/////////////////////////////////////////// // Running convGAN-proximary-full on folding_car-vgood /////////////////////////////////////////// Load 'data_input/folding_car-vgood' 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 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 17s - loss: 1.2061e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.1024  82/133 [=================>............] - ETA: 0s - loss: 0.0743 122/133 [==========================>...] - ETA: 0s - loss: 0.0722 133/133 [==============================] - 0s 1ms/step - loss: 0.0763 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 2.6368e-04 43/133 [========>.....................] - ETA: 0s - loss: 0.0411  86/133 [==================>...........] - ETA: 0s - loss: 0.0687 130/133 [============================>.] - ETA: 0s - loss: 0.0536 133/133 [==============================] - 0s 1ms/step - loss: 0.0524 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0111 43/133 [========>.....................] - ETA: 0s - loss: 0.0566 85/133 [==================>...........] - ETA: 0s - loss: 0.0370 127/133 [===========================>..] - ETA: 0s - loss: 0.0391 133/133 [==============================] - 0s 1ms/step - loss: 0.0416 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0051 44/133 [========>.....................] - ETA: 0s - loss: 0.0371 87/133 [==================>...........] - ETA: 0s - loss: 0.0465 126/133 [===========================>..] - ETA: 0s - loss: 0.0386 133/133 [==============================] - 0s 1ms/step - loss: 0.0366 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 1.3009e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.0156  82/133 [=================>............] - ETA: 0s - loss: 0.0230 124/133 [==========================>...] - ETA: 0s - loss: 0.0291 133/133 [==============================] - 0s 1ms/step - loss: 0.0279 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0054 43/133 [========>.....................] - ETA: 0s - loss: 0.0149 83/133 [=================>............] - ETA: 0s - loss: 0.0263 125/133 [===========================>..] - ETA: 0s - loss: 0.0276 133/133 [==============================] - 0s 1ms/step - loss: 0.0260 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0010 42/133 [========>.....................] - ETA: 0s - loss: 0.0370 82/133 [=================>............] - ETA: 0s - loss: 0.0290 125/133 [===========================>..] - ETA: 0s - loss: 0.0279 133/133 [==============================] - 0s 1ms/step - loss: 0.0263 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 2.3610e-04 44/133 [========>.....................] - ETA: 0s - loss: 0.0273  87/133 [==================>...........] - ETA: 0s - loss: 0.0237 129/133 [============================>.] - ETA: 0s - loss: 0.0254 133/133 [==============================] - 0s 1ms/step - loss: 0.0247 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 42/133 [========>.....................] - ETA: 0s - loss: 0.0185 83/133 [=================>............] - ETA: 0s - loss: 0.0184 124/133 [==========================>...] - ETA: 0s - loss: 0.0197 133/133 [==============================] - 0s 1ms/step - loss: 0.0195 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0472 43/133 [========>.....................] - ETA: 0s - loss: 0.0257 86/133 [==================>...........] - ETA: 0s - loss: 0.0189 128/133 [===========================>..] - ETA: 0s - loss: 0.0196 133/133 [==============================] - 0s 1ms/step - loss: 0.0196 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 1, 12 GAN f1 score: 0.857 GAN cohens kappa score: 0.851 -> test with 'LR' LR tn, fp: 296, 37 LR fn, tp: 0, 13 LR f1 score: 0.413 LR cohens kappa score: 0.375 LR average precision score: 0.357 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 329, 4 KNN fn, tp: 0, 13 KNN f1 score: 0.867 KNN cohens kappa score: 0.861 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 7.6320e-06 42/133 [========>.....................] - ETA: 0s - loss: 0.0544  84/133 [=================>............] - ETA: 0s - loss: 0.0681 127/133 [===========================>..] - ETA: 0s - loss: 0.0687 133/133 [==============================] - 0s 1ms/step - loss: 0.0688 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 7.5677e-05 43/133 [========>.....................] - ETA: 0s - loss: 0.0552  84/133 [=================>............] - ETA: 0s - loss: 0.0518 126/133 [===========================>..] - ETA: 0s - loss: 0.0512 133/133 [==============================] - 0s 1ms/step - loss: 0.0487 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0913 42/133 [========>.....................] - ETA: 0s - loss: 0.0599 77/133 [================>.............] - ETA: 0s - loss: 0.0520 114/133 [========================>.....] - ETA: 0s - loss: 0.0422 133/133 [==============================] - 0s 1ms/step - loss: 0.0383 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0013 41/133 [========>.....................] - ETA: 0s - loss: 0.0156 84/133 [=================>............] - ETA: 0s - loss: 0.0203 126/133 [===========================>..] - ETA: 0s - loss: 0.0294 133/133 [==============================] - 0s 1ms/step - loss: 0.0298 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0168 45/133 [=========>....................] - ETA: 0s - loss: 0.0188 84/133 [=================>............] - ETA: 0s - loss: 0.0186 125/133 [===========================>..] - ETA: 0s - loss: 0.0262 133/133 [==============================] - 0s 1ms/step - loss: 0.0267 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.1039 44/133 [========>.....................] - ETA: 0s - loss: 0.0377 87/133 [==================>...........] - ETA: 0s - loss: 0.0314 130/133 [============================>.] - ETA: 0s - loss: 0.0252 133/133 [==============================] - 0s 1ms/step - loss: 0.0250 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0041 44/133 [========>.....................] - ETA: 0s - loss: 0.0198 87/133 [==================>...........] - ETA: 0s - loss: 0.0171 130/133 [============================>.] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 1ms/step - loss: 0.0202 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0093 42/133 [========>.....................] - ETA: 0s - loss: 0.0148 79/133 [================>.............] - ETA: 0s - loss: 0.0212 114/133 [========================>.....] - ETA: 0s - loss: 0.0197 133/133 [==============================] - 0s 1ms/step - loss: 0.0185 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 2.2231e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0191  82/133 [=================>............] - ETA: 0s - loss: 0.0217 123/133 [==========================>...] - ETA: 0s - loss: 0.0186 133/133 [==============================] - 0s 1ms/step - loss: 0.0178 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.2274 43/133 [========>.....................] - ETA: 0s - loss: 0.0172 87/133 [==================>...........] - ETA: 0s - loss: 0.0119 131/133 [============================>.] - ETA: 0s - loss: 0.0152 133/133 [==============================] - 0s 1ms/step - loss: 0.0160 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 1, 12 GAN f1 score: 0.857 GAN cohens kappa score: 0.851 -> test with 'LR' LR tn, fp: 297, 36 LR fn, tp: 1, 12 LR f1 score: 0.393 LR cohens kappa score: 0.355 LR average precision score: 0.296 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 1, 12 GB f1 score: 0.960 GB cohens kappa score: 0.959 -> test with 'KNN' KNN tn, fp: 324, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 5.5249e-07 44/133 [========>.....................] - ETA: 0s - loss: 0.1177  84/133 [=================>............] - ETA: 0s - loss: 0.1370 122/133 [==========================>...] - ETA: 0s - loss: 0.1427 133/133 [==============================] - 0s 1ms/step - loss: 0.1409 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0775 39/133 [=======>......................] - ETA: 0s - loss: 0.1119 76/133 [================>.............] - ETA: 0s - loss: 0.0932 112/133 [========================>.....] - ETA: 0s - loss: 0.0928 133/133 [==============================] - 0s 1ms/step - loss: 0.0838 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.6040e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.0807  83/133 [=================>............] - ETA: 0s - loss: 0.0736 122/133 [==========================>...] - ETA: 0s - loss: 0.0749 133/133 [==============================] - 0s 1ms/step - loss: 0.0690 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 6.2149e-05 43/133 [========>.....................] - ETA: 0s - loss: 0.0635  85/133 [==================>...........] - ETA: 0s - loss: 0.0479 127/133 [===========================>..] - ETA: 0s - loss: 0.0540 133/133 [==============================] - 0s 1ms/step - loss: 0.0543 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 9.0181e-05 36/133 [=======>......................] - ETA: 0s - loss: 0.0557  76/133 [================>.............] - ETA: 0s - loss: 0.0562 117/133 [=========================>....] - ETA: 0s - loss: 0.0482 133/133 [==============================] - 0s 1ms/step - loss: 0.0478 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.2470 42/133 [========>.....................] - ETA: 0s - loss: 0.0545 83/133 [=================>............] - ETA: 0s - loss: 0.0460 123/133 [==========================>...] - ETA: 0s - loss: 0.0459 133/133 [==============================] - 0s 1ms/step - loss: 0.0426 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 5.4382e-04 43/133 [========>.....................] - ETA: 0s - loss: 0.0497  85/133 [==================>...........] - ETA: 0s - loss: 0.0411 124/133 [==========================>...] - ETA: 0s - loss: 0.0363 133/133 [==============================] - 0s 1ms/step - loss: 0.0367 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 2.0503e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.0283  82/133 [=================>............] - ETA: 0s - loss: 0.0335 124/133 [==========================>...] - ETA: 0s - loss: 0.0352 133/133 [==============================] - 0s 1ms/step - loss: 0.0344 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0017 43/133 [========>.....................] - ETA: 0s - loss: 0.0342 85/133 [==================>...........] - ETA: 0s - loss: 0.0379 127/133 [===========================>..] - ETA: 0s - loss: 0.0324 133/133 [==============================] - 0s 1ms/step - loss: 0.0327 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 2.8836e-04 43/133 [========>.....................] - ETA: 0s - loss: 0.0188  85/133 [==================>...........] - ETA: 0s - loss: 0.0285 125/133 [===========================>..] - ETA: 0s - loss: 0.0305 133/133 [==============================] - 0s 1ms/step - loss: 0.0296 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 6, 7 GAN f1 score: 0.609 GAN cohens kappa score: 0.595 -> test with 'LR' LR tn, fp: 297, 36 LR fn, tp: 0, 13 LR f1 score: 0.419 LR cohens kappa score: 0.383 LR average precision score: 0.400 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 3, 10 RF f1 score: 0.870 RF cohens kappa score: 0.865 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 1, 12 GB f1 score: 0.960 GB cohens kappa score: 0.959 -> test with 'KNN' KNN tn, fp: 330, 3 KNN fn, tp: 3, 10 KNN f1 score: 0.769 KNN cohens kappa score: 0.760 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 17s - loss: 0.7737 41/133 [========>.....................] - ETA: 0s - loss: 0.1070  83/133 [=================>............] - ETA: 0s - loss: 0.0793 124/133 [==========================>...] - ETA: 0s - loss: 0.0606 133/133 [==============================] - 0s 1ms/step - loss: 0.0595 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0299 39/133 [=======>......................] - ETA: 0s - loss: 0.0525 76/133 [================>.............] - ETA: 0s - loss: 0.0335 115/133 [========================>.....] - ETA: 0s - loss: 0.0315 133/133 [==============================] - 0s 1ms/step - loss: 0.0300 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 43/133 [========>.....................] - ETA: 0s - loss: 0.0199 84/133 [=================>............] - ETA: 0s - loss: 0.0183 125/133 [===========================>..] - ETA: 0s - loss: 0.0173 133/133 [==============================] - 0s 1ms/step - loss: 0.0197 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 5.5786e-05 41/133 [========>.....................] - ETA: 0s - loss: 0.0103  81/133 [=================>............] - ETA: 0s - loss: 0.0125 124/133 [==========================>...] - ETA: 0s - loss: 0.0142 133/133 [==============================] - 0s 1ms/step - loss: 0.0157 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0010 41/133 [========>.....................] - ETA: 0s - loss: 0.0155 83/133 [=================>............] - ETA: 0s - loss: 0.0150 125/133 [===========================>..] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 1ms/step - loss: 0.0139 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0035 41/133 [========>.....................] - ETA: 0s - loss: 0.0200 83/133 [=================>............] - ETA: 0s - loss: 0.0125 126/133 [===========================>..] - ETA: 0s - loss: 0.0108 133/133 [==============================] - 0s 1ms/step - loss: 0.0118 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0045 43/133 [========>.....................] - ETA: 0s - loss: 0.0112 82/133 [=================>............] - ETA: 0s - loss: 0.0135 118/133 [=========================>....] - ETA: 0s - loss: 0.0101 133/133 [==============================] - 0s 1ms/step - loss: 0.0093 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 8.7359e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.0046  75/133 [===============>..............] - ETA: 0s - loss: 0.0116 115/133 [========================>.....] - ETA: 0s - loss: 0.0103 133/133 [==============================] - 0s 1ms/step - loss: 0.0103 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0093 44/133 [========>.....................] - ETA: 0s - loss: 0.0088 84/133 [=================>............] - ETA: 0s - loss: 0.0068 127/133 [===========================>..] - ETA: 0s - loss: 0.0085 133/133 [==============================] - 0s 1ms/step - loss: 0.0086 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.7484e-04 42/133 [========>.....................] - ETA: 0s - loss: 0.0084  85/133 [==================>...........] - ETA: 0s - loss: 0.0076 126/133 [===========================>..] - ETA: 0s - loss: 0.0075 133/133 [==============================] - 0s 1ms/step - loss: 0.0074 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 1, 12 GAN f1 score: 0.889 GAN cohens kappa score: 0.884 -> test with 'LR' LR tn, fp: 293, 40 LR fn, tp: 0, 13 LR f1 score: 0.394 LR cohens kappa score: 0.355 LR average precision score: 0.374 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 325, 8 KNN fn, tp: 0, 13 KNN f1 score: 0.765 KNN cohens kappa score: 0.753 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 39s - loss: 2.4584e-04 29/134 [=====>........................] - ETA: 0s - loss: 0.0448  58/134 [===========>..................] - ETA: 0s - loss: 0.0496 81/134 [=================>............] - ETA: 0s - loss: 0.0512 115/134 [========================>.....] - ETA: 0s - loss: 0.0424 134/134 [==============================] - 1s 2ms/step - loss: 0.0375 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.0029 35/134 [======>.......................] - ETA: 0s - loss: 0.0240 73/134 [===============>..............] - ETA: 0s - loss: 0.0274 107/134 [======================>.......] - ETA: 0s - loss: 0.0208 134/134 [==============================] - 0s 1ms/step - loss: 0.0200 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 2.1898e-04 37/134 [=======>......................] - ETA: 0s - loss: 0.0105  71/134 [==============>...............] - ETA: 0s - loss: 0.0115 92/134 [===================>..........] - ETA: 0s - loss: 0.0109 115/134 [========================>.....] - ETA: 0s - loss: 0.0125 134/134 [==============================] - 0s 2ms/step - loss: 0.0114 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0050 32/134 [======>.......................] - ETA: 0s - loss: 0.0053 60/134 [============>.................] - ETA: 0s - loss: 0.0068 97/134 [====================>.........] - ETA: 0s - loss: 0.0108 132/134 [============================>.] - ETA: 0s - loss: 0.0107 134/134 [==============================] - 0s 2ms/step - loss: 0.0107 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.0025 34/134 [======>.......................] - ETA: 0s - loss: 0.0038 70/134 [==============>...............] - ETA: 0s - loss: 0.0044 104/134 [======================>.......] - ETA: 0s - loss: 0.0060 132/134 [============================>.] - ETA: 0s - loss: 0.0081 134/134 [==============================] - 0s 2ms/step - loss: 0.0080 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 4.2315e-04 32/134 [======>.......................] - ETA: 0s - loss: 0.0099  55/134 [===========>..................] - ETA: 0s - loss: 0.0095 83/134 [=================>............] - ETA: 0s - loss: 0.0098 115/134 [========================>.....] - ETA: 0s - loss: 0.0086 134/134 [==============================] - 0s 2ms/step - loss: 0.0085 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0014 35/134 [======>.......................] - ETA: 0s - loss: 0.0068 65/134 [=============>................] - ETA: 0s - loss: 0.0063 95/134 [====================>.........] - ETA: 0s - loss: 0.0054 128/134 [===========================>..] - ETA: 0s - loss: 0.0072 134/134 [==============================] - 0s 2ms/step - loss: 0.0071 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0037 34/134 [======>.......................] - ETA: 0s - loss: 0.0142 69/134 [==============>...............] - ETA: 0s - loss: 0.0085 103/134 [======================>.......] - ETA: 0s - loss: 0.0070 134/134 [==============================] - 0s 1ms/step - loss: 0.0060 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 3.8703e-04 35/134 [======>.......................] - ETA: 0s - loss: 0.0033  69/134 [==============>...............] - ETA: 0s - loss: 0.0079 104/134 [======================>.......] - ETA: 0s - loss: 0.0069 134/134 [==============================] - 0s 1ms/step - loss: 0.0060 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0013 37/134 [=======>......................] - ETA: 0s - loss: 0.0063 75/134 [===============>..............] - ETA: 0s - loss: 0.0083 112/134 [========================>.....] - ETA: 0s - loss: 0.0070 134/134 [==============================] - 0s 1ms/step - loss: 0.0062 -> test with GAN.predict GAN tn, fp: 330, 1 GAN fn, tp: 2, 11 GAN f1 score: 0.880 GAN cohens kappa score: 0.875 -> test with 'LR' LR tn, fp: 298, 33 LR fn, tp: 1, 12 LR f1 score: 0.414 LR cohens kappa score: 0.377 LR average precision score: 0.446 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 3, 10 RF f1 score: 0.870 RF cohens kappa score: 0.865 -> test with 'GB' GB tn, fp: 329, 2 GB fn, tp: 0, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 322, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 21s - loss: 1.2327e-04 43/133 [========>.....................] - ETA: 0s - loss: 0.1817  85/133 [==================>...........] - ETA: 0s - loss: 0.1395 127/133 [===========================>..] - ETA: 0s - loss: 0.1503 133/133 [==============================] - 0s 1ms/step - loss: 0.1481 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 43/133 [========>.....................] - ETA: 0s - loss: 0.0597 84/133 [=================>............] - ETA: 0s - loss: 0.0582 122/133 [==========================>...] - ETA: 0s - loss: 0.0715 133/133 [==============================] - 0s 1ms/step - loss: 0.0751 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.1838 43/133 [========>.....................] - ETA: 0s - loss: 0.0709 85/133 [==================>...........] - ETA: 0s - loss: 0.0522 127/133 [===========================>..] - ETA: 0s - loss: 0.0505 133/133 [==============================] - 0s 1ms/step - loss: 0.0553 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 4.8014e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.0360  83/133 [=================>............] - ETA: 0s - loss: 0.0430 125/133 [===========================>..] - ETA: 0s - loss: 0.0505 133/133 [==============================] - 0s 1ms/step - loss: 0.0494 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 2.1087e-04 44/133 [========>.....................] - ETA: 0s - loss: 0.0665  82/133 [=================>............] - ETA: 0s - loss: 0.0505 123/133 [==========================>...] - ETA: 0s - loss: 0.0444 133/133 [==============================] - 0s 1ms/step - loss: 0.0433 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0075 44/133 [========>.....................] - ETA: 0s - loss: 0.0283 85/133 [==================>...........] - ETA: 0s - loss: 0.0320 127/133 [===========================>..] - ETA: 0s - loss: 0.0366 133/133 [==============================] - 0s 1ms/step - loss: 0.0377 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 3.1363e-04 42/133 [========>.....................] - ETA: 0s - loss: 0.0275  83/133 [=================>............] - ETA: 0s - loss: 0.0350 126/133 [===========================>..] - ETA: 0s - loss: 0.0347 133/133 [==============================] - 0s 1ms/step - loss: 0.0335 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 3.6536e-04 44/133 [========>.....................] - ETA: 0s - loss: 0.0281  85/133 [==================>...........] - ETA: 0s - loss: 0.0312 126/133 [===========================>..] - ETA: 0s - loss: 0.0322 133/133 [==============================] - 0s 1ms/step - loss: 0.0314 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 5.6095e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0362  80/133 [=================>............] - ETA: 0s - loss: 0.0330 114/133 [========================>.....] - ETA: 0s - loss: 0.0286 133/133 [==============================] - 0s 1ms/step - loss: 0.0278 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.1097 41/133 [========>.....................] - ETA: 0s - loss: 0.0204 82/133 [=================>............] - ETA: 0s - loss: 0.0257 123/133 [==========================>...] - ETA: 0s - loss: 0.0275 133/133 [==============================] - 0s 1ms/step - loss: 0.0270 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 5, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.627 -> test with 'LR' LR tn, fp: 301, 32 LR fn, tp: 1, 12 LR f1 score: 0.421 LR cohens kappa score: 0.385 LR average precision score: 0.287 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 324, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.8200 40/133 [========>.....................] - ETA: 0s - loss: 0.2521  79/133 [================>.............] - ETA: 0s - loss: 0.2404 118/133 [=========================>....] - ETA: 0s - loss: 0.2042 133/133 [==============================] - 0s 1ms/step - loss: 0.2069 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.3491 41/133 [========>.....................] - ETA: 0s - loss: 0.1409 78/133 [================>.............] - ETA: 0s - loss: 0.1133 117/133 [=========================>....] - ETA: 0s - loss: 0.1104 133/133 [==============================] - 0s 1ms/step - loss: 0.1006 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.7261e-04 34/133 [======>.......................] - ETA: 0s - loss: 0.0732  73/133 [===============>..............] - ETA: 0s - loss: 0.0669 110/133 [=======================>......] - ETA: 0s - loss: 0.0775 133/133 [==============================] - 0s 1ms/step - loss: 0.0817 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 3.5818e-04 42/133 [========>.....................] - ETA: 0s - loss: 0.0731  84/133 [=================>............] - ETA: 0s - loss: 0.0639 125/133 [===========================>..] - ETA: 0s - loss: 0.0675 133/133 [==============================] - 0s 1ms/step - loss: 0.0674 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.1314 42/133 [========>.....................] - ETA: 0s - loss: 0.0377 83/133 [=================>............] - ETA: 0s - loss: 0.0562 122/133 [==========================>...] - ETA: 0s - loss: 0.0583 133/133 [==============================] - 0s 1ms/step - loss: 0.0627 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0860 44/133 [========>.....................] - ETA: 0s - loss: 0.0740 85/133 [==================>...........] - ETA: 0s - loss: 0.0532 127/133 [===========================>..] - ETA: 0s - loss: 0.0518 133/133 [==============================] - 0s 1ms/step - loss: 0.0533 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0203 43/133 [========>.....................] - ETA: 0s - loss: 0.0365 85/133 [==================>...........] - ETA: 0s - loss: 0.0603 125/133 [===========================>..] - ETA: 0s - loss: 0.0510 133/133 [==============================] - 0s 1ms/step - loss: 0.0510 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0061 39/133 [=======>......................] - ETA: 0s - loss: 0.0497 73/133 [===============>..............] - ETA: 0s - loss: 0.0489 110/133 [=======================>......] - ETA: 0s - loss: 0.0435 133/133 [==============================] - 0s 1ms/step - loss: 0.0453 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 33/133 [======>.......................] - ETA: 0s - loss: 0.0313 67/133 [==============>...............] - ETA: 0s - loss: 0.0435 107/133 [=======================>......] - ETA: 0s - loss: 0.0417 133/133 [==============================] - 0s 1ms/step - loss: 0.0419 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 43/133 [========>.....................] - ETA: 0s - loss: 0.0539 84/133 [=================>............] - ETA: 0s - loss: 0.0478 126/133 [===========================>..] - ETA: 0s - loss: 0.0389 133/133 [==============================] - 0s 1ms/step - loss: 0.0399 -> test with GAN.predict GAN tn, fp: 328, 5 GAN fn, tp: 1, 12 GAN f1 score: 0.800 GAN cohens kappa score: 0.791 -> test with 'LR' LR tn, fp: 287, 46 LR fn, tp: 0, 13 LR f1 score: 0.361 LR cohens kappa score: 0.319 LR average precision score: 0.365 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 332, 1 GB fn, tp: 0, 13 GB f1 score: 0.963 GB cohens kappa score: 0.961 -> test with 'KNN' KNN tn, fp: 322, 11 KNN fn, tp: 0, 13 KNN f1 score: 0.703 KNN cohens kappa score: 0.687 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 25s - loss: 0.1980 34/133 [======>.......................] - ETA: 0s - loss: 0.3444  68/133 [==============>...............] - ETA: 0s - loss: 0.2722 102/133 [======================>.......] - ETA: 0s - loss: 0.2374 133/133 [==============================] - 0s 2ms/step - loss: 0.2129 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0257 39/133 [=======>......................] - ETA: 0s - loss: 0.1955 79/133 [================>.............] - ETA: 0s - loss: 0.1221 120/133 [==========================>...] - ETA: 0s - loss: 0.1101 133/133 [==============================] - 0s 1ms/step - loss: 0.1142 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0147 40/133 [========>.....................] - ETA: 0s - loss: 0.1246 78/133 [================>.............] - ETA: 0s - loss: 0.1127 118/133 [=========================>....] - ETA: 0s - loss: 0.0889 133/133 [==============================] - 0s 1ms/step - loss: 0.0834 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 8.9541e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.0989  77/133 [================>.............] - ETA: 0s - loss: 0.0746 113/133 [========================>.....] - ETA: 0s - loss: 0.0792 133/133 [==============================] - 0s 1ms/step - loss: 0.0699 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.3302 30/133 [=====>........................] - ETA: 0s - loss: 0.0543 59/133 [============>.................] - ETA: 0s - loss: 0.0480 88/133 [==================>...........] - ETA: 0s - loss: 0.0553 123/133 [==========================>...] - ETA: 0s - loss: 0.0588 133/133 [==============================] - 0s 2ms/step - loss: 0.0604 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0148 32/133 [======>.......................] - ETA: 0s - loss: 0.0482 66/133 [=============>................] - ETA: 0s - loss: 0.0589 98/133 [=====================>........] - ETA: 0s - loss: 0.0581 130/133 [============================>.] - ETA: 0s - loss: 0.0523 133/133 [==============================] - 0s 2ms/step - loss: 0.0540 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0069 42/133 [========>.....................] - ETA: 0s - loss: 0.0712 83/133 [=================>............] - ETA: 0s - loss: 0.0610 124/133 [==========================>...] - ETA: 0s - loss: 0.0497 133/133 [==============================] - 0s 1ms/step - loss: 0.0510 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0121 33/133 [======>.......................] - ETA: 0s - loss: 0.0228 65/133 [=============>................] - ETA: 0s - loss: 0.0319 97/133 [====================>.........] - ETA: 0s - loss: 0.0530 129/133 [============================>.] - ETA: 0s - loss: 0.0518 133/133 [==============================] - 0s 2ms/step - loss: 0.0512 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0300 30/133 [=====>........................] - ETA: 0s - loss: 0.0650 61/133 [============>.................] - ETA: 0s - loss: 0.0544 96/133 [====================>.........] - ETA: 0s - loss: 0.0499 129/133 [============================>.] - ETA: 0s - loss: 0.0465 133/133 [==============================] - 0s 2ms/step - loss: 0.0455 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0179 34/133 [======>.......................] - ETA: 0s - loss: 0.0591 66/133 [=============>................] - ETA: 0s - loss: 0.0563 96/133 [====================>.........] - ETA: 0s - loss: 0.0500 125/133 [===========================>..] - ETA: 0s - loss: 0.0449 133/133 [==============================] - 0s 2ms/step - loss: 0.0432 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 0, 13 GAN f1 score: 0.867 GAN cohens kappa score: 0.861 -> test with 'LR' LR tn, fp: 294, 39 LR fn, tp: 1, 12 LR f1 score: 0.375 LR cohens kappa score: 0.335 LR average precision score: 0.340 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 325, 8 KNN fn, tp: 0, 13 KNN f1 score: 0.765 KNN cohens kappa score: 0.753 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 2.4436e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.1749  84/133 [=================>............] - ETA: 0s - loss: 0.1636 123/133 [==========================>...] - ETA: 0s - loss: 0.1343 133/133 [==============================] - 0s 1ms/step - loss: 0.1419 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.1620 36/133 [=======>......................] - ETA: 0s - loss: 0.1193 76/133 [================>.............] - ETA: 0s - loss: 0.0916 113/133 [========================>.....] - ETA: 0s - loss: 0.0853 133/133 [==============================] - 0s 1ms/step - loss: 0.0827 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0686 31/133 [=====>........................] - ETA: 0s - loss: 0.0755 54/133 [===========>..................] - ETA: 0s - loss: 0.0709 80/133 [=================>............] - ETA: 0s - loss: 0.0804 106/133 [======================>.......] - ETA: 0s - loss: 0.0672 133/133 [==============================] - 0s 2ms/step - loss: 0.0670 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0560 34/133 [======>.......................] - ETA: 0s - loss: 0.0687 63/133 [=============>................] - ETA: 0s - loss: 0.0488 94/133 [====================>.........] - ETA: 0s - loss: 0.0509 123/133 [==========================>...] - ETA: 0s - loss: 0.0570 133/133 [==============================] - 0s 2ms/step - loss: 0.0575 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0022 32/133 [======>.......................] - ETA: 0s - loss: 0.0662 64/133 [=============>................] - ETA: 0s - loss: 0.0472 97/133 [====================>.........] - ETA: 0s - loss: 0.0496 133/133 [==============================] - 0s 1ms/step - loss: 0.0519 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 6.2552e-05 40/133 [========>.....................] - ETA: 0s - loss: 0.0540  82/133 [=================>............] - ETA: 0s - loss: 0.0420 120/133 [==========================>...] - ETA: 0s - loss: 0.0484 133/133 [==============================] - 0s 1ms/step - loss: 0.0456 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0113 35/133 [======>.......................] - ETA: 0s - loss: 0.0349 75/133 [===============>..............] - ETA: 0s - loss: 0.0340 115/133 [========================>.....] - ETA: 0s - loss: 0.0354 133/133 [==============================] - 0s 1ms/step - loss: 0.0425 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0135 43/133 [========>.....................] - ETA: 0s - loss: 0.0366 77/133 [================>.............] - ETA: 0s - loss: 0.0334 116/133 [=========================>....] - ETA: 0s - loss: 0.0344 133/133 [==============================] - 0s 1ms/step - loss: 0.0404 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0043 41/133 [========>.....................] - ETA: 0s - loss: 0.0307 82/133 [=================>............] - ETA: 0s - loss: 0.0272 122/133 [==========================>...] - ETA: 0s - loss: 0.0374 133/133 [==============================] - 0s 1ms/step - loss: 0.0382 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0221 36/133 [=======>......................] - ETA: 0s - loss: 0.0475 77/133 [================>.............] - ETA: 0s - loss: 0.0354 116/133 [=========================>....] - ETA: 0s - loss: 0.0355 133/133 [==============================] - 0s 1ms/step - loss: 0.0353 -> test with GAN.predict GAN tn, fp: 326, 7 GAN fn, tp: 3, 10 GAN f1 score: 0.667 GAN cohens kappa score: 0.652 -> test with 'LR' LR tn, fp: 298, 35 LR fn, tp: 0, 13 LR f1 score: 0.426 LR cohens kappa score: 0.390 LR average precision score: 0.284 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 3, 10 GB f1 score: 0.870 GB cohens kappa score: 0.865 -> test with 'KNN' KNN tn, fp: 326, 7 KNN fn, tp: 0, 13 KNN f1 score: 0.788 KNN cohens kappa score: 0.778 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 20s - loss: 0.9143 40/134 [=======>......................] - ETA: 0s - loss: 0.2004  79/134 [================>.............] - ETA: 0s - loss: 0.1970 118/134 [=========================>....] - ETA: 0s - loss: 0.1417 134/134 [==============================] - 0s 1ms/step - loss: 0.1354 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.1473 40/134 [=======>......................] - ETA: 0s - loss: 0.0845 79/134 [================>.............] - ETA: 0s - loss: 0.0763 115/134 [========================>.....] - ETA: 0s - loss: 0.0679 134/134 [==============================] - 0s 1ms/step - loss: 0.0716 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 4.0201e-05 35/134 [======>.......................] - ETA: 0s - loss: 0.0639  66/134 [=============>................] - ETA: 0s - loss: 0.0537 102/134 [=====================>........] - ETA: 0s - loss: 0.0463 134/134 [==============================] - 0s 1ms/step - loss: 0.0566 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0033 38/134 [=======>......................] - ETA: 0s - loss: 0.0620 76/134 [================>.............] - ETA: 0s - loss: 0.0450 113/134 [========================>.....] - ETA: 0s - loss: 0.0490 134/134 [==============================] - 0s 1ms/step - loss: 0.0494 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 9.3223e-05 41/134 [========>.....................] - ETA: 0s - loss: 0.0435  80/134 [================>.............] - ETA: 0s - loss: 0.0373 119/134 [=========================>....] - ETA: 0s - loss: 0.0357 134/134 [==============================] - 0s 1ms/step - loss: 0.0424 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0394 37/134 [=======>......................] - ETA: 0s - loss: 0.0234 76/134 [================>.............] - ETA: 0s - loss: 0.0229 115/134 [========================>.....] - ETA: 0s - loss: 0.0360 134/134 [==============================] - 0s 1ms/step - loss: 0.0368 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0902 40/134 [=======>......................] - ETA: 0s - loss: 0.0443 78/134 [================>.............] - ETA: 0s - loss: 0.0421 115/134 [========================>.....] - ETA: 0s - loss: 0.0354 134/134 [==============================] - 0s 1ms/step - loss: 0.0348 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0024 40/134 [=======>......................] - ETA: 0s - loss: 0.0303 79/134 [================>.............] - ETA: 0s - loss: 0.0377 118/134 [=========================>....] - ETA: 0s - loss: 0.0325 134/134 [==============================] - 0s 1ms/step - loss: 0.0318 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0083 39/134 [=======>......................] - ETA: 0s - loss: 0.0380 78/134 [================>.............] - ETA: 0s - loss: 0.0272 116/134 [========================>.....] - ETA: 0s - loss: 0.0345 134/134 [==============================] - 0s 1ms/step - loss: 0.0317 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0010 38/134 [=======>......................] - ETA: 0s - loss: 0.0276 76/134 [================>.............] - ETA: 0s - loss: 0.0259 114/134 [========================>.....] - ETA: 0s - loss: 0.0281 134/134 [==============================] - 0s 1ms/step - loss: 0.0287 -> test with GAN.predict GAN tn, fp: 324, 7 GAN fn, tp: 2, 11 GAN f1 score: 0.710 GAN cohens kappa score: 0.696 -> test with 'LR' LR tn, fp: 296, 35 LR fn, tp: 1, 12 LR f1 score: 0.400 LR cohens kappa score: 0.362 LR average precision score: 0.549 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 0, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 331, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 330, 1 KNN fn, tp: 0, 13 KNN f1 score: 0.963 KNN cohens kappa score: 0.961 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 24s - loss: 1.1021e-04 38/133 [=======>......................] - ETA: 0s - loss: 0.0867  75/133 [===============>..............] - ETA: 0s - loss: 0.0611 112/133 [========================>.....] - ETA: 0s - loss: 0.0494 133/133 [==============================] - 0s 1ms/step - loss: 0.0443 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0110 38/133 [=======>......................] - ETA: 0s - loss: 0.0302 76/133 [================>.............] - ETA: 0s - loss: 0.0331 114/133 [========================>.....] - ETA: 0s - loss: 0.0245 133/133 [==============================] - 0s 1ms/step - loss: 0.0222 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0051 38/133 [=======>......................] - ETA: 0s - loss: 0.0161 76/133 [================>.............] - ETA: 0s - loss: 0.0126 113/133 [========================>.....] - ETA: 0s - loss: 0.0149 133/133 [==============================] - 0s 1ms/step - loss: 0.0168 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 37/133 [=======>......................] - ETA: 0s - loss: 0.0091 74/133 [===============>..............] - ETA: 0s - loss: 0.0131 110/133 [=======================>......] - ETA: 0s - loss: 0.0142 133/133 [==============================] - 0s 1ms/step - loss: 0.0122 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0022 37/133 [=======>......................] - ETA: 0s - loss: 0.0142 74/133 [===============>..............] - ETA: 0s - loss: 0.0158 109/133 [=======================>......] - ETA: 0s - loss: 0.0140 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0011 37/133 [=======>......................] - ETA: 0s - loss: 0.0089 71/133 [===============>..............] - ETA: 0s - loss: 0.0074 101/133 [=====================>........] - ETA: 0s - loss: 0.0068 133/133 [==============================] - ETA: 0s - loss: 0.0098 133/133 [==============================] - 0s 2ms/step - loss: 0.0098 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0102 35/133 [======>.......................] - ETA: 0s - loss: 0.0081 71/133 [===============>..............] - ETA: 0s - loss: 0.0096 104/133 [======================>.......] - ETA: 0s - loss: 0.0098 133/133 [==============================] - 0s 1ms/step - loss: 0.0105 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0140 35/133 [======>.......................] - ETA: 0s - loss: 0.0041 68/133 [==============>...............] - ETA: 0s - loss: 0.0093 104/133 [======================>.......] - ETA: 0s - loss: 0.0104 133/133 [==============================] - 0s 1ms/step - loss: 0.0090 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 6.9491e-06 34/133 [======>.......................] - ETA: 0s - loss: 0.0068  68/133 [==============>...............] - ETA: 0s - loss: 0.0096 101/133 [=====================>........] - ETA: 0s - loss: 0.0091 133/133 [==============================] - 0s 1ms/step - loss: 0.0083 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0011 41/133 [========>.....................] - ETA: 0s - loss: 0.0037 76/133 [================>.............] - ETA: 0s - loss: 0.0061 111/133 [========================>.....] - ETA: 0s - loss: 0.0065 133/133 [==============================] - 0s 1ms/step - loss: 0.0071 -> test with GAN.predict GAN tn, fp: 332, 1 GAN fn, tp: 7, 6 GAN f1 score: 0.600 GAN cohens kappa score: 0.589 -> test with 'LR' LR tn, fp: 292, 41 LR fn, tp: 1, 12 LR f1 score: 0.364 LR cohens kappa score: 0.323 LR average precision score: 0.311 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 4, 9 RF f1 score: 0.818 RF cohens kappa score: 0.812 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 2, 11 GB f1 score: 0.917 GB cohens kappa score: 0.914 -> test with 'KNN' KNN tn, fp: 324, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 4.5898e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.0927  82/133 [=================>............] - ETA: 0s - loss: 0.0911 124/133 [==========================>...] - ETA: 0s - loss: 0.0670 133/133 [==============================] - 0s 1ms/step - loss: 0.0626 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 7.1411e-04 43/133 [========>.....................] - ETA: 0s - loss: 0.0341  85/133 [==================>...........] - ETA: 0s - loss: 0.0335 127/133 [===========================>..] - ETA: 0s - loss: 0.0319 133/133 [==============================] - 0s 1ms/step - loss: 0.0375 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0536 43/133 [========>.....................] - ETA: 0s - loss: 0.0103 83/133 [=================>............] - ETA: 0s - loss: 0.0295 126/133 [===========================>..] - ETA: 0s - loss: 0.0242 133/133 [==============================] - 0s 1ms/step - loss: 0.0238 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0058 38/133 [=======>......................] - ETA: 0s - loss: 0.0212 76/133 [================>.............] - ETA: 0s - loss: 0.0224 116/133 [=========================>....] - ETA: 0s - loss: 0.0187 133/133 [==============================] - 0s 1ms/step - loss: 0.0220 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 7.5644e-05 43/133 [========>.....................] - ETA: 0s - loss: 0.0097  83/133 [=================>............] - ETA: 0s - loss: 0.0133 124/133 [==========================>...] - ETA: 0s - loss: 0.0170 133/133 [==============================] - 0s 1ms/step - loss: 0.0168 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 4.3358e-06 42/133 [========>.....................] - ETA: 0s - loss: 0.0111  78/133 [================>.............] - ETA: 0s - loss: 0.0089 119/133 [=========================>....] - ETA: 0s - loss: 0.0111 133/133 [==============================] - 0s 1ms/step - loss: 0.0141 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 5.5020e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.0087  85/133 [==================>...........] - ETA: 0s - loss: 0.0119 123/133 [==========================>...] - ETA: 0s - loss: 0.0133 133/133 [==============================] - 0s 1ms/step - loss: 0.0134 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 9.7379e-08 35/133 [======>.......................] - ETA: 0s - loss: 0.0087  69/133 [==============>...............] - ETA: 0s - loss: 0.0093 108/133 [=======================>......] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 1ms/step - loss: 0.0104 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 42/133 [========>.....................] - ETA: 0s - loss: 0.0189 82/133 [=================>............] - ETA: 0s - loss: 0.0111 124/133 [==========================>...] - ETA: 0s - loss: 0.0100 133/133 [==============================] - 0s 1ms/step - loss: 0.0100 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0061 43/133 [========>.....................] - ETA: 0s - loss: 0.0148 84/133 [=================>............] - ETA: 0s - loss: 0.0107 125/133 [===========================>..] - ETA: 0s - loss: 0.0092 133/133 [==============================] - 0s 1ms/step - loss: 0.0088 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 2, 11 GAN f1 score: 0.846 GAN cohens kappa score: 0.840 -> test with 'LR' LR tn, fp: 304, 29 LR fn, tp: 0, 13 LR f1 score: 0.473 LR cohens kappa score: 0.441 LR average precision score: 0.432 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 327, 6 KNN fn, tp: 0, 13 KNN f1 score: 0.813 KNN cohens kappa score: 0.804 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 7.5991e-06 38/133 [=======>......................] - ETA: 0s - loss: 0.1484  76/133 [================>.............] - ETA: 0s - loss: 0.1327 113/133 [========================>.....] - ETA: 0s - loss: 0.1271 133/133 [==============================] - 0s 1ms/step - loss: 0.1122 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.1324 40/133 [========>.....................] - ETA: 0s - loss: 0.0699 81/133 [=================>............] - ETA: 0s - loss: 0.0647 122/133 [==========================>...] - ETA: 0s - loss: 0.0605 133/133 [==============================] - 0s 1ms/step - loss: 0.0577 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 2.5852e-05 41/133 [========>.....................] - ETA: 0s - loss: 0.0282  82/133 [=================>............] - ETA: 0s - loss: 0.0399 124/133 [==========================>...] - ETA: 0s - loss: 0.0491 133/133 [==============================] - 0s 1ms/step - loss: 0.0494 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0240 42/133 [========>.....................] - ETA: 0s - loss: 0.0304 83/133 [=================>............] - ETA: 0s - loss: 0.0444 123/133 [==========================>...] - ETA: 0s - loss: 0.0437 133/133 [==============================] - 0s 1ms/step - loss: 0.0408 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0478 43/133 [========>.....................] - ETA: 0s - loss: 0.0409 83/133 [=================>............] - ETA: 0s - loss: 0.0418 125/133 [===========================>..] - ETA: 0s - loss: 0.0385 133/133 [==============================] - 0s 1ms/step - loss: 0.0382 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 1.7687e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0380  68/133 [==============>...............] - ETA: 0s - loss: 0.0400 99/133 [=====================>........] - ETA: 0s - loss: 0.0368 129/133 [============================>.] - ETA: 0s - loss: 0.0322 133/133 [==============================] - 0s 2ms/step - loss: 0.0314 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 1.3694e-04 39/133 [=======>......................] - ETA: 0s - loss: 0.0251  80/133 [=================>............] - ETA: 0s - loss: 0.0337 122/133 [==========================>...] - ETA: 0s - loss: 0.0274 133/133 [==============================] - 0s 1ms/step - loss: 0.0273 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0461 42/133 [========>.....................] - ETA: 0s - loss: 0.0355 84/133 [=================>............] - ETA: 0s - loss: 0.0289 126/133 [===========================>..] - ETA: 0s - loss: 0.0272 133/133 [==============================] - 0s 1ms/step - loss: 0.0268 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.1247 41/133 [========>.....................] - ETA: 0s - loss: 0.0363 81/133 [=================>............] - ETA: 0s - loss: 0.0249 123/133 [==========================>...] - ETA: 0s - loss: 0.0237 133/133 [==============================] - 0s 1ms/step - loss: 0.0238 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0043 37/133 [=======>......................] - ETA: 0s - loss: 0.0243 75/133 [===============>..............] - ETA: 0s - loss: 0.0183 114/133 [========================>.....] - ETA: 0s - loss: 0.0233 133/133 [==============================] - 0s 1ms/step - loss: 0.0229 -> test with GAN.predict GAN tn, fp: 326, 7 GAN fn, tp: 4, 9 GAN f1 score: 0.621 GAN cohens kappa score: 0.604 -> test with 'LR' LR tn, fp: 299, 34 LR fn, tp: 1, 12 LR f1 score: 0.407 LR cohens kappa score: 0.370 LR average precision score: 0.334 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 0, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 332, 1 KNN fn, tp: 3, 10 KNN f1 score: 0.833 KNN cohens kappa score: 0.827 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 22s - loss: 2.0380e-06 35/133 [======>.......................] - ETA: 0s - loss: 0.0661  71/133 [===============>..............] - ETA: 0s - loss: 0.0648 111/133 [========================>.....] - ETA: 0s - loss: 0.0553 133/133 [==============================] - 0s 1ms/step - loss: 0.0490 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0042 40/133 [========>.....................] - ETA: 0s - loss: 0.0374 79/133 [================>.............] - ETA: 0s - loss: 0.0316 119/133 [=========================>....] - ETA: 0s - loss: 0.0254 133/133 [==============================] - 0s 1ms/step - loss: 0.0272 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 3.8412e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.0160  81/133 [=================>............] - ETA: 0s - loss: 0.0229 120/133 [==========================>...] - ETA: 0s - loss: 0.0235 133/133 [==============================] - 0s 1ms/step - loss: 0.0246 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0046 41/133 [========>.....................] - ETA: 0s - loss: 0.0361 80/133 [=================>............] - ETA: 0s - loss: 0.0271 121/133 [==========================>...] - ETA: 0s - loss: 0.0229 133/133 [==============================] - 0s 1ms/step - loss: 0.0229 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 38/133 [=======>......................] - ETA: 0s - loss: 0.0074 79/133 [================>.............] - ETA: 0s - loss: 0.0175 120/133 [==========================>...] - ETA: 0s - loss: 0.0177 133/133 [==============================] - 0s 1ms/step - loss: 0.0169 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 4.0753e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.0102  81/133 [=================>............] - ETA: 0s - loss: 0.0101 120/133 [==========================>...] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 1ms/step - loss: 0.0131 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 1.0971e-05 43/133 [========>.....................] - ETA: 0s - loss: 0.0179  78/133 [================>.............] - ETA: 0s - loss: 0.0123 119/133 [=========================>....] - ETA: 0s - loss: 0.0138 133/133 [==============================] - 0s 1ms/step - loss: 0.0131 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0035 42/133 [========>.....................] - ETA: 0s - loss: 0.0085 82/133 [=================>............] - ETA: 0s - loss: 0.0109 117/133 [=========================>....] - ETA: 0s - loss: 0.0109 133/133 [==============================] - 0s 1ms/step - loss: 0.0121 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0029 35/133 [======>.......................] - ETA: 0s - loss: 0.0074 73/133 [===============>..............] - ETA: 0s - loss: 0.0065 114/133 [========================>.....] - ETA: 0s - loss: 0.0126 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0060 42/133 [========>.....................] - ETA: 0s - loss: 0.0107 84/133 [=================>............] - ETA: 0s - loss: 0.0126 123/133 [==========================>...] - ETA: 0s - loss: 0.0099 133/133 [==============================] - 0s 1ms/step - loss: 0.0097 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 2, 11 GAN f1 score: 0.846 GAN cohens kappa score: 0.840 -> test with 'LR' LR tn, fp: 297, 36 LR fn, tp: 0, 13 LR f1 score: 0.419 LR cohens kappa score: 0.383 LR average precision score: 0.388 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 0, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 328, 5 KNN fn, tp: 0, 13 KNN f1 score: 0.839 KNN cohens kappa score: 0.831 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 27s - loss: 4.4227e-06 33/134 [======>.......................] - ETA: 0s - loss: 0.0787  63/134 [=============>................] - ETA: 0s - loss: 0.0735 94/134 [====================>.........] - ETA: 0s - loss: 0.0615 127/134 [===========================>..] - ETA: 0s - loss: 0.0629 134/134 [==============================] - 0s 2ms/step - loss: 0.0628 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.0285 34/134 [======>.......................] - ETA: 0s - loss: 0.0431 69/134 [==============>...............] - ETA: 0s - loss: 0.0291 99/134 [=====================>........] - ETA: 0s - loss: 0.0274 134/134 [==============================] - 0s 2ms/step - loss: 0.0274 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 3.8721e-04 33/134 [======>.......................] - ETA: 0s - loss: 0.0421  67/134 [==============>...............] - ETA: 0s - loss: 0.0306 100/134 [=====================>........] - ETA: 0s - loss: 0.0270 134/134 [==============================] - 0s 2ms/step - loss: 0.0210 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 3.6166e-05 34/134 [======>.......................] - ETA: 0s - loss: 0.0113  73/134 [===============>..............] - ETA: 0s - loss: 0.0117 104/134 [======================>.......] - ETA: 0s - loss: 0.0147 133/134 [============================>.] - ETA: 0s - loss: 0.0176 134/134 [==============================] - 0s 2ms/step - loss: 0.0176 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 8.3432e-06 32/134 [======>.......................] - ETA: 0s - loss: 0.0051  65/134 [=============>................] - ETA: 0s - loss: 0.0109 101/134 [=====================>........] - ETA: 0s - loss: 0.0140 134/134 [==============================] - 0s 2ms/step - loss: 0.0138 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0020 34/134 [======>.......................] - ETA: 0s - loss: 0.0106 68/134 [==============>...............] - ETA: 0s - loss: 0.0101 104/134 [======================>.......] - ETA: 0s - loss: 0.0101 134/134 [==============================] - 0s 1ms/step - loss: 0.0111 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0088 35/134 [======>.......................] - ETA: 0s - loss: 0.0134 69/134 [==============>...............] - ETA: 0s - loss: 0.0116 104/134 [======================>.......] - ETA: 0s - loss: 0.0122 134/134 [==============================] - 0s 1ms/step - loss: 0.0119 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0051 32/134 [======>.......................] - ETA: 0s - loss: 0.0084 66/134 [=============>................] - ETA: 0s - loss: 0.0074 101/134 [=====================>........] - ETA: 0s - loss: 0.0096 134/134 [==============================] - ETA: 0s - loss: 0.0109 134/134 [==============================] - 0s 2ms/step - loss: 0.0109 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0040 35/134 [======>.......................] - ETA: 0s - loss: 0.0145 68/134 [==============>...............] - ETA: 0s - loss: 0.0109 100/134 [=====================>........] - ETA: 0s - loss: 0.0101 134/134 [==============================] - ETA: 0s - loss: 0.0097 134/134 [==============================] - 0s 2ms/step - loss: 0.0097 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 8.8152e-06 36/134 [=======>......................] - ETA: 0s - loss: 0.0081  72/134 [===============>..............] - ETA: 0s - loss: 0.0080 106/134 [======================>.......] - ETA: 0s - loss: 0.0085 134/134 [==============================] - 0s 1ms/step - loss: 0.0089 -> test with GAN.predict GAN tn, fp: 329, 2 GAN fn, tp: 3, 10 GAN f1 score: 0.800 GAN cohens kappa score: 0.792 -> test with 'LR' LR tn, fp: 297, 34 LR fn, tp: 3, 10 LR f1 score: 0.351 LR cohens kappa score: 0.311 LR average precision score: 0.379 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 4, 9 RF f1 score: 0.818 RF cohens kappa score: 0.812 -> test with 'GB' GB tn, fp: 331, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 327, 4 KNN fn, tp: 0, 13 KNN f1 score: 0.867 KNN cohens kappa score: 0.861 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 32s - loss: 0.2736 25/133 [====>.........................] - ETA: 0s - loss: 0.0500  55/133 [===========>..................] - ETA: 0s - loss: 0.0667 88/133 [==================>...........] - ETA: 0s - loss: 0.0597 117/133 [=========================>....] - ETA: 0s - loss: 0.0509 133/133 [==============================] - 0s 2ms/step - loss: 0.0483 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 8.0460e-06 34/133 [======>.......................] - ETA: 0s - loss: 0.0202  65/133 [=============>................] - ETA: 0s - loss: 0.0261 89/133 [===================>..........] - ETA: 0s - loss: 0.0222 121/133 [==========================>...] - ETA: 0s - loss: 0.0245 133/133 [==============================] - 0s 2ms/step - loss: 0.0249 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.6244e-06 36/133 [=======>......................] - ETA: 0s - loss: 0.0066  72/133 [===============>..............] - ETA: 0s - loss: 0.0076 109/133 [=======================>......] - ETA: 0s - loss: 0.0188 133/133 [==============================] - 0s 1ms/step - loss: 0.0191 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 6.7994e-04 34/133 [======>.......................] - ETA: 0s - loss: 0.0124  66/133 [=============>................] - ETA: 0s - loss: 0.0214 99/133 [=====================>........] - ETA: 0s - loss: 0.0189 133/133 [==============================] - 0s 2ms/step - loss: 0.0172 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0069 37/133 [=======>......................] - ETA: 0s - loss: 0.0166 74/133 [===============>..............] - ETA: 0s - loss: 0.0166 111/133 [========================>.....] - ETA: 0s - loss: 0.0154 133/133 [==============================] - 0s 1ms/step - loss: 0.0166 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0037 38/133 [=======>......................] - ETA: 0s - loss: 0.0259 75/133 [===============>..............] - ETA: 0s - loss: 0.0174 110/133 [=======================>......] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 1ms/step - loss: 0.0157 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0277 32/133 [======>.......................] - ETA: 0s - loss: 0.0050 65/133 [=============>................] - ETA: 0s - loss: 0.0096 93/133 [===================>..........] - ETA: 0s - loss: 0.0176 124/133 [==========================>...] - ETA: 0s - loss: 0.0147 133/133 [==============================] - 0s 2ms/step - loss: 0.0143 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0400 36/133 [=======>......................] - ETA: 0s - loss: 0.0074 73/133 [===============>..............] - ETA: 0s - loss: 0.0186 108/133 [=======================>......] - ETA: 0s - loss: 0.0163 133/133 [==============================] - 0s 1ms/step - loss: 0.0138 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 1.4733e-04 38/133 [=======>......................] - ETA: 0s - loss: 0.0095  74/133 [===============>..............] - ETA: 0s - loss: 0.0087 111/133 [========================>.....] - ETA: 0s - loss: 0.0113 133/133 [==============================] - 0s 1ms/step - loss: 0.0122 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 7.4155e-05 38/133 [=======>......................] - ETA: 0s - loss: 0.0108  74/133 [===============>..............] - ETA: 0s - loss: 0.0141 112/133 [========================>.....] - ETA: 0s - loss: 0.0159 133/133 [==============================] - 0s 1ms/step - loss: 0.0142 -> test with GAN.predict GAN tn, fp: 333, 0 GAN fn, tp: 3, 10 GAN f1 score: 0.870 GAN cohens kappa score: 0.865 -> test with 'LR' LR tn, fp: 299, 34 LR fn, tp: 0, 13 LR f1 score: 0.433 LR cohens kappa score: 0.398 LR average precision score: 0.426 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 0, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 327, 6 KNN fn, tp: 0, 13 KNN f1 score: 0.813 KNN cohens kappa score: 0.804 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 24s - loss: 0.4291 31/133 [=====>........................] - ETA: 0s - loss: 0.0416  52/133 [==========>...................] - ETA: 0s - loss: 0.0640 80/133 [=================>............] - ETA: 0s - loss: 0.0464 111/133 [========================>.....] - ETA: 0s - loss: 0.0429 133/133 [==============================] - 0s 2ms/step - loss: 0.0441 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0130 34/133 [======>.......................] - ETA: 0s - loss: 0.0099 71/133 [===============>..............] - ETA: 0s - loss: 0.0125 97/133 [====================>.........] - ETA: 0s - loss: 0.0255 120/133 [==========================>...] - ETA: 0s - loss: 0.0209 133/133 [==============================] - 0s 2ms/step - loss: 0.0203 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.3787e-04 25/133 [====>.........................] - ETA: 0s - loss: 0.0062  57/133 [===========>..................] - ETA: 0s - loss: 0.0111 87/133 [==================>...........] - ETA: 0s - loss: 0.0173 115/133 [========================>.....] - ETA: 0s - loss: 0.0163 133/133 [==============================] - 0s 2ms/step - loss: 0.0172 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0314 19/133 [===>..........................] - ETA: 0s - loss: 0.0148 38/133 [=======>......................] - ETA: 0s - loss: 0.0150 68/133 [==============>...............] - ETA: 0s - loss: 0.0120 97/133 [====================>.........] - ETA: 0s - loss: 0.0159 124/133 [==========================>...] - ETA: 0s - loss: 0.0177 133/133 [==============================] - 0s 2ms/step - loss: 0.0168 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0075 29/133 [=====>........................] - ETA: 0s - loss: 0.0099 55/133 [===========>..................] - ETA: 0s - loss: 0.0157 88/133 [==================>...........] - ETA: 0s - loss: 0.0136 122/133 [==========================>...] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 2ms/step - loss: 0.0113 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0307 40/133 [========>.....................] - ETA: 0s - loss: 0.0096 79/133 [================>.............] - ETA: 0s - loss: 0.0101 111/133 [========================>.....] - ETA: 0s - loss: 0.0115 133/133 [==============================] - 0s 1ms/step - loss: 0.0105 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 26/133 [====>.........................] - ETA: 0s - loss: 0.0077 55/133 [===========>..................] - ETA: 0s - loss: 0.0107 85/133 [==================>...........] - ETA: 0s - loss: 0.0084 115/133 [========================>.....] - ETA: 0s - loss: 0.0072 133/133 [==============================] - 0s 2ms/step - loss: 0.0100 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0051 30/133 [=====>........................] - ETA: 0s - loss: 0.0034 59/133 [============>.................] - ETA: 0s - loss: 0.0059 88/133 [==================>...........] - ETA: 0s - loss: 0.0081 118/133 [=========================>....] - ETA: 0s - loss: 0.0092 133/133 [==============================] - 0s 2ms/step - loss: 0.0088 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 9.8930e-05 31/133 [=====>........................] - ETA: 0s - loss: 0.0092  60/133 [============>.................] - ETA: 0s - loss: 0.0061 87/133 [==================>...........] - ETA: 0s - loss: 0.0051 124/133 [==========================>...] - ETA: 0s - loss: 0.0067 133/133 [==============================] - 0s 2ms/step - loss: 0.0078 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0994 40/133 [========>.....................] - ETA: 0s - loss: 0.0132 77/133 [================>.............] - ETA: 0s - loss: 0.0088 114/133 [========================>.....] - ETA: 0s - loss: 0.0075 133/133 [==============================] - 0s 1ms/step - loss: 0.0066 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 3, 10 GAN f1 score: 0.769 GAN cohens kappa score: 0.760 -> test with 'LR' LR tn, fp: 289, 44 LR fn, tp: 1, 12 LR f1 score: 0.348 LR cohens kappa score: 0.305 LR average precision score: 0.507 -> test with 'RF' RF tn, fp: 332, 1 RF fn, tp: 1, 12 RF f1 score: 0.923 RF cohens kappa score: 0.920 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 325, 8 KNN fn, tp: 0, 13 KNN f1 score: 0.765 KNN cohens kappa score: 0.753 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 3.2608e-07 40/133 [========>.....................] - ETA: 0s - loss: 0.0527  70/133 [==============>...............] - ETA: 0s - loss: 0.0529 104/133 [======================>.......] - ETA: 0s - loss: 0.0420 133/133 [==============================] - 0s 1ms/step - loss: 0.0401 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 1.2064e-04 36/133 [=======>......................] - ETA: 0s - loss: 0.0162  72/133 [===============>..............] - ETA: 0s - loss: 0.0181 111/133 [========================>.....] - ETA: 0s - loss: 0.0176 133/133 [==============================] - 0s 1ms/step - loss: 0.0218 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 4.9798e-05 36/133 [=======>......................] - ETA: 0s - loss: 0.0132  72/133 [===============>..............] - ETA: 0s - loss: 0.0139 111/133 [========================>.....] - ETA: 0s - loss: 0.0149 133/133 [==============================] - 0s 1ms/step - loss: 0.0180 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 5.6043e-05 37/133 [=======>......................] - ETA: 0s - loss: 0.0275  72/133 [===============>..............] - ETA: 0s - loss: 0.0166 104/133 [======================>.......] - ETA: 0s - loss: 0.0160 133/133 [==============================] - 0s 1ms/step - loss: 0.0158 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0479 38/133 [=======>......................] - ETA: 0s - loss: 0.0233 76/133 [================>.............] - ETA: 0s - loss: 0.0184 114/133 [========================>.....] - ETA: 0s - loss: 0.0150 133/133 [==============================] - 0s 1ms/step - loss: 0.0152 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 1.9936e-04 38/133 [=======>......................] - ETA: 0s - loss: 0.0192  73/133 [===============>..............] - ETA: 0s - loss: 0.0171 112/133 [========================>.....] - ETA: 0s - loss: 0.0124 133/133 [==============================] - 0s 1ms/step - loss: 0.0120 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 8.7821e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0079  78/133 [================>.............] - ETA: 0s - loss: 0.0131 116/133 [=========================>....] - ETA: 0s - loss: 0.0119 133/133 [==============================] - 0s 1ms/step - loss: 0.0125 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0091 39/133 [=======>......................] - ETA: 0s - loss: 0.0020 77/133 [================>.............] - ETA: 0s - loss: 0.0091 118/133 [=========================>....] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0109 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0021 40/133 [========>.....................] - ETA: 0s - loss: 0.0075 79/133 [================>.............] - ETA: 0s - loss: 0.0049 118/133 [=========================>....] - ETA: 0s - loss: 0.0073 133/133 [==============================] - 0s 1ms/step - loss: 0.0100 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0176 40/133 [========>.....................] - ETA: 0s - loss: 0.0100 78/133 [================>.............] - ETA: 0s - loss: 0.0088 115/133 [========================>.....] - ETA: 0s - loss: 0.0095 133/133 [==============================] - 0s 1ms/step - loss: 0.0090 -> test with GAN.predict GAN tn, fp: 326, 7 GAN fn, tp: 0, 13 GAN f1 score: 0.788 GAN cohens kappa score: 0.778 -> test with 'LR' LR tn, fp: 291, 42 LR fn, tp: 0, 13 LR f1 score: 0.382 LR cohens kappa score: 0.342 LR average precision score: 0.320 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 0, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 332, 1 GB fn, tp: 0, 13 GB f1 score: 0.963 GB cohens kappa score: 0.961 -> test with 'KNN' KNN tn, fp: 325, 8 KNN fn, tp: 0, 13 KNN f1 score: 0.765 KNN cohens kappa score: 0.753 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 25s - loss: 0.1499 28/133 [=====>........................] - ETA: 0s - loss: 0.0091  66/133 [=============>................] - ETA: 0s - loss: 0.0300 97/133 [====================>.........] - ETA: 0s - loss: 0.0383 126/133 [===========================>..] - ETA: 0s - loss: 0.0409 133/133 [==============================] - 0s 2ms/step - loss: 0.0391 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0040 34/133 [======>.......................] - ETA: 0s - loss: 0.0241 71/133 [===============>..............] - ETA: 0s - loss: 0.0172 109/133 [=======================>......] - ETA: 0s - loss: 0.0241 133/133 [==============================] - 0s 1ms/step - loss: 0.0216 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 7.4234e-06 40/133 [========>.....................] - ETA: 0s - loss: 0.0183  76/133 [================>.............] - ETA: 0s - loss: 0.0213 113/133 [========================>.....] - ETA: 0s - loss: 0.0200 133/133 [==============================] - 0s 1ms/step - loss: 0.0205 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 39/133 [=======>......................] - ETA: 0s - loss: 0.0122 75/133 [===============>..............] - ETA: 0s - loss: 0.0130 107/133 [=======================>......] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 1ms/step - loss: 0.0159 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 39/133 [=======>......................] - ETA: 0s - loss: 0.0164 78/133 [================>.............] - ETA: 0s - loss: 0.0133 116/133 [=========================>....] - ETA: 0s - loss: 0.0135 133/133 [==============================] - 0s 1ms/step - loss: 0.0140 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.2042 37/133 [=======>......................] - ETA: 0s - loss: 0.0183 71/133 [===============>..............] - ETA: 0s - loss: 0.0158 109/133 [=======================>......] - ETA: 0s - loss: 0.0136 133/133 [==============================] - 0s 1ms/step - loss: 0.0142 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 3.2118e-05 40/133 [========>.....................] - ETA: 0s - loss: 0.0133  80/133 [=================>............] - ETA: 0s - loss: 0.0094 119/133 [=========================>....] - ETA: 0s - loss: 0.0114 133/133 [==============================] - 0s 1ms/step - loss: 0.0120 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 6.3443e-05 39/133 [=======>......................] - ETA: 0s - loss: 0.0105  75/133 [===============>..............] - ETA: 0s - loss: 0.0121 114/133 [========================>.....] - ETA: 0s - loss: 0.0101 133/133 [==============================] - 0s 1ms/step - loss: 0.0107 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 6.6170e-05 40/133 [========>.....................] - ETA: 0s - loss: 0.0128  81/133 [=================>............] - ETA: 0s - loss: 0.0090 120/133 [==========================>...] - ETA: 0s - loss: 0.0113 133/133 [==============================] - 0s 1ms/step - loss: 0.0104 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 39/133 [=======>......................] - ETA: 0s - loss: 0.0067 78/133 [================>.............] - ETA: 0s - loss: 0.0053 118/133 [=========================>....] - ETA: 0s - loss: 0.0091 133/133 [==============================] - 0s 1ms/step - loss: 0.0101 -> test with GAN.predict GAN tn, fp: 328, 5 GAN fn, tp: 7, 6 GAN f1 score: 0.500 GAN cohens kappa score: 0.482 -> test with 'LR' LR tn, fp: 298, 35 LR fn, tp: 1, 12 LR f1 score: 0.400 LR cohens kappa score: 0.362 LR average precision score: 0.278 -> test with 'RF' RF tn, fp: 332, 1 RF fn, tp: 5, 8 RF f1 score: 0.727 RF cohens kappa score: 0.719 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 323, 10 KNN fn, tp: 1, 12 KNN f1 score: 0.686 KNN cohens kappa score: 0.670 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 39s - loss: 0.5897 31/134 [=====>........................] - ETA: 0s - loss: 0.0562  55/134 [===========>..................] - ETA: 0s - loss: 0.0464 84/134 [=================>............] - ETA: 0s - loss: 0.0415 117/134 [=========================>....] - ETA: 0s - loss: 0.0459 134/134 [==============================] - 1s 2ms/step - loss: 0.0477 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 4.8765e-04 28/134 [=====>........................] - ETA: 0s - loss: 0.0172  53/134 [==========>...................] - ETA: 0s - loss: 0.0387 85/134 [==================>...........] - ETA: 0s - loss: 0.0328 119/134 [=========================>....] - ETA: 0s - loss: 0.0283 134/134 [==============================] - 0s 2ms/step - loss: 0.0325 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.0510 32/134 [======>.......................] - ETA: 0s - loss: 0.0591 64/134 [=============>................] - ETA: 0s - loss: 0.0381 89/134 [==================>...........] - ETA: 0s - loss: 0.0317 119/134 [=========================>....] - ETA: 0s - loss: 0.0254 134/134 [==============================] - 0s 2ms/step - loss: 0.0270 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 2.2536e-05 32/134 [======>.......................] - ETA: 0s - loss: 0.0147  62/134 [============>.................] - ETA: 0s - loss: 0.0180 94/134 [====================>.........] - ETA: 0s - loss: 0.0249 122/134 [==========================>...] - ETA: 0s - loss: 0.0233 134/134 [==============================] - 0s 2ms/step - loss: 0.0229 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 6.3510e-05 30/134 [=====>........................] - ETA: 0s - loss: 0.0050  56/134 [===========>..................] - ETA: 0s - loss: 0.0178 87/134 [==================>...........] - ETA: 0s - loss: 0.0280 119/134 [=========================>....] - ETA: 0s - loss: 0.0213 134/134 [==============================] - 0s 2ms/step - loss: 0.0196 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0457 33/134 [======>.......................] - ETA: 0s - loss: 0.0185 56/134 [===========>..................] - ETA: 0s - loss: 0.0166 71/134 [==============>...............] - ETA: 0s - loss: 0.0169 88/134 [==================>...........] - ETA: 0s - loss: 0.0153 111/134 [=======================>......] - ETA: 0s - loss: 0.0154 134/134 [==============================] - 0s 2ms/step - loss: 0.0159 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0030 33/134 [======>.......................] - ETA: 0s - loss: 0.0179 66/134 [=============>................] - ETA: 0s - loss: 0.0221 95/134 [====================>.........] - ETA: 0s - loss: 0.0202 128/134 [===========================>..] - ETA: 0s - loss: 0.0194 134/134 [==============================] - 0s 2ms/step - loss: 0.0186 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0015 32/134 [======>.......................] - ETA: 0s - loss: 0.0238 65/134 [=============>................] - ETA: 0s - loss: 0.0219 98/134 [====================>.........] - ETA: 0s - loss: 0.0169 127/134 [===========================>..] - ETA: 0s - loss: 0.0152 134/134 [==============================] - 0s 2ms/step - loss: 0.0147 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 2.3462e-04 36/134 [=======>......................] - ETA: 0s - loss: 0.0068  67/134 [==============>...............] - ETA: 0s - loss: 0.0115 98/134 [====================>.........] - ETA: 0s - loss: 0.0133 127/134 [===========================>..] - ETA: 0s - loss: 0.0127 134/134 [==============================] - 0s 2ms/step - loss: 0.0135 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 1.2853e-04 32/134 [======>.......................] - ETA: 0s - loss: 0.0253  63/134 [=============>................] - ETA: 0s - loss: 0.0159 95/134 [====================>.........] - ETA: 0s - loss: 0.0141 126/134 [===========================>..] - ETA: 0s - loss: 0.0134 134/134 [==============================] - 0s 2ms/step - loss: 0.0134 -> test with GAN.predict GAN tn, fp: 327, 4 GAN fn, tp: 3, 10 GAN f1 score: 0.741 GAN cohens kappa score: 0.730 -> test with 'LR' LR tn, fp: 302, 29 LR fn, tp: 2, 11 LR f1 score: 0.415 LR cohens kappa score: 0.380 LR average precision score: 0.337 -> test with 'RF' RF tn, fp: 330, 1 RF fn, tp: 2, 11 RF f1 score: 0.880 RF cohens kappa score: 0.875 -> test with 'GB' GB tn, fp: 331, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 324, 7 KNN fn, tp: 1, 12 KNN f1 score: 0.750 KNN cohens kappa score: 0.738 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 22s - loss: 4.3703e-06 33/133 [======>.......................] - ETA: 0s - loss: 0.1131  65/133 [=============>................] - ETA: 0s - loss: 0.0808 98/133 [=====================>........] - ETA: 0s - loss: 0.0698 127/133 [===========================>..] - ETA: 0s - loss: 0.0612 133/133 [==============================] - 0s 2ms/step - loss: 0.0593 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 6.1992e-04 36/133 [=======>......................] - ETA: 0s - loss: 0.0181  70/133 [==============>...............] - ETA: 0s - loss: 0.0301 108/133 [=======================>......] - ETA: 0s - loss: 0.0294 133/133 [==============================] - 0s 1ms/step - loss: 0.0299 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0698 37/133 [=======>......................] - ETA: 0s - loss: 0.0296 72/133 [===============>..............] - ETA: 0s - loss: 0.0252 106/133 [======================>.......] - ETA: 0s - loss: 0.0208 133/133 [==============================] - 0s 1ms/step - loss: 0.0215 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0082 36/133 [=======>......................] - ETA: 0s - loss: 0.0194 68/133 [==============>...............] - ETA: 0s - loss: 0.0252 98/133 [=====================>........] - ETA: 0s - loss: 0.0211 133/133 [==============================] - 0s 2ms/step - loss: 0.0187 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 35/133 [======>.......................] - ETA: 0s - loss: 0.0179 71/133 [===============>..............] - ETA: 0s - loss: 0.0163 108/133 [=======================>......] - ETA: 0s - loss: 0.0190 133/133 [==============================] - 0s 1ms/step - loss: 0.0165 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 1.6494e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0142  77/133 [================>.............] - ETA: 0s - loss: 0.0147 112/133 [========================>.....] - ETA: 0s - loss: 0.0128 133/133 [==============================] - 0s 1ms/step - loss: 0.0143 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0098 38/133 [=======>......................] - ETA: 0s - loss: 0.0185 73/133 [===============>..............] - ETA: 0s - loss: 0.0166 106/133 [======================>.......] - ETA: 0s - loss: 0.0168 132/133 [============================>.] - ETA: 0s - loss: 0.0165 133/133 [==============================] - 0s 2ms/step - loss: 0.0163 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 1.6421e-04 31/133 [=====>........................] - ETA: 0s - loss: 0.0110  62/133 [============>.................] - ETA: 0s - loss: 0.0075 99/133 [=====================>........] - ETA: 0s - loss: 0.0092 133/133 [==============================] - 0s 2ms/step - loss: 0.0124 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 2.4096e-05 38/133 [=======>......................] - ETA: 0s - loss: 0.0083  75/133 [===============>..............] - ETA: 0s - loss: 0.0103 112/133 [========================>.....] - ETA: 0s - loss: 0.0123 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0120 39/133 [=======>......................] - ETA: 0s - loss: 0.0156 76/133 [================>.............] - ETA: 0s - loss: 0.0124 114/133 [========================>.....] - ETA: 0s - loss: 0.0120 133/133 [==============================] - 0s 1ms/step - loss: 0.0111 -> test with GAN.predict GAN tn, fp: 327, 6 GAN fn, tp: 2, 11 GAN f1 score: 0.733 GAN cohens kappa score: 0.721 -> test with 'LR' LR tn, fp: 287, 46 LR fn, tp: 0, 13 LR f1 score: 0.361 LR cohens kappa score: 0.319 LR average precision score: 0.298 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 326, 7 KNN fn, tp: 0, 13 KNN f1 score: 0.788 KNN cohens kappa score: 0.778 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 0.3295 42/133 [========>.....................] - ETA: 0s - loss: 0.0867  75/133 [===============>..............] - ETA: 0s - loss: 0.0979 111/133 [========================>.....] - ETA: 0s - loss: 0.0946 133/133 [==============================] - 0s 1ms/step - loss: 0.0847 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 2.3860e-06 39/133 [=======>......................] - ETA: 0s - loss: 0.0463  79/133 [================>.............] - ETA: 0s - loss: 0.0485 119/133 [=========================>....] - ETA: 0s - loss: 0.0508 133/133 [==============================] - 0s 1ms/step - loss: 0.0493 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.7333e-06 41/133 [========>.....................] - ETA: 0s - loss: 0.0250  81/133 [=================>............] - ETA: 0s - loss: 0.0362 120/133 [==========================>...] - ETA: 0s - loss: 0.0360 133/133 [==============================] - 0s 1ms/step - loss: 0.0336 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 2.9619e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0311  80/133 [=================>............] - ETA: 0s - loss: 0.0336 122/133 [==========================>...] - ETA: 0s - loss: 0.0373 133/133 [==============================] - 0s 1ms/step - loss: 0.0343 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 3.1002e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0403  78/133 [================>.............] - ETA: 0s - loss: 0.0378 115/133 [========================>.....] - ETA: 0s - loss: 0.0304 133/133 [==============================] - 0s 1ms/step - loss: 0.0268 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0114 42/133 [========>.....................] - ETA: 0s - loss: 0.0253 77/133 [================>.............] - ETA: 0s - loss: 0.0192 113/133 [========================>.....] - ETA: 0s - loss: 0.0213 133/133 [==============================] - 0s 1ms/step - loss: 0.0215 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 4.4887e-04 40/133 [========>.....................] - ETA: 0s - loss: 0.0213  75/133 [===============>..............] - ETA: 0s - loss: 0.0224 108/133 [=======================>......] - ETA: 0s - loss: 0.0214 133/133 [==============================] - 0s 1ms/step - loss: 0.0204 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0021 40/133 [========>.....................] - ETA: 0s - loss: 0.0163 79/133 [================>.............] - ETA: 0s - loss: 0.0156 119/133 [=========================>....] - ETA: 0s - loss: 0.0167 133/133 [==============================] - 0s 1ms/step - loss: 0.0174 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0651 43/133 [========>.....................] - ETA: 0s - loss: 0.0214 85/133 [==================>...........] - ETA: 0s - loss: 0.0189 125/133 [===========================>..] - ETA: 0s - loss: 0.0175 133/133 [==============================] - 0s 1ms/step - loss: 0.0169 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0162 43/133 [========>.....................] - ETA: 0s - loss: 0.0096 84/133 [=================>............] - ETA: 0s - loss: 0.0135 126/133 [===========================>..] - ETA: 0s - loss: 0.0135 133/133 [==============================] - 0s 1ms/step - loss: 0.0164 -> test with GAN.predict GAN tn, fp: 332, 1 GAN fn, tp: 6, 7 GAN f1 score: 0.667 GAN cohens kappa score: 0.657 -> test with 'LR' LR tn, fp: 307, 26 LR fn, tp: 3, 10 LR f1 score: 0.408 LR cohens kappa score: 0.374 LR average precision score: 0.356 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 3, 10 RF f1 score: 0.870 RF cohens kappa score: 0.865 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 327, 6 KNN fn, tp: 0, 13 KNN f1 score: 0.813 KNN cohens kappa score: 0.804 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 6.6750e-08 40/133 [========>.....................] - ETA: 0s - loss: 0.1491  76/133 [================>.............] - ETA: 0s - loss: 0.1267 114/133 [========================>.....] - ETA: 0s - loss: 0.1117 133/133 [==============================] - 0s 1ms/step - loss: 0.1063 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 7.3052e-04 38/133 [=======>......................] - ETA: 0s - loss: 0.0414  75/133 [===============>..............] - ETA: 0s - loss: 0.0615 108/133 [=======================>......] - ETA: 0s - loss: 0.0538 133/133 [==============================] - 0s 1ms/step - loss: 0.0617 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0785 31/133 [=====>........................] - ETA: 0s - loss: 0.0598 66/133 [=============>................] - ETA: 0s - loss: 0.0486 107/133 [=======================>......] - ETA: 0s - loss: 0.0467 133/133 [==============================] - 0s 1ms/step - loss: 0.0498 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 6.4012e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.0370  82/133 [=================>............] - ETA: 0s - loss: 0.0555 124/133 [==========================>...] - ETA: 0s - loss: 0.0432 133/133 [==============================] - 0s 1ms/step - loss: 0.0431 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 5.1460e-05 35/133 [======>.......................] - ETA: 0s - loss: 0.0189  74/133 [===============>..............] - ETA: 0s - loss: 0.0366 112/133 [========================>.....] - ETA: 0s - loss: 0.0344 133/133 [==============================] - 0s 1ms/step - loss: 0.0410 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0092 41/133 [========>.....................] - ETA: 0s - loss: 0.0423 80/133 [=================>............] - ETA: 0s - loss: 0.0299 122/133 [==========================>...] - ETA: 0s - loss: 0.0315 133/133 [==============================] - 0s 1ms/step - loss: 0.0358 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 5.3356e-04 42/133 [========>.....................] - ETA: 0s - loss: 0.0434  83/133 [=================>............] - ETA: 0s - loss: 0.0389 125/133 [===========================>..] - ETA: 0s - loss: 0.0341 133/133 [==============================] - 0s 1ms/step - loss: 0.0338 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 8.0557e-05 42/133 [========>.....................] - ETA: 0s - loss: 0.0223  83/133 [=================>............] - ETA: 0s - loss: 0.0305 126/133 [===========================>..] - ETA: 0s - loss: 0.0278 133/133 [==============================] - 0s 1ms/step - loss: 0.0285 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0039 42/133 [========>.....................] - ETA: 0s - loss: 0.0214 83/133 [=================>............] - ETA: 0s - loss: 0.0234 125/133 [===========================>..] - ETA: 0s - loss: 0.0234 133/133 [==============================] - 0s 1ms/step - loss: 0.0262 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0069 42/133 [========>.....................] - ETA: 0s - loss: 0.0239 79/133 [================>.............] - ETA: 0s - loss: 0.0247 120/133 [==========================>...] - ETA: 0s - loss: 0.0230 133/133 [==============================] - 0s 1ms/step - loss: 0.0245 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 5, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.627 -> test with 'LR' LR tn, fp: 308, 25 LR fn, tp: 2, 11 LR f1 score: 0.449 LR cohens kappa score: 0.417 LR average precision score: 0.339 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 4, 9 RF f1 score: 0.818 RF cohens kappa score: 0.812 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 330, 3 KNN fn, tp: 0, 13 KNN f1 score: 0.897 KNN cohens kappa score: 0.892 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 4.1847e-08 42/133 [========>.....................] - ETA: 0s - loss: 0.1663  77/133 [================>.............] - ETA: 0s - loss: 0.1157 116/133 [=========================>....] - ETA: 0s - loss: 0.1208 133/133 [==============================] - 0s 1ms/step - loss: 0.1165 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0328 39/133 [=======>......................] - ETA: 0s - loss: 0.0455 78/133 [================>.............] - ETA: 0s - loss: 0.0529 119/133 [=========================>....] - ETA: 0s - loss: 0.0562 133/133 [==============================] - 0s 1ms/step - loss: 0.0588 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0640 40/133 [========>.....................] - ETA: 0s - loss: 0.0534 74/133 [===============>..............] - ETA: 0s - loss: 0.0418 112/133 [========================>.....] - ETA: 0s - loss: 0.0386 133/133 [==============================] - 0s 1ms/step - loss: 0.0438 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.1643 42/133 [========>.....................] - ETA: 0s - loss: 0.0365 77/133 [================>.............] - ETA: 0s - loss: 0.0306 116/133 [=========================>....] - ETA: 0s - loss: 0.0363 133/133 [==============================] - 0s 1ms/step - loss: 0.0403 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 41/133 [========>.....................] - ETA: 0s - loss: 0.0324 79/133 [================>.............] - ETA: 0s - loss: 0.0341 121/133 [==========================>...] - ETA: 0s - loss: 0.0339 133/133 [==============================] - 0s 1ms/step - loss: 0.0338 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 7.1647e-04 42/133 [========>.....................] - ETA: 0s - loss: 0.0426  83/133 [=================>............] - ETA: 0s - loss: 0.0307 124/133 [==========================>...] - ETA: 0s - loss: 0.0326 133/133 [==============================] - 0s 1ms/step - loss: 0.0312 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0090 43/133 [========>.....................] - ETA: 0s - loss: 0.0238 78/133 [================>.............] - ETA: 0s - loss: 0.0232 116/133 [=========================>....] - ETA: 0s - loss: 0.0279 133/133 [==============================] - 0s 1ms/step - loss: 0.0274 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 8.6652e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.0312  79/133 [================>.............] - ETA: 0s - loss: 0.0262 120/133 [==========================>...] - ETA: 0s - loss: 0.0258 133/133 [==============================] - 0s 1ms/step - loss: 0.0252 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0309 38/133 [=======>......................] - ETA: 0s - loss: 0.0214 74/133 [===============>..............] - ETA: 0s - loss: 0.0268 112/133 [========================>.....] - ETA: 0s - loss: 0.0221 133/133 [==============================] - 0s 1ms/step - loss: 0.0225 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0218 43/133 [========>.....................] - ETA: 0s - loss: 0.0268 84/133 [=================>............] - ETA: 0s - loss: 0.0202 125/133 [===========================>..] - ETA: 0s - loss: 0.0204 133/133 [==============================] - 0s 1ms/step - loss: 0.0206 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 2, 11 GAN f1 score: 0.786 GAN cohens kappa score: 0.777 -> test with 'LR' LR tn, fp: 292, 41 LR fn, tp: 1, 12 LR f1 score: 0.364 LR cohens kappa score: 0.323 LR average precision score: 0.293 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 0, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 328, 5 KNN fn, tp: 0, 13 KNN f1 score: 0.839 KNN cohens kappa score: 0.831 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 31s - loss: 1.7392e-05 37/134 [=======>......................] - ETA: 0s - loss: 0.1641  70/134 [==============>...............] - ETA: 0s - loss: 0.1866 106/134 [======================>.......] - ETA: 0s - loss: 0.1470 134/134 [==============================] - 0s 1ms/step - loss: 0.1677 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.2228 34/134 [======>.......................] - ETA: 0s - loss: 0.1149 66/134 [=============>................] - ETA: 0s - loss: 0.1153 96/134 [====================>.........] - ETA: 0s - loss: 0.0950 133/134 [============================>.] - ETA: 0s - loss: 0.0875 134/134 [==============================] - 0s 2ms/step - loss: 0.0873 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.0031 39/134 [=======>......................] - ETA: 0s - loss: 0.0949 76/134 [================>.............] - ETA: 0s - loss: 0.0740 113/134 [========================>.....] - ETA: 0s - loss: 0.0679 134/134 [==============================] - 0s 1ms/step - loss: 0.0678 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0119 34/134 [======>.......................] - ETA: 0s - loss: 0.0632 70/134 [==============>...............] - ETA: 0s - loss: 0.0565 104/134 [======================>.......] - ETA: 0s - loss: 0.0588 134/134 [==============================] - 0s 1ms/step - loss: 0.0549 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.0067 38/134 [=======>......................] - ETA: 0s - loss: 0.0201 74/134 [===============>..............] - ETA: 0s - loss: 0.0508 112/134 [========================>.....] - ETA: 0s - loss: 0.0533 134/134 [==============================] - 0s 1ms/step - loss: 0.0466 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0033 37/134 [=======>......................] - ETA: 0s - loss: 0.0507 74/134 [===============>..............] - ETA: 0s - loss: 0.0471 111/134 [=======================>......] - ETA: 0s - loss: 0.0464 134/134 [==============================] - 0s 1ms/step - loss: 0.0424 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0195 38/134 [=======>......................] - ETA: 0s - loss: 0.0441 76/134 [================>.............] - ETA: 0s - loss: 0.0332 109/134 [=======================>......] - ETA: 0s - loss: 0.0309 134/134 [==============================] - 0s 1ms/step - loss: 0.0355 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.2096 38/134 [=======>......................] - ETA: 0s - loss: 0.0313 75/134 [===============>..............] - ETA: 0s - loss: 0.0311 114/134 [========================>.....] - ETA: 0s - loss: 0.0313 134/134 [==============================] - 0s 1ms/step - loss: 0.0323 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0108 39/134 [=======>......................] - ETA: 0s - loss: 0.0365 76/134 [================>.............] - ETA: 0s - loss: 0.0370 113/134 [========================>.....] - ETA: 0s - loss: 0.0362 134/134 [==============================] - 0s 1ms/step - loss: 0.0325 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0032 38/134 [=======>......................] - ETA: 0s - loss: 0.0398 77/134 [================>.............] - ETA: 0s - loss: 0.0336 116/134 [========================>.....] - ETA: 0s - loss: 0.0289 134/134 [==============================] - 0s 1ms/step - loss: 0.0267 -> test with GAN.predict GAN tn, fp: 330, 1 GAN fn, tp: 3, 10 GAN f1 score: 0.833 GAN cohens kappa score: 0.827 -> test with 'LR' LR tn, fp: 292, 39 LR fn, tp: 0, 13 LR f1 score: 0.400 LR cohens kappa score: 0.361 LR average precision score: 0.473 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.958 -> test with 'GB' GB tn, fp: 331, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 324, 7 KNN fn, tp: 0, 13 KNN f1 score: 0.788 KNN cohens kappa score: 0.778 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 308, 46 LR fn, tp: 3, 13 LR f1 score: 0.473 LR cohens kappa score: 0.441 LR average precision score: 0.549 average: LR tn, fp: 296.44, 36.16 LR fn, tp: 0.8, 12.2 LR f1 score: 0.400 LR cohens kappa score: 0.362 LR average precision score: 0.367 minimum: LR tn, fp: 287, 25 LR fn, tp: 0, 10 LR f1 score: 0.348 LR cohens kappa score: 0.305 LR average precision score: 0.278 -----[ RF ]----- maximum: RF tn, fp: 333, 1 RF fn, tp: 5, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 average: RF tn, fp: 332.48, 0.12 RF fn, tp: 1.72, 11.28 RF f1 score: 0.921 RF cohens kappa score: 0.918 minimum: RF tn, fp: 330, 0 RF fn, tp: 0, 8 RF f1 score: 0.727 RF cohens kappa score: 0.719 -----[ GB ]----- maximum: GB tn, fp: 333, 2 GB fn, tp: 3, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 average: GB tn, fp: 332.44, 0.16 GB fn, tp: 0.28, 12.72 GB f1 score: 0.982 GB cohens kappa score: 0.982 minimum: GB tn, fp: 329, 0 GB fn, tp: 0, 10 GB f1 score: 0.870 GB cohens kappa score: 0.865 -----[ KNN ]----- maximum: KNN tn, fp: 332, 11 KNN fn, tp: 3, 13 KNN f1 score: 0.963 KNN cohens kappa score: 0.961 average: KNN tn, fp: 326.16, 6.44 KNN fn, tp: 0.32, 12.68 KNN f1 score: 0.794 KNN cohens kappa score: 0.784 minimum: KNN tn, fp: 322, 1 KNN fn, tp: 0, 10 KNN f1 score: 0.686 KNN cohens kappa score: 0.670 -----[ GAN ]----- maximum: GAN tn, fp: 333, 7 GAN fn, tp: 7, 13 GAN f1 score: 0.889 GAN cohens kappa score: 0.884 average: GAN tn, fp: 329.08, 3.52 GAN fn, tp: 2.96, 10.04 GAN f1 score: 0.753 GAN cohens kappa score: 0.743 minimum: GAN tn, fp: 324, 0 GAN fn, tp: 0, 6 GAN f1 score: 0.500 GAN cohens kappa score: 0.482