/////////////////////////////////////////// // Running convGAN-majority-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: 15s - loss: 8.9905e-07 51/133 [==========>...................] - ETA: 0s - loss: 0.0515  102/133 [======================>.......] - ETA: 0s - loss: 0.0466 133/133 [==============================] - 0s 997us/step - loss: 0.0449 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0020 52/133 [==========>...................] - ETA: 0s - loss: 0.0252 103/133 [======================>.......] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 986us/step - loss: 0.0291 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.0109e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0348  103/133 [======================>.......] - ETA: 0s - loss: 0.0305 133/133 [==============================] - 0s 984us/step - loss: 0.0272 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0432 52/133 [==========>...................] - ETA: 0s - loss: 0.0235 103/133 [======================>.......] - ETA: 0s - loss: 0.0241 133/133 [==============================] - 0s 993us/step - loss: 0.0216 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 5.9335e-06 53/133 [==========>...................] - ETA: 0s - loss: 0.0258  104/133 [======================>.......] - ETA: 0s - loss: 0.0261 133/133 [==============================] - 0s 989us/step - loss: 0.0251 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0144 52/133 [==========>...................] - ETA: 0s - loss: 0.0304 104/133 [======================>.......] - ETA: 0s - loss: 0.0242 133/133 [==============================] - 0s 985us/step - loss: 0.0199 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 4.6013e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0173  103/133 [======================>.......] - ETA: 0s - loss: 0.0179 133/133 [==============================] - 0s 985us/step - loss: 0.0191 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0011 52/133 [==========>...................] - ETA: 0s - loss: 0.0203 103/133 [======================>.......] - ETA: 0s - loss: 0.0177 133/133 [==============================] - 0s 987us/step - loss: 0.0172 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 1.1574e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0144  103/133 [======================>.......] - ETA: 0s - loss: 0.0155 133/133 [==============================] - 0s 988us/step - loss: 0.0175 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 6.6941e-05 53/133 [==========>...................] - ETA: 0s - loss: 0.0236  105/133 [======================>.......] - ETA: 0s - loss: 0.0165 133/133 [==============================] - 0s 980us/step - loss: 0.0170 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 6, 7 GAN f1 score: 0.636 GAN cohens kappa score: 0.625 -> test with 'LR' LR tn, fp: 303, 30 LR fn, tp: 1, 12 LR f1 score: 0.436 LR cohens kappa score: 0.402 LR average precision score: 0.365 -> 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: 333, 0 KNN fn, tp: 1, 12 KNN f1 score: 0.960 KNN cohens kappa score: 0.959 ------ 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: 16s - loss: 0.1735 51/133 [==========>...................] - ETA: 0s - loss: 0.0577  102/133 [======================>.......] - ETA: 0s - loss: 0.0487 133/133 [==============================] - 0s 997us/step - loss: 0.0407 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 1.3881e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0258  103/133 [======================>.......] - ETA: 0s - loss: 0.0274 133/133 [==============================] - 0s 985us/step - loss: 0.0281 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 3.9064e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0281  103/133 [======================>.......] - ETA: 0s - loss: 0.0320 133/133 [==============================] - 0s 986us/step - loss: 0.0272 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0367 52/133 [==========>...................] - ETA: 0s - loss: 0.0134 103/133 [======================>.......] - ETA: 0s - loss: 0.0190 133/133 [==============================] - 0s 986us/step - loss: 0.0218 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0424 52/133 [==========>...................] - ETA: 0s - loss: 0.0121 103/133 [======================>.......] - ETA: 0s - loss: 0.0167 133/133 [==============================] - 0s 984us/step - loss: 0.0163 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 3.6757e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0136  103/133 [======================>.......] - ETA: 0s - loss: 0.0178 133/133 [==============================] - 0s 994us/step - loss: 0.0172 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 6.9095e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0136  103/133 [======================>.......] - ETA: 0s - loss: 0.0169 133/133 [==============================] - 0s 993us/step - loss: 0.0167 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 8.6818e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0044  96/133 [====================>.........] - ETA: 0s - loss: 0.0087 133/133 [==============================] - 0s 1ms/step - loss: 0.0148 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0103 46/133 [=========>....................] - ETA: 0s - loss: 0.0136 97/133 [====================>.........] - ETA: 0s - loss: 0.0132 133/133 [==============================] - 0s 1ms/step - loss: 0.0135 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 6.2211e-06 53/133 [==========>...................] - ETA: 0s - loss: 0.0139  103/133 [======================>.......] - ETA: 0s - loss: 0.0148 133/133 [==============================] - 0s 994us/step - loss: 0.0139 -> test with GAN.predict GAN tn, fp: 332, 1 GAN fn, tp: 4, 9 GAN f1 score: 0.783 GAN cohens kappa score: 0.775 -> test with 'LR' LR tn, fp: 300, 33 LR fn, tp: 3, 10 LR f1 score: 0.357 LR cohens kappa score: 0.318 LR average precision score: 0.292 -> 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: 0, 13 KNN f1 score: 0.897 KNN cohens kappa score: 0.892 ------ 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: 15s - loss: 0.1562 48/133 [=========>....................] - ETA: 0s - loss: 0.0614  98/133 [=====================>........] - ETA: 0s - loss: 0.0534 133/133 [==============================] - 0s 1ms/step - loss: 0.0441 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 3.4221e-04 53/133 [==========>...................] - ETA: 0s - loss: 0.0134  103/133 [======================>.......] - ETA: 0s - loss: 0.0244 133/133 [==============================] - 0s 1000us/step - loss: 0.0258 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.1459 52/133 [==========>...................] - ETA: 0s - loss: 0.0250 103/133 [======================>.......] - ETA: 0s - loss: 0.0183 133/133 [==============================] - 0s 987us/step - loss: 0.0191 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 2.1129e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0212  103/133 [======================>.......] - ETA: 0s - loss: 0.0183 133/133 [==============================] - 0s 992us/step - loss: 0.0162 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 1.7554e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0142  95/133 [====================>.........] - ETA: 0s - loss: 0.0131 133/133 [==============================] - 0s 1ms/step - loss: 0.0132 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.1782 45/133 [=========>....................] - ETA: 0s - loss: 0.0169 96/133 [====================>.........] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 1ms/step - loss: 0.0112 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 4.5335e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0098  103/133 [======================>.......] - ETA: 0s - loss: 0.0117 133/133 [==============================] - 0s 994us/step - loss: 0.0111 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 1.2575e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0064  103/133 [======================>.......] - ETA: 0s - loss: 0.0098 133/133 [==============================] - 0s 995us/step - loss: 0.0098 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 6.7928e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0105  101/133 [=====================>........] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0093 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.6314e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0059  101/133 [=====================>........] - ETA: 0s - loss: 0.0077 133/133 [==============================] - 0s 1ms/step - loss: 0.0087 -> test with GAN.predict GAN tn, fp: 327, 6 GAN fn, tp: 4, 9 GAN f1 score: 0.643 GAN cohens kappa score: 0.628 -> test with 'LR' LR tn, fp: 295, 38 LR fn, tp: 0, 13 LR f1 score: 0.406 LR cohens kappa score: 0.368 LR average precision score: 0.400 -> 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: 326, 7 KNN fn, tp: 2, 11 KNN f1 score: 0.710 KNN cohens kappa score: 0.696 ------ 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: 16s - loss: 3.5443e-06 51/133 [==========>...................] - ETA: 0s - loss: 0.0829  102/133 [======================>.......] - ETA: 0s - loss: 0.0644 133/133 [==============================] - 0s 993us/step - loss: 0.0578 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0130 53/133 [==========>...................] - ETA: 0s - loss: 0.0445 105/133 [======================>.......] - ETA: 0s - loss: 0.0411 133/133 [==============================] - 0s 982us/step - loss: 0.0357 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.9767e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0410  100/133 [=====================>........] - ETA: 0s - loss: 0.0296 133/133 [==============================] - 0s 1ms/step - loss: 0.0286 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 5.1779e-06 47/133 [=========>....................] - ETA: 0s - loss: 0.0243  94/133 [====================>.........] - ETA: 0s - loss: 0.0249 133/133 [==============================] - 0s 1ms/step - loss: 0.0249 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 52/133 [==========>...................] - ETA: 0s - loss: 0.0295 103/133 [======================>.......] - ETA: 0s - loss: 0.0223 133/133 [==============================] - 0s 984us/step - loss: 0.0216 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 4.7801e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0191  103/133 [======================>.......] - ETA: 0s - loss: 0.0201 133/133 [==============================] - 0s 986us/step - loss: 0.0184 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 1.7417e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0148  103/133 [======================>.......] - ETA: 0s - loss: 0.0178 133/133 [==============================] - 0s 986us/step - loss: 0.0184 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 6.8766e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0070  103/133 [======================>.......] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 995us/step - loss: 0.0155 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0030 52/133 [==========>...................] - ETA: 0s - loss: 0.0171 103/133 [======================>.......] - ETA: 0s - loss: 0.0158 133/133 [==============================] - 0s 995us/step - loss: 0.0144 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 2.8375e-04 53/133 [==========>...................] - ETA: 0s - loss: 0.0163  104/133 [======================>.......] - ETA: 0s - loss: 0.0138 133/133 [==============================] - 0s 980us/step - loss: 0.0131 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 4, 9 GAN f1 score: 0.750 GAN cohens kappa score: 0.741 -> test with 'LR' LR tn, fp: 305, 28 LR fn, tp: 1, 12 LR f1 score: 0.453 LR cohens kappa score: 0.420 LR average precision score: 0.377 -> 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: 332, 1 KNN fn, tp: 1, 12 KNN f1 score: 0.923 KNN cohens kappa score: 0.920 ------ 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: 19s - loss: 0.0061 45/134 [=========>....................] - ETA: 0s - loss: 0.0656  88/134 [==================>...........] - ETA: 0s - loss: 0.0722 130/134 [============================>.] - ETA: 0s - loss: 0.0732 134/134 [==============================] - 0s 1ms/step - loss: 0.0735 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 2.3658e-06 49/134 [=========>....................] - ETA: 0s - loss: 0.0267  97/134 [====================>.........] - ETA: 0s - loss: 0.0528 134/134 [==============================] - 0s 1ms/step - loss: 0.0462 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 5.4571e-06 50/134 [==========>...................] - ETA: 0s - loss: 0.0464  98/134 [====================>.........] - ETA: 0s - loss: 0.0422 134/134 [==============================] - 0s 1ms/step - loss: 0.0368 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0082 50/134 [==========>...................] - ETA: 0s - loss: 0.0135 99/134 [=====================>........] - ETA: 0s - loss: 0.0292 134/134 [==============================] - 0s 1ms/step - loss: 0.0342 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 7.3234e-06 49/134 [=========>....................] - ETA: 0s - loss: 0.0457  98/134 [====================>.........] - ETA: 0s - loss: 0.0304 134/134 [==============================] - 0s 1ms/step - loss: 0.0249 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 2.3077e-05 49/134 [=========>....................] - ETA: 0s - loss: 0.0181  97/134 [====================>.........] - ETA: 0s - loss: 0.0304 134/134 [==============================] - 0s 1ms/step - loss: 0.0278 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0814 49/134 [=========>....................] - ETA: 0s - loss: 0.0119 98/134 [====================>.........] - ETA: 0s - loss: 0.0181 134/134 [==============================] - 0s 1ms/step - loss: 0.0228 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0085 48/134 [=========>....................] - ETA: 0s - loss: 0.0226 96/134 [====================>.........] - ETA: 0s - loss: 0.0199 134/134 [==============================] - 0s 1ms/step - loss: 0.0217 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 1.3308e-05 49/134 [=========>....................] - ETA: 0s - loss: 0.0249  97/134 [====================>.........] - ETA: 0s - loss: 0.0204 134/134 [==============================] - 0s 1ms/step - loss: 0.0210 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 5.5245e-04 45/134 [=========>....................] - ETA: 0s - loss: 0.0106  93/134 [===================>..........] - ETA: 0s - loss: 0.0199 134/134 [==============================] - 0s 1ms/step - loss: 0.0192 -> test with GAN.predict GAN tn, fp: 329, 2 GAN fn, tp: 4, 9 GAN f1 score: 0.750 GAN cohens kappa score: 0.741 -> test with 'LR' LR tn, fp: 308, 23 LR fn, tp: 3, 10 LR f1 score: 0.435 LR cohens kappa score: 0.402 LR average precision score: 0.430 -> 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: 329, 2 GB fn, tp: 0, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 329, 2 KNN fn, tp: 0, 13 KNN f1 score: 0.929 KNN cohens kappa score: 0.926 ====== 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: 17s - loss: 1.4274e-06 51/133 [==========>...................] - ETA: 0s - loss: 0.0463  101/133 [=====================>........] - ETA: 0s - loss: 0.0618 133/133 [==============================] - 0s 1ms/step - loss: 0.0551 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 4.8779e-07 52/133 [==========>...................] - ETA: 0s - loss: 0.0295  103/133 [======================>.......] - ETA: 0s - loss: 0.0315 133/133 [==============================] - 0s 996us/step - loss: 0.0366 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 4.8495e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0259  99/133 [=====================>........] - ETA: 0s - loss: 0.0176 133/133 [==============================] - 0s 1ms/step - loss: 0.0239 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0023 52/133 [==========>...................] - ETA: 0s - loss: 0.0326 103/133 [======================>.......] - ETA: 0s - loss: 0.0235 133/133 [==============================] - 0s 994us/step - loss: 0.0210 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0201 52/133 [==========>...................] - ETA: 0s - loss: 0.0225 103/133 [======================>.......] - ETA: 0s - loss: 0.0210 133/133 [==============================] - 0s 997us/step - loss: 0.0179 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0183 52/133 [==========>...................] - ETA: 0s - loss: 0.0083 101/133 [=====================>........] - ETA: 0s - loss: 0.0103 133/133 [==============================] - 0s 1ms/step - loss: 0.0155 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0850 47/133 [=========>....................] - ETA: 0s - loss: 0.0149 96/133 [====================>.........] - ETA: 0s - loss: 0.0142 133/133 [==============================] - 0s 1ms/step - loss: 0.0155 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 3.1198e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0069  103/133 [======================>.......] - ETA: 0s - loss: 0.0166 133/133 [==============================] - 0s 990us/step - loss: 0.0144 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0039 43/133 [========>.....................] - ETA: 0s - loss: 0.0154 85/133 [==================>...........] - ETA: 0s - loss: 0.0129 129/133 [============================>.] - ETA: 0s - loss: 0.0135 133/133 [==============================] - 0s 1ms/step - loss: 0.0131 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.1233e-05 48/133 [=========>....................] - ETA: 0s - loss: 0.0102  98/133 [=====================>........] - ETA: 0s - loss: 0.0152 133/133 [==============================] - 0s 1ms/step - loss: 0.0138 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 5, 8 GAN f1 score: 0.696 GAN cohens kappa score: 0.685 -> test with 'LR' LR tn, fp: 309, 24 LR fn, tp: 5, 8 LR f1 score: 0.356 LR cohens kappa score: 0.319 LR average precision score: 0.285 -> 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: 330, 3 KNN fn, tp: 1, 12 KNN f1 score: 0.857 KNN cohens kappa score: 0.851 ------ 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: 16s - loss: 5.5838e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0745  103/133 [======================>.......] - ETA: 0s - loss: 0.0502 133/133 [==============================] - 0s 994us/step - loss: 0.0534 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 1.6150e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0313  103/133 [======================>.......] - ETA: 0s - loss: 0.0376 133/133 [==============================] - 0s 985us/step - loss: 0.0390 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 6.0168e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0274  103/133 [======================>.......] - ETA: 0s - loss: 0.0354 133/133 [==============================] - 0s 996us/step - loss: 0.0297 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0058 51/133 [==========>...................] - ETA: 0s - loss: 0.0236 100/133 [=====================>........] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 1ms/step - loss: 0.0239 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 3.1223e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0241  100/133 [=====================>........] - ETA: 0s - loss: 0.0238 133/133 [==============================] - 0s 1ms/step - loss: 0.0221 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0034 51/133 [==========>...................] - ETA: 0s - loss: 0.0252 102/133 [======================>.......] - ETA: 0s - loss: 0.0181 133/133 [==============================] - 0s 991us/step - loss: 0.0184 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0203 52/133 [==========>...................] - ETA: 0s - loss: 0.0206 103/133 [======================>.......] - ETA: 0s - loss: 0.0219 133/133 [==============================] - 0s 990us/step - loss: 0.0171 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 2.0746e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0199  101/133 [=====================>........] - ETA: 0s - loss: 0.0137 133/133 [==============================] - 0s 1ms/step - loss: 0.0139 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 7.9716e-05 49/133 [==========>...................] - ETA: 0s - loss: 0.0128  100/133 [=====================>........] - ETA: 0s - loss: 0.0159 133/133 [==============================] - 0s 1ms/step - loss: 0.0138 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0071 52/133 [==========>...................] - ETA: 0s - loss: 0.0103 103/133 [======================>.......] - ETA: 0s - loss: 0.0105 133/133 [==============================] - 0s 991us/step - loss: 0.0141 -> test with GAN.predict GAN tn, fp: 332, 1 GAN fn, tp: 4, 9 GAN f1 score: 0.783 GAN cohens kappa score: 0.775 -> test with 'LR' LR tn, fp: 294, 39 LR fn, tp: 0, 13 LR f1 score: 0.400 LR cohens kappa score: 0.362 LR average precision score: 0.329 -> 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: 326, 7 KNN fn, tp: 1, 12 KNN f1 score: 0.750 KNN cohens kappa score: 0.738 ------ 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: 17s - loss: 2.0750e-06 51/133 [==========>...................] - ETA: 0s - loss: 0.0533  102/133 [======================>.......] - ETA: 0s - loss: 0.0517 133/133 [==============================] - 0s 1ms/step - loss: 0.0514 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 1.5956e-05 51/133 [==========>...................] - ETA: 0s - loss: 0.0254  102/133 [======================>.......] - ETA: 0s - loss: 0.0309 133/133 [==============================] - 0s 1ms/step - loss: 0.0296 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 8.6009e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0146  103/133 [======================>.......] - ETA: 0s - loss: 0.0212 133/133 [==============================] - 0s 991us/step - loss: 0.0249 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.2891 52/133 [==========>...................] - ETA: 0s - loss: 0.0345 103/133 [======================>.......] - ETA: 0s - loss: 0.0239 133/133 [==============================] - 0s 985us/step - loss: 0.0222 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 3.1527e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0283  99/133 [=====================>........] - ETA: 0s - loss: 0.0206 133/133 [==============================] - 0s 1ms/step - loss: 0.0177 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 1.2337e-05 48/133 [=========>....................] - ETA: 0s - loss: 0.0246  95/133 [====================>.........] - ETA: 0s - loss: 0.0204 133/133 [==============================] - 0s 1ms/step - loss: 0.0185 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 2.6076e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0152  103/133 [======================>.......] - ETA: 0s - loss: 0.0214 133/133 [==============================] - 0s 999us/step - loss: 0.0192 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 1.4218e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0144  100/133 [=====================>........] - ETA: 0s - loss: 0.0131 133/133 [==============================] - 0s 1ms/step - loss: 0.0156 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 2.4330e-05 51/133 [==========>...................] - ETA: 0s - loss: 0.0139  101/133 [=====================>........] - ETA: 0s - loss: 0.0154 133/133 [==============================] - 0s 1ms/step - loss: 0.0139 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0176 52/133 [==========>...................] - ETA: 0s - loss: 0.0117 103/133 [======================>.......] - ETA: 0s - loss: 0.0156 133/133 [==============================] - 0s 990us/step - loss: 0.0138 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 3, 10 GAN f1 score: 0.800 GAN cohens kappa score: 0.793 -> test with 'LR' LR tn, fp: 303, 30 LR fn, tp: 2, 11 LR f1 score: 0.407 LR cohens kappa score: 0.372 LR average precision score: 0.334 -> 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: 332, 1 KNN fn, tp: 3, 10 KNN f1 score: 0.833 KNN cohens kappa score: 0.827 ------ 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: 15s - loss: 0.2742 49/133 [==========>...................] - ETA: 0s - loss: 0.0342  99/133 [=====================>........] - ETA: 0s - loss: 0.0404 133/133 [==============================] - 0s 1ms/step - loss: 0.0420 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0149 52/133 [==========>...................] - ETA: 0s - loss: 0.0233 103/133 [======================>.......] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 986us/step - loss: 0.0284 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 2.4979e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0150  103/133 [======================>.......] - ETA: 0s - loss: 0.0191 133/133 [==============================] - 0s 986us/step - loss: 0.0245 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0661 48/133 [=========>....................] - ETA: 0s - loss: 0.0109 97/133 [====================>.........] - ETA: 0s - loss: 0.0238 133/133 [==============================] - 0s 1ms/step - loss: 0.0205 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 2.1955e-06 53/133 [==========>...................] - ETA: 0s - loss: 0.0263  104/133 [======================>.......] - ETA: 0s - loss: 0.0165 133/133 [==============================] - 0s 986us/step - loss: 0.0154 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 2.5915e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0164  104/133 [======================>.......] - ETA: 0s - loss: 0.0115 133/133 [==============================] - 0s 984us/step - loss: 0.0139 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.1567 53/133 [==========>...................] - ETA: 0s - loss: 0.0130 104/133 [======================>.......] - ETA: 0s - loss: 0.0117 133/133 [==============================] - 0s 984us/step - loss: 0.0121 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 52/133 [==========>...................] - ETA: 0s - loss: 0.0051 103/133 [======================>.......] - ETA: 0s - loss: 0.0128 133/133 [==============================] - 0s 990us/step - loss: 0.0132 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 52/133 [==========>...................] - ETA: 0s - loss: 0.0087 103/133 [======================>.......] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 989us/step - loss: 0.0112 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 6.9869e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0087  104/133 [======================>.......] - ETA: 0s - loss: 0.0109 133/133 [==============================] - 0s 986us/step - loss: 0.0115 -> test with GAN.predict GAN tn, fp: 327, 6 GAN fn, tp: 5, 8 GAN f1 score: 0.593 GAN cohens kappa score: 0.576 -> test with 'LR' LR tn, fp: 306, 27 LR fn, tp: 0, 13 LR f1 score: 0.491 LR cohens kappa score: 0.460 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: 3, 10 GB f1 score: 0.870 GB cohens kappa score: 0.865 -> test with 'KNN' KNN tn, fp: 332, 1 KNN fn, tp: 2, 11 KNN f1 score: 0.880 KNN cohens kappa score: 0.876 ------ 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: 23s - loss: 1.3652e-06 49/134 [=========>....................] - ETA: 0s - loss: 0.0573  98/134 [====================>.........] - ETA: 0s - loss: 0.0702 134/134 [==============================] - 0s 1ms/step - loss: 0.0616 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 6.8564e-07 49/134 [=========>....................] - ETA: 0s - loss: 0.0188  98/134 [====================>.........] - ETA: 0s - loss: 0.0322 134/134 [==============================] - 0s 1ms/step - loss: 0.0285 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.4708 48/134 [=========>....................] - ETA: 0s - loss: 0.0342 90/134 [===================>..........] - ETA: 0s - loss: 0.0247 133/134 [============================>.] - ETA: 0s - loss: 0.0239 134/134 [==============================] - 0s 1ms/step - loss: 0.0238 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 6.4692e-07 46/134 [=========>....................] - ETA: 0s - loss: 0.0067  95/134 [====================>.........] - ETA: 0s - loss: 0.0190 134/134 [==============================] - 0s 1ms/step - loss: 0.0243 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 8.2855e-07 49/134 [=========>....................] - ETA: 0s - loss: 0.0179  97/134 [====================>.........] - ETA: 0s - loss: 0.0214 134/134 [==============================] - 0s 1ms/step - loss: 0.0214 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0018 49/134 [=========>....................] - ETA: 0s - loss: 0.0116 97/134 [====================>.........] - ETA: 0s - loss: 0.0208 134/134 [==============================] - 0s 1ms/step - loss: 0.0192 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 1.1005e-06 49/134 [=========>....................] - ETA: 0s - loss: 0.0152  97/134 [====================>.........] - ETA: 0s - loss: 0.0162 134/134 [==============================] - 0s 1ms/step - loss: 0.0193 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 4.1779e-06 50/134 [==========>...................] - ETA: 0s - loss: 0.0110  99/134 [=====================>........] - ETA: 0s - loss: 0.0132 134/134 [==============================] - 0s 1ms/step - loss: 0.0156 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0207 44/134 [========>.....................] - ETA: 0s - loss: 0.0176 92/134 [===================>..........] - ETA: 0s - loss: 0.0120 134/134 [==============================] - 0s 1ms/step - loss: 0.0175 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0089 47/134 [=========>....................] - ETA: 0s - loss: 0.0110 95/134 [====================>.........] - ETA: 0s - loss: 0.0109 134/134 [==============================] - 0s 1ms/step - loss: 0.0149 -> test with GAN.predict GAN tn, fp: 326, 5 GAN fn, tp: 3, 10 GAN f1 score: 0.714 GAN cohens kappa score: 0.702 -> test with 'LR' LR tn, fp: 303, 28 LR fn, tp: 1, 12 LR f1 score: 0.453 LR cohens kappa score: 0.420 LR average precision score: 0.559 -> 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: 331, 0 KNN fn, tp: 0, 13 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 16s - loss: 3.9267e-04 51/133 [==========>...................] - ETA: 0s - loss: 0.0692  102/133 [======================>.......] - ETA: 0s - loss: 0.0777 133/133 [==============================] - 0s 998us/step - loss: 0.0747 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 2.7408e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0526  103/133 [======================>.......] - ETA: 0s - loss: 0.0411 133/133 [==============================] - 0s 990us/step - loss: 0.0345 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 6.2981e-06 50/133 [==========>...................] - ETA: 0s - loss: 0.0368  101/133 [=====================>........] - ETA: 0s - loss: 0.0362 133/133 [==============================] - 0s 1ms/step - loss: 0.0313 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 5.9492e-06 50/133 [==========>...................] - ETA: 0s - loss: 0.0211  100/133 [=====================>........] - ETA: 0s - loss: 0.0240 133/133 [==============================] - 0s 1ms/step - loss: 0.0277 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 7.7788e-06 53/133 [==========>...................] - ETA: 0s - loss: 0.0360  104/133 [======================>.......] - ETA: 0s - loss: 0.0261 133/133 [==============================] - 0s 985us/step - loss: 0.0239 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 2.3003e-05 51/133 [==========>...................] - ETA: 0s - loss: 0.0237  102/133 [======================>.......] - ETA: 0s - loss: 0.0222 133/133 [==============================] - 0s 996us/step - loss: 0.0208 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.2385 52/133 [==========>...................] - ETA: 0s - loss: 0.0234 104/133 [======================>.......] - ETA: 0s - loss: 0.0211 133/133 [==============================] - 0s 1ms/step - loss: 0.0193 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0162 51/133 [==========>...................] - ETA: 0s - loss: 0.0081 97/133 [====================>.........] - ETA: 0s - loss: 0.0183 133/133 [==============================] - 0s 1ms/step - loss: 0.0200 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 5.6497e-06 49/133 [==========>...................] - ETA: 0s - loss: 0.0117  100/133 [=====================>........] - ETA: 0s - loss: 0.0166 133/133 [==============================] - 0s 1ms/step - loss: 0.0152 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.6416e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0109  103/133 [======================>.......] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 984us/step - loss: 0.0169 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 7, 6 GAN f1 score: 0.571 GAN cohens kappa score: 0.559 -> test with 'LR' LR tn, fp: 304, 29 LR fn, tp: 2, 11 LR f1 score: 0.415 LR cohens kappa score: 0.380 LR average precision score: 0.310 -> 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: 2, 11 GB f1 score: 0.917 GB cohens kappa score: 0.914 -> test with 'KNN' KNN tn, fp: 333, 0 KNN fn, tp: 3, 10 KNN f1 score: 0.870 KNN cohens kappa score: 0.865 ------ 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: 16s - loss: 1.2150e-06 51/133 [==========>...................] - ETA: 0s - loss: 0.0443  101/133 [=====================>........] - ETA: 0s - loss: 0.0616 133/133 [==============================] - 0s 1ms/step - loss: 0.0574 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.6370 52/133 [==========>...................] - ETA: 0s - loss: 0.0375 103/133 [======================>.......] - ETA: 0s - loss: 0.0379 133/133 [==============================] - 0s 1ms/step - loss: 0.0362 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.3386e-06 51/133 [==========>...................] - ETA: 0s - loss: 0.0349  102/133 [======================>.......] - ETA: 0s - loss: 0.0303 133/133 [==============================] - 0s 1ms/step - loss: 0.0274 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 6.9959e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0304  103/133 [======================>.......] - ETA: 0s - loss: 0.0218 133/133 [==============================] - 0s 1ms/step - loss: 0.0225 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 1.6452e-05 46/133 [=========>....................] - ETA: 0s - loss: 0.0155  93/133 [===================>..........] - ETA: 0s - loss: 0.0216 133/133 [==============================] - 0s 1ms/step - loss: 0.0214 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 2.8900e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0167  103/133 [======================>.......] - ETA: 0s - loss: 0.0188 133/133 [==============================] - 0s 994us/step - loss: 0.0193 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 4.3592e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0155  102/133 [======================>.......] - ETA: 0s - loss: 0.0147 133/133 [==============================] - 0s 999us/step - loss: 0.0169 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 1.0018e-05 50/133 [==========>...................] - ETA: 0s - loss: 0.0107  101/133 [=====================>........] - ETA: 0s - loss: 0.0148 133/133 [==============================] - 0s 1ms/step - loss: 0.0155 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0062 52/133 [==========>...................] - ETA: 0s - loss: 0.0158 103/133 [======================>.......] - ETA: 0s - loss: 0.0147 133/133 [==============================] - 0s 991us/step - loss: 0.0140 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 5.8354e-05 50/133 [==========>...................] - ETA: 0s - loss: 0.0168  100/133 [=====================>........] - ETA: 0s - loss: 0.0137 133/133 [==============================] - 0s 1ms/step - loss: 0.0143 -> 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: 309, 24 LR fn, tp: 0, 13 LR f1 score: 0.520 LR cohens kappa score: 0.492 LR average precision score: 0.433 -> 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: 332, 1 KNN fn, tp: 1, 12 KNN f1 score: 0.923 KNN cohens kappa score: 0.920 ------ 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: 16s - loss: 1.7397e-05 51/133 [==========>...................] - ETA: 0s - loss: 0.0428  102/133 [======================>.......] - ETA: 0s - loss: 0.0471 133/133 [==============================] - 0s 993us/step - loss: 0.0499 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 6.2705e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0304  99/133 [=====================>........] - ETA: 0s - loss: 0.0288 133/133 [==============================] - 0s 1ms/step - loss: 0.0305 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.2084 48/133 [=========>....................] - ETA: 0s - loss: 0.0315 98/133 [=====================>........] - ETA: 0s - loss: 0.0237 133/133 [==============================] - 0s 1ms/step - loss: 0.0224 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 9.6316e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0258  103/133 [======================>.......] - ETA: 0s - loss: 0.0213 133/133 [==============================] - 0s 990us/step - loss: 0.0207 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 4.0876e-04 47/133 [=========>....................] - ETA: 0s - loss: 0.0266  98/133 [=====================>........] - ETA: 0s - loss: 0.0211 133/133 [==============================] - 0s 1ms/step - loss: 0.0182 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 7.3352e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0218  104/133 [======================>.......] - ETA: 0s - loss: 0.0150 133/133 [==============================] - 0s 983us/step - loss: 0.0136 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 9.2029e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0067  104/133 [======================>.......] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 984us/step - loss: 0.0144 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0323 52/133 [==========>...................] - ETA: 0s - loss: 0.0173 102/133 [======================>.......] - ETA: 0s - loss: 0.0161 133/133 [==============================] - 0s 995us/step - loss: 0.0135 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 9.3994e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0065  103/133 [======================>.......] - ETA: 0s - loss: 0.0114 133/133 [==============================] - 0s 1ms/step - loss: 0.0103 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0012 39/133 [=======>......................] - ETA: 0s - loss: 0.0105 84/133 [=================>............] - ETA: 0s - loss: 0.0107 129/133 [============================>.] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 1ms/step - loss: 0.0113 -> test with GAN.predict GAN tn, fp: 332, 1 GAN fn, tp: 3, 10 GAN f1 score: 0.833 GAN cohens kappa score: 0.827 -> 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: 0.326 -> 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: 1, 12 KNN f1 score: 0.923 KNN cohens kappa score: 0.920 ------ 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: 16s - loss: 1.6681e-06 46/133 [=========>....................] - ETA: 0s - loss: 0.0302  93/133 [===================>..........] - ETA: 0s - loss: 0.0376 133/133 [==============================] - 0s 1ms/step - loss: 0.0421 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 5.9094e-06 48/133 [=========>....................] - ETA: 0s - loss: 0.0210  95/133 [====================>.........] - ETA: 0s - loss: 0.0288 133/133 [==============================] - 0s 1ms/step - loss: 0.0285 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 5.3610e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0271  95/133 [====================>.........] - ETA: 0s - loss: 0.0327 133/133 [==============================] - 0s 1ms/step - loss: 0.0258 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 4.6395e-06 47/133 [=========>....................] - ETA: 0s - loss: 0.0190  95/133 [====================>.........] - ETA: 0s - loss: 0.0182 133/133 [==============================] - 0s 1ms/step - loss: 0.0233 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 3.3125e-06 49/133 [==========>...................] - ETA: 0s - loss: 0.0142  96/133 [====================>.........] - ETA: 0s - loss: 0.0154 133/133 [==============================] - 0s 1ms/step - loss: 0.0170 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 4.8561e-06 46/133 [=========>....................] - ETA: 0s - loss: 0.0258  94/133 [====================>.........] - ETA: 0s - loss: 0.0159 133/133 [==============================] - 0s 1ms/step - loss: 0.0172 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 8.4834e-04 48/133 [=========>....................] - ETA: 0s - loss: 0.0141  96/133 [====================>.........] - ETA: 0s - loss: 0.0158 133/133 [==============================] - 0s 1ms/step - loss: 0.0169 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 6.8423e-04 47/133 [=========>....................] - ETA: 0s - loss: 0.0199  87/133 [==================>...........] - ETA: 0s - loss: 0.0190 117/133 [=========================>....] - ETA: 0s - loss: 0.0174 133/133 [==============================] - 0s 2ms/step - loss: 0.0159 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 23/133 [====>.........................] - ETA: 0s - loss: 0.0206 49/133 [==========>...................] - ETA: 0s - loss: 0.0163 83/133 [=================>............] - ETA: 0s - loss: 0.0155 117/133 [=========================>....] - ETA: 0s - loss: 0.0125 133/133 [==============================] - 0s 2ms/step - loss: 0.0110 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.2995e-05 38/133 [=======>......................] - ETA: 0s - loss: 0.0124  70/133 [==============>...............] - ETA: 0s - loss: 0.0110 115/133 [========================>.....] - ETA: 0s - loss: 0.0141 133/133 [==============================] - 0s 1ms/step - loss: 0.0134 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 3, 10 GAN f1 score: 0.800 GAN cohens kappa score: 0.793 -> 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: 0.386 -> 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: 333, 0 KNN fn, tp: 0, 13 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 19s - loss: 3.9676e-05 49/134 [=========>....................] - ETA: 0s - loss: 0.0878  97/134 [====================>.........] - ETA: 0s - loss: 0.0639 134/134 [==============================] - 0s 1ms/step - loss: 0.0590 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.0020 44/134 [========>.....................] - ETA: 0s - loss: 0.0227 91/134 [===================>..........] - ETA: 0s - loss: 0.0457 134/134 [==============================] - 0s 1ms/step - loss: 0.0405 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 3.7881e-06 44/134 [========>.....................] - ETA: 0s - loss: 0.0373  92/134 [===================>..........] - ETA: 0s - loss: 0.0345 134/134 [==============================] - 0s 1ms/step - loss: 0.0348 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0013 50/134 [==========>...................] - ETA: 0s - loss: 0.0377 98/134 [====================>.........] - ETA: 0s - loss: 0.0269 134/134 [==============================] - 0s 1ms/step - loss: 0.0269 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 6.5640e-06 48/134 [=========>....................] - ETA: 0s - loss: 0.0252  96/134 [====================>.........] - ETA: 0s - loss: 0.0228 134/134 [==============================] - 0s 1ms/step - loss: 0.0230 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 7.2914e-04 49/134 [=========>....................] - ETA: 0s - loss: 0.0172  97/134 [====================>.........] - ETA: 0s - loss: 0.0165 134/134 [==============================] - 0s 1ms/step - loss: 0.0203 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0051 49/134 [=========>....................] - ETA: 0s - loss: 0.0199 98/134 [====================>.........] - ETA: 0s - loss: 0.0159 134/134 [==============================] - 0s 1ms/step - loss: 0.0185 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 5.1791e-06 50/134 [==========>...................] - ETA: 0s - loss: 0.0180  98/134 [====================>.........] - ETA: 0s - loss: 0.0151 134/134 [==============================] - 0s 1ms/step - loss: 0.0155 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 1.5844e-05 48/134 [=========>....................] - ETA: 0s - loss: 0.0216  95/134 [====================>.........] - ETA: 0s - loss: 0.0194 134/134 [==============================] - 0s 1ms/step - loss: 0.0176 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 6.2495e-06 47/134 [=========>....................] - ETA: 0s - loss: 0.0201  90/134 [===================>..........] - ETA: 0s - loss: 0.0174 132/134 [============================>.] - ETA: 0s - loss: 0.0150 134/134 [==============================] - 0s 1ms/step - loss: 0.0148 -> 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: 306, 25 LR fn, tp: 3, 10 LR f1 score: 0.417 LR cohens kappa score: 0.383 LR average precision score: 0.386 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 5, 8 RF f1 score: 0.762 RF cohens kappa score: 0.755 -> 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: 331, 0 KNN fn, tp: 2, 11 KNN f1 score: 0.917 KNN cohens kappa score: 0.914 ====== 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: 16s - loss: 8.6887e-04 51/133 [==========>...................] - ETA: 0s - loss: 0.0969  102/133 [======================>.......] - ETA: 0s - loss: 0.0706 133/133 [==============================] - 0s 997us/step - loss: 0.0686 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0444 52/133 [==========>...................] - ETA: 0s - loss: 0.0473 103/133 [======================>.......] - ETA: 0s - loss: 0.0454 133/133 [==============================] - 0s 986us/step - loss: 0.0516 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0157 52/133 [==========>...................] - ETA: 0s - loss: 0.0478 103/133 [======================>.......] - ETA: 0s - loss: 0.0370 133/133 [==============================] - 0s 988us/step - loss: 0.0358 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0148 53/133 [==========>...................] - ETA: 0s - loss: 0.0397 104/133 [======================>.......] - ETA: 0s - loss: 0.0440 133/133 [==============================] - 0s 984us/step - loss: 0.0381 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0085 51/133 [==========>...................] - ETA: 0s - loss: 0.0276 98/133 [=====================>........] - ETA: 0s - loss: 0.0282 133/133 [==============================] - 0s 1ms/step - loss: 0.0277 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0111 50/133 [==========>...................] - ETA: 0s - loss: 0.0188 101/133 [=====================>........] - ETA: 0s - loss: 0.0254 133/133 [==============================] - 0s 1ms/step - loss: 0.0249 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 9.3741e-06 46/133 [=========>....................] - ETA: 0s - loss: 0.0354  92/133 [===================>..........] - ETA: 0s - loss: 0.0229 133/133 [==============================] - 0s 1ms/step - loss: 0.0231 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 8.7900e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0198  103/133 [======================>.......] - ETA: 0s - loss: 0.0245 133/133 [==============================] - 0s 986us/step - loss: 0.0202 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 1.2751e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0162  104/133 [======================>.......] - ETA: 0s - loss: 0.0209 133/133 [==============================] - 0s 987us/step - loss: 0.0196 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.3965e-05 53/133 [==========>...................] - ETA: 0s - loss: 0.0256  104/133 [======================>.......] - ETA: 0s - loss: 0.0208 133/133 [==============================] - 0s 1ms/step - loss: 0.0187 -> test with GAN.predict GAN tn, fp: 333, 0 GAN fn, tp: 6, 7 GAN f1 score: 0.700 GAN cohens kappa score: 0.692 -> test with 'LR' LR tn, fp: 305, 28 LR fn, tp: 1, 12 LR f1 score: 0.453 LR cohens kappa score: 0.420 LR average precision score: 0.420 -> 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: 1, 12 GB f1 score: 0.960 GB cohens kappa score: 0.959 -> test with 'KNN' KNN tn, fp: 331, 2 KNN fn, tp: 2, 11 KNN f1 score: 0.846 KNN cohens kappa score: 0.840 ------ 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: 17s - loss: 6.2274e-07 51/133 [==========>...................] - ETA: 0s - loss: 0.0951  102/133 [======================>.......] - ETA: 0s - loss: 0.0847 133/133 [==============================] - 0s 1ms/step - loss: 0.0752 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 6.0864e-06 47/133 [=========>....................] - ETA: 0s - loss: 0.0420  94/133 [====================>.........] - ETA: 0s - loss: 0.0580 133/133 [==============================] - 0s 1ms/step - loss: 0.0500 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.7489e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0217  101/133 [=====================>........] - ETA: 0s - loss: 0.0261 133/133 [==============================] - 0s 1ms/step - loss: 0.0364 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 4.9584e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0174  103/133 [======================>.......] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 993us/step - loss: 0.0291 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 2.9646e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0150  102/133 [======================>.......] - ETA: 0s - loss: 0.0145 133/133 [==============================] - 0s 991us/step - loss: 0.0246 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0010 52/133 [==========>...................] - ETA: 0s - loss: 0.0185 99/133 [=====================>........] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 1ms/step - loss: 0.0249 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 2.9751e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0256  103/133 [======================>.......] - ETA: 0s - loss: 0.0223 133/133 [==============================] - 0s 998us/step - loss: 0.0216 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 6.2179e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0226  103/133 [======================>.......] - ETA: 0s - loss: 0.0215 133/133 [==============================] - 0s 1000us/step - loss: 0.0188 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 5.5780e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0249  102/133 [======================>.......] - ETA: 0s - loss: 0.0202 133/133 [==============================] - 0s 999us/step - loss: 0.0165 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 4.1703e-06 51/133 [==========>...................] - ETA: 0s - loss: 0.0101  102/133 [======================>.......] - ETA: 0s - loss: 0.0129 133/133 [==============================] - 0s 1ms/step - loss: 0.0150 -> test with GAN.predict GAN tn, fp: 332, 1 GAN fn, tp: 4, 9 GAN f1 score: 0.783 GAN cohens kappa score: 0.775 -> 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: 0.514 -> test with 'RF' RF tn, fp: 332, 1 RF fn, tp: 2, 11 RF f1 score: 0.880 RF cohens kappa score: 0.876 -> 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: 333, 0 KNN fn, tp: 4, 9 KNN f1 score: 0.818 KNN cohens kappa score: 0.812 ------ 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: 18s - loss: 0.7179 49/133 [==========>...................] - ETA: 0s - loss: 0.0372  97/133 [====================>.........] - ETA: 0s - loss: 0.0347 133/133 [==============================] - 0s 1ms/step - loss: 0.0419 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0012 52/133 [==========>...................] - ETA: 0s - loss: 0.0307 102/133 [======================>.......] - ETA: 0s - loss: 0.0233 133/133 [==============================] - 0s 999us/step - loss: 0.0277 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 6.2871e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0212  103/133 [======================>.......] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 995us/step - loss: 0.0188 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 1.4383e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0129  103/133 [======================>.......] - ETA: 0s - loss: 0.0163 133/133 [==============================] - 0s 995us/step - loss: 0.0146 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 2.9647e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0105  103/133 [======================>.......] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 998us/step - loss: 0.0131 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 7.4600e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0175  101/133 [=====================>........] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 1ms/step - loss: 0.0131 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0252 51/133 [==========>...................] - ETA: 0s - loss: 0.0093 100/133 [=====================>........] - ETA: 0s - loss: 0.0099 133/133 [==============================] - 0s 1ms/step - loss: 0.0123 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0281 47/133 [=========>....................] - ETA: 0s - loss: 0.0070 94/133 [====================>.........] - ETA: 0s - loss: 0.0107 133/133 [==============================] - 0s 1ms/step - loss: 0.0099 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 52/133 [==========>...................] - ETA: 0s - loss: 0.0056 103/133 [======================>.......] - ETA: 0s - loss: 0.0070 133/133 [==============================] - 0s 990us/step - loss: 0.0092 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.0563e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0065  100/133 [=====================>........] - ETA: 0s - loss: 0.0080 133/133 [==============================] - 0s 1ms/step - loss: 0.0088 -> 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: 298, 35 LR fn, tp: 1, 12 LR f1 score: 0.400 LR cohens kappa score: 0.362 LR average precision score: 0.312 -> 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: 330, 3 KNN fn, tp: 0, 13 KNN f1 score: 0.897 KNN cohens kappa score: 0.892 ------ 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: 15s - loss: 3.8479e-06 51/133 [==========>...................] - ETA: 0s - loss: 0.0587  102/133 [======================>.......] - ETA: 0s - loss: 0.0568 133/133 [==============================] - 0s 1ms/step - loss: 0.0525 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 4.6599e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0579  103/133 [======================>.......] - ETA: 0s - loss: 0.0407 133/133 [==============================] - 0s 991us/step - loss: 0.0402 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.1806 52/133 [==========>...................] - ETA: 0s - loss: 0.0302 103/133 [======================>.......] - ETA: 0s - loss: 0.0300 133/133 [==============================] - 0s 989us/step - loss: 0.0259 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 2.6903e-05 49/133 [==========>...................] - ETA: 0s - loss: 0.0185  100/133 [=====================>........] - ETA: 0s - loss: 0.0198 133/133 [==============================] - 0s 1ms/step - loss: 0.0217 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 52/133 [==========>...................] - ETA: 0s - loss: 0.0085 103/133 [======================>.......] - ETA: 0s - loss: 0.0199 133/133 [==============================] - 0s 996us/step - loss: 0.0200 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 4.2247e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0151  102/133 [======================>.......] - ETA: 0s - loss: 0.0169 133/133 [==============================] - 0s 1ms/step - loss: 0.0170 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0317 47/133 [=========>....................] - ETA: 0s - loss: 0.0129 94/133 [====================>.........] - ETA: 0s - loss: 0.0154 133/133 [==============================] - 0s 1ms/step - loss: 0.0153 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 4.6428e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0176  103/133 [======================>.......] - ETA: 0s - loss: 0.0178 133/133 [==============================] - 0s 991us/step - loss: 0.0152 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 4.0178e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0132  103/133 [======================>.......] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 989us/step - loss: 0.0135 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 7.0648e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0068  103/133 [======================>.......] - ETA: 0s - loss: 0.0124 133/133 [==============================] - 0s 999us/step - loss: 0.0128 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 7, 6 GAN f1 score: 0.522 GAN cohens kappa score: 0.506 -> test with 'LR' LR tn, fp: 304, 29 LR fn, tp: 3, 10 LR f1 score: 0.385 LR cohens kappa score: 0.348 LR average precision score: 0.277 -> 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: 332, 1 KNN fn, tp: 1, 12 KNN f1 score: 0.923 KNN cohens kappa score: 0.920 ------ 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: 22s - loss: 5.3228e-04 43/134 [========>.....................] - ETA: 0s - loss: 0.0616  85/134 [==================>...........] - ETA: 0s - loss: 0.0466 133/134 [============================>.] - ETA: 0s - loss: 0.0532 134/134 [==============================] - 0s 1ms/step - loss: 0.0532 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.2456 48/134 [=========>....................] - ETA: 0s - loss: 0.0424 96/134 [====================>.........] - ETA: 0s - loss: 0.0287 134/134 [==============================] - 0s 1ms/step - loss: 0.0278 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 1.2164e-05 49/134 [=========>....................] - ETA: 0s - loss: 0.0231  97/134 [====================>.........] - ETA: 0s - loss: 0.0234 134/134 [==============================] - 0s 1ms/step - loss: 0.0206 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 5.0380e-06 49/134 [=========>....................] - ETA: 0s - loss: 0.0253  97/134 [====================>.........] - ETA: 0s - loss: 0.0212 134/134 [==============================] - 0s 1ms/step - loss: 0.0164 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.1761 49/134 [=========>....................] - ETA: 0s - loss: 0.0153 97/134 [====================>.........] - ETA: 0s - loss: 0.0183 134/134 [==============================] - 0s 1ms/step - loss: 0.0157 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 6.7345e-06 49/134 [=========>....................] - ETA: 0s - loss: 0.0115  92/134 [===================>..........] - ETA: 0s - loss: 0.0150 134/134 [==============================] - 0s 1ms/step - loss: 0.0150 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 4.0590e-04 49/134 [=========>....................] - ETA: 0s - loss: 0.0180  97/134 [====================>.........] - ETA: 0s - loss: 0.0127 134/134 [==============================] - 0s 1ms/step - loss: 0.0130 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 1.9236e-05 49/134 [=========>....................] - ETA: 0s - loss: 0.0100  97/134 [====================>.........] - ETA: 0s - loss: 0.0112 134/134 [==============================] - 0s 1ms/step - loss: 0.0110 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0053 49/134 [=========>....................] - ETA: 0s - loss: 0.0091 97/134 [====================>.........] - ETA: 0s - loss: 0.0118 134/134 [==============================] - 0s 1ms/step - loss: 0.0110 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0178 49/134 [=========>....................] - ETA: 0s - loss: 0.0064 97/134 [====================>.........] - ETA: 0s - loss: 0.0087 134/134 [==============================] - 0s 1ms/step - loss: 0.0099 -> test with GAN.predict GAN tn, fp: 328, 3 GAN fn, tp: 4, 9 GAN f1 score: 0.720 GAN cohens kappa score: 0.709 -> 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: 0.333 -> 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: 19s - loss: 0.0024 51/133 [==========>...................] - ETA: 0s - loss: 0.0520  101/133 [=====================>........] - ETA: 0s - loss: 0.0424 133/133 [==============================] - 0s 1ms/step - loss: 0.0353 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 9.7177e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0153  103/133 [======================>.......] - ETA: 0s - loss: 0.0208 133/133 [==============================] - 0s 995us/step - loss: 0.0199 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 52/133 [==========>...................] - ETA: 0s - loss: 0.0282 103/133 [======================>.......] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 994us/step - loss: 0.0213 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 2.2763e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0108  103/133 [======================>.......] - ETA: 0s - loss: 0.0123 133/133 [==============================] - 0s 995us/step - loss: 0.0147 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 3.4967e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0191  103/133 [======================>.......] - ETA: 0s - loss: 0.0154 133/133 [==============================] - 0s 992us/step - loss: 0.0167 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0073 51/133 [==========>...................] - ETA: 0s - loss: 0.0054 101/133 [=====================>........] - ETA: 0s - loss: 0.0136 133/133 [==============================] - 0s 1ms/step - loss: 0.0143 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0170 50/133 [==========>...................] - ETA: 0s - loss: 0.0099 101/133 [=====================>........] - ETA: 0s - loss: 0.0151 133/133 [==============================] - 0s 1ms/step - loss: 0.0132 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 5.7424e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0108  102/133 [======================>.......] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 1ms/step - loss: 0.0120 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 1.2325e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0118  103/133 [======================>.......] - ETA: 0s - loss: 0.0086 133/133 [==============================] - 0s 991us/step - loss: 0.0092 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 1.4192e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0122  103/133 [======================>.......] - ETA: 0s - loss: 0.0097 133/133 [==============================] - 0s 991us/step - loss: 0.0090 -> test with GAN.predict GAN tn, fp: 332, 1 GAN fn, tp: 3, 10 GAN f1 score: 0.833 GAN cohens kappa score: 0.827 -> test with 'LR' LR tn, fp: 292, 41 LR fn, tp: 0, 13 LR f1 score: 0.388 LR cohens kappa score: 0.349 LR average precision score: 0.291 -> 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: 330, 3 KNN fn, tp: 0, 13 KNN f1 score: 0.897 KNN cohens kappa score: 0.892 ------ 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: 17s - loss: 5.3369e-06 46/133 [=========>....................] - ETA: 0s - loss: 0.0310  87/133 [==================>...........] - ETA: 0s - loss: 0.0549 130/133 [============================>.] - ETA: 0s - loss: 0.0459 133/133 [==============================] - 0s 1ms/step - loss: 0.0449 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 1.2061e-05 51/133 [==========>...................] - ETA: 0s - loss: 0.0168  102/133 [======================>.......] - ETA: 0s - loss: 0.0195 133/133 [==============================] - 0s 1ms/step - loss: 0.0265 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 6.8805e-06 44/133 [========>.....................] - ETA: 0s - loss: 0.0234  95/133 [====================>.........] - ETA: 0s - loss: 0.0237 133/133 [==============================] - 0s 1ms/step - loss: 0.0236 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 2.9472e-05 48/133 [=========>....................] - ETA: 0s - loss: 0.0092  99/133 [=====================>........] - ETA: 0s - loss: 0.0126 133/133 [==============================] - 0s 1ms/step - loss: 0.0160 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0069 50/133 [==========>...................] - ETA: 0s - loss: 0.0079 98/133 [=====================>........] - ETA: 0s - loss: 0.0109 133/133 [==============================] - 0s 1ms/step - loss: 0.0168 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 9.7259e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0156  102/133 [======================>.......] - ETA: 0s - loss: 0.0140 133/133 [==============================] - 0s 1000us/step - loss: 0.0158 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 3.7540e-05 51/133 [==========>...................] - ETA: 0s - loss: 0.0093  96/133 [====================>.........] - ETA: 0s - loss: 0.0138 133/133 [==============================] - 0s 1ms/step - loss: 0.0140 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0029 51/133 [==========>...................] - ETA: 0s - loss: 0.0192 98/133 [=====================>........] - ETA: 0s - loss: 0.0132 133/133 [==============================] - 0s 1ms/step - loss: 0.0134 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 2.1097e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0129  102/133 [======================>.......] - ETA: 0s - loss: 0.0107 133/133 [==============================] - 0s 1ms/step - loss: 0.0096 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0786 51/133 [==========>...................] - ETA: 0s - loss: 0.0148 101/133 [=====================>........] - ETA: 0s - loss: 0.0107 133/133 [==============================] - 0s 1ms/step - loss: 0.0090 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 6, 7 GAN f1 score: 0.636 GAN cohens kappa score: 0.625 -> test with 'LR' LR tn, fp: 312, 21 LR fn, tp: 3, 10 LR f1 score: 0.455 LR cohens kappa score: 0.424 LR average precision score: 0.338 -> 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: 330, 3 KNN fn, tp: 1, 12 KNN f1 score: 0.857 KNN cohens kappa score: 0.851 ------ 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: 19s - loss: 0.4206 51/133 [==========>...................] - ETA: 0s - loss: 0.0931  102/133 [======================>.......] - ETA: 0s - loss: 0.0750 133/133 [==============================] - 0s 1ms/step - loss: 0.0770 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 3.2657e-07 51/133 [==========>...................] - ETA: 0s - loss: 0.0565  102/133 [======================>.......] - ETA: 0s - loss: 0.0594 133/133 [==============================] - 0s 1ms/step - loss: 0.0504 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0537 52/133 [==========>...................] - ETA: 0s - loss: 0.0415 103/133 [======================>.......] - ETA: 0s - loss: 0.0377 133/133 [==============================] - 0s 991us/step - loss: 0.0325 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 3.9033e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0183  102/133 [======================>.......] - ETA: 0s - loss: 0.0340 133/133 [==============================] - 0s 997us/step - loss: 0.0308 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 1.1025e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0313  103/133 [======================>.......] - ETA: 0s - loss: 0.0252 133/133 [==============================] - 0s 990us/step - loss: 0.0287 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 2.0820e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0212  103/133 [======================>.......] - ETA: 0s - loss: 0.0229 133/133 [==============================] - 0s 994us/step - loss: 0.0251 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0087 52/133 [==========>...................] - ETA: 0s - loss: 0.0193 103/133 [======================>.......] - ETA: 0s - loss: 0.0185 133/133 [==============================] - 0s 992us/step - loss: 0.0202 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 1.5027e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0229  100/133 [=====================>........] - ETA: 0s - loss: 0.0175 133/133 [==============================] - 0s 1ms/step - loss: 0.0184 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0139 46/133 [=========>....................] - ETA: 0s - loss: 0.0174 94/133 [====================>.........] - ETA: 0s - loss: 0.0177 133/133 [==============================] - 0s 1ms/step - loss: 0.0172 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0013 52/133 [==========>...................] - ETA: 0s - loss: 0.0076 99/133 [=====================>........] - ETA: 0s - loss: 0.0150 133/133 [==============================] - 0s 1ms/step - loss: 0.0156 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 5, 8 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 313, 20 LR fn, tp: 3, 10 LR f1 score: 0.465 LR cohens kappa score: 0.436 LR average precision score: 0.338 -> 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: 333, 0 KNN fn, tp: 3, 10 KNN f1 score: 0.870 KNN cohens kappa score: 0.865 ------ 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: 18s - loss: 1.5161e-05 51/133 [==========>...................] - ETA: 0s - loss: 0.0823  102/133 [======================>.......] - ETA: 0s - loss: 0.0771 133/133 [==============================] - 0s 1ms/step - loss: 0.0632 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 9.7206e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0475  103/133 [======================>.......] - ETA: 0s - loss: 0.0369 133/133 [==============================] - 0s 999us/step - loss: 0.0298 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 1.1666e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0328  103/133 [======================>.......] - ETA: 0s - loss: 0.0269 133/133 [==============================] - 0s 996us/step - loss: 0.0244 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 7.7657e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0194  103/133 [======================>.......] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 994us/step - loss: 0.0210 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 1.3079e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0087  103/133 [======================>.......] - ETA: 0s - loss: 0.0164 133/133 [==============================] - 0s 996us/step - loss: 0.0190 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0046 52/133 [==========>...................] - ETA: 0s - loss: 0.0243 103/133 [======================>.......] - ETA: 0s - loss: 0.0178 133/133 [==============================] - 0s 994us/step - loss: 0.0167 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 6.5036e-06 52/133 [==========>...................] - ETA: 0s - loss: 0.0156  102/133 [======================>.......] - ETA: 0s - loss: 0.0190 133/133 [==============================] - 0s 1ms/step - loss: 0.0166 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0012 52/133 [==========>...................] - ETA: 0s - loss: 0.0125 103/133 [======================>.......] - ETA: 0s - loss: 0.0114 133/133 [==============================] - 0s 995us/step - loss: 0.0148 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 4.4639e-05 52/133 [==========>...................] - ETA: 0s - loss: 0.0173  103/133 [======================>.......] - ETA: 0s - loss: 0.0134 133/133 [==============================] - 0s 998us/step - loss: 0.0151 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0083 51/133 [==========>...................] - ETA: 0s - loss: 0.0090 99/133 [=====================>........] - ETA: 0s - loss: 0.0113 133/133 [==============================] - 0s 1ms/step - loss: 0.0126 -> 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: 296, 37 LR fn, tp: 1, 12 LR f1 score: 0.387 LR cohens kappa score: 0.348 LR average precision score: 0.295 -> 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 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: 20s - loss: 0.2510 49/134 [=========>....................] - ETA: 0s - loss: 0.0667  97/134 [====================>.........] - ETA: 0s - loss: 0.0732 134/134 [==============================] - 0s 1ms/step - loss: 0.0791 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 3.2878e-04 49/134 [=========>....................] - ETA: 0s - loss: 0.0284  97/134 [====================>.........] - ETA: 0s - loss: 0.0351 134/134 [==============================] - 0s 1ms/step - loss: 0.0424 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 1.7080e-05 49/134 [=========>....................] - ETA: 0s - loss: 0.0291  95/134 [====================>.........] - ETA: 0s - loss: 0.0280 134/134 [==============================] - 0s 1ms/step - loss: 0.0334 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0491 48/134 [=========>....................] - ETA: 0s - loss: 0.0285 96/134 [====================>.........] - ETA: 0s - loss: 0.0260 134/134 [==============================] - 0s 1ms/step - loss: 0.0266 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 8.3756e-05 49/134 [=========>....................] - ETA: 0s - loss: 0.0207  97/134 [====================>.........] - ETA: 0s - loss: 0.0236 134/134 [==============================] - 0s 1ms/step - loss: 0.0221 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0665 49/134 [=========>....................] - ETA: 0s - loss: 0.0301 97/134 [====================>.........] - ETA: 0s - loss: 0.0276 134/134 [==============================] - 0s 1ms/step - loss: 0.0250 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 8.4235e-04 49/134 [=========>....................] - ETA: 0s - loss: 0.0212  97/134 [====================>.........] - ETA: 0s - loss: 0.0216 134/134 [==============================] - 0s 1ms/step - loss: 0.0191 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 6.2428e-06 50/134 [==========>...................] - ETA: 0s - loss: 0.0233  98/134 [====================>.........] - ETA: 0s - loss: 0.0231 134/134 [==============================] - 0s 1ms/step - loss: 0.0189 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 1.7209e-04 49/134 [=========>....................] - ETA: 0s - loss: 0.0095  97/134 [====================>.........] - ETA: 0s - loss: 0.0200 134/134 [==============================] - 0s 1ms/step - loss: 0.0177 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0251 49/134 [=========>....................] - ETA: 0s - loss: 0.0133 97/134 [====================>.........] - ETA: 0s - loss: 0.0118 134/134 [==============================] - 0s 1ms/step - loss: 0.0167 -> test with GAN.predict GAN tn, fp: 328, 3 GAN fn, tp: 5, 8 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 301, 30 LR fn, tp: 0, 13 LR f1 score: 0.464 LR cohens kappa score: 0.431 LR average precision score: 0.479 -> test with 'RF' RF tn, fp: 330, 1 RF fn, tp: 1, 12 RF f1 score: 0.923 RF cohens kappa score: 0.920 -> 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: 2, 11 KNN f1 score: 0.880 KNN cohens kappa score: 0.875 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 313, 41 LR fn, tp: 5, 13 LR f1 score: 0.520 LR cohens kappa score: 0.492 LR average precision score: 0.559 average: LR tn, fp: 302.44, 30.16 LR fn, tp: 1.52, 11.48 LR f1 score: 0.422 LR cohens kappa score: 0.387 LR average precision score: 0.364 minimum: LR tn, fp: 292, 20 LR fn, tp: 0, 8 LR f1 score: 0.356 LR cohens kappa score: 0.318 LR average precision score: 0.277 -----[ 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: 332.4, 0.2 RF fn, tp: 1.48, 11.52 RF f1 score: 0.929 RF cohens kappa score: 0.927 minimum: RF tn, fp: 330, 0 RF fn, tp: 0, 8 RF f1 score: 0.762 RF cohens kappa score: 0.755 -----[ 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: 332.48, 0.12 GB fn, tp: 0.32, 12.68 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: 333, 7 KNN fn, tp: 4, 13 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 average: KNN tn, fp: 330.56, 2.04 KNN fn, tp: 1.28, 11.72 KNN f1 score: 0.879 KNN cohens kappa score: 0.874 minimum: KNN tn, fp: 324, 0 KNN fn, tp: 0, 9 KNN f1 score: 0.710 KNN cohens kappa score: 0.696 -----[ GAN ]----- maximum: GAN tn, fp: 333, 6 GAN fn, tp: 7, 11 GAN f1 score: 0.846 GAN cohens kappa score: 0.840 average: GAN tn, fp: 330.0, 2.6 GAN fn, tp: 4.16, 8.84 GAN f1 score: 0.721 GAN cohens kappa score: 0.712 minimum: GAN tn, fp: 326, 0 GAN fn, tp: 2, 6 GAN f1 score: 0.522 GAN cohens kappa score: 0.506