/////////////////////////////////////////// // Running convGAN-majority-full on folding_yeast5 /////////////////////////////////////////// Load 'data_input/folding_yeast5' 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 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0022 39/116 [=========>....................] - ETA: 0s - loss: 0.0377  72/116 [=================>............] - ETA: 0s - loss: 0.0378 105/116 [==========================>...] - ETA: 0s - loss: 0.0391 116/116 [==============================] - 0s 2ms/step - loss: 0.0422 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0110 39/116 [=========>....................] - ETA: 0s - loss: 0.0398 71/116 [=================>............] - ETA: 0s - loss: 0.0411 103/116 [=========================>....] - ETA: 0s - loss: 0.0417 116/116 [==============================] - 0s 1ms/step - loss: 0.0417 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0245 31/116 [=======>......................] - ETA: 0s - loss: 0.0363 70/116 [=================>............] - ETA: 0s - loss: 0.0428 109/116 [===========================>..] - ETA: 0s - loss: 0.0412 116/116 [==============================] - 0s 1ms/step - loss: 0.0413 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0312 38/116 [========>.....................] - ETA: 0s - loss: 0.0404 76/116 [==================>...........] - ETA: 0s - loss: 0.0439 113/116 [============================>.] - ETA: 0s - loss: 0.0435 116/116 [==============================] - 0s 1ms/step - loss: 0.0429 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0055 38/116 [========>.....................] - ETA: 0s - loss: 0.0301 73/116 [=================>............] - ETA: 0s - loss: 0.0382 111/116 [===========================>..] - ETA: 0s - loss: 0.0405 116/116 [==============================] - 0s 1ms/step - loss: 0.0404 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0416 39/116 [=========>....................] - ETA: 0s - loss: 0.0377 79/116 [===================>..........] - ETA: 0s - loss: 0.0396 116/116 [==============================] - ETA: 0s - loss: 0.0398 116/116 [==============================] - 0s 1ms/step - loss: 0.0398 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0223 37/116 [========>.....................] - ETA: 0s - loss: 0.0346 75/116 [==================>...........] - ETA: 0s - loss: 0.0341 114/116 [============================>.] - ETA: 0s - loss: 0.0408 116/116 [==============================] - 0s 1ms/step - loss: 0.0405 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0026 40/116 [=========>....................] - ETA: 0s - loss: 0.0231 79/116 [===================>..........] - ETA: 0s - loss: 0.0347 113/116 [============================>.] - ETA: 0s - loss: 0.0378 116/116 [==============================] - 0s 1ms/step - loss: 0.0389 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0050 31/116 [=======>......................] - ETA: 0s - loss: 0.0284 68/116 [================>.............] - ETA: 0s - loss: 0.0331 108/116 [==========================>...] - ETA: 0s - loss: 0.0397 116/116 [==============================] - 0s 1ms/step - loss: 0.0387 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1205 40/116 [=========>....................] - ETA: 0s - loss: 0.0450 77/116 [==================>...........] - ETA: 0s - loss: 0.0381 114/116 [============================>.] - ETA: 0s - loss: 0.0387 116/116 [==============================] - 0s 1ms/step - loss: 0.0383 -> test with GAN.predict GAN tn, fp: 285, 3 GAN fn, tp: 3, 6 GAN f1 score: 0.667 GAN cohens kappa score: 0.656 -> test with 'LR' LR tn, fp: 282, 6 LR fn, tp: 0, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.895 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 3, 6 RF f1 score: 0.800 RF cohens kappa score: 0.795 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 4, 5 GB f1 score: 0.625 GB cohens kappa score: 0.615 -> test with 'KNN' KNN tn, fp: 280, 8 KNN fn, tp: 0, 9 KNN f1 score: 0.692 KNN cohens kappa score: 0.680 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0049 37/116 [========>.....................] - ETA: 0s - loss: 0.0426  75/116 [==================>...........] - ETA: 0s - loss: 0.0503 112/116 [===========================>..] - ETA: 0s - loss: 0.0434 116/116 [==============================] - 0s 1ms/step - loss: 0.0425 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1166 39/116 [=========>....................] - ETA: 0s - loss: 0.0489 76/116 [==================>...........] - ETA: 0s - loss: 0.0427 113/116 [============================>.] - ETA: 0s - loss: 0.0407 116/116 [==============================] - 0s 1ms/step - loss: 0.0416 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0098 39/116 [=========>....................] - ETA: 0s - loss: 0.0583 77/116 [==================>...........] - ETA: 0s - loss: 0.0535 113/116 [============================>.] - ETA: 0s - loss: 0.0434 116/116 [==============================] - 0s 1ms/step - loss: 0.0427 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0080 40/116 [=========>....................] - ETA: 0s - loss: 0.0496 78/116 [===================>..........] - ETA: 0s - loss: 0.0473 110/116 [===========================>..] - ETA: 0s - loss: 0.0460 116/116 [==============================] - 0s 1ms/step - loss: 0.0446 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0121 39/116 [=========>....................] - ETA: 0s - loss: 0.0555 76/116 [==================>...........] - ETA: 0s - loss: 0.0493 113/116 [============================>.] - ETA: 0s - loss: 0.0429 116/116 [==============================] - 0s 1ms/step - loss: 0.0421 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0055 37/116 [========>.....................] - ETA: 0s - loss: 0.0335 75/116 [==================>...........] - ETA: 0s - loss: 0.0328 111/116 [===========================>..] - ETA: 0s - loss: 0.0425 116/116 [==============================] - 0s 1ms/step - loss: 0.0415 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0086 40/116 [=========>....................] - ETA: 0s - loss: 0.0296 79/116 [===================>..........] - ETA: 0s - loss: 0.0337 116/116 [==============================] - 0s 1ms/step - loss: 0.0404 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0340 38/116 [========>.....................] - ETA: 0s - loss: 0.0440 77/116 [==================>...........] - ETA: 0s - loss: 0.0381 115/116 [============================>.] - ETA: 0s - loss: 0.0410 116/116 [==============================] - 0s 1ms/step - loss: 0.0410 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0168 40/116 [=========>....................] - ETA: 0s - loss: 0.0531 73/116 [=================>............] - ETA: 0s - loss: 0.0518 111/116 [===========================>..] - ETA: 0s - loss: 0.0429 116/116 [==============================] - 0s 1ms/step - loss: 0.0419 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1555 37/116 [========>.....................] - ETA: 0s - loss: 0.0396 72/116 [=================>............] - ETA: 0s - loss: 0.0462 105/116 [==========================>...] - ETA: 0s - loss: 0.0410 116/116 [==============================] - 0s 1ms/step - loss: 0.0405 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 0, 9 GAN f1 score: 0.643 GAN cohens kappa score: 0.628 -> test with 'LR' LR tn, fp: 273, 15 LR fn, tp: 0, 9 LR f1 score: 0.545 LR cohens kappa score: 0.524 LR average precision score: 0.696 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 0, 9 RF f1 score: 0.857 RF cohens kappa score: 0.852 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 2, 7 GB f1 score: 0.700 GB cohens kappa score: 0.690 -> test with 'KNN' KNN tn, fp: 273, 15 KNN fn, tp: 0, 9 KNN f1 score: 0.545 KNN cohens kappa score: 0.524 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0015 39/116 [=========>....................] - ETA: 0s - loss: 0.0499  78/116 [===================>..........] - ETA: 0s - loss: 0.0311 116/116 [==============================] - 0s 1ms/step - loss: 0.0344 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0035 41/116 [=========>....................] - ETA: 0s - loss: 0.0319 81/116 [===================>..........] - ETA: 0s - loss: 0.0340 116/116 [==============================] - 0s 1ms/step - loss: 0.0366 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0278 40/116 [=========>....................] - ETA: 0s - loss: 0.0288 79/116 [===================>..........] - ETA: 0s - loss: 0.0342 115/116 [============================>.] - ETA: 0s - loss: 0.0311 116/116 [==============================] - 0s 1ms/step - loss: 0.0311 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0200 42/116 [=========>....................] - ETA: 0s - loss: 0.0299 82/116 [====================>.........] - ETA: 0s - loss: 0.0276 116/116 [==============================] - 0s 1ms/step - loss: 0.0324 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0048 40/116 [=========>....................] - ETA: 0s - loss: 0.0313 78/116 [===================>..........] - ETA: 0s - loss: 0.0255 116/116 [==============================] - 0s 1ms/step - loss: 0.0322 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1915 41/116 [=========>....................] - ETA: 0s - loss: 0.0421 78/116 [===================>..........] - ETA: 0s - loss: 0.0314 116/116 [==============================] - ETA: 0s - loss: 0.0305 116/116 [==============================] - 0s 1ms/step - loss: 0.0305 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0057 40/116 [=========>....................] - ETA: 0s - loss: 0.0271 80/116 [===================>..........] - ETA: 0s - loss: 0.0283 114/116 [============================>.] - ETA: 0s - loss: 0.0324 116/116 [==============================] - 0s 1ms/step - loss: 0.0323 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0181 40/116 [=========>....................] - ETA: 0s - loss: 0.0167 79/116 [===================>..........] - ETA: 0s - loss: 0.0266 116/116 [==============================] - 0s 1ms/step - loss: 0.0311 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0375 39/116 [=========>....................] - ETA: 0s - loss: 0.0200 77/116 [==================>...........] - ETA: 0s - loss: 0.0343 116/116 [==============================] - 0s 1ms/step - loss: 0.0331 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0461 38/116 [========>.....................] - ETA: 0s - loss: 0.0414 76/116 [==================>...........] - ETA: 0s - loss: 0.0308 110/116 [===========================>..] - ETA: 0s - loss: 0.0303 116/116 [==============================] - 0s 1ms/step - loss: 0.0291 -> test with GAN.predict GAN tn, fp: 282, 6 GAN fn, tp: 1, 8 GAN f1 score: 0.696 GAN cohens kappa score: 0.684 -> test with 'LR' LR tn, fp: 280, 8 LR fn, tp: 1, 8 LR f1 score: 0.640 LR cohens kappa score: 0.625 LR average precision score: 0.621 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 3, 6 RF f1 score: 0.706 RF cohens kappa score: 0.697 -> test with 'GB' GB tn, fp: 285, 3 GB fn, tp: 3, 6 GB f1 score: 0.667 GB cohens kappa score: 0.656 -> test with 'KNN' KNN tn, fp: 280, 8 KNN fn, tp: 1, 8 KNN f1 score: 0.640 KNN cohens kappa score: 0.625 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0255 37/116 [========>.....................] - ETA: 0s - loss: 0.0352  71/116 [=================>............] - ETA: 0s - loss: 0.0338 104/116 [=========================>....] - ETA: 0s - loss: 0.0429 116/116 [==============================] - 0s 1ms/step - loss: 0.0440 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0070 33/116 [=======>......................] - ETA: 0s - loss: 0.0145 36/116 [========>.....................] - ETA: 0s - loss: 0.0142 71/116 [=================>............] - ETA: 0s - loss: 0.0240 103/116 [=========================>....] - ETA: 0s - loss: 0.0358 116/116 [==============================] - 0s 3ms/step - loss: 0.0406 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0302 40/116 [=========>....................] - ETA: 0s - loss: 0.0420 79/116 [===================>..........] - ETA: 0s - loss: 0.0364 116/116 [==============================] - 0s 1ms/step - loss: 0.0428 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1221 41/116 [=========>....................] - ETA: 0s - loss: 0.0450 79/116 [===================>..........] - ETA: 0s - loss: 0.0483 116/116 [==============================] - 0s 1ms/step - loss: 0.0400 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0034 40/116 [=========>....................] - ETA: 0s - loss: 0.0578 76/116 [==================>...........] - ETA: 0s - loss: 0.0422 109/116 [===========================>..] - ETA: 0s - loss: 0.0431 116/116 [==============================] - 0s 1ms/step - loss: 0.0418 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0769 35/116 [========>.....................] - ETA: 0s - loss: 0.0381 75/116 [==================>...........] - ETA: 0s - loss: 0.0447 112/116 [===========================>..] - ETA: 0s - loss: 0.0404 116/116 [==============================] - 0s 1ms/step - loss: 0.0413 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0610 40/116 [=========>....................] - ETA: 0s - loss: 0.0370 78/116 [===================>..........] - ETA: 0s - loss: 0.0460 116/116 [==============================] - 0s 1ms/step - loss: 0.0396 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0219 39/116 [=========>....................] - ETA: 0s - loss: 0.0413 76/116 [==================>...........] - ETA: 0s - loss: 0.0391 114/116 [============================>.] - ETA: 0s - loss: 0.0406 116/116 [==============================] - 0s 1ms/step - loss: 0.0403 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1002 39/116 [=========>....................] - ETA: 0s - loss: 0.0364 75/116 [==================>...........] - ETA: 0s - loss: 0.0395 112/116 [===========================>..] - ETA: 0s - loss: 0.0393 116/116 [==============================] - 0s 1ms/step - loss: 0.0394 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0116 39/116 [=========>....................] - ETA: 0s - loss: 0.0386 76/116 [==================>...........] - ETA: 0s - loss: 0.0483 114/116 [============================>.] - ETA: 0s - loss: 0.0391 116/116 [==============================] - 0s 1ms/step - loss: 0.0387 -> test with GAN.predict GAN tn, fp: 285, 3 GAN fn, tp: 4, 5 GAN f1 score: 0.588 GAN cohens kappa score: 0.576 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 2, 7 LR f1 score: 0.609 LR cohens kappa score: 0.594 LR average precision score: 0.738 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 3, 6 RF f1 score: 0.750 RF cohens kappa score: 0.743 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 3, 6 GB f1 score: 0.750 GB cohens kappa score: 0.743 -> test with 'KNN' KNN tn, fp: 286, 2 KNN fn, tp: 1, 8 KNN f1 score: 0.842 KNN cohens kappa score: 0.837 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.0078 39/116 [=========>....................] - ETA: 0s - loss: 0.0381  77/116 [==================>...........] - ETA: 0s - loss: 0.0387 114/116 [============================>.] - ETA: 0s - loss: 0.0476 116/116 [==============================] - 0s 1ms/step - loss: 0.0472 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0054 39/116 [=========>....................] - ETA: 0s - loss: 0.0377 77/116 [==================>...........] - ETA: 0s - loss: 0.0482 116/116 [==============================] - ETA: 0s - loss: 0.0476 116/116 [==============================] - 0s 1ms/step - loss: 0.0476 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0021 39/116 [=========>....................] - ETA: 0s - loss: 0.0282 71/116 [=================>............] - ETA: 0s - loss: 0.0454 109/116 [===========================>..] - ETA: 0s - loss: 0.0476 116/116 [==============================] - 0s 1ms/step - loss: 0.0470 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0073 40/116 [=========>....................] - ETA: 0s - loss: 0.0479 78/116 [===================>..........] - ETA: 0s - loss: 0.0383 116/116 [==============================] - 0s 1ms/step - loss: 0.0455 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0039 38/116 [========>.....................] - ETA: 0s - loss: 0.0736 80/116 [===================>..........] - ETA: 0s - loss: 0.0537 116/116 [==============================] - 0s 1ms/step - loss: 0.0470 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0307 40/116 [=========>....................] - ETA: 0s - loss: 0.0453 80/116 [===================>..........] - ETA: 0s - loss: 0.0562 116/116 [==============================] - 0s 1ms/step - loss: 0.0477 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0237 38/116 [========>.....................] - ETA: 0s - loss: 0.0415 76/116 [==================>...........] - ETA: 0s - loss: 0.0397 113/116 [============================>.] - ETA: 0s - loss: 0.0435 116/116 [==============================] - 0s 1ms/step - loss: 0.0442 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0026 38/116 [========>.....................] - ETA: 0s - loss: 0.0384 75/116 [==================>...........] - ETA: 0s - loss: 0.0384 112/116 [===========================>..] - ETA: 0s - loss: 0.0448 116/116 [==============================] - 0s 1ms/step - loss: 0.0455 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0026 37/116 [========>.....................] - ETA: 0s - loss: 0.0444 77/116 [==================>...........] - ETA: 0s - loss: 0.0422 115/116 [============================>.] - ETA: 0s - loss: 0.0458 116/116 [==============================] - 0s 1ms/step - loss: 0.0458 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2057 35/116 [========>.....................] - ETA: 0s - loss: 0.0616 68/116 [================>.............] - ETA: 0s - loss: 0.0494 102/116 [=========================>....] - ETA: 0s - loss: 0.0493 116/116 [==============================] - 0s 2ms/step - loss: 0.0457 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 0, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.626 -> test with 'LR' LR tn, fp: 273, 15 LR fn, tp: 0, 8 LR f1 score: 0.516 LR cohens kappa score: 0.496 LR average precision score: 0.703 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 1, 7 RF f1 score: 0.778 RF cohens kappa score: 0.771 -> test with 'GB' GB tn, fp: 285, 3 GB fn, tp: 1, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 276, 12 KNN fn, tp: 0, 8 KNN f1 score: 0.571 KNN cohens kappa score: 0.554 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 23s - loss: 0.2017 38/116 [========>.....................] - ETA: 0s - loss: 0.0630  75/116 [==================>...........] - ETA: 0s - loss: 0.0551 113/116 [============================>.] - ETA: 0s - loss: 0.0536 116/116 [==============================] - 0s 1ms/step - loss: 0.0530 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0074 39/116 [=========>....................] - ETA: 0s - loss: 0.0445 76/116 [==================>...........] - ETA: 0s - loss: 0.0409 113/116 [============================>.] - ETA: 0s - loss: 0.0524 116/116 [==============================] - 0s 1ms/step - loss: 0.0517 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0143 39/116 [=========>....................] - ETA: 0s - loss: 0.0562 78/116 [===================>..........] - ETA: 0s - loss: 0.0506 115/116 [============================>.] - ETA: 0s - loss: 0.0498 116/116 [==============================] - 0s 1ms/step - loss: 0.0513 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0065 38/116 [========>.....................] - ETA: 0s - loss: 0.0597 76/116 [==================>...........] - ETA: 0s - loss: 0.0527 113/116 [============================>.] - ETA: 0s - loss: 0.0512 116/116 [==============================] - 0s 1ms/step - loss: 0.0509 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0126 36/116 [========>.....................] - ETA: 0s - loss: 0.0455 72/116 [=================>............] - ETA: 0s - loss: 0.0529 108/116 [==========================>...] - ETA: 0s - loss: 0.0543 116/116 [==============================] - 0s 1ms/step - loss: 0.0519 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0248 37/116 [========>.....................] - ETA: 0s - loss: 0.0616 74/116 [==================>...........] - ETA: 0s - loss: 0.0588 111/116 [===========================>..] - ETA: 0s - loss: 0.0533 116/116 [==============================] - 0s 1ms/step - loss: 0.0519 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0112 39/116 [=========>....................] - ETA: 0s - loss: 0.0503 78/116 [===================>..........] - ETA: 0s - loss: 0.0438 116/116 [==============================] - 0s 1ms/step - loss: 0.0513 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0210 38/116 [========>.....................] - ETA: 0s - loss: 0.0660 75/116 [==================>...........] - ETA: 0s - loss: 0.0583 113/116 [============================>.] - ETA: 0s - loss: 0.0502 116/116 [==============================] - 0s 1ms/step - loss: 0.0500 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0198 41/116 [=========>....................] - ETA: 0s - loss: 0.0466 79/116 [===================>..........] - ETA: 0s - loss: 0.0499 116/116 [==============================] - 0s 1ms/step - loss: 0.0507 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0071 37/116 [========>.....................] - ETA: 0s - loss: 0.0611 76/116 [==================>...........] - ETA: 0s - loss: 0.0476 114/116 [============================>.] - ETA: 0s - loss: 0.0491 116/116 [==============================] - 0s 1ms/step - loss: 0.0507 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 1, 8 GAN f1 score: 0.615 GAN cohens kappa score: 0.600 -> test with 'LR' LR tn, fp: 276, 12 LR fn, tp: 0, 9 LR f1 score: 0.600 LR cohens kappa score: 0.582 LR average precision score: 0.703 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 1, 8 RF f1 score: 0.842 RF cohens kappa score: 0.837 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 1, 8 GB f1 score: 0.842 GB cohens kappa score: 0.837 -> test with 'KNN' KNN tn, fp: 278, 10 KNN fn, tp: 0, 9 KNN f1 score: 0.643 KNN cohens kappa score: 0.628 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 24s - loss: 0.0062 40/116 [=========>....................] - ETA: 0s - loss: 0.0289  79/116 [===================>..........] - ETA: 0s - loss: 0.0342 116/116 [==============================] - 0s 1ms/step - loss: 0.0363 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0218 41/116 [=========>....................] - ETA: 0s - loss: 0.0302 78/116 [===================>..........] - ETA: 0s - loss: 0.0279 116/116 [==============================] - ETA: 0s - loss: 0.0367 116/116 [==============================] - 0s 1ms/step - loss: 0.0367 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0075 38/116 [========>.....................] - ETA: 0s - loss: 0.0406 77/116 [==================>...........] - ETA: 0s - loss: 0.0364 111/116 [===========================>..] - ETA: 0s - loss: 0.0370 116/116 [==============================] - 0s 1ms/step - loss: 0.0361 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0121 39/116 [=========>....................] - ETA: 0s - loss: 0.0411 75/116 [==================>...........] - ETA: 0s - loss: 0.0345 112/116 [===========================>..] - ETA: 0s - loss: 0.0334 116/116 [==============================] - 0s 1ms/step - loss: 0.0352 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0021 38/116 [========>.....................] - ETA: 0s - loss: 0.0347 75/116 [==================>...........] - ETA: 0s - loss: 0.0415 114/116 [============================>.] - ETA: 0s - loss: 0.0358 116/116 [==============================] - 0s 1ms/step - loss: 0.0357 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0119 38/116 [========>.....................] - ETA: 0s - loss: 0.0164 76/116 [==================>...........] - ETA: 0s - loss: 0.0253 112/116 [===========================>..] - ETA: 0s - loss: 0.0352 116/116 [==============================] - 0s 1ms/step - loss: 0.0349 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0046 39/116 [=========>....................] - ETA: 0s - loss: 0.0399 70/116 [=================>............] - ETA: 0s - loss: 0.0412 101/116 [=========================>....] - ETA: 0s - loss: 0.0359 116/116 [==============================] - 0s 2ms/step - loss: 0.0346 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0128 36/116 [========>.....................] - ETA: 0s - loss: 0.0353 73/116 [=================>............] - ETA: 0s - loss: 0.0317 110/116 [===========================>..] - ETA: 0s - loss: 0.0357 116/116 [==============================] - 0s 1ms/step - loss: 0.0346 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0029 39/116 [=========>....................] - ETA: 0s - loss: 0.0375 78/116 [===================>..........] - ETA: 0s - loss: 0.0384 115/116 [============================>.] - ETA: 0s - loss: 0.0351 116/116 [==============================] - 0s 1ms/step - loss: 0.0350 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0555 36/116 [========>.....................] - ETA: 0s - loss: 0.0293 75/116 [==================>...........] - ETA: 0s - loss: 0.0364 111/116 [===========================>..] - ETA: 0s - loss: 0.0356 116/116 [==============================] - 0s 1ms/step - loss: 0.0346 -> test with GAN.predict GAN tn, fp: 277, 11 GAN fn, tp: 3, 6 GAN f1 score: 0.462 GAN cohens kappa score: 0.439 -> test with 'LR' LR tn, fp: 272, 16 LR fn, tp: 1, 8 LR f1 score: 0.485 LR cohens kappa score: 0.461 LR average precision score: 0.414 -> test with 'RF' RF tn, fp: 281, 7 RF fn, tp: 3, 6 RF f1 score: 0.545 RF cohens kappa score: 0.529 -> test with 'GB' GB tn, fp: 280, 8 GB fn, tp: 4, 5 GB f1 score: 0.455 GB cohens kappa score: 0.434 -> test with 'KNN' KNN tn, fp: 275, 13 KNN fn, tp: 0, 9 KNN f1 score: 0.581 KNN cohens kappa score: 0.562 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0031 40/116 [=========>....................] - ETA: 0s - loss: 0.0551  73/116 [=================>............] - ETA: 0s - loss: 0.0545 111/116 [===========================>..] - ETA: 0s - loss: 0.0509 116/116 [==============================] - 0s 1ms/step - loss: 0.0505 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0148 39/116 [=========>....................] - ETA: 0s - loss: 0.0566 75/116 [==================>...........] - ETA: 0s - loss: 0.0541 112/116 [===========================>..] - ETA: 0s - loss: 0.0504 116/116 [==============================] - 0s 1ms/step - loss: 0.0494 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1451 38/116 [========>.....................] - ETA: 0s - loss: 0.0487 75/116 [==================>...........] - ETA: 0s - loss: 0.0490 113/116 [============================>.] - ETA: 0s - loss: 0.0505 116/116 [==============================] - 0s 1ms/step - loss: 0.0503 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0817 40/116 [=========>....................] - ETA: 0s - loss: 0.0585 74/116 [==================>...........] - ETA: 0s - loss: 0.0538 108/116 [==========================>...] - ETA: 0s - loss: 0.0527 116/116 [==============================] - 0s 1ms/step - loss: 0.0512 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1202 36/116 [========>.....................] - ETA: 0s - loss: 0.0433 74/116 [==================>...........] - ETA: 0s - loss: 0.0407 110/116 [===========================>..] - ETA: 0s - loss: 0.0492 116/116 [==============================] - 0s 1ms/step - loss: 0.0485 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0125 37/116 [========>.....................] - ETA: 0s - loss: 0.0562 73/116 [=================>............] - ETA: 0s - loss: 0.0528 111/116 [===========================>..] - ETA: 0s - loss: 0.0506 116/116 [==============================] - 0s 1ms/step - loss: 0.0498 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0454 40/116 [=========>....................] - ETA: 0s - loss: 0.0562 77/116 [==================>...........] - ETA: 0s - loss: 0.0496 112/116 [===========================>..] - ETA: 0s - loss: 0.0486 116/116 [==============================] - 0s 1ms/step - loss: 0.0484 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0069 37/116 [========>.....................] - ETA: 0s - loss: 0.0528 75/116 [==================>...........] - ETA: 0s - loss: 0.0509 112/116 [===========================>..] - ETA: 0s - loss: 0.0482 116/116 [==============================] - 0s 1ms/step - loss: 0.0478 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0379 38/116 [========>.....................] - ETA: 0s - loss: 0.0555 77/116 [==================>...........] - ETA: 0s - loss: 0.0468 115/116 [============================>.] - ETA: 0s - loss: 0.0474 116/116 [==============================] - 0s 1ms/step - loss: 0.0474 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0570 39/116 [=========>....................] - ETA: 0s - loss: 0.0501 76/116 [==================>...........] - ETA: 0s - loss: 0.0476 108/116 [==========================>...] - ETA: 0s - loss: 0.0478 116/116 [==============================] - 0s 1ms/step - loss: 0.0474 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 1, 8 GAN f1 score: 0.727 GAN cohens kappa score: 0.717 -> test with 'LR' LR tn, fp: 282, 6 LR fn, tp: 0, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.755 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 2, 7 RF f1 score: 0.824 RF cohens kappa score: 0.818 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 1, 8 GB f1 score: 0.842 GB cohens kappa score: 0.837 -> test with 'KNN' KNN tn, fp: 281, 7 KNN fn, tp: 1, 8 KNN f1 score: 0.667 KNN cohens kappa score: 0.654 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0058 40/116 [=========>....................] - ETA: 0s - loss: 0.0595  78/116 [===================>..........] - ETA: 0s - loss: 0.0489 116/116 [==============================] - ETA: 0s - loss: 0.0457 116/116 [==============================] - 0s 1ms/step - loss: 0.0457 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0024 40/116 [=========>....................] - ETA: 0s - loss: 0.0469 79/116 [===================>..........] - ETA: 0s - loss: 0.0425 116/116 [==============================] - 0s 1ms/step - loss: 0.0427 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0579 40/116 [=========>....................] - ETA: 0s - loss: 0.0394 76/116 [==================>...........] - ETA: 0s - loss: 0.0476 113/116 [============================>.] - ETA: 0s - loss: 0.0434 116/116 [==============================] - 0s 1ms/step - loss: 0.0443 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1737 37/116 [========>.....................] - ETA: 0s - loss: 0.0545 73/116 [=================>............] - ETA: 0s - loss: 0.0494 112/116 [===========================>..] - ETA: 0s - loss: 0.0430 116/116 [==============================] - 0s 1ms/step - loss: 0.0438 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.3883 31/116 [=======>......................] - ETA: 0s - loss: 0.0540 64/116 [===============>..............] - ETA: 0s - loss: 0.0389 97/116 [========================>.....] - ETA: 0s - loss: 0.0440 116/116 [==============================] - 0s 2ms/step - loss: 0.0432 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0049 38/116 [========>.....................] - ETA: 0s - loss: 0.0512 75/116 [==================>...........] - ETA: 0s - loss: 0.0451 113/116 [============================>.] - ETA: 0s - loss: 0.0410 116/116 [==============================] - 0s 1ms/step - loss: 0.0405 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0267 38/116 [========>.....................] - ETA: 0s - loss: 0.0314 73/116 [=================>............] - ETA: 0s - loss: 0.0371 110/116 [===========================>..] - ETA: 0s - loss: 0.0421 116/116 [==============================] - 0s 1ms/step - loss: 0.0430 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0131 40/116 [=========>....................] - ETA: 0s - loss: 0.0438 80/116 [===================>..........] - ETA: 0s - loss: 0.0433 116/116 [==============================] - 0s 1ms/step - loss: 0.0401 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0044 40/116 [=========>....................] - ETA: 0s - loss: 0.0449 79/116 [===================>..........] - ETA: 0s - loss: 0.0371 116/116 [==============================] - 0s 1ms/step - loss: 0.0400 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0159 39/116 [=========>....................] - ETA: 0s - loss: 0.0440 73/116 [=================>............] - ETA: 0s - loss: 0.0425 111/116 [===========================>..] - ETA: 0s - loss: 0.0417 116/116 [==============================] - 0s 1ms/step - loss: 0.0411 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 0, 9 GAN f1 score: 0.667 GAN cohens kappa score: 0.653 -> test with 'LR' LR tn, fp: 279, 9 LR fn, tp: 0, 9 LR f1 score: 0.667 LR cohens kappa score: 0.653 LR average precision score: 0.897 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 1, 8 RF f1 score: 0.842 RF cohens kappa score: 0.837 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 1, 8 GB f1 score: 0.842 GB cohens kappa score: 0.837 -> test with 'KNN' KNN tn, fp: 276, 12 KNN fn, tp: 0, 9 KNN f1 score: 0.600 KNN cohens kappa score: 0.582 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0509 39/116 [=========>....................] - ETA: 0s - loss: 0.0369  79/116 [===================>..........] - ETA: 0s - loss: 0.0362 115/116 [============================>.] - ETA: 0s - loss: 0.0403 116/116 [==============================] - 0s 1ms/step - loss: 0.0403 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0105 41/116 [=========>....................] - ETA: 0s - loss: 0.0542 81/116 [===================>..........] - ETA: 0s - loss: 0.0409 116/116 [==============================] - 0s 1ms/step - loss: 0.0386 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0121 38/116 [========>.....................] - ETA: 0s - loss: 0.0516 78/116 [===================>..........] - ETA: 0s - loss: 0.0464 113/116 [============================>.] - ETA: 0s - loss: 0.0394 116/116 [==============================] - 0s 1ms/step - loss: 0.0395 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0052 35/116 [========>.....................] - ETA: 0s - loss: 0.0263 72/116 [=================>............] - ETA: 0s - loss: 0.0345 109/116 [===========================>..] - ETA: 0s - loss: 0.0406 116/116 [==============================] - 0s 1ms/step - loss: 0.0397 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0041 38/116 [========>.....................] - ETA: 0s - loss: 0.0369 72/116 [=================>............] - ETA: 0s - loss: 0.0349 107/116 [==========================>...] - ETA: 0s - loss: 0.0390 116/116 [==============================] - 0s 1ms/step - loss: 0.0388 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0033 38/116 [========>.....................] - ETA: 0s - loss: 0.0395 74/116 [==================>...........] - ETA: 0s - loss: 0.0343 113/116 [============================>.] - ETA: 0s - loss: 0.0385 116/116 [==============================] - 0s 1ms/step - loss: 0.0383 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0542 39/116 [=========>....................] - ETA: 0s - loss: 0.0444 77/116 [==================>...........] - ETA: 0s - loss: 0.0365 114/116 [============================>.] - ETA: 0s - loss: 0.0383 116/116 [==============================] - 0s 1ms/step - loss: 0.0380 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0508 36/116 [========>.....................] - ETA: 0s - loss: 0.0329 72/116 [=================>............] - ETA: 0s - loss: 0.0412 107/116 [==========================>...] - ETA: 0s - loss: 0.0412 116/116 [==============================] - 0s 1ms/step - loss: 0.0392 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0114 36/116 [========>.....................] - ETA: 0s - loss: 0.0418 74/116 [==================>...........] - ETA: 0s - loss: 0.0307 111/116 [===========================>..] - ETA: 0s - loss: 0.0370 116/116 [==============================] - 0s 1ms/step - loss: 0.0382 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2288 39/116 [=========>....................] - ETA: 0s - loss: 0.0484 74/116 [==================>...........] - ETA: 0s - loss: 0.0410 110/116 [===========================>..] - ETA: 0s - loss: 0.0388 116/116 [==============================] - 0s 1ms/step - loss: 0.0374 -> test with GAN.predict GAN tn, fp: 282, 6 GAN fn, tp: 1, 7 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 279, 9 LR fn, tp: 0, 8 LR f1 score: 0.640 LR cohens kappa score: 0.626 LR average precision score: 0.664 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 4, 4 RF f1 score: 0.615 RF cohens kappa score: 0.607 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 3, 5 GB f1 score: 0.667 GB cohens kappa score: 0.658 -> test with 'KNN' KNN tn, fp: 282, 6 KNN fn, tp: 0, 8 KNN f1 score: 0.727 KNN cohens kappa score: 0.718 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 22s - loss: 0.0151 41/116 [=========>....................] - ETA: 0s - loss: 0.0494  80/116 [===================>..........] - ETA: 0s - loss: 0.0434 116/116 [==============================] - 0s 1ms/step - loss: 0.0407 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0210 41/116 [=========>....................] - ETA: 0s - loss: 0.0285 80/116 [===================>..........] - ETA: 0s - loss: 0.0377 116/116 [==============================] - 0s 1ms/step - loss: 0.0421 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0130 40/116 [=========>....................] - ETA: 0s - loss: 0.0391 79/116 [===================>..........] - ETA: 0s - loss: 0.0385 116/116 [==============================] - 0s 1ms/step - loss: 0.0398 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0060 39/116 [=========>....................] - ETA: 0s - loss: 0.0580 79/116 [===================>..........] - ETA: 0s - loss: 0.0480 116/116 [==============================] - 0s 1ms/step - loss: 0.0413 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0242 40/116 [=========>....................] - ETA: 0s - loss: 0.0221 79/116 [===================>..........] - ETA: 0s - loss: 0.0372 116/116 [==============================] - 0s 1ms/step - loss: 0.0411 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0110 40/116 [=========>....................] - ETA: 0s - loss: 0.0365 80/116 [===================>..........] - ETA: 0s - loss: 0.0403 116/116 [==============================] - 0s 1ms/step - loss: 0.0406 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0067 41/116 [=========>....................] - ETA: 0s - loss: 0.0468 79/116 [===================>..........] - ETA: 0s - loss: 0.0388 116/116 [==============================] - 0s 1ms/step - loss: 0.0399 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0066 41/116 [=========>....................] - ETA: 0s - loss: 0.0330 80/116 [===================>..........] - ETA: 0s - loss: 0.0316 116/116 [==============================] - 0s 1ms/step - loss: 0.0389 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0223 40/116 [=========>....................] - ETA: 0s - loss: 0.0523 76/116 [==================>...........] - ETA: 0s - loss: 0.0423 116/116 [==============================] - 0s 1ms/step - loss: 0.0389 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0049 42/116 [=========>....................] - ETA: 0s - loss: 0.0321 82/116 [====================>.........] - ETA: 0s - loss: 0.0449 116/116 [==============================] - 0s 1ms/step - loss: 0.0411 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 1, 8 GAN f1 score: 0.615 GAN cohens kappa score: 0.600 -> test with 'LR' LR tn, fp: 274, 14 LR fn, tp: 0, 9 LR f1 score: 0.562 LR cohens kappa score: 0.543 LR average precision score: 0.657 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 3, 6 RF f1 score: 0.706 RF cohens kappa score: 0.697 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 2, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 274, 14 KNN fn, tp: 0, 9 KNN f1 score: 0.562 KNN cohens kappa score: 0.543 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0024 41/116 [=========>....................] - ETA: 0s - loss: 0.0309  82/116 [====================>.........] - ETA: 0s - loss: 0.0309 116/116 [==============================] - 0s 1ms/step - loss: 0.0347 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0067 40/116 [=========>....................] - ETA: 0s - loss: 0.0402 79/116 [===================>..........] - ETA: 0s - loss: 0.0393 116/116 [==============================] - 0s 1ms/step - loss: 0.0346 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0050 41/116 [=========>....................] - ETA: 0s - loss: 0.0377 82/116 [====================>.........] - ETA: 0s - loss: 0.0397 116/116 [==============================] - 0s 1ms/step - loss: 0.0346 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0023 38/116 [========>.....................] - ETA: 0s - loss: 0.0281 76/116 [==================>...........] - ETA: 0s - loss: 0.0379 116/116 [==============================] - ETA: 0s - loss: 0.0364 116/116 [==============================] - 0s 1ms/step - loss: 0.0364 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0030 39/116 [=========>....................] - ETA: 0s - loss: 0.0222 79/116 [===================>..........] - ETA: 0s - loss: 0.0242 115/116 [============================>.] - ETA: 0s - loss: 0.0326 116/116 [==============================] - 0s 1ms/step - loss: 0.0326 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0183 42/116 [=========>....................] - ETA: 0s - loss: 0.0387 82/116 [====================>.........] - ETA: 0s - loss: 0.0315 116/116 [==============================] - 0s 1ms/step - loss: 0.0339 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2287 40/116 [=========>....................] - ETA: 0s - loss: 0.0240 78/116 [===================>..........] - ETA: 0s - loss: 0.0328 116/116 [==============================] - 0s 1ms/step - loss: 0.0308 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2919 35/116 [========>.....................] - ETA: 0s - loss: 0.0447 71/116 [=================>............] - ETA: 0s - loss: 0.0370 111/116 [===========================>..] - ETA: 0s - loss: 0.0324 116/116 [==============================] - 0s 1ms/step - loss: 0.0318 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0063 40/116 [=========>....................] - ETA: 0s - loss: 0.0222 80/116 [===================>..........] - ETA: 0s - loss: 0.0315 116/116 [==============================] - 0s 1ms/step - loss: 0.0316 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0061 40/116 [=========>....................] - ETA: 0s - loss: 0.0335 79/116 [===================>..........] - ETA: 0s - loss: 0.0317 116/116 [==============================] - 0s 1ms/step - loss: 0.0307 -> test with GAN.predict GAN tn, fp: 281, 7 GAN fn, tp: 2, 7 GAN f1 score: 0.609 GAN cohens kappa score: 0.594 -> test with 'LR' LR tn, fp: 278, 10 LR fn, tp: 0, 9 LR f1 score: 0.643 LR cohens kappa score: 0.628 LR average precision score: 0.684 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 2, 7 RF f1 score: 0.778 RF cohens kappa score: 0.771 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 2, 7 GB f1 score: 0.700 GB cohens kappa score: 0.690 -> test with 'KNN' KNN tn, fp: 278, 10 KNN fn, tp: 1, 8 KNN f1 score: 0.593 KNN cohens kappa score: 0.575 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0055 34/116 [=======>......................] - ETA: 0s - loss: 0.0555  70/116 [=================>............] - ETA: 0s - loss: 0.0444 107/116 [==========================>...] - ETA: 0s - loss: 0.0519 116/116 [==============================] - 0s 1ms/step - loss: 0.0522 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2861 39/116 [=========>....................] - ETA: 0s - loss: 0.0396 75/116 [==================>...........] - ETA: 0s - loss: 0.0445 103/116 [=========================>....] - ETA: 0s - loss: 0.0488 116/116 [==============================] - 0s 2ms/step - loss: 0.0502 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0219 32/116 [=======>......................] - ETA: 0s - loss: 0.0235 68/116 [================>.............] - ETA: 0s - loss: 0.0500 103/116 [=========================>....] - ETA: 0s - loss: 0.0468 116/116 [==============================] - 0s 1ms/step - loss: 0.0489 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2242 32/116 [=======>......................] - ETA: 0s - loss: 0.0550 69/116 [================>.............] - ETA: 0s - loss: 0.0542 102/116 [=========================>....] - ETA: 0s - loss: 0.0489 116/116 [==============================] - 0s 1ms/step - loss: 0.0489 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1535 35/116 [========>.....................] - ETA: 0s - loss: 0.0583 68/116 [================>.............] - ETA: 0s - loss: 0.0531 103/116 [=========================>....] - ETA: 0s - loss: 0.0520 116/116 [==============================] - 0s 2ms/step - loss: 0.0499 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0070 39/116 [=========>....................] - ETA: 0s - loss: 0.0414 77/116 [==================>...........] - ETA: 0s - loss: 0.0454 116/116 [==============================] - ETA: 0s - loss: 0.0474 116/116 [==============================] - 0s 1ms/step - loss: 0.0474 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0036 38/116 [========>.....................] - ETA: 0s - loss: 0.0595 73/116 [=================>............] - ETA: 0s - loss: 0.0518 105/116 [==========================>...] - ETA: 0s - loss: 0.0495 116/116 [==============================] - 0s 1ms/step - loss: 0.0471 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0622 38/116 [========>.....................] - ETA: 0s - loss: 0.0439 75/116 [==================>...........] - ETA: 0s - loss: 0.0555 110/116 [===========================>..] - ETA: 0s - loss: 0.0492 116/116 [==============================] - 0s 1ms/step - loss: 0.0483 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0687 36/116 [========>.....................] - ETA: 0s - loss: 0.0399 71/116 [=================>............] - ETA: 0s - loss: 0.0502 110/116 [===========================>..] - ETA: 0s - loss: 0.0477 116/116 [==============================] - 0s 1ms/step - loss: 0.0466 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0041 36/116 [========>.....................] - ETA: 0s - loss: 0.0482 70/116 [=================>............] - ETA: 0s - loss: 0.0525 107/116 [==========================>...] - ETA: 0s - loss: 0.0489 116/116 [==============================] - 0s 1ms/step - loss: 0.0471 -> test with GAN.predict GAN tn, fp: 286, 2 GAN fn, tp: 3, 6 GAN f1 score: 0.706 GAN cohens kappa score: 0.697 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 1, 8 LR f1 score: 0.667 LR cohens kappa score: 0.654 LR average precision score: 0.807 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 1, 8 RF f1 score: 0.941 RF cohens kappa score: 0.939 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 2, 7 GB f1 score: 0.824 GB cohens kappa score: 0.818 -> test with 'KNN' KNN tn, fp: 283, 5 KNN fn, tp: 1, 8 KNN f1 score: 0.727 KNN cohens kappa score: 0.717 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0368 39/116 [=========>....................] - ETA: 0s - loss: 0.0361  79/116 [===================>..........] - ETA: 0s - loss: 0.0330 116/116 [==============================] - 0s 1ms/step - loss: 0.0355 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0157 41/116 [=========>....................] - ETA: 0s - loss: 0.0415 79/116 [===================>..........] - ETA: 0s - loss: 0.0348 116/116 [==============================] - ETA: 0s - loss: 0.0348 116/116 [==============================] - 0s 1ms/step - loss: 0.0348 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0029 35/116 [========>.....................] - ETA: 0s - loss: 0.0429 69/116 [================>.............] - ETA: 0s - loss: 0.0394 103/116 [=========================>....] - ETA: 0s - loss: 0.0398 116/116 [==============================] - 0s 1ms/step - loss: 0.0399 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0061 35/116 [========>.....................] - ETA: 0s - loss: 0.0463 71/116 [=================>............] - ETA: 0s - loss: 0.0381 106/116 [==========================>...] - ETA: 0s - loss: 0.0346 116/116 [==============================] - 0s 1ms/step - loss: 0.0351 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0329 35/116 [========>.....................] - ETA: 0s - loss: 0.0274 71/116 [=================>............] - ETA: 0s - loss: 0.0390 110/116 [===========================>..] - ETA: 0s - loss: 0.0347 116/116 [==============================] - 0s 1ms/step - loss: 0.0336 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0194 35/116 [========>.....................] - ETA: 0s - loss: 0.0231 69/116 [================>.............] - ETA: 0s - loss: 0.0399 103/116 [=========================>....] - ETA: 0s - loss: 0.0336 116/116 [==============================] - 0s 1ms/step - loss: 0.0333 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0019 41/116 [=========>....................] - ETA: 0s - loss: 0.0400 81/116 [===================>..........] - ETA: 0s - loss: 0.0357 116/116 [==============================] - ETA: 0s - loss: 0.0325 116/116 [==============================] - 0s 1ms/step - loss: 0.0325 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0027 40/116 [=========>....................] - ETA: 0s - loss: 0.0342 77/116 [==================>...........] - ETA: 0s - loss: 0.0375 115/116 [============================>.] - ETA: 0s - loss: 0.0340 116/116 [==============================] - 0s 1ms/step - loss: 0.0342 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0144 38/116 [========>.....................] - ETA: 0s - loss: 0.0312 77/116 [==================>...........] - ETA: 0s - loss: 0.0366 115/116 [============================>.] - ETA: 0s - loss: 0.0330 116/116 [==============================] - 0s 1ms/step - loss: 0.0330 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0034 39/116 [=========>....................] - ETA: 0s - loss: 0.0212 77/116 [==================>...........] - ETA: 0s - loss: 0.0285 116/116 [==============================] - ETA: 0s - loss: 0.0326 116/116 [==============================] - 0s 1ms/step - loss: 0.0326 -> test with GAN.predict GAN tn, fp: 286, 2 GAN fn, tp: 2, 7 GAN f1 score: 0.778 GAN cohens kappa score: 0.771 -> test with 'LR' LR tn, fp: 282, 6 LR fn, tp: 0, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.738 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 4, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 5, 4 GB f1 score: 0.571 GB cohens kappa score: 0.562 -> test with 'KNN' KNN tn, fp: 283, 5 KNN fn, tp: 1, 8 KNN f1 score: 0.727 KNN cohens kappa score: 0.717 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.1720 33/116 [=======>......................] - ETA: 0s - loss: 0.0417  65/116 [===============>..............] - ETA: 0s - loss: 0.0414 96/116 [=======================>......] - ETA: 0s - loss: 0.0410 116/116 [==============================] - 0s 2ms/step - loss: 0.0441 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0113 34/116 [=======>......................] - ETA: 0s - loss: 0.0237 71/116 [=================>............] - ETA: 0s - loss: 0.0356 104/116 [=========================>....] - ETA: 0s - loss: 0.0417 116/116 [==============================] - 0s 2ms/step - loss: 0.0441 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0023 35/116 [========>.....................] - ETA: 0s - loss: 0.0413 71/116 [=================>............] - ETA: 0s - loss: 0.0495 104/116 [=========================>....] - ETA: 0s - loss: 0.0460 116/116 [==============================] - 0s 1ms/step - loss: 0.0439 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0057 35/116 [========>.....................] - ETA: 0s - loss: 0.0302 71/116 [=================>............] - ETA: 0s - loss: 0.0265 108/116 [==========================>...] - ETA: 0s - loss: 0.0405 116/116 [==============================] - 0s 1ms/step - loss: 0.0422 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0649 37/116 [========>.....................] - ETA: 0s - loss: 0.0347 70/116 [=================>............] - ETA: 0s - loss: 0.0404 105/116 [==========================>...] - ETA: 0s - loss: 0.0455 116/116 [==============================] - 0s 1ms/step - loss: 0.0443 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0365 33/116 [=======>......................] - ETA: 0s - loss: 0.0430 67/116 [================>.............] - ETA: 0s - loss: 0.0392 101/116 [=========================>....] - ETA: 0s - loss: 0.0455 116/116 [==============================] - 0s 2ms/step - loss: 0.0432 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0177 30/116 [======>.......................] - ETA: 0s - loss: 0.0359 64/116 [===============>..............] - ETA: 0s - loss: 0.0354 103/116 [=========================>....] - ETA: 0s - loss: 0.0336 116/116 [==============================] - 0s 1ms/step - loss: 0.0423 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0060 37/116 [========>.....................] - ETA: 0s - loss: 0.0495 73/116 [=================>............] - ETA: 0s - loss: 0.0451 110/116 [===========================>..] - ETA: 0s - loss: 0.0438 116/116 [==============================] - 0s 1ms/step - loss: 0.0423 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0088 36/116 [========>.....................] - ETA: 0s - loss: 0.0366 72/116 [=================>............] - ETA: 0s - loss: 0.0417 109/116 [===========================>..] - ETA: 0s - loss: 0.0426 116/116 [==============================] - 0s 1ms/step - loss: 0.0434 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0657 37/116 [========>.....................] - ETA: 0s - loss: 0.0386 72/116 [=================>............] - ETA: 0s - loss: 0.0334 108/116 [==========================>...] - ETA: 0s - loss: 0.0380 116/116 [==============================] - 0s 1ms/step - loss: 0.0421 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 1, 7 GAN f1 score: 0.583 GAN cohens kappa score: 0.568 -> test with 'LR' LR tn, fp: 275, 13 LR fn, tp: 0, 8 LR f1 score: 0.552 LR cohens kappa score: 0.533 LR average precision score: 0.397 -> test with 'RF' RF tn, fp: 283, 5 RF fn, tp: 1, 7 RF f1 score: 0.700 RF cohens kappa score: 0.690 -> test with 'GB' GB tn, fp: 283, 5 GB fn, tp: 1, 7 GB f1 score: 0.700 GB cohens kappa score: 0.690 -> test with 'KNN' KNN tn, fp: 277, 11 KNN fn, tp: 0, 8 KNN f1 score: 0.593 KNN cohens kappa score: 0.576 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0046 36/116 [========>.....................] - ETA: 0s - loss: 0.0356  64/116 [===============>..............] - ETA: 0s - loss: 0.0424 104/116 [=========================>....] - ETA: 0s - loss: 0.0345 116/116 [==============================] - 0s 1ms/step - loss: 0.0386 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1186 41/116 [=========>....................] - ETA: 0s - loss: 0.0214 81/116 [===================>..........] - ETA: 0s - loss: 0.0332 116/116 [==============================] - 0s 1ms/step - loss: 0.0379 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1453 42/116 [=========>....................] - ETA: 0s - loss: 0.0404 82/116 [====================>.........] - ETA: 0s - loss: 0.0339 116/116 [==============================] - 0s 1ms/step - loss: 0.0376 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0255 40/116 [=========>....................] - ETA: 0s - loss: 0.0333 81/116 [===================>..........] - ETA: 0s - loss: 0.0312 116/116 [==============================] - 0s 1ms/step - loss: 0.0356 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0094 41/116 [=========>....................] - ETA: 0s - loss: 0.0344 78/116 [===================>..........] - ETA: 0s - loss: 0.0331 116/116 [==============================] - 0s 1ms/step - loss: 0.0364 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0093 41/116 [=========>....................] - ETA: 0s - loss: 0.0380 81/116 [===================>..........] - ETA: 0s - loss: 0.0330 116/116 [==============================] - 0s 1ms/step - loss: 0.0367 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0120 41/116 [=========>....................] - ETA: 0s - loss: 0.0333 79/116 [===================>..........] - ETA: 0s - loss: 0.0314 116/116 [==============================] - 0s 1ms/step - loss: 0.0341 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0045 40/116 [=========>....................] - ETA: 0s - loss: 0.0305 80/116 [===================>..........] - ETA: 0s - loss: 0.0370 116/116 [==============================] - 0s 1ms/step - loss: 0.0340 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0069 42/116 [=========>....................] - ETA: 0s - loss: 0.0220 83/116 [====================>.........] - ETA: 0s - loss: 0.0310 116/116 [==============================] - 0s 1ms/step - loss: 0.0342 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0957 41/116 [=========>....................] - ETA: 0s - loss: 0.0361 82/116 [====================>.........] - ETA: 0s - loss: 0.0333 116/116 [==============================] - 0s 1ms/step - loss: 0.0345 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 1, 8 GAN f1 score: 0.727 GAN cohens kappa score: 0.717 -> test with 'LR' LR tn, fp: 275, 13 LR fn, tp: 1, 8 LR f1 score: 0.533 LR cohens kappa score: 0.513 LR average precision score: 0.742 -> test with 'RF' RF tn, fp: 284, 4 RF fn, tp: 1, 8 RF f1 score: 0.762 RF cohens kappa score: 0.753 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 1, 8 GB f1 score: 0.762 GB cohens kappa score: 0.753 -> test with 'KNN' KNN tn, fp: 276, 12 KNN fn, tp: 0, 9 KNN f1 score: 0.600 KNN cohens kappa score: 0.582 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.1755 42/116 [=========>....................] - ETA: 0s - loss: 0.0498  80/116 [===================>..........] - ETA: 0s - loss: 0.0487 116/116 [==============================] - 0s 1ms/step - loss: 0.0448 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0106 41/116 [=========>....................] - ETA: 0s - loss: 0.0467 81/116 [===================>..........] - ETA: 0s - loss: 0.0452 116/116 [==============================] - 0s 1ms/step - loss: 0.0437 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2326 40/116 [=========>....................] - ETA: 0s - loss: 0.0526 77/116 [==================>...........] - ETA: 0s - loss: 0.0446 115/116 [============================>.] - ETA: 0s - loss: 0.0419 116/116 [==============================] - 0s 1ms/step - loss: 0.0418 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0155 39/116 [=========>....................] - ETA: 0s - loss: 0.0404 78/116 [===================>..........] - ETA: 0s - loss: 0.0446 116/116 [==============================] - 0s 1ms/step - loss: 0.0415 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0258 39/116 [=========>....................] - ETA: 0s - loss: 0.0514 77/116 [==================>...........] - ETA: 0s - loss: 0.0429 116/116 [==============================] - 0s 1ms/step - loss: 0.0422 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0222 39/116 [=========>....................] - ETA: 0s - loss: 0.0375 78/116 [===================>..........] - ETA: 0s - loss: 0.0429 116/116 [==============================] - 0s 1ms/step - loss: 0.0403 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0039 38/116 [========>.....................] - ETA: 0s - loss: 0.0222 74/116 [==================>...........] - ETA: 0s - loss: 0.0328 109/116 [===========================>..] - ETA: 0s - loss: 0.0415 116/116 [==============================] - 0s 1ms/step - loss: 0.0414 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0068 41/116 [=========>....................] - ETA: 0s - loss: 0.0576 81/116 [===================>..........] - ETA: 0s - loss: 0.0484 116/116 [==============================] - 0s 1ms/step - loss: 0.0420 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0095 40/116 [=========>....................] - ETA: 0s - loss: 0.0406 79/116 [===================>..........] - ETA: 0s - loss: 0.0469 116/116 [==============================] - 0s 1ms/step - loss: 0.0433 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0218 40/116 [=========>....................] - ETA: 0s - loss: 0.0272 79/116 [===================>..........] - ETA: 0s - loss: 0.0419 113/116 [============================>.] - ETA: 0s - loss: 0.0411 116/116 [==============================] - 0s 1ms/step - loss: 0.0406 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 2, 7 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 274, 14 LR fn, tp: 1, 8 LR f1 score: 0.516 LR cohens kappa score: 0.494 LR average precision score: 0.608 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 2, 7 RF f1 score: 0.824 RF cohens kappa score: 0.818 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 2, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 281, 7 KNN fn, tp: 0, 9 KNN f1 score: 0.720 KNN cohens kappa score: 0.709 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0407 42/116 [=========>....................] - ETA: 0s - loss: 0.0317  81/116 [===================>..........] - ETA: 0s - loss: 0.0250 116/116 [==============================] - 0s 1ms/step - loss: 0.0307 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0885 41/116 [=========>....................] - ETA: 0s - loss: 0.0269 80/116 [===================>..........] - ETA: 0s - loss: 0.0285 116/116 [==============================] - 0s 1ms/step - loss: 0.0306 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0384 42/116 [=========>....................] - ETA: 0s - loss: 0.0257 82/116 [====================>.........] - ETA: 0s - loss: 0.0311 116/116 [==============================] - 0s 1ms/step - loss: 0.0290 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0136 40/116 [=========>....................] - ETA: 0s - loss: 0.0292 80/116 [===================>..........] - ETA: 0s - loss: 0.0278 116/116 [==============================] - 0s 1ms/step - loss: 0.0294 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0094 41/116 [=========>....................] - ETA: 0s - loss: 0.0298 81/116 [===================>..........] - ETA: 0s - loss: 0.0263 116/116 [==============================] - 0s 1ms/step - loss: 0.0306 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0419 37/116 [========>.....................] - ETA: 0s - loss: 0.0325 73/116 [=================>............] - ETA: 0s - loss: 0.0265 114/116 [============================>.] - ETA: 0s - loss: 0.0300 116/116 [==============================] - 0s 1ms/step - loss: 0.0298 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0619 41/116 [=========>....................] - ETA: 0s - loss: 0.0348 80/116 [===================>..........] - ETA: 0s - loss: 0.0280 116/116 [==============================] - 0s 1ms/step - loss: 0.0286 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0073 38/116 [========>.....................] - ETA: 0s - loss: 0.0310 79/116 [===================>..........] - ETA: 0s - loss: 0.0327 116/116 [==============================] - 0s 1ms/step - loss: 0.0278 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0097 41/116 [=========>....................] - ETA: 0s - loss: 0.0203 81/116 [===================>..........] - ETA: 0s - loss: 0.0241 116/116 [==============================] - 0s 1ms/step - loss: 0.0306 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0387 40/116 [=========>....................] - ETA: 0s - loss: 0.0366 79/116 [===================>..........] - ETA: 0s - loss: 0.0305 116/116 [==============================] - 0s 1ms/step - loss: 0.0286 -> test with GAN.predict GAN tn, fp: 281, 7 GAN fn, tp: 4, 5 GAN f1 score: 0.476 GAN cohens kappa score: 0.457 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 2, 7 LR f1 score: 0.609 LR cohens kappa score: 0.594 LR average precision score: 0.721 -> test with 'RF' RF tn, fp: 283, 5 RF fn, tp: 4, 5 RF f1 score: 0.526 RF cohens kappa score: 0.511 -> test with 'GB' GB tn, fp: 283, 5 GB fn, tp: 4, 5 GB f1 score: 0.526 GB cohens kappa score: 0.511 -> test with 'KNN' KNN tn, fp: 279, 9 KNN fn, tp: 2, 7 KNN f1 score: 0.560 KNN cohens kappa score: 0.542 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0173 37/116 [========>.....................] - ETA: 0s - loss: 0.0446  71/116 [=================>............] - ETA: 0s - loss: 0.0340 104/116 [=========================>....] - ETA: 0s - loss: 0.0330 116/116 [==============================] - 0s 1ms/step - loss: 0.0328 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0326 34/116 [=======>......................] - ETA: 0s - loss: 0.0175 68/116 [================>.............] - ETA: 0s - loss: 0.0270 102/116 [=========================>....] - ETA: 0s - loss: 0.0374 116/116 [==============================] - 0s 2ms/step - loss: 0.0359 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0042 26/116 [=====>........................] - ETA: 0s - loss: 0.0427 54/116 [============>.................] - ETA: 0s - loss: 0.0437 89/116 [======================>.......] - ETA: 0s - loss: 0.0354 116/116 [==============================] - 0s 2ms/step - loss: 0.0341 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0191 35/116 [========>.....................] - ETA: 0s - loss: 0.0432 68/116 [================>.............] - ETA: 0s - loss: 0.0331 103/116 [=========================>....] - ETA: 0s - loss: 0.0364 116/116 [==============================] - 0s 1ms/step - loss: 0.0347 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0054 38/116 [========>.....................] - ETA: 0s - loss: 0.0286 73/116 [=================>............] - ETA: 0s - loss: 0.0287 104/116 [=========================>....] - ETA: 0s - loss: 0.0358 116/116 [==============================] - 0s 2ms/step - loss: 0.0346 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 8.6572e-04 36/116 [========>.....................] - ETA: 0s - loss: 0.0414  70/116 [=================>............] - ETA: 0s - loss: 0.0379 105/116 [==========================>...] - ETA: 0s - loss: 0.0345 116/116 [==============================] - 0s 1ms/step - loss: 0.0340 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0131 34/116 [=======>......................] - ETA: 0s - loss: 0.0237 68/116 [================>.............] - ETA: 0s - loss: 0.0313 102/116 [=========================>....] - ETA: 0s - loss: 0.0365 116/116 [==============================] - 0s 1ms/step - loss: 0.0340 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0049 37/116 [========>.....................] - ETA: 0s - loss: 0.0270 73/116 [=================>............] - ETA: 0s - loss: 0.0345 110/116 [===========================>..] - ETA: 0s - loss: 0.0337 116/116 [==============================] - 0s 1ms/step - loss: 0.0347 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0121 37/116 [========>.....................] - ETA: 0s - loss: 0.0152 72/116 [=================>............] - ETA: 0s - loss: 0.0291 111/116 [===========================>..] - ETA: 0s - loss: 0.0344 116/116 [==============================] - 0s 1ms/step - loss: 0.0341 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0138 31/116 [=======>......................] - ETA: 0s - loss: 0.0231 66/116 [================>.............] - ETA: 0s - loss: 0.0392 102/116 [=========================>....] - ETA: 0s - loss: 0.0352 116/116 [==============================] - 0s 2ms/step - loss: 0.0328 -> test with GAN.predict GAN tn, fp: 287, 1 GAN fn, tp: 3, 6 GAN f1 score: 0.750 GAN cohens kappa score: 0.743 -> test with 'LR' LR tn, fp: 282, 6 LR fn, tp: 0, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.676 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 5, 4 RF f1 score: 0.615 RF cohens kappa score: 0.608 -> test with 'GB' GB tn, fp: 288, 0 GB fn, tp: 3, 6 GB f1 score: 0.800 GB cohens kappa score: 0.795 -> test with 'KNN' KNN tn, fp: 283, 5 KNN fn, tp: 1, 8 KNN f1 score: 0.727 KNN cohens kappa score: 0.717 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.0355 42/116 [=========>....................] - ETA: 0s - loss: 0.0517  82/116 [====================>.........] - ETA: 0s - loss: 0.0520 116/116 [==============================] - 0s 1ms/step - loss: 0.0500 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1493 42/116 [=========>....................] - ETA: 0s - loss: 0.0454 81/116 [===================>..........] - ETA: 0s - loss: 0.0556 116/116 [==============================] - 0s 1ms/step - loss: 0.0484 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0029 42/116 [=========>....................] - ETA: 0s - loss: 0.0530 83/116 [====================>.........] - ETA: 0s - loss: 0.0443 116/116 [==============================] - 0s 1ms/step - loss: 0.0464 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0187 42/116 [=========>....................] - ETA: 0s - loss: 0.0398 83/116 [====================>.........] - ETA: 0s - loss: 0.0458 116/116 [==============================] - 0s 1ms/step - loss: 0.0475 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0196 40/116 [=========>....................] - ETA: 0s - loss: 0.0412 80/116 [===================>..........] - ETA: 0s - loss: 0.0477 116/116 [==============================] - 0s 1ms/step - loss: 0.0488 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0100 41/116 [=========>....................] - ETA: 0s - loss: 0.0580 81/116 [===================>..........] - ETA: 0s - loss: 0.0488 116/116 [==============================] - 0s 1ms/step - loss: 0.0482 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0084 41/116 [=========>....................] - ETA: 0s - loss: 0.0634 82/116 [====================>.........] - ETA: 0s - loss: 0.0511 116/116 [==============================] - 0s 1ms/step - loss: 0.0441 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0071 40/116 [=========>....................] - ETA: 0s - loss: 0.0559 80/116 [===================>..........] - ETA: 0s - loss: 0.0528 116/116 [==============================] - 0s 1ms/step - loss: 0.0491 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0028 42/116 [=========>....................] - ETA: 0s - loss: 0.0495 84/116 [====================>.........] - ETA: 0s - loss: 0.0482 116/116 [==============================] - 0s 1ms/step - loss: 0.0454 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1459 41/116 [=========>....................] - ETA: 0s - loss: 0.0456 82/116 [====================>.........] - ETA: 0s - loss: 0.0484 116/116 [==============================] - 0s 1ms/step - loss: 0.0447 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 0, 8 GAN f1 score: 0.762 GAN cohens kappa score: 0.754 -> test with 'LR' LR tn, fp: 278, 10 LR fn, tp: 0, 8 LR f1 score: 0.615 LR cohens kappa score: 0.600 LR average precision score: 0.773 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 1, 7 RF f1 score: 0.875 RF cohens kappa score: 0.872 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 1, 7 GB f1 score: 0.824 GB cohens kappa score: 0.818 -> test with 'KNN' KNN tn, fp: 276, 12 KNN fn, tp: 0, 8 KNN f1 score: 0.571 KNN cohens kappa score: 0.554 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.1756 41/116 [=========>....................] - ETA: 0s - loss: 0.0599  81/116 [===================>..........] - ETA: 0s - loss: 0.0484 116/116 [==============================] - 0s 1ms/step - loss: 0.0406 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2316 42/116 [=========>....................] - ETA: 0s - loss: 0.0322 80/116 [===================>..........] - ETA: 0s - loss: 0.0435 116/116 [==============================] - 0s 1ms/step - loss: 0.0412 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0299 42/116 [=========>....................] - ETA: 0s - loss: 0.0310 82/116 [====================>.........] - ETA: 0s - loss: 0.0334 116/116 [==============================] - 0s 1ms/step - loss: 0.0410 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0043 41/116 [=========>....................] - ETA: 0s - loss: 0.0591 81/116 [===================>..........] - ETA: 0s - loss: 0.0452 115/116 [============================>.] - ETA: 0s - loss: 0.0404 116/116 [==============================] - 0s 1ms/step - loss: 0.0403 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0036 40/116 [=========>....................] - ETA: 0s - loss: 0.0255 79/116 [===================>..........] - ETA: 0s - loss: 0.0371 116/116 [==============================] - 0s 1ms/step - loss: 0.0404 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0038 40/116 [=========>....................] - ETA: 0s - loss: 0.0481 80/116 [===================>..........] - ETA: 0s - loss: 0.0405 116/116 [==============================] - 0s 1ms/step - loss: 0.0412 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0239 42/116 [=========>....................] - ETA: 0s - loss: 0.0254 79/116 [===================>..........] - ETA: 0s - loss: 0.0357 116/116 [==============================] - 0s 1ms/step - loss: 0.0388 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0215 38/116 [========>.....................] - ETA: 0s - loss: 0.0579 76/116 [==================>...........] - ETA: 0s - loss: 0.0425 116/116 [==============================] - ETA: 0s - loss: 0.0420 116/116 [==============================] - 0s 1ms/step - loss: 0.0420 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0122 41/116 [=========>....................] - ETA: 0s - loss: 0.0195 79/116 [===================>..........] - ETA: 0s - loss: 0.0399 111/116 [===========================>..] - ETA: 0s - loss: 0.0394 116/116 [==============================] - 0s 1ms/step - loss: 0.0401 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0091 35/116 [========>.....................] - ETA: 0s - loss: 0.0493 72/116 [=================>............] - ETA: 0s - loss: 0.0386 111/116 [===========================>..] - ETA: 0s - loss: 0.0349 116/116 [==============================] - 0s 1ms/step - loss: 0.0380 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 0, 9 GAN f1 score: 0.643 GAN cohens kappa score: 0.628 -> test with 'LR' LR tn, fp: 272, 16 LR fn, tp: 0, 9 LR f1 score: 0.529 LR cohens kappa score: 0.507 LR average precision score: 0.724 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 1, 8 RF f1 score: 0.800 RF cohens kappa score: 0.793 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 1, 8 GB f1 score: 0.762 GB cohens kappa score: 0.753 -> test with 'KNN' KNN tn, fp: 271, 17 KNN fn, tp: 0, 9 KNN f1 score: 0.514 KNN cohens kappa score: 0.491 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 24s - loss: 0.0087 40/116 [=========>....................] - ETA: 0s - loss: 0.0304  78/116 [===================>..........] - ETA: 0s - loss: 0.0377 112/116 [===========================>..] - ETA: 0s - loss: 0.0370 116/116 [==============================] - 0s 1ms/step - loss: 0.0360 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1759 30/116 [======>.......................] - ETA: 0s - loss: 0.0270 62/116 [===============>..............] - ETA: 0s - loss: 0.0320 95/116 [=======================>......] - ETA: 0s - loss: 0.0315 116/116 [==============================] - 0s 2ms/step - loss: 0.0349 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0032 32/116 [=======>......................] - ETA: 0s - loss: 0.0175 69/116 [================>.............] - ETA: 0s - loss: 0.0352 106/116 [==========================>...] - ETA: 0s - loss: 0.0367 116/116 [==============================] - 0s 1ms/step - loss: 0.0345 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0741 37/116 [========>.....................] - ETA: 0s - loss: 0.0409 74/116 [==================>...........] - ETA: 0s - loss: 0.0344 108/116 [==========================>...] - ETA: 0s - loss: 0.0369 116/116 [==============================] - 0s 1ms/step - loss: 0.0358 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0046 38/116 [========>.....................] - ETA: 0s - loss: 0.0390 70/116 [=================>............] - ETA: 0s - loss: 0.0395 101/116 [=========================>....] - ETA: 0s - loss: 0.0334 116/116 [==============================] - 0s 2ms/step - loss: 0.0353 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0170 40/116 [=========>....................] - ETA: 0s - loss: 0.0287 78/116 [===================>..........] - ETA: 0s - loss: 0.0305 115/116 [============================>.] - ETA: 0s - loss: 0.0337 116/116 [==============================] - 0s 1ms/step - loss: 0.0337 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0083 38/116 [========>.....................] - ETA: 0s - loss: 0.0413 74/116 [==================>...........] - ETA: 0s - loss: 0.0359 109/116 [===========================>..] - ETA: 0s - loss: 0.0336 116/116 [==============================] - 0s 1ms/step - loss: 0.0333 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0061 36/116 [========>.....................] - ETA: 0s - loss: 0.0332 74/116 [==================>...........] - ETA: 0s - loss: 0.0351 116/116 [==============================] - 0s 1ms/step - loss: 0.0333 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0074 44/116 [==========>...................] - ETA: 0s - loss: 0.0448 85/116 [====================>.........] - ETA: 0s - loss: 0.0348 116/116 [==============================] - 0s 1ms/step - loss: 0.0332 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0829 45/116 [==========>...................] - ETA: 0s - loss: 0.0315 88/116 [=====================>........] - ETA: 0s - loss: 0.0291 116/116 [==============================] - 0s 1ms/step - loss: 0.0319 -> test with GAN.predict GAN tn, fp: 285, 3 GAN fn, tp: 3, 6 GAN f1 score: 0.667 GAN cohens kappa score: 0.656 -> test with 'LR' LR tn, fp: 282, 6 LR fn, tp: 0, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.812 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 4, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 3, 6 GB f1 score: 0.750 GB cohens kappa score: 0.743 -> test with 'KNN' KNN tn, fp: 284, 4 KNN fn, tp: 1, 8 KNN f1 score: 0.762 KNN cohens kappa score: 0.753 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0285 42/116 [=========>....................] - ETA: 0s - loss: 0.0528  82/116 [====================>.........] - ETA: 0s - loss: 0.0518 116/116 [==============================] - 0s 1ms/step - loss: 0.0509 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2353 41/116 [=========>....................] - ETA: 0s - loss: 0.0898 82/116 [====================>.........] - ETA: 0s - loss: 0.0582 116/116 [==============================] - 0s 1ms/step - loss: 0.0534 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1484 41/116 [=========>....................] - ETA: 0s - loss: 0.0352 79/116 [===================>..........] - ETA: 0s - loss: 0.0457 116/116 [==============================] - 0s 1ms/step - loss: 0.0506 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0129 45/116 [==========>...................] - ETA: 0s - loss: 0.0564 85/116 [====================>.........] - ETA: 0s - loss: 0.0495 116/116 [==============================] - 0s 1ms/step - loss: 0.0497 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0481 41/116 [=========>....................] - ETA: 0s - loss: 0.0506 81/116 [===================>..........] - ETA: 0s - loss: 0.0518 116/116 [==============================] - 0s 1ms/step - loss: 0.0507 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0449 40/116 [=========>....................] - ETA: 0s - loss: 0.0458 78/116 [===================>..........] - ETA: 0s - loss: 0.0400 116/116 [==============================] - 0s 1ms/step - loss: 0.0498 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0065 41/116 [=========>....................] - ETA: 0s - loss: 0.0440 80/116 [===================>..........] - ETA: 0s - loss: 0.0492 116/116 [==============================] - 0s 1ms/step - loss: 0.0486 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0066 40/116 [=========>....................] - ETA: 0s - loss: 0.0461 81/116 [===================>..........] - ETA: 0s - loss: 0.0455 116/116 [==============================] - 0s 1ms/step - loss: 0.0503 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0357 39/116 [=========>....................] - ETA: 0s - loss: 0.0582 78/116 [===================>..........] - ETA: 0s - loss: 0.0488 116/116 [==============================] - 0s 1ms/step - loss: 0.0487 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0085 42/116 [=========>....................] - ETA: 0s - loss: 0.0496 81/116 [===================>..........] - ETA: 0s - loss: 0.0537 116/116 [==============================] - 0s 1ms/step - loss: 0.0505 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 0, 9 GAN f1 score: 0.783 GAN cohens kappa score: 0.774 -> test with 'LR' LR tn, fp: 279, 9 LR fn, tp: 0, 9 LR f1 score: 0.667 LR cohens kappa score: 0.653 LR average precision score: 0.775 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 2, 7 RF f1 score: 0.778 RF cohens kappa score: 0.771 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 1, 8 GB f1 score: 0.889 GB cohens kappa score: 0.885 -> test with 'KNN' KNN tn, fp: 281, 7 KNN fn, tp: 0, 9 KNN f1 score: 0.720 KNN cohens kappa score: 0.709 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1117 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0139 42/116 [=========>....................] - ETA: 0s - loss: 0.0447  82/116 [====================>.........] - ETA: 0s - loss: 0.0336 116/116 [==============================] - 0s 1ms/step - loss: 0.0373 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1829 36/116 [========>.....................] - ETA: 0s - loss: 0.0371 74/116 [==================>...........] - ETA: 0s - loss: 0.0348 112/116 [===========================>..] - ETA: 0s - loss: 0.0360 116/116 [==============================] - 0s 1ms/step - loss: 0.0365 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0032 40/116 [=========>....................] - ETA: 0s - loss: 0.0414 78/116 [===================>..........] - ETA: 0s - loss: 0.0349 116/116 [==============================] - ETA: 0s - loss: 0.0357 116/116 [==============================] - 0s 1ms/step - loss: 0.0357 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0338 40/116 [=========>....................] - ETA: 0s - loss: 0.0404 81/116 [===================>..........] - ETA: 0s - loss: 0.0388 116/116 [==============================] - 0s 1ms/step - loss: 0.0362 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1273 42/116 [=========>....................] - ETA: 0s - loss: 0.0288 82/116 [====================>.........] - ETA: 0s - loss: 0.0384 116/116 [==============================] - 0s 1ms/step - loss: 0.0367 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0127 40/116 [=========>....................] - ETA: 0s - loss: 0.0362 80/116 [===================>..........] - ETA: 0s - loss: 0.0330 116/116 [==============================] - 0s 1ms/step - loss: 0.0355 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0043 41/116 [=========>....................] - ETA: 0s - loss: 0.0377 81/116 [===================>..........] - ETA: 0s - loss: 0.0327 116/116 [==============================] - 0s 1ms/step - loss: 0.0362 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1054 40/116 [=========>....................] - ETA: 0s - loss: 0.0442 81/116 [===================>..........] - ETA: 0s - loss: 0.0347 116/116 [==============================] - 0s 1ms/step - loss: 0.0341 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0413 41/116 [=========>....................] - ETA: 0s - loss: 0.0354 82/116 [====================>.........] - ETA: 0s - loss: 0.0406 116/116 [==============================] - 0s 1ms/step - loss: 0.0354 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1409 41/116 [=========>....................] - ETA: 0s - loss: 0.0501 78/116 [===================>..........] - ETA: 0s - loss: 0.0375 116/116 [==============================] - 0s 1ms/step - loss: 0.0351 -> test with GAN.predict GAN tn, fp: 285, 3 GAN fn, tp: 3, 6 GAN f1 score: 0.667 GAN cohens kappa score: 0.656 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 2, 7 LR f1 score: 0.609 LR cohens kappa score: 0.594 LR average precision score: 0.577 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 4, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 287, 1 GB fn, tp: 3, 6 GB f1 score: 0.750 GB cohens kappa score: 0.743 -> test with 'KNN' KNN tn, fp: 284, 4 KNN fn, tp: 0, 9 KNN f1 score: 0.818 KNN cohens kappa score: 0.811 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1116 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0050 42/116 [=========>....................] - ETA: 0s - loss: 0.0371  83/116 [====================>.........] - ETA: 0s - loss: 0.0402 116/116 [==============================] - 0s 1ms/step - loss: 0.0335 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.3076 42/116 [=========>....................] - ETA: 0s - loss: 0.0248 78/116 [===================>..........] - ETA: 0s - loss: 0.0323 116/116 [==============================] - 0s 1ms/step - loss: 0.0308 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0037 42/116 [=========>....................] - ETA: 0s - loss: 0.0361 82/116 [====================>.........] - ETA: 0s - loss: 0.0299 116/116 [==============================] - 0s 1ms/step - loss: 0.0289 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0200 41/116 [=========>....................] - ETA: 0s - loss: 0.0368 77/116 [==================>...........] - ETA: 0s - loss: 0.0312 116/116 [==============================] - 0s 1ms/step - loss: 0.0302 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0147 42/116 [=========>....................] - ETA: 0s - loss: 0.0336 83/116 [====================>.........] - ETA: 0s - loss: 0.0316 116/116 [==============================] - 0s 1ms/step - loss: 0.0289 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0266 41/116 [=========>....................] - ETA: 0s - loss: 0.0208 82/116 [====================>.........] - ETA: 0s - loss: 0.0275 116/116 [==============================] - 0s 1ms/step - loss: 0.0302 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0038 40/116 [=========>....................] - ETA: 0s - loss: 0.0307 78/116 [===================>..........] - ETA: 0s - loss: 0.0352 116/116 [==============================] - ETA: 0s - loss: 0.0338 116/116 [==============================] - 0s 1ms/step - loss: 0.0338 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2976 41/116 [=========>....................] - ETA: 0s - loss: 0.0474 82/116 [====================>.........] - ETA: 0s - loss: 0.0324 116/116 [==============================] - 0s 1ms/step - loss: 0.0295 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0110 40/116 [=========>....................] - ETA: 0s - loss: 0.0377 80/116 [===================>..........] - ETA: 0s - loss: 0.0320 116/116 [==============================] - 0s 1ms/step - loss: 0.0277 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0021 39/116 [=========>....................] - ETA: 0s - loss: 0.0279 77/116 [==================>...........] - ETA: 0s - loss: 0.0234 116/116 [==============================] - 0s 1ms/step - loss: 0.0274 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 2, 6 GAN f1 score: 0.500 GAN cohens kappa score: 0.481 -> test with 'LR' LR tn, fp: 277, 11 LR fn, tp: 1, 7 LR f1 score: 0.538 LR cohens kappa score: 0.521 LR average precision score: 0.507 -> test with 'RF' RF tn, fp: 284, 4 RF fn, tp: 3, 5 RF f1 score: 0.588 RF cohens kappa score: 0.576 -> test with 'GB' GB tn, fp: 282, 6 GB fn, tp: 3, 5 GB f1 score: 0.526 GB cohens kappa score: 0.511 -> test with 'KNN' KNN tn, fp: 275, 13 KNN fn, tp: 2, 6 KNN f1 score: 0.444 KNN cohens kappa score: 0.422 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 282, 16 LR fn, tp: 2, 9 LR f1 score: 0.750 LR cohens kappa score: 0.740 LR average precision score: 0.897 average: LR tn, fp: 277.92, 10.08 LR fn, tp: 0.48, 8.32 LR f1 score: 0.620 LR cohens kappa score: 0.604 LR average precision score: 0.691 minimum: LR tn, fp: 272, 6 LR fn, tp: 0, 7 LR f1 score: 0.485 LR cohens kappa score: 0.461 LR average precision score: 0.397 -----[ RF ]----- maximum: RF tn, fp: 288, 7 RF fn, tp: 5, 9 RF f1 score: 0.941 RF cohens kappa score: 0.939 average: RF tn, fp: 285.84, 2.16 RF fn, tp: 2.36, 6.44 RF f1 score: 0.738 RF cohens kappa score: 0.730 minimum: RF tn, fp: 281, 0 RF fn, tp: 0, 4 RF f1 score: 0.526 RF cohens kappa score: 0.511 -----[ GB ]----- maximum: GB tn, fp: 288, 8 GB fn, tp: 5, 8 GB f1 score: 0.889 GB cohens kappa score: 0.885 average: GB tn, fp: 285.28, 2.72 GB fn, tp: 2.28, 6.52 GB f1 score: 0.724 GB cohens kappa score: 0.716 minimum: GB tn, fp: 280, 0 GB fn, tp: 1, 4 GB f1 score: 0.455 GB cohens kappa score: 0.434 -----[ KNN ]----- maximum: KNN tn, fp: 286, 17 KNN fn, tp: 2, 9 KNN f1 score: 0.842 KNN cohens kappa score: 0.837 average: KNN tn, fp: 278.88, 9.12 KNN fn, tp: 0.48, 8.32 KNN f1 score: 0.646 KNN cohens kappa score: 0.631 minimum: KNN tn, fp: 271, 2 KNN fn, tp: 0, 6 KNN f1 score: 0.444 KNN cohens kappa score: 0.422 -----[ GAN ]----- maximum: GAN tn, fp: 287, 11 GAN fn, tp: 4, 9 GAN f1 score: 0.783 GAN cohens kappa score: 0.774 average: GAN tn, fp: 281.84, 6.16 GAN fn, tp: 1.64, 7.16 GAN f1 score: 0.652 GAN cohens kappa score: 0.639 minimum: GAN tn, fp: 277, 1 GAN fn, tp: 0, 5 GAN f1 score: 0.462 GAN cohens kappa score: 0.439