 [========>.....................] - ETA: 0s - loss: 1.4488e-05
 65/128 [==============>...............] - ETA: 0s - loss: 9.4811e-06
103/128 [=======================>......] - ETA: 0s - loss: 6.2727e-06
128/128 [==============================] - 0s 2ms/step - loss: 9.6690e-06
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 5.3489e-04
 35/128 [=======>......................] - ETA: 0s - loss: 1.6215e-05
 62/128 [=============>................] - ETA: 0s - loss: 9.4174e-06
 83/128 [==================>...........] - ETA: 0s - loss: 7.2078e-06
116/128 [==========================>...] - ETA: 0s - loss: 9.3884e-06
128/128 [==============================] - 0s 2ms/step - loss: 8.6523e-06
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 1.1711e-06
 35/128 [=======>......................] - ETA: 0s - loss: 5.8691e-07
 70/128 [===============>..............] - ETA: 0s - loss: 7.3062e-07
 97/128 [=====================>........] - ETA: 0s - loss: 9.6579e-06
115/128 [=========================>....] - ETA: 0s - loss: 8.2008e-06
128/128 [==============================] - 0s 2ms/step - loss: 7.4535e-06
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 3.9541e-07
 37/128 [=======>......................] - ETA: 0s - loss: 6.8523e-07
 74/128 [================>.............] - ETA: 0s - loss: 1.0969e-05
107/128 [========================>.....] - ETA: 0s - loss: 7.7213e-06
128/128 [==============================] - 0s 1ms/step - loss: 6.5497e-06
Epoch 6/10

  1/128 [..............................] - ETA: 1s - loss: 4.2674e-07
 19/128 [===>..........................] - ETA: 0s - loss: 5.1622e-07
 56/128 [============>.................] - ETA: 0s - loss: 4.7672e-07
 92/128 [====================>.........] - ETA: 0s - loss: 7.8239e-06
124/128 [============================>.] - ETA: 0s - loss: 5.9373e-06
128/128 [==============================] - 0s 2ms/step - loss: 5.8194e-06
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 9.4706e-08
 29/128 [=====>........................] - ETA: 0s - loss: 1.1224e-05
 43/128 [=========>....................] - ETA: 0s - loss: 7.7280e-06
 81/128 [=================>............] - ETA: 0s - loss: 7.8523e-06
119/128 [==========================>...] - ETA: 0s - loss: 5.5309e-06
128/128 [==============================] - 0s 2ms/step - loss: 5.1960e-06
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 2.3276e-07
 34/128 [======>.......................] - ETA: 0s - loss: 8.2718e-06
 68/128 [==============>...............] - ETA: 0s - loss: 4.3064e-06
 84/128 [==================>...........] - ETA: 0s - loss: 6.8018e-06
121/128 [===========================>..] - ETA: 0s - loss: 4.8819e-06
128/128 [==============================] - 0s 2ms/step - loss: 4.6605e-06
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.2066e-07
 39/128 [========>.....................] - ETA: 0s - loss: 1.2888e-05
 72/128 [===============>..............] - ETA: 0s - loss: 7.1290e-06
 99/128 [======================>.......] - ETA: 0s - loss: 5.3078e-06
114/128 [=========================>....] - ETA: 0s - loss: 4.6411e-06
128/128 [==============================] - 0s 2ms/step - loss: 4.1903e-06
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 2.4924e-07
 37/128 [=======>......................] - ETA: 0s - loss: 2.7773e-07
 73/128 [================>.............] - ETA: 0s - loss: 3.4196e-06
104/128 [=======================>......] - ETA: 0s - loss: 4.5070e-06
128/128 [==============================] - 0s 1ms/step - loss: 3.7784e-06
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 2/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 24s - loss: 5.5512e-06
 38/128 [=======>......................] - ETA: 0s - loss: 4.0048e-06 
 74/128 [================>.............] - ETA: 0s - loss: 5.7812e-06
111/128 [=========================>....] - ETA: 0s - loss: 4.4779e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.9599e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 4.3547e-06
 37/128 [=======>......................] - ETA: 0s - loss: 4.9741e-06
 72/128 [===============>..............] - ETA: 0s - loss: 1.6270e-05
110/128 [========================>.....] - ETA: 0s - loss: 1.2160e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.4434e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 2.9445e-06
 38/128 [=======>......................] - ETA: 0s - loss: 6.3300e-06
 75/128 [================>.............] - ETA: 0s - loss: 4.0816e-05
113/128 [=========================>....] - ETA: 0s - loss: 3.3943e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.0505e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 2.0702e-06
 37/128 [=======>......................] - ETA: 0s - loss: 3.5843e-06
 73/128 [================>.............] - ETA: 0s - loss: 1.1886e-05
108/128 [========================>.....] - ETA: 0s - loss: 3.0779e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.7368e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 6.2175e-05
 39/128 [========>.....................] - ETA: 0s - loss: 5.8896e-06
 75/128 [================>.............] - ETA: 0s - loss: 1.1135e-05
111/128 [=========================>....] - ETA: 0s - loss: 2.7741e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.4515e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 1.4422e-06
 37/128 [=======>......................] - ETA: 0s - loss: 3.2786e-06
 71/128 [===============>..............] - ETA: 0s - loss: 3.6315e-06
108/128 [========================>.....] - ETA: 0s - loss: 2.1218e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.2083e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 1.5627e-06
 37/128 [=======>......................] - ETA: 0s - loss: 5.9829e-05
 74/128 [================>.............] - ETA: 0s - loss: 3.2019e-05
111/128 [=========================>....] - ETA: 0s - loss: 2.2439e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.9872e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 1.8434e-06
 38/128 [=======>......................] - ETA: 0s - loss: 1.9993e-06
 74/128 [================>.............] - ETA: 0s - loss: 7.5614e-06
109/128 [========================>.....] - ETA: 0s - loss: 6.3260e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.7910e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.6917e-06
 37/128 [=======>......................] - ETA: 0s - loss: 2.7480e-06
 74/128 [================>.............] - ETA: 0s - loss: 2.8328e-06
111/128 [=========================>....] - ETA: 0s - loss: 1.8065e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.6246e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 1.4263e-06
 35/128 [=======>......................] - ETA: 0s - loss: 2.1112e-06
 73/128 [================>.............] - ETA: 0s - loss: 2.4339e-06
109/128 [========================>.....] - ETA: 0s - loss: 4.7932e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.4710e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 317, 1
LR fn, tp: 0, 11
LR f1 score: 0.957
LR cohens kappa score: 0.955
LR average precision score: 0.917

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 1
KNN fn, tp: 0, 11
KNN f1 score: 0.957
KNN cohens kappa score: 0.955


------ Step 2/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 27s - loss: 6.7425e-07
 37/128 [=======>......................] - ETA: 0s - loss: 0.0020     
 75/128 [================>.............] - ETA: 0s - loss: 0.0014
111/128 [=========================>....] - ETA: 0s - loss: 0.0018
128/128 [==============================] - 0s 1ms/step - loss: 0.0016
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 3.6906e-07
 33/128 [======>.......................] - ETA: 0s - loss: 1.5971e-04
 40/128 [========>.....................] - ETA: 0s - loss: 1.3182e-04
 75/128 [================>.............] - ETA: 0s - loss: 9.3395e-04
111/128 [=========================>....] - ETA: 0s - loss: 0.0018    
128/128 [==============================] - 0s 2ms/step - loss: 0.0016
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 0.0317
 37/128 [=======>......................] - ETA: 0s - loss: 0.0035
 68/128 [==============>...............] - ETA: 0s - loss: 0.0024
 85/128 [==================>...........] - ETA: 0s - loss: 0.0019
123/128 [===========================>..] - ETA: 0s - loss: 0.0016
128/128 [==============================] - 0s 2ms/step - loss: 0.0015
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 5.6000e-08
 38/128 [=======>......................] - ETA: 0s - loss: 8.1061e-04
 73/128 [================>.............] - ETA: 0s - loss: 0.0021    
106/128 [=======================>......] - ETA: 0s - loss: 0.0015
112/128 [=========================>....] - ETA: 0s - loss: 0.0014
128/128 [==============================] - 0s 2ms/step - loss: 0.0015
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 2.3204e-08
 39/128 [========>.....................] - ETA: 0s - loss: 8.5746e-04
 76/128 [================>.............] - ETA: 0s - loss: 8.3137e-04
106/128 [=======================>......] - ETA: 0s - loss: 0.0014    
128/128 [==============================] - 0s 1ms/step - loss: 0.0014
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 1.0930e-08
 11/128 [=>............................] - ETA: 0s - loss: 0.0026    
 36/128 [=======>......................] - ETA: 0s - loss: 8.0242e-04
 73/128 [================>.............] - ETA: 0s - loss: 0.0016    
110/128 [========================>.....] - ETA: 0s - loss: 0.0016
128/128 [==============================] - 0s 2ms/step - loss: 0.0014
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 9.3791e-10
 31/128 [======>.......................] - ETA: 0s - loss: 0.0027    
 53/128 [===========>..................] - ETA: 0s - loss: 0.0021
 90/128 [====================>.........] - ETA: 0s - loss: 0.0016
125/128 [============================>.] - ETA: 0s - loss: 0.0013
128/128 [==============================] - 0s 2ms/step - loss: 0.0013
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 3.1702e-10
 35/128 [=======>......................] - ETA: 0s - loss: 0.0015    
 55/128 [===========>..................] - ETA: 0s - loss: 9.5487e-04
 78/128 [=================>............] - ETA: 0s - loss: 0.0010    
116/128 [==========================>...] - ETA: 0s - loss: 0.0011
128/128 [==============================] - 0s 2ms/step - loss: 0.0012
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.9045e-11
 40/128 [========>.....................] - ETA: 0s - loss: 6.2075e-04
 75/128 [================>.............] - ETA: 0s - loss: 0.0010    
 98/128 [=====================>........] - ETA: 0s - loss: 0.0010
116/128 [==========================>...] - ETA: 0s - loss: 0.0013
128/128 [==============================] - 0s 2ms/step - loss: 0.0012
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 6.3496e-12
 37/128 [=======>......................] - ETA: 0s - loss: 0.0012    
 74/128 [================>.............] - ETA: 0s - loss: 9.2984e-04
108/128 [========================>.....] - ETA: 0s - loss: 8.6309e-04
127/128 [============================>.] - ETA: 0s - loss: 0.0011    
128/128 [==============================] - 0s 2ms/step - loss: 0.0011
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 1
KNN fn, tp: 0, 11
KNN f1 score: 0.957
KNN cohens kappa score: 0.955


------ Step 2/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 21s - loss: 1.0948e-06
 37/128 [=======>......................] - ETA: 0s - loss: 2.0263e-05 
 76/128 [================>.............] - ETA: 0s - loss: 4.7133e-05
113/128 [=========================>....] - ETA: 0s - loss: 1.0133e-04
128/128 [==============================] - 0s 1ms/step - loss: 9.0686e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 1.6427e-07
 39/128 [========>.....................] - ETA: 0s - loss: 7.9301e-07
 77/128 [=================>............] - ETA: 0s - loss: 3.8978e-05
114/128 [=========================>....] - ETA: 0s - loss: 2.8320e-05
128/128 [==============================] - 0s 1ms/step - loss: 8.1260e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 7.5155e-07
 38/128 [=======>......................] - ETA: 0s - loss: 1.7477e-04
 74/128 [================>.............] - ETA: 0s - loss: 1.2399e-04
111/128 [=========================>....] - ETA: 0s - loss: 8.2869e-05
128/128 [==============================] - 0s 1ms/step - loss: 7.2694e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 6.2258e-07
 37/128 [=======>......................] - ETA: 0s - loss: 5.0285e-05
 73/128 [================>.............] - ETA: 0s - loss: 1.1333e-04
105/128 [=======================>......] - ETA: 0s - loss: 7.8941e-05
128/128 [==============================] - 0s 1ms/step - loss: 6.5318e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 2.2532e-07
 35/128 [=======>......................] - ETA: 0s - loss: 1.6482e-06
 72/128 [===============>..............] - ETA: 0s - loss: 8.1191e-05
106/128 [=======================>......] - ETA: 0s - loss: 7.0616e-05
128/128 [==============================] - 0s 1ms/step - loss: 5.8968e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 4.5233e-07
 37/128 [=======>......................] - ETA: 0s - loss: 1.2942e-04
 74/128 [================>.............] - ETA: 0s - loss: 8.8927e-05
112/128 [=========================>....] - ETA: 0s - loss: 5.9782e-05
128/128 [==============================] - 0s 1ms/step - loss: 5.2716e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 2.8480e-07
 36/128 [=======>......................] - ETA: 0s - loss: 1.2326e-04
 66/128 [==============>...............] - ETA: 0s - loss: 7.3659e-05
 99/128 [======================>.......] - ETA: 0s - loss: 6.0952e-05
128/128 [==============================] - 0s 2ms/step - loss: 4.7542e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 3.4968e-07
 39/128 [========>.....................] - ETA: 0s - loss: 1.1074e-04
 74/128 [================>.............] - ETA: 0s - loss: 5.9379e-05
111/128 [=========================>....] - ETA: 0s - loss: 3.9700e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.2440e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 7.6535e-08
 39/128 [========>.....................] - ETA: 0s - loss: 1.0112e-04
 76/128 [================>.............] - ETA: 0s - loss: 5.2108e-05
112/128 [=========================>....] - ETA: 0s - loss: 4.2871e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.7812e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 2.9637e-07
 37/128 [=======>......................] - ETA: 0s - loss: 2.8614e-05
 75/128 [================>.............] - ETA: 0s - loss: 1.4234e-05
110/128 [========================>.....] - ETA: 0s - loss: 3.8727e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.3545e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 2/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1228 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 20s - loss: 8.3567e-09
 30/128 [======>.......................] - ETA: 0s - loss: 1.0271e-07 
 41/128 [========>.....................] - ETA: 0s - loss: 7.7492e-08
 78/128 [=================>............] - ETA: 0s - loss: 7.1361e-07
114/128 [=========================>....] - ETA: 0s - loss: 3.9163e-06
128/128 [==============================] - 0s 2ms/step - loss: 3.5396e-06
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 4.8121e-05
 35/128 [=======>......................] - ETA: 0s - loss: 2.1694e-06
 67/128 [==============>...............] - ETA: 0s - loss: 5.7481e-06
 78/128 [=================>............] - ETA: 0s - loss: 4.9386e-06
116/128 [==========================>...] - ETA: 0s - loss: 3.3551e-06
128/128 [==============================] - 0s 2ms/step - loss: 3.0603e-06
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 9.6696e-07
 38/128 [=======>......................] - ETA: 0s - loss: 4.4006e-08
 72/128 [===============>..............] - ETA: 0s - loss: 6.7951e-07
102/128 [======================>.......] - ETA: 0s - loss: 3.2146e-06
110/128 [========================>.....] - ETA: 0s - loss: 2.9814e-06
128/128 [==============================] - 0s 2ms/step - loss: 2.5919e-06
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 2.5427e-07
 39/128 [========>.....................] - ETA: 0s - loss: 1.3308e-08
 75/128 [================>.............] - ETA: 0s - loss: 3.1799e-06
110/128 [========================>.....] - ETA: 0s - loss: 2.4836e-06
128/128 [==============================] - 0s 1ms/step - loss: 2.2464e-06
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 9.2976e-09
 26/128 [=====>........................] - ETA: 0s - loss: 7.8555e-06
 39/128 [========>.....................] - ETA: 0s - loss: 5.2694e-06
 79/128 [=================>............] - ETA: 0s - loss: 2.6538e-06
114/128 [=========================>....] - ETA: 0s - loss: 2.1072e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.9726e-06
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 5.1480e-09
 38/128 [=======>......................] - ETA: 0s - loss: 3.5399e-08
 70/128 [===============>..............] - ETA: 0s - loss: 2.1713e-08
 85/128 [==================>...........] - ETA: 0s - loss: 1.8857e-08
108/128 [========================>.....] - ETA: 0s - loss: 1.7862e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.7474e-06
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 5.8750e-09
 37/128 [=======>......................] - ETA: 0s - loss: 9.0816e-08
 75/128 [================>.............] - ETA: 0s - loss: 2.6227e-06
106/128 [=======================>......] - ETA: 0s - loss: 1.8576e-06
127/128 [============================>.] - ETA: 0s - loss: 1.5523e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.5499e-06
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 5.3029e-09
 22/128 [====>.........................] - ETA: 0s - loss: 7.0065e-06
 59/128 [============>.................] - ETA: 0s - loss: 2.6274e-06
 96/128 [=====================>........] - ETA: 0s - loss: 1.6171e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.3868e-06
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 6.4541e-09
 34/128 [======>.......................] - ETA: 0s - loss: 7.2112e-08
 45/128 [=========>....................] - ETA: 0s - loss: 5.5762e-08
 65/128 [==============>...............] - ETA: 0s - loss: 2.3539e-06
 94/128 [=====================>........] - ETA: 0s - loss: 1.6931e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.2544e-06
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 4.5064e-09
 37/128 [=======>......................] - ETA: 0s - loss: 5.3709e-09
 68/128 [==============>...............] - ETA: 0s - loss: 9.5874e-08
 87/128 [===================>..........] - ETA: 0s - loss: 1.4544e-06
104/128 [=======================>......] - ETA: 0s - loss: 1.3687e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.1200e-06
-> test with GAN.predict
GAN tn, fp: 317, 0
GAN fn, tp: 0, 9
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 317, 0
LR fn, tp: 0, 9
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 317, 0
RF fn, tp: 0, 9
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 317, 0
GB fn, tp: 0, 9
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 0
KNN fn, tp: 0, 9
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


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

------ Step 3/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 22s - loss: 6.4172e-06
 33/128 [======>.......................] - ETA: 0s - loss: 1.1014e-04 
 45/128 [=========>....................] - ETA: 0s - loss: 8.4429e-05
 86/128 [===================>..........] - ETA: 0s - loss: 5.1229e-05
126/128 [============================>.] - ETA: 0s - loss: 3.7744e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.7446e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 8.3987e-06
 37/128 [=======>......................] - ETA: 0s - loss: 7.2181e-06
 73/128 [================>.............] - ETA: 0s - loss: 5.0390e-05
 84/128 [==================>...........] - ETA: 0s - loss: 4.8075e-05
113/128 [=========================>....] - ETA: 0s - loss: 3.7201e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.4024e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 4.8990e-06
 34/128 [======>.......................] - ETA: 0s - loss: 9.0852e-05
 68/128 [==============>...............] - ETA: 0s - loss: 4.8482e-05
101/128 [======================>.......] - ETA: 0s - loss: 3.8118e-05
119/128 [==========================>...] - ETA: 0s - loss: 3.3107e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.1373e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 4.9627e-06
 40/128 [========>.....................] - ETA: 0s - loss: 7.9449e-05
 75/128 [================>.............] - ETA: 0s - loss: 4.5436e-05
114/128 [=========================>....] - ETA: 0s - loss: 3.1684e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.8975e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 6.8262e-06
 37/128 [=======>......................] - ETA: 0s - loss: 4.8339e-06
 52/128 [===========>..................] - ETA: 0s - loss: 6.2387e-06
 78/128 [=================>............] - ETA: 0s - loss: 5.7951e-06
117/128 [==========================>...] - ETA: 0s - loss: 7.3301e-06
128/128 [==============================] - 0s 2ms/step - loss: 2.6656e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 3.1619e-06
 40/128 [========>.....................] - ETA: 0s - loss: 1.1883e-05
 75/128 [================>.............] - ETA: 0s - loss: 8.2036e-06
 98/128 [=====================>........] - ETA: 0s - loss: 7.3945e-06
111/128 [=========================>....] - ETA: 0s - loss: 7.0594e-06
128/128 [==============================] - 0s 2ms/step - loss: 2.4553e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 3.6345e-06
 41/128 [========>.....................] - ETA: 0s - loss: 4.0407e-06
 79/128 [=================>............] - ETA: 0s - loss: 3.1384e-05
115/128 [=========================>....] - ETA: 0s - loss: 2.2772e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.2565e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 3.5181e-06
 17/128 [==>...........................] - ETA: 0s - loss: 3.8279e-06
 45/128 [=========>....................] - ETA: 0s - loss: 4.7779e-05
 84/128 [==================>...........] - ETA: 0s - loss: 2.7096e-05
123/128 [===========================>..] - ETA: 0s - loss: 2.1304e-05
128/128 [==============================] - 0s 2ms/step - loss: 2.0819e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.4167e-06
 39/128 [========>.....................] - ETA: 0s - loss: 5.0203e-05
 76/128 [================>.............] - ETA: 0s - loss: 2.7122e-05
 84/128 [==================>...........] - ETA: 0s - loss: 2.4937e-05
116/128 [==========================>...] - ETA: 0s - loss: 1.9216e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.9200e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 2.7663e-06
 34/128 [======>.......................] - ETA: 0s - loss: 5.3343e-05
 71/128 [===============>..............] - ETA: 0s - loss: 2.7431e-05
106/128 [=======================>......] - ETA: 0s - loss: 2.0670e-05
124/128 [============================>.] - ETA: 0s - loss: 1.8121e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.7736e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 317, 1
LR fn, tp: 0, 11
LR f1 score: 0.957
LR cohens kappa score: 0.955
LR average precision score: 0.917

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 1
KNN fn, tp: 0, 11
KNN f1 score: 0.957
KNN cohens kappa score: 0.955


------ Step 3/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 21s - loss: 3.9808e-04
 36/128 [=======>......................] - ETA: 0s - loss: 7.3589e-04 
 71/128 [===============>..............] - ETA: 0s - loss: 7.5167e-04
106/128 [=======================>......] - ETA: 0s - loss: 6.5896e-04
128/128 [==============================] - 0s 1ms/step - loss: 6.4389e-04
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 5.8684e-04
 38/128 [=======>......................] - ETA: 0s - loss: 4.9313e-04
 76/128 [================>.............] - ETA: 0s - loss: 5.3630e-04
113/128 [=========================>....] - ETA: 0s - loss: 4.9938e-04
128/128 [==============================] - 0s 1ms/step - loss: 4.8962e-04
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 4.5189e-04
 39/128 [========>.....................] - ETA: 0s - loss: 4.8043e-04
 74/128 [================>.............] - ETA: 0s - loss: 4.3822e-04
110/128 [========================>.....] - ETA: 0s - loss: 3.8899e-04
128/128 [==============================] - 0s 1ms/step - loss: 3.8069e-04
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 5.4751e-09
 38/128 [=======>......................] - ETA: 0s - loss: 2.6716e-04
 74/128 [================>.............] - ETA: 0s - loss: 2.8598e-04
110/128 [========================>.....] - ETA: 0s - loss: 3.1039e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.9899e-04
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 1.4011e-04
 36/128 [=======>......................] - ETA: 0s - loss: 2.6235e-04
 74/128 [================>.............] - ETA: 0s - loss: 2.5303e-04
109/128 [========================>.....] - ETA: 0s - loss: 2.3731e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.4019e-04
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 2.2781e-04
 37/128 [=======>......................] - ETA: 0s - loss: 1.9182e-04
 73/128 [================>.............] - ETA: 0s - loss: 2.0428e-04
110/128 [========================>.....] - ETA: 0s - loss: 1.9890e-04
128/128 [==============================] - 0s 1ms/step - loss: 1.9438e-04
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 2.7776e-04
 34/128 [======>.......................] - ETA: 0s - loss: 1.7558e-04
 69/128 [===============>..............] - ETA: 0s - loss: 1.7510e-04
105/128 [=======================>......] - ETA: 0s - loss: 1.6545e-04
128/128 [==============================] - 0s 1ms/step - loss: 1.6054e-04
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 1.5466e-04
 36/128 [=======>......................] - ETA: 0s - loss: 1.4480e-04
 72/128 [===============>..............] - ETA: 0s - loss: 1.4424e-04
107/128 [========================>.....] - ETA: 0s - loss: 1.3749e-04
128/128 [==============================] - 0s 1ms/step - loss: 1.3440e-04
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.2983e-04
 30/128 [======>.......................] - ETA: 0s - loss: 1.2753e-04
 62/128 [=============>................] - ETA: 0s - loss: 1.2079e-04
 93/128 [====================>.........] - ETA: 0s - loss: 1.1838e-04
127/128 [============================>.] - ETA: 0s - loss: 1.1348e-04
128/128 [==============================] - 0s 2ms/step - loss: 1.1339e-04
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 1.0996e-04
 38/128 [=======>......................] - ETA: 0s - loss: 9.3665e-05
 75/128 [================>.............] - ETA: 0s - loss: 9.8965e-05
115/128 [=========================>....] - ETA: 0s - loss: 9.7905e-05
128/128 [==============================] - 0s 1ms/step - loss: 9.6414e-05
-> test with GAN.predict
GAN tn, fp: 316, 2
GAN fn, tp: 0, 11
GAN f1 score: 0.917
GAN cohens kappa score: 0.914

-> test with 'LR'
LR tn, fp: 316, 2
LR fn, tp: 0, 11
LR f1 score: 0.917
LR cohens kappa score: 0.914
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 315, 3
GB fn, tp: 0, 11
GB f1 score: 0.880
GB cohens kappa score: 0.875

-> test with 'KNN'
KNN tn, fp: 316, 2
KNN fn, tp: 0, 11
KNN f1 score: 0.917
KNN cohens kappa score: 0.914


------ Step 3/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 21s - loss: 2.8972e-07
 39/128 [========>.....................] - ETA: 0s - loss: 2.7105e-07 
 77/128 [=================>............] - ETA: 0s - loss: 1.1551e-05
115/128 [=========================>....] - ETA: 0s - loss: 2.1925e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.9861e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 2.4401e-07
 39/128 [========>.....................] - ETA: 0s - loss: 1.9466e-05
 79/128 [=================>............] - ETA: 0s - loss: 2.8159e-05
117/128 [==========================>...] - ETA: 0s - loss: 1.9094e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.7595e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 2.4525e-07
 39/128 [========>.....................] - ETA: 0s - loss: 1.6942e-05
 76/128 [================>.............] - ETA: 0s - loss: 8.8159e-06
114/128 [=========================>....] - ETA: 0s - loss: 1.7442e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.5665e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 2.2232e-07
 39/128 [========>.....................] - ETA: 0s - loss: 3.1265e-05
 76/128 [================>.............] - ETA: 0s - loss: 2.3314e-05
113/128 [=========================>....] - ETA: 0s - loss: 1.5736e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.4012e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 2.0434e-07
 38/128 [=======>......................] - ETA: 0s - loss: 4.1916e-05
 76/128 [================>.............] - ETA: 0s - loss: 2.1051e-05
115/128 [=========================>....] - ETA: 0s - loss: 1.3968e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.2652e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 6.4544e-08
 39/128 [========>.....................] - ETA: 0s - loss: 2.5802e-05
 76/128 [================>.............] - ETA: 0s - loss: 1.3312e-05
108/128 [========================>.....] - ETA: 0s - loss: 9.4088e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.1312e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 1.4188e-07
 38/128 [=======>......................] - ETA: 0s - loss: 3.3929e-05
 76/128 [================>.............] - ETA: 0s - loss: 1.7037e-05
114/128 [=========================>....] - ETA: 0s - loss: 1.1403e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.0240e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 1.4200e-07
 40/128 [========>.....................] - ETA: 0s - loss: 2.0888e-05
 79/128 [=================>............] - ETA: 0s - loss: 1.0634e-05
117/128 [==========================>...] - ETA: 0s - loss: 9.9848e-06
128/128 [==============================] - 0s 1ms/step - loss: 9.2005e-06
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.0294e-07
 39/128 [========>.....................] - ETA: 0s - loss: 7.7266e-06
 76/128 [================>.............] - ETA: 0s - loss: 4.0171e-06
110/128 [========================>.....] - ETA: 0s - loss: 2.8110e-06
128/128 [==============================] - 0s 1ms/step - loss: 8.2877e-06
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 9.9738e-08
 39/128 [========>.....................] - ETA: 0s - loss: 8.3227e-08
 76/128 [================>.............] - ETA: 0s - loss: 9.0967e-06
114/128 [=========================>....] - ETA: 0s - loss: 8.2854e-06
128/128 [==============================] - 0s 1ms/step - loss: 7.4379e-06
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 3/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 22s - loss: 1.6637e-07
 37/128 [=======>......................] - ETA: 0s - loss: 1.0972e-04 
 75/128 [================>.............] - ETA: 0s - loss: 5.7542e-05
113/128 [=========================>....] - ETA: 0s - loss: 3.8338e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.7856e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 1.8191e-07
 33/128 [======>.......................] - ETA: 0s - loss: 1.0938e-04
 70/128 [===============>..............] - ETA: 0s - loss: 5.1862e-05
110/128 [========================>.....] - ETA: 0s - loss: 3.8873e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.4212e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 4.6768e-08
 40/128 [========>.....................] - ETA: 0s - loss: 1.8564e-06
 77/128 [=================>............] - ETA: 0s - loss: 1.4094e-06
115/128 [=========================>....] - ETA: 0s - loss: 3.2901e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.1097e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 1.9542e-07
 37/128 [=======>......................] - ETA: 0s - loss: 8.6927e-05
 77/128 [=================>............] - ETA: 0s - loss: 4.1920e-05
117/128 [==========================>...] - ETA: 0s - loss: 3.0550e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.8133e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 1.1516e-07
 39/128 [========>.....................] - ETA: 0s - loss: 5.2133e-07
 77/128 [=================>............] - ETA: 0s - loss: 3.7795e-05
112/128 [=========================>....] - ETA: 0s - loss: 2.8679e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.5317e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 1.1931e-07
 39/128 [========>.....................] - ETA: 0s - loss: 3.5452e-06
 77/128 [=================>............] - ETA: 0s - loss: 2.3763e-06
114/128 [=========================>....] - ETA: 0s - loss: 4.0941e-06
128/128 [==============================] - 0s 1ms/step - loss: 2.2897e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 5.9272e-08
 40/128 [========>.....................] - ETA: 0s - loss: 3.1246e-06
 78/128 [=================>............] - ETA: 0s - loss: 3.3558e-05
116/128 [==========================>...] - ETA: 0s - loss: 2.2603e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.0865e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 8.3116e-08
 37/128 [=======>......................] - ETA: 0s - loss: 5.5439e-05
 75/128 [================>.............] - ETA: 0s - loss: 3.0292e-05
114/128 [=========================>....] - ETA: 0s - loss: 2.0959e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.8824e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.2916e-07
 33/128 [======>.......................] - ETA: 0s - loss: 5.6843e-05
 64/128 [==============>...............] - ETA: 0s - loss: 3.2363e-05
 95/128 [=====================>........] - ETA: 0s - loss: 2.2056e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.7129e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 7.9524e-08
 38/128 [=======>......................] - ETA: 0s - loss: 4.5083e-05
 71/128 [===============>..............] - ETA: 0s - loss: 2.6590e-05
102/128 [======================>.......] - ETA: 0s - loss: 1.9201e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.5554e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 3/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1228 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 22s - loss: 1.9324e-06
 41/128 [========>.....................] - ETA: 0s - loss: 8.8475e-04 
 79/128 [=================>............] - ETA: 0s - loss: 0.0018    
116/128 [==========================>...] - ETA: 0s - loss: 0.0012
128/128 [==============================] - 0s 1ms/step - loss: 0.0017
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 2.6399e-07
 39/128 [========>.....................] - ETA: 0s - loss: 8.7300e-04
 74/128 [================>.............] - ETA: 0s - loss: 0.0023    
108/128 [========================>.....] - ETA: 0s - loss: 0.0016
128/128 [==============================] - 0s 1ms/step - loss: 0.0016
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 2.2744e-06
 38/128 [=======>......................] - ETA: 0s - loss: 9.0571e-04
 77/128 [=================>............] - ETA: 0s - loss: 0.0013    
115/128 [=========================>....] - ETA: 0s - loss: 0.0015
128/128 [==============================] - 0s 1ms/step - loss: 0.0016
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 9.5722e-07
 40/128 [========>.....................] - ETA: 0s - loss: 8.4063e-04
 78/128 [=================>............] - ETA: 0s - loss: 0.0021    
117/128 [==========================>...] - ETA: 0s - loss: 0.0017
128/128 [==============================] - 0s 1ms/step - loss: 0.0016
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 2.6555e-07
 34/128 [======>.......................] - ETA: 0s - loss: 9.4843e-04
 72/128 [===============>..............] - ETA: 0s - loss: 0.0022    
109/128 [========================>.....] - ETA: 0s - loss: 0.0015
128/128 [==============================] - 0s 1ms/step - loss: 0.0015
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 1.4360e-07
 36/128 [=======>......................] - ETA: 0s - loss: 9.1073e-04
 69/128 [===============>..............] - ETA: 0s - loss: 9.2915e-04
100/128 [======================>.......] - ETA: 0s - loss: 0.0016    
128/128 [==============================] - 0s 2ms/step - loss: 0.0015
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 4.6657e-08
 38/128 [=======>......................] - ETA: 0s - loss: 8.5000e-04
 76/128 [================>.............] - ETA: 0s - loss: 8.2563e-04
114/128 [=========================>....] - ETA: 0s - loss: 0.0011    
128/128 [==============================] - 0s 1ms/step - loss: 0.0014
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 3.7788e-08
 39/128 [========>.....................] - ETA: 0s - loss: 3.8435e-05
 70/128 [===============>..............] - ETA: 0s - loss: 0.0013    
101/128 [======================>.......] - ETA: 0s - loss: 8.8986e-04
128/128 [==============================] - 0s 2ms/step - loss: 0.0014
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 2.0919e-08
 39/128 [========>.....................] - ETA: 0s - loss: 0.0015    
 76/128 [================>.............] - ETA: 0s - loss: 0.0015
112/128 [=========================>....] - ETA: 0s - loss: 0.0013
128/128 [==============================] - 0s 1ms/step - loss: 0.0013
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 1.0529e-08
 42/128 [========>.....................] - ETA: 0s - loss: 0.0013    
 79/128 [=================>............] - ETA: 0s - loss: 0.0010
118/128 [==========================>...] - ETA: 0s - loss: 0.0014
128/128 [==============================] - 0s 1ms/step - loss: 0.0013
-> test with GAN.predict
GAN tn, fp: 317, 0
GAN fn, tp: 0, 9
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 317, 0
LR fn, tp: 0, 9
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 317, 0
RF fn, tp: 0, 9
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 317, 0
GB fn, tp: 0, 9
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 0
KNN fn, tp: 0, 9
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


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

------ Step 4/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 25s - loss: 9.0527e-04
 39/128 [========>.....................] - ETA: 0s - loss: 5.1207e-04 
 71/128 [===============>..............] - ETA: 0s - loss: 5.4757e-04
105/128 [=======================>......] - ETA: 0s - loss: 5.7521e-04
128/128 [==============================] - 0s 1ms/step - loss: 5.5083e-04
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 7.7463e-04
 35/128 [=======>......................] - ETA: 0s - loss: 5.3303e-04
 67/128 [==============>...............] - ETA: 0s - loss: 5.1169e-04
 99/128 [======================>.......] - ETA: 0s - loss: 4.9738e-04
128/128 [==============================] - 0s 2ms/step - loss: 4.7440e-04
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 2.2201e-04
 29/128 [=====>........................] - ETA: 0s - loss: 4.2175e-04
 61/128 [=============>................] - ETA: 0s - loss: 4.5763e-04
 98/128 [=====================>........] - ETA: 0s - loss: 4.2640e-04
128/128 [==============================] - 0s 2ms/step - loss: 4.1000e-04
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 9.5902e-04
 36/128 [=======>......................] - ETA: 0s - loss: 3.6291e-04
 68/128 [==============>...............] - ETA: 0s - loss: 4.1943e-04
105/128 [=======================>......] - ETA: 0s - loss: 3.8675e-04
128/128 [==============================] - 0s 1ms/step - loss: 3.5595e-04
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 3.3100e-04
 36/128 [=======>......................] - ETA: 0s - loss: 3.3415e-04
 70/128 [===============>..............] - ETA: 0s - loss: 3.0157e-04
104/128 [=======================>......] - ETA: 0s - loss: 3.0068e-04
128/128 [==============================] - 0s 2ms/step - loss: 3.1058e-04
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 2.8986e-04
 36/128 [=======>......................] - ETA: 0s - loss: 2.5857e-04
 75/128 [================>.............] - ETA: 0s - loss: 2.8344e-04
106/128 [=======================>......] - ETA: 0s - loss: 2.8321e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.7106e-04
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 1.2593e-04
 38/128 [=======>......................] - ETA: 0s - loss: 2.7764e-04
 72/128 [===============>..............] - ETA: 0s - loss: 2.6421e-04
107/128 [========================>.....] - ETA: 0s - loss: 2.4767e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.3842e-04
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 1.9423e-04
 35/128 [=======>......................] - ETA: 0s - loss: 1.9234e-04
 70/128 [===============>..............] - ETA: 0s - loss: 2.0874e-04
106/128 [=======================>......] - ETA: 0s - loss: 2.1452e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.1077e-04
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 2.9291e-04
 35/128 [=======>......................] - ETA: 0s - loss: 2.2425e-04
 72/128 [===============>..............] - ETA: 0s - loss: 1.8780e-04
107/128 [========================>.....] - ETA: 0s - loss: 1.9012e-04
128/128 [==============================] - 0s 1ms/step - loss: 1.8687e-04
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 8.6390e-05
 38/128 [=======>......................] - ETA: 0s - loss: 1.4119e-04
 75/128 [================>.............] - ETA: 0s - loss: 1.5594e-04
107/128 [========================>.....] - ETA: 0s - loss: 1.7082e-04
128/128 [==============================] - 0s 1ms/step - loss: 1.6630e-04
-> test with GAN.predict
GAN tn, fp: 317, 1
GAN fn, tp: 0, 11
GAN f1 score: 0.957
GAN cohens kappa score: 0.955

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 1
KNN fn, tp: 0, 11
KNN f1 score: 0.957
KNN cohens kappa score: 0.955


------ Step 4/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 21s - loss: 1.1568e-04
 15/128 [==>...........................] - ETA: 0s - loss: 9.7939e-06 
 36/128 [=======>......................] - ETA: 0s - loss: 1.2869e-04
 72/128 [===============>..............] - ETA: 0s - loss: 6.5689e-05
106/128 [=======================>......] - ETA: 0s - loss: 4.6222e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.8982e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 2.0297e-06
 31/128 [======>.......................] - ETA: 0s - loss: 1.2833e-04
 36/128 [=======>......................] - ETA: 0s - loss: 1.1084e-04
 67/128 [==============>...............] - ETA: 0s - loss: 6.0679e-05
100/128 [======================>.......] - ETA: 0s - loss: 4.1559e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.4308e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 2.2285e-06
 32/128 [======>.......................] - ETA: 0s - loss: 6.6065e-06
 61/128 [=============>................] - ETA: 0s - loss: 4.4915e-06
 85/128 [==================>...........] - ETA: 0s - loss: 4.3990e-06
119/128 [==========================>...] - ETA: 0s - loss: 3.1747e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.0438e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 3.1942e-06
 36/128 [=======>......................] - ETA: 0s - loss: 3.8621e-06
 65/128 [==============>...............] - ETA: 0s - loss: 4.9849e-05
 86/128 [===================>..........] - ETA: 0s - loss: 3.8383e-05
106/128 [=======================>......] - ETA: 0s - loss: 3.1544e-05
128/128 [==============================] - 0s 2ms/step - loss: 2.6969e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 1.2179e-06
 29/128 [=====>........................] - ETA: 0s - loss: 9.0712e-05
 54/128 [===========>..................] - ETA: 0s - loss: 5.1877e-05
 79/128 [=================>............] - ETA: 0s - loss: 3.6636e-05
 90/128 [====================>.........] - ETA: 0s - loss: 3.2467e-05
124/128 [============================>.] - ETA: 0s - loss: 2.4050e-05
128/128 [==============================] - 0s 2ms/step - loss: 2.3509e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 2.0089e-06
 30/128 [======>.......................] - ETA: 0s - loss: 7.7520e-05
 58/128 [============>.................] - ETA: 0s - loss: 4.1449e-05
 87/128 [===================>..........] - ETA: 0s - loss: 2.9622e-05
 92/128 [====================>.........] - ETA: 0s - loss: 2.8101e-05
127/128 [============================>.] - ETA: 0s - loss: 2.0817e-05
128/128 [==============================] - 0s 2ms/step - loss: 2.0801e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 1.9491e-06
 34/128 [======>.......................] - ETA: 0s - loss: 3.7755e-06
 69/128 [===============>..............] - ETA: 0s - loss: 3.1551e-05
101/128 [======================>.......] - ETA: 0s - loss: 2.2781e-05
127/128 [============================>.] - ETA: 0s - loss: 1.8441e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.8427e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 1.1263e-06
 21/128 [===>..........................] - ETA: 0s - loss: 8.5781e-05
 52/128 [===========>..................] - ETA: 0s - loss: 3.5511e-05
 87/128 [===================>..........] - ETA: 0s - loss: 2.1860e-05
118/128 [==========================>...] - ETA: 0s - loss: 1.7296e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.6402e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.2976e-06
 21/128 [===>..........................] - ETA: 0s - loss: 1.3714e-06
 42/128 [========>.....................] - ETA: 0s - loss: 1.4785e-06
 78/128 [=================>............] - ETA: 0s - loss: 2.1608e-05
111/128 [=========================>....] - ETA: 0s - loss: 1.5853e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.4637e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 8.7383e-07
 30/128 [======>.......................] - ETA: 0s - loss: 4.9160e-05
 46/128 [=========>....................] - ETA: 0s - loss: 3.2502e-05
 64/128 [==============>...............] - ETA: 0s - loss: 2.4083e-05
 90/128 [====================>.........] - ETA: 0s - loss: 1.7459e-05
123/128 [===========================>..] - ETA: 0s - loss: 1.3534e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.3132e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 4/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 24s - loss: 3.1139e-06
 41/128 [========>.....................] - ETA: 0s - loss: 8.5943e-06 
 81/128 [=================>............] - ETA: 0s - loss: 3.6505e-05
119/128 [==========================>...] - ETA: 0s - loss: 5.0024e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.7061e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 3.9592e-06
 38/128 [=======>......................] - ETA: 0s - loss: 1.0601e-05
 77/128 [=================>............] - ETA: 0s - loss: 3.8457e-05
115/128 [=========================>....] - ETA: 0s - loss: 2.7511e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.1749e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 2.0117e-06
 39/128 [========>.....................] - ETA: 0s - loss: 4.3494e-05
 77/128 [=================>............] - ETA: 0s - loss: 2.9133e-05
113/128 [=========================>....] - ETA: 0s - loss: 4.1645e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.7267e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 3.3502e-06
 41/128 [========>.....................] - ETA: 0s - loss: 8.2955e-06
 78/128 [=================>............] - ETA: 0s - loss: 3.3776e-05
117/128 [==========================>...] - ETA: 0s - loss: 3.4983e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.3306e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 2.2995e-06
 39/128 [========>.....................] - ETA: 0s - loss: 3.5747e-05
 76/128 [================>.............] - ETA: 0s - loss: 2.0754e-05
113/128 [=========================>....] - ETA: 0s - loss: 3.2228e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.9687e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 1.7972e-06
 36/128 [=======>......................] - ETA: 0s - loss: 3.4041e-05
 72/128 [===============>..............] - ETA: 0s - loss: 4.4445e-05
109/128 [========================>.....] - ETA: 0s - loss: 2.9782e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.6034e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 5.1172e-07
 36/128 [=======>......................] - ETA: 0s - loss: 4.0946e-06
 75/128 [================>.............] - ETA: 0s - loss: 1.9327e-05
112/128 [=========================>....] - ETA: 0s - loss: 1.3173e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.4093e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 4.8338e-07
 37/128 [=======>......................] - ETA: 0s - loss: 1.6442e-06
 71/128 [===============>..............] - ETA: 0s - loss: 1.3827e-05
108/128 [========================>.....] - ETA: 0s - loss: 2.3971e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.1013e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 3.3906e-07
 36/128 [=======>......................] - ETA: 0s - loss: 2.3524e-06
 67/128 [==============>...............] - ETA: 0s - loss: 3.1913e-06
100/128 [======================>.......] - ETA: 0s - loss: 2.3419e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.8741e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 3.8988e-07
 37/128 [=======>......................] - ETA: 0s - loss: 3.4526e-05
 75/128 [================>.............] - ETA: 0s - loss: 2.6283e-05
111/128 [=========================>....] - ETA: 0s - loss: 1.8829e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.6684e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 4/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 20s - loss: 1.4350e-04
 42/128 [========>.....................] - ETA: 0s - loss: 9.5883e-04 
 82/128 [==================>...........] - ETA: 0s - loss: 4.9693e-04
123/128 [===========================>..] - ETA: 0s - loss: 0.0017    
128/128 [==============================] - 0s 1ms/step - loss: 0.0016
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 1.5947e-07
 42/128 [========>.....................] - ETA: 0s - loss: 7.9093e-04
 81/128 [=================>............] - ETA: 0s - loss: 4.3341e-04
120/128 [===========================>..] - ETA: 0s - loss: 0.0012    
128/128 [==============================] - 0s 1ms/step - loss: 0.0016
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 2.4969e-08
 38/128 [=======>......................] - ETA: 0s - loss: 9.9395e-04
 77/128 [=================>............] - ETA: 0s - loss: 0.0017    
116/128 [==========================>...] - ETA: 0s - loss: 0.0017
128/128 [==============================] - 0s 1ms/step - loss: 0.0016
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 1.0718e-07
 41/128 [========>.....................] - ETA: 0s - loss: 7.6875e-04
 80/128 [=================>............] - ETA: 0s - loss: 7.8698e-04
119/128 [==========================>...] - ETA: 0s - loss: 0.0011    
128/128 [==============================] - 0s 1ms/step - loss: 0.0015
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 0.0308
 41/128 [========>.....................] - ETA: 0s - loss: 0.0015
 81/128 [=================>............] - ETA: 0s - loss: 0.0023
120/128 [===========================>..] - ETA: 0s - loss: 0.0016
128/128 [==============================] - 0s 1ms/step - loss: 0.0015
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 5.3771e-08
 39/128 [========>.....................] - ETA: 0s - loss: 0.0015    
 77/128 [=================>............] - ETA: 0s - loss: 0.0015
116/128 [==========================>...] - ETA: 0s - loss: 0.0016
128/128 [==============================] - 0s 1ms/step - loss: 0.0014
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 0.0037
 40/128 [========>.....................] - ETA: 0s - loss: 0.0015
 79/128 [=================>............] - ETA: 0s - loss: 0.0018
118/128 [==========================>...] - ETA: 0s - loss: 0.0015
128/128 [==============================] - 0s 1ms/step - loss: 0.0014
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 3.0759e-09
 40/128 [========>.....................] - ETA: 0s - loss: 0.0021    
 79/128 [=================>............] - ETA: 0s - loss: 0.0018
118/128 [==========================>...] - ETA: 0s - loss: 0.0012
128/128 [==============================] - 0s 1ms/step - loss: 0.0013
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 7.4445e-09
 36/128 [=======>......................] - ETA: 0s - loss: 0.0014    
 71/128 [===============>..............] - ETA: 0s - loss: 0.0014
103/128 [=======================>......] - ETA: 0s - loss: 9.9656e-04
128/128 [==============================] - 0s 2ms/step - loss: 0.0012
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 2.8492e-09
 35/128 [=======>......................] - ETA: 0s - loss: 0.0021    
 76/128 [================>.............] - ETA: 0s - loss: 9.6069e-04
114/128 [=========================>....] - ETA: 0s - loss: 0.0011    
128/128 [==============================] - 0s 1ms/step - loss: 0.0011
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 4/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1228 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 22s - loss: 1.1041e-06
 41/128 [========>.....................] - ETA: 0s - loss: 9.9848e-05 
 82/128 [==================>...........] - ETA: 0s - loss: 7.1668e-05
121/128 [===========================>..] - ETA: 0s - loss: 5.1044e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.8635e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 1.0528e-06
 38/128 [=======>......................] - ETA: 0s - loss: 1.2078e-06
 76/128 [================>.............] - ETA: 0s - loss: 4.3172e-06
116/128 [==========================>...] - ETA: 0s - loss: 4.7624e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.3528e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 1.0843e-06
 41/128 [========>.....................] - ETA: 0s - loss: 2.6546e-05
 81/128 [=================>............] - ETA: 0s - loss: 1.6057e-05
122/128 [===========================>..] - ETA: 0s - loss: 4.0277e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.8672e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 8.8837e-07
 39/128 [========>.....................] - ETA: 0s - loss: 2.6940e-05
 79/128 [=================>............] - ETA: 0s - loss: 5.0950e-05
119/128 [==========================>...] - ETA: 0s - loss: 3.7039e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.4711e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 3.7156e-07
 41/128 [========>.....................] - ETA: 0s - loss: 3.0332e-05
 83/128 [==================>...........] - ETA: 0s - loss: 1.5428e-05
115/128 [=========================>....] - ETA: 0s - loss: 3.4073e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.1104e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 4.7120e-07
 35/128 [=======>......................] - ETA: 0s - loss: 8.4295e-07
 70/128 [===============>..............] - ETA: 0s - loss: 4.9210e-06
108/128 [========================>.....] - ETA: 0s - loss: 3.2737e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.8034e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 1.3353e-06
 39/128 [========>.....................] - ETA: 0s - loss: 2.2731e-05
 77/128 [=================>............] - ETA: 0s - loss: 1.3185e-05
112/128 [=========================>....] - ETA: 0s - loss: 2.8417e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.5195e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 3.4505e-07
 41/128 [========>.....................] - ETA: 0s - loss: 7.3553e-06
 82/128 [==================>...........] - ETA: 0s - loss: 4.2583e-06
123/128 [===========================>..] - ETA: 0s - loss: 2.3374e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.2626e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 5.4242e-07
 41/128 [========>.....................] - ETA: 0s - loss: 5.0850e-06
 80/128 [=================>............] - ETA: 0s - loss: 3.1982e-05
120/128 [===========================>..] - ETA: 0s - loss: 2.1613e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.0458e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 4.4285e-07
 39/128 [========>.....................] - ETA: 0s - loss: 5.4336e-05
 78/128 [=================>............] - ETA: 0s - loss: 2.7590e-05
116/128 [==========================>...] - ETA: 0s - loss: 1.9990e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.8279e-05
-> test with GAN.predict
GAN tn, fp: 317, 0
GAN fn, tp: 0, 9
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 316, 1
LR fn, tp: 0, 9
LR f1 score: 0.947
LR cohens kappa score: 0.946
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 317, 0
RF fn, tp: 0, 9
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 317, 0
GB fn, tp: 0, 9
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 316, 1
KNN fn, tp: 0, 9
KNN f1 score: 0.947
KNN cohens kappa score: 0.946


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

------ Step 5/5: Slice 1/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 19s - loss: 7.8676e-08
 41/128 [========>.....................] - ETA: 0s - loss: 4.1302e-05 
 81/128 [=================>............] - ETA: 0s - loss: 2.1582e-05
120/128 [===========================>..] - ETA: 0s - loss: 4.4853e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.2353e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 0.0031
 39/128 [========>.....................] - ETA: 0s - loss: 1.1060e-04
 77/128 [=================>............] - ETA: 0s - loss: 6.1872e-05
117/128 [==========================>...] - ETA: 0s - loss: 4.0812e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.7575e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 9.6756e-08
 41/128 [========>.....................] - ETA: 0s - loss: 7.4986e-05
 80/128 [=================>............] - ETA: 0s - loss: 5.2362e-05
119/128 [==========================>...] - ETA: 0s - loss: 3.5259e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.3018e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 5.3059e-08
 40/128 [========>.....................] - ETA: 0s - loss: 6.9527e-05
 79/128 [=================>............] - ETA: 0s - loss: 3.5929e-05
117/128 [==========================>...] - ETA: 0s - loss: 3.2146e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.9599e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 2.7649e-04
 41/128 [========>.....................] - ETA: 0s - loss: 2.7904e-05
 79/128 [=================>............] - ETA: 0s - loss: 4.2654e-05
119/128 [==========================>...] - ETA: 0s - loss: 2.8364e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.6626e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 7.0431e-08
 41/128 [========>.....................] - ETA: 0s - loss: 2.0821e-07
 80/128 [=================>............] - ETA: 0s - loss: 8.7736e-06
120/128 [===========================>..] - ETA: 0s - loss: 2.5202e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.3852e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 5.9612e-04
 41/128 [========>.....................] - ETA: 0s - loss: 1.4883e-05
 81/128 [=================>............] - ETA: 0s - loss: 3.0849e-05
121/128 [===========================>..] - ETA: 0s - loss: 2.2408e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.1336e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 8.8178e-08
 42/128 [========>.....................] - ETA: 0s - loss: 1.9014e-07
 83/128 [==================>...........] - ETA: 0s - loss: 2.4704e-06
124/128 [============================>.] - ETA: 0s - loss: 1.5335e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.9066e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 6.0677e-08
 42/128 [========>.....................] - ETA: 0s - loss: 3.6704e-05
 82/128 [==================>...........] - ETA: 0s - loss: 2.1172e-05
122/128 [===========================>..] - ETA: 0s - loss: 1.7815e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.7102e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 3.7669e-08
 40/128 [========>.....................] - ETA: 0s - loss: 3.5569e-05
 78/128 [=================>............] - ETA: 0s - loss: 2.3327e-05
119/128 [==========================>...] - ETA: 0s - loss: 1.6491e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.5444e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 317, 1
LR fn, tp: 0, 11
LR f1 score: 0.957
LR cohens kappa score: 0.955
LR average precision score: 0.917

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 1
KNN fn, tp: 0, 11
KNN f1 score: 0.957
KNN cohens kappa score: 0.955


------ Step 5/5: Slice 2/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 31s - loss: 1.9459e-05
 41/128 [========>.....................] - ETA: 0s - loss: 6.9523e-05 
 81/128 [=================>............] - ETA: 0s - loss: 4.1536e-05
116/128 [==========================>...] - ETA: 0s - loss: 3.3334e-05
125/128 [============================>.] - ETA: 0s - loss: 3.1655e-05
128/128 [==============================] - 0s 2ms/step - loss: 3.1289e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 6.6887e-06
 41/128 [========>.....................] - ETA: 0s - loss: 1.2087e-05
 80/128 [=================>............] - ETA: 0s - loss: 1.0897e-05
119/128 [==========================>...] - ETA: 0s - loss: 1.1129e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.6716e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 1.1379e-05
 34/128 [======>.......................] - ETA: 0s - loss: 4.5368e-05
 53/128 [===========>..................] - ETA: 0s - loss: 3.2173e-05
 90/128 [====================>.........] - ETA: 0s - loss: 2.3031e-05
124/128 [============================>.] - ETA: 0s - loss: 2.3363e-05
128/128 [==============================] - 0s 2ms/step - loss: 2.3008e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 6.5275e-06
 39/128 [========>.....................] - ETA: 0s - loss: 9.2133e-06
 76/128 [================>.............] - ETA: 0s - loss: 8.8087e-06
 87/128 [===================>..........] - ETA: 0s - loss: 8.6379e-06
126/128 [============================>.] - ETA: 0s - loss: 2.0158e-05
128/128 [==============================] - 0s 2ms/step - loss: 2.0029e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 4.1409e-06
 40/128 [========>.....................] - ETA: 0s - loss: 6.5750e-06
 79/128 [=================>............] - ETA: 0s - loss: 7.2214e-06
115/128 [=========================>....] - ETA: 0s - loss: 7.1642e-06
123/128 [===========================>..] - ETA: 0s - loss: 7.2093e-06
128/128 [==============================] - 0s 2ms/step - loss: 1.7328e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 8.1603e-06
 41/128 [========>.....................] - ETA: 0s - loss: 1.2774e-05
 81/128 [=================>............] - ETA: 0s - loss: 1.9814e-05
118/128 [==========================>...] - ETA: 0s - loss: 1.5635e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.4890e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 4.5628e-06
 26/128 [=====>........................] - ETA: 0s - loss: 3.5435e-05
 53/128 [===========>..................] - ETA: 0s - loss: 1.9595e-05
 93/128 [====================>.........] - ETA: 0s - loss: 1.5947e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.2872e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 3.3406e-06
 34/128 [======>.......................] - ETA: 0s - loss: 5.2098e-06
 66/128 [==============>...............] - ETA: 0s - loss: 1.5048e-05
 77/128 [=================>............] - ETA: 0s - loss: 1.3351e-05
110/128 [========================>.....] - ETA: 0s - loss: 1.0343e-05
128/128 [==============================] - 0s 2ms/step - loss: 1.1094e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 2.9969e-06
 40/128 [========>.....................] - ETA: 0s - loss: 8.0586e-06
 78/128 [=================>............] - ETA: 0s - loss: 5.5406e-06
107/128 [========================>.....] - ETA: 0s - loss: 4.9567e-06
128/128 [==============================] - ETA: 0s - loss: 9.4641e-06
128/128 [==============================] - 0s 2ms/step - loss: 9.4641e-06
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 2.7549e-06
 39/128 [========>.....................] - ETA: 0s - loss: 2.7297e-06
 80/128 [=================>............] - ETA: 0s - loss: 2.8017e-06
117/128 [==========================>...] - ETA: 0s - loss: 8.4873e-06
128/128 [==============================] - 0s 1ms/step - loss: 7.9534e-06
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 5/5: Slice 3/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 26s - loss: 6.4674e-04
 39/128 [========>.....................] - ETA: 0s - loss: 5.7114e-04 
 74/128 [================>.............] - ETA: 0s - loss: 5.5169e-04
108/128 [========================>.....] - ETA: 0s - loss: 5.7491e-04
128/128 [==============================] - 0s 1ms/step - loss: 5.9586e-04
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 8.1762e-04
 37/128 [=======>......................] - ETA: 0s - loss: 4.9035e-04
 72/128 [===============>..............] - ETA: 0s - loss: 4.8866e-04
105/128 [=======================>......] - ETA: 0s - loss: 5.1842e-04
128/128 [==============================] - 0s 1ms/step - loss: 5.1236e-04
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 7.0051e-04
 33/128 [======>.......................] - ETA: 0s - loss: 4.3752e-04
 67/128 [==============>...............] - ETA: 0s - loss: 4.6982e-04
 99/128 [======================>.......] - ETA: 0s - loss: 4.4486e-04
128/128 [==============================] - 0s 2ms/step - loss: 4.4336e-04
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 2.0113e-04
 36/128 [=======>......................] - ETA: 0s - loss: 4.9547e-04
 75/128 [================>.............] - ETA: 0s - loss: 4.0848e-04
110/128 [========================>.....] - ETA: 0s - loss: 4.0652e-04
128/128 [==============================] - 0s 1ms/step - loss: 3.8483e-04
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 1.7270e-04
 35/128 [=======>......................] - ETA: 0s - loss: 4.6032e-04
 69/128 [===============>..............] - ETA: 0s - loss: 3.9714e-04
108/128 [========================>.....] - ETA: 0s - loss: 3.5678e-04
128/128 [==============================] - 0s 1ms/step - loss: 3.3668e-04
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 1.5049e-04
 37/128 [=======>......................] - ETA: 0s - loss: 2.7187e-04
 71/128 [===============>..............] - ETA: 0s - loss: 2.8187e-04
105/128 [=======================>......] - ETA: 0s - loss: 2.8585e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.9643e-04
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 2.6342e-04
 33/128 [======>.......................] - ETA: 0s - loss: 2.5363e-04
 67/128 [==============>...............] - ETA: 0s - loss: 2.7325e-04
103/128 [=======================>......] - ETA: 0s - loss: 2.7597e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.5922e-04
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 2.3975e-08
 40/128 [========>.....................] - ETA: 0s - loss: 1.8743e-04
 72/128 [===============>..............] - ETA: 0s - loss: 2.4823e-04
110/128 [========================>.....] - ETA: 0s - loss: 2.3196e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.2872e-04
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 1.0055e-04
 37/128 [=======>......................] - ETA: 0s - loss: 1.6608e-04
 71/128 [===============>..............] - ETA: 0s - loss: 2.1346e-04
108/128 [========================>.....] - ETA: 0s - loss: 2.0714e-04
128/128 [==============================] - 0s 1ms/step - loss: 2.0283e-04
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 8.8631e-05
 38/128 [=======>......................] - ETA: 0s - loss: 2.2914e-04
 75/128 [================>.............] - ETA: 0s - loss: 2.0092e-04
110/128 [========================>.....] - ETA: 0s - loss: 1.8502e-04
128/128 [==============================] - 0s 1ms/step - loss: 1.8063e-04
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 5/5: Slice 4/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1229 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 22s - loss: 5.5413e-08
 42/128 [========>.....................] - ETA: 0s - loss: 7.1133e-07 
 83/128 [==================>...........] - ETA: 0s - loss: 6.0356e-05
124/128 [============================>.] - ETA: 0s - loss: 4.5201e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.4102e-05
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 1.5591e-07
 41/128 [========>.....................] - ETA: 0s - loss: 1.2468e-04
 81/128 [=================>............] - ETA: 0s - loss: 6.3543e-05
120/128 [===========================>..] - ETA: 0s - loss: 4.2929e-05
128/128 [==============================] - 0s 1ms/step - loss: 4.0537e-05
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 3.7356e-08
 41/128 [========>.....................] - ETA: 0s - loss: 2.1920e-07
 82/128 [==================>...........] - ETA: 0s - loss: 2.9883e-07
121/128 [===========================>..] - ETA: 0s - loss: 3.8967e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.7101e-05
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 1.1194e-07
 40/128 [========>.....................] - ETA: 0s - loss: 1.0772e-04
 78/128 [=================>............] - ETA: 0s - loss: 5.5287e-05
114/128 [=========================>....] - ETA: 0s - loss: 3.7951e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.4127e-05
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 1.1961e-07
 39/128 [========>.....................] - ETA: 0s - loss: 6.0063e-07
 78/128 [=================>............] - ETA: 0s - loss: 4.5199e-05
119/128 [==========================>...] - ETA: 0s - loss: 3.2960e-05
128/128 [==============================] - 0s 1ms/step - loss: 3.0863e-05
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 7.6513e-08
 33/128 [======>.......................] - ETA: 0s - loss: 7.1875e-08
 67/128 [==============>...............] - ETA: 0s - loss: 4.7301e-05
100/128 [======================>.......] - ETA: 0s - loss: 3.1889e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.7862e-05
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 1.4914e-08
 43/128 [=========>....................] - ETA: 0s - loss: 1.1872e-07
 84/128 [==================>...........] - ETA: 0s - loss: 3.8220e-05
123/128 [===========================>..] - ETA: 0s - loss: 2.6168e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.5376e-05
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 6.0589e-08
 39/128 [========>.....................] - ETA: 0s - loss: 7.9787e-06
 79/128 [=================>............] - ETA: 0s - loss: 3.6655e-05
119/128 [==========================>...] - ETA: 0s - loss: 2.4392e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.2840e-05
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 4.3304e-08
 41/128 [========>.....................] - ETA: 0s - loss: 5.7809e-05
 77/128 [=================>............] - ETA: 0s - loss: 3.0930e-05
117/128 [==========================>...] - ETA: 0s - loss: 2.2580e-05
128/128 [==============================] - 0s 1ms/step - loss: 2.0790e-05
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 5.0296e-08
 42/128 [========>.....................] - ETA: 0s - loss: 6.9651e-08
 83/128 [==================>...........] - ETA: 0s - loss: 2.6127e-05
123/128 [===========================>..] - ETA: 0s - loss: 1.9600e-05
128/128 [==============================] - 0s 1ms/step - loss: 1.8970e-05
-> test with GAN.predict
GAN tn, fp: 318, 0
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000

-> test with 'LR'
LR tn, fp: 318, 0
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 318, 0
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 318, 0
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


------ Step 5/5: Slice 5/5 -------
-> Reset the GAN
-> Train generator for synthetic samples
-> create 1228 synthetic samples
-> retrain GAN for predict
Epoch 1/10

  1/128 [..............................] - ETA: 19s - loss: 8.5138e-09
 41/128 [========>.....................] - ETA: 0s - loss: 9.1310e-08 
 81/128 [=================>............] - ETA: 0s - loss: 2.5136e-06
121/128 [===========================>..] - ETA: 0s - loss: 1.9408e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.8466e-06
Epoch 2/10

  1/128 [..............................] - ETA: 0s - loss: 7.1321e-09
 42/128 [========>.....................] - ETA: 0s - loss: 2.5401e-07
 83/128 [==================>...........] - ETA: 0s - loss: 2.6180e-06
123/128 [===========================>..] - ETA: 0s - loss: 1.7983e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.7392e-06
Epoch 3/10

  1/128 [..............................] - ETA: 0s - loss: 6.3140e-09
 40/128 [========>.....................] - ETA: 0s - loss: 7.7809e-09
 82/128 [==================>...........] - ETA: 0s - loss: 2.4937e-06
123/128 [===========================>..] - ETA: 0s - loss: 1.7016e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.6457e-06
Epoch 4/10

  1/128 [..............................] - ETA: 0s - loss: 5.0437e-09
 37/128 [=======>......................] - ETA: 0s - loss: 5.7504e-08
 77/128 [=================>............] - ETA: 0s - loss: 2.5585e-06
118/128 [==========================>...] - ETA: 0s - loss: 1.6817e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.5604e-06
Epoch 5/10

  1/128 [..............................] - ETA: 0s - loss: 5.4754e-09
 40/128 [========>.....................] - ETA: 0s - loss: 4.6594e-07
 78/128 [=================>............] - ETA: 0s - loss: 2.2996e-06
116/128 [==========================>...] - ETA: 0s - loss: 1.6152e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.4735e-06
Epoch 6/10

  1/128 [..............................] - ETA: 0s - loss: 7.1887e-09
 40/128 [========>.....................] - ETA: 0s - loss: 5.2199e-07
 76/128 [================>.............] - ETA: 0s - loss: 2.2165e-06
114/128 [=========================>....] - ETA: 0s - loss: 1.4974e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.3942e-06
Epoch 7/10

  1/128 [..............................] - ETA: 0s - loss: 4.7136e-09
 39/128 [========>.....................] - ETA: 0s - loss: 1.9775e-07
 81/128 [=================>............] - ETA: 0s - loss: 2.0673e-06
120/128 [===========================>..] - ETA: 0s - loss: 1.3993e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.3203e-06
Epoch 8/10

  1/128 [..............................] - ETA: 0s - loss: 2.8347e-06
 41/128 [========>.....................] - ETA: 0s - loss: 1.0829e-07
 80/128 [=================>............] - ETA: 0s - loss: 1.9982e-06
119/128 [==========================>...] - ETA: 0s - loss: 1.3451e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.2586e-06
Epoch 9/10

  1/128 [..............................] - ETA: 0s - loss: 8.5252e-07
 37/128 [=======>......................] - ETA: 0s - loss: 6.1174e-07
 77/128 [=================>............] - ETA: 0s - loss: 2.9619e-07
118/128 [==========================>...] - ETA: 0s - loss: 1.2947e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.2039e-06
Epoch 10/10

  1/128 [..............................] - ETA: 0s - loss: 5.1318e-09
 40/128 [========>.....................] - ETA: 0s - loss: 6.2249e-09
 80/128 [=================>............] - ETA: 0s - loss: 1.6077e-06
119/128 [==========================>...] - ETA: 0s - loss: 1.2312e-06
128/128 [==============================] - 0s 1ms/step - loss: 1.1522e-06
-> test with GAN.predict
GAN tn, fp: 315, 2
GAN fn, tp: 0, 9
GAN f1 score: 0.900
GAN cohens kappa score: 0.897

-> test with 'LR'
LR tn, fp: 317, 0
LR fn, tp: 0, 9
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000

-> test with 'RF'
RF tn, fp: 317, 0
RF fn, tp: 0, 9
RF f1 score: 1.000
RF cohens kappa score: 1.000

-> test with 'GB'
GB tn, fp: 317, 0
GB fn, tp: 0, 9
GB f1 score: 1.000
GB cohens kappa score: 1.000

-> test with 'KNN'
KNN tn, fp: 317, 0
KNN fn, tp: 0, 9
KNN f1 score: 1.000
KNN cohens kappa score: 1.000

### Exercise is done.

-----[ LR ]-----
maximum:
LR tn, fp: 318, 2
LR fn, tp: 0, 11
LR f1 score: 1.000
LR cohens kappa score: 1.000
LR average precision score: 1.000


average:
LR tn, fp: 317.56, 0.24
LR fn, tp: 0.0, 10.6
LR f1 score: 0.989
LR cohens kappa score: 0.989
LR average precision score: 0.990


minimum:
LR tn, fp: 316, 0
LR fn, tp: 0, 9
LR f1 score: 0.917
LR cohens kappa score: 0.914
LR average precision score: 0.917


-----[ RF ]-----
maximum:
RF tn, fp: 318, 0
RF fn, tp: 0, 11
RF f1 score: 1.000
RF cohens kappa score: 1.000


average:
RF tn, fp: 317.8, 0.0
RF fn, tp: 0.0, 10.6
RF f1 score: 1.000
RF cohens kappa score: 1.000


minimum:
RF tn, fp: 317, 0
RF fn, tp: 0, 9
RF f1 score: 1.000
RF cohens kappa score: 1.000


-----[ GB ]-----
maximum:
GB tn, fp: 318, 3
GB fn, tp: 0, 11
GB f1 score: 1.000
GB cohens kappa score: 1.000


average:
GB tn, fp: 317.68, 0.12
GB fn, tp: 0.0, 10.6
GB f1 score: 0.995
GB cohens kappa score: 0.995


minimum:
GB tn, fp: 315, 0
GB fn, tp: 0, 9
GB f1 score: 0.880
GB cohens kappa score: 0.875


-----[ KNN ]-----
maximum:
KNN tn, fp: 318, 2
KNN fn, tp: 0, 11
KNN f1 score: 1.000
KNN cohens kappa score: 1.000


average:
KNN tn, fp: 317.4, 0.4
KNN fn, tp: 0.0, 10.6
KNN f1 score: 0.982
KNN cohens kappa score: 0.982


minimum:
KNN tn, fp: 316, 0
KNN fn, tp: 0, 9
KNN f1 score: 0.917
KNN cohens kappa score: 0.914


-----[ GAN ]-----
maximum:
GAN tn, fp: 318, 2
GAN fn, tp: 0, 11
GAN f1 score: 1.000
GAN cohens kappa score: 1.000


average:
GAN tn, fp: 317.6, 0.2
GAN fn, tp: 0.0, 10.6
GAN f1 score: 0.991
GAN cohens kappa score: 0.991


minimum:
GAN tn, fp: 315, 0
GAN fn, tp: 0, 9
GAN f1 score: 0.900
GAN cohens kappa score: 0.897