/////////////////////////////////////////// // Running convGAN-proximary-5 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: 18s - loss: 0.4827 41/116 [=========>....................] - ETA: 0s - loss: 0.5310  80/116 [===================>..........] - ETA: 0s - loss: 0.4731 113/116 [============================>.] - ETA: 0s - loss: 0.4178 116/116 [==============================] - 0s 1ms/step - loss: 0.4138 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1428 31/116 [=======>......................] - ETA: 0s - loss: 0.2228 67/116 [================>.............] - ETA: 0s - loss: 0.2135 105/116 [==========================>...] - ETA: 0s - loss: 0.1905 116/116 [==============================] - 0s 1ms/step - loss: 0.1863 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1076 39/116 [=========>....................] - ETA: 0s - loss: 0.1550 77/116 [==================>...........] - ETA: 0s - loss: 0.1423 116/116 [==============================] - 0s 1ms/step - loss: 0.1312 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1288 40/116 [=========>....................] - ETA: 0s - loss: 0.1307 79/116 [===================>..........] - ETA: 0s - loss: 0.1155 116/116 [==============================] - 0s 1ms/step - loss: 0.1087 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2291 41/116 [=========>....................] - ETA: 0s - loss: 0.0948 81/116 [===================>..........] - ETA: 0s - loss: 0.1009 116/116 [==============================] - 0s 1ms/step - loss: 0.0974 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0528 41/116 [=========>....................] - ETA: 0s - loss: 0.1063 79/116 [===================>..........] - ETA: 0s - loss: 0.0899 116/116 [==============================] - 0s 1ms/step - loss: 0.0898 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2327 42/116 [=========>....................] - ETA: 0s - loss: 0.0840 82/116 [====================>.........] - ETA: 0s - loss: 0.0889 116/116 [==============================] - 0s 1ms/step - loss: 0.0856 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0081 43/116 [==========>...................] - ETA: 0s - loss: 0.0838 82/116 [====================>.........] - ETA: 0s - loss: 0.0828 116/116 [==============================] - 0s 1ms/step - loss: 0.0818 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2570 40/116 [=========>....................] - ETA: 0s - loss: 0.0931 75/116 [==================>...........] - ETA: 0s - loss: 0.0730 107/116 [==========================>...] - ETA: 0s - loss: 0.0783 116/116 [==============================] - 0s 2ms/step - loss: 0.0775 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0220 31/116 [=======>......................] - ETA: 0s - loss: 0.0768 65/116 [===============>..............] - ETA: 0s - loss: 0.0730 96/116 [=======================>......] - ETA: 0s - loss: 0.0770 116/116 [==============================] - 0s 2ms/step - loss: 0.0756 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 3, 6 GAN f1 score: 0.480 GAN cohens kappa score: 0.459 -> 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: 0.897 -> 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: 287, 1 GB fn, tp: 3, 6 GB f1 score: 0.750 GB cohens kappa score: 0.743 -> 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: 0.5337 42/116 [=========>....................] - ETA: 0s - loss: 0.4231  79/116 [===================>..........] - ETA: 0s - loss: 0.3744 112/116 [===========================>..] - ETA: 0s - loss: 0.3421 116/116 [==============================] - 0s 1ms/step - loss: 0.3408 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.3199 34/116 [=======>......................] - ETA: 0s - loss: 0.1996 75/116 [==================>...........] - ETA: 0s - loss: 0.1782 115/116 [============================>.] - ETA: 0s - loss: 0.1629 116/116 [==============================] - 0s 1ms/step - loss: 0.1627 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0323 41/116 [=========>....................] - ETA: 0s - loss: 0.1232 75/116 [==================>...........] - ETA: 0s - loss: 0.1159 111/116 [===========================>..] - ETA: 0s - loss: 0.1164 116/116 [==============================] - 0s 1ms/step - loss: 0.1147 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1133 39/116 [=========>....................] - ETA: 0s - loss: 0.1133 78/116 [===================>..........] - ETA: 0s - loss: 0.1033 115/116 [============================>.] - ETA: 0s - loss: 0.0990 116/116 [==============================] - 0s 1ms/step - loss: 0.0988 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0459 39/116 [=========>....................] - ETA: 0s - loss: 0.0894 76/116 [==================>...........] - ETA: 0s - loss: 0.0947 115/116 [============================>.] - ETA: 0s - loss: 0.0904 116/116 [==============================] - 0s 1ms/step - loss: 0.0904 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0397 40/116 [=========>....................] - ETA: 0s - loss: 0.0714 79/116 [===================>..........] - ETA: 0s - loss: 0.0821 116/116 [==============================] - 0s 1ms/step - loss: 0.0830 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0761 40/116 [=========>....................] - ETA: 0s - loss: 0.0756 77/116 [==================>...........] - ETA: 0s - loss: 0.0704 116/116 [==============================] - 0s 1ms/step - loss: 0.0783 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0579 41/116 [=========>....................] - ETA: 0s - loss: 0.0781 81/116 [===================>..........] - ETA: 0s - loss: 0.0692 116/116 [==============================] - 0s 1ms/step - loss: 0.0768 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0853 39/116 [=========>....................] - ETA: 0s - loss: 0.0748 78/116 [===================>..........] - ETA: 0s - loss: 0.0706 116/116 [==============================] - 0s 1ms/step - loss: 0.0733 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0112 42/116 [=========>....................] - ETA: 0s - loss: 0.0664 80/116 [===================>..........] - ETA: 0s - loss: 0.0651 116/116 [==============================] - 0s 1ms/step - loss: 0.0695 -> test with GAN.predict GAN tn, fp: 276, 12 GAN fn, tp: 0, 9 GAN f1 score: 0.600 GAN cohens kappa score: 0.582 -> 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: 0.701 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 2, 7 RF f1 score: 0.737 RF cohens kappa score: 0.728 -> 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: 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: 0.2982 41/116 [=========>....................] - ETA: 0s - loss: 0.2365  79/116 [===================>..........] - ETA: 0s - loss: 0.1919 116/116 [==============================] - 0s 1ms/step - loss: 0.1754 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1489 41/116 [=========>....................] - ETA: 0s - loss: 0.0994 80/116 [===================>..........] - ETA: 0s - loss: 0.1092 116/116 [==============================] - ETA: 0s - loss: 0.1108 116/116 [==============================] - 0s 1ms/step - loss: 0.1108 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0582 40/116 [=========>....................] - ETA: 0s - loss: 0.0842 77/116 [==================>...........] - ETA: 0s - loss: 0.0924 116/116 [==============================] - 0s 1ms/step - loss: 0.0947 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0547 42/116 [=========>....................] - ETA: 0s - loss: 0.0942 82/116 [====================>.........] - ETA: 0s - loss: 0.0892 116/116 [==============================] - 0s 1ms/step - loss: 0.0860 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0285 41/116 [=========>....................] - ETA: 0s - loss: 0.0859 82/116 [====================>.........] - ETA: 0s - loss: 0.0865 116/116 [==============================] - 0s 1ms/step - loss: 0.0812 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1254 40/116 [=========>....................] - ETA: 0s - loss: 0.0886 80/116 [===================>..........] - ETA: 0s - loss: 0.0750 116/116 [==============================] - 0s 1ms/step - loss: 0.0762 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0259 39/116 [=========>....................] - ETA: 0s - loss: 0.0554 78/116 [===================>..........] - ETA: 0s - loss: 0.0661 116/116 [==============================] - 0s 1ms/step - loss: 0.0744 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1373 42/116 [=========>....................] - ETA: 0s - loss: 0.0852 82/116 [====================>.........] - ETA: 0s - loss: 0.0775 116/116 [==============================] - 0s 1ms/step - loss: 0.0724 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0924 30/116 [======>.......................] - ETA: 0s - loss: 0.0631 58/116 [==============>...............] - ETA: 0s - loss: 0.0599 92/116 [======================>.......] - ETA: 0s - loss: 0.0668 116/116 [==============================] - 0s 2ms/step - loss: 0.0700 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0334 41/116 [=========>....................] - ETA: 0s - loss: 0.0541 82/116 [====================>.........] - ETA: 0s - loss: 0.0647 116/116 [==============================] - 0s 1ms/step - loss: 0.0676 -> test with GAN.predict GAN tn, fp: 280, 8 GAN fn, tp: 1, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.625 -> test with 'LR' LR tn, fp: 277, 11 LR fn, tp: 0, 9 LR f1 score: 0.621 LR cohens kappa score: 0.604 LR average precision score: 0.603 -> 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: 284, 4 GB fn, tp: 3, 6 GB f1 score: 0.632 GB cohens kappa score: 0.619 -> 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 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: 22s - loss: 0.6226 44/116 [==========>...................] - ETA: 0s - loss: 0.6283  83/116 [====================>.........] - ETA: 0s - loss: 0.5243 116/116 [==============================] - 0s 1ms/step - loss: 0.4543 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1891 42/116 [=========>....................] - ETA: 0s - loss: 0.1770 84/116 [====================>.........] - ETA: 0s - loss: 0.1730 116/116 [==============================] - 0s 1ms/step - loss: 0.1650 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1014 39/116 [=========>....................] - ETA: 0s - loss: 0.1252 79/116 [===================>..........] - ETA: 0s - loss: 0.1230 116/116 [==============================] - 0s 1ms/step - loss: 0.1173 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0670 38/116 [========>.....................] - ETA: 0s - loss: 0.1031 72/116 [=================>............] - ETA: 0s - loss: 0.1033 104/116 [=========================>....] - ETA: 0s - loss: 0.1006 116/116 [==============================] - 0s 1ms/step - loss: 0.1014 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0901 33/116 [=======>......................] - ETA: 0s - loss: 0.0718 65/116 [===============>..............] - ETA: 0s - loss: 0.0816 95/116 [=======================>......] - ETA: 0s - loss: 0.0899 116/116 [==============================] - 0s 2ms/step - loss: 0.0923 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1378 38/116 [========>.....................] - ETA: 0s - loss: 0.0712 74/116 [==================>...........] - ETA: 0s - loss: 0.0772 110/116 [===========================>..] - ETA: 0s - loss: 0.0831 116/116 [==============================] - 0s 1ms/step - loss: 0.0860 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0335 37/116 [========>.....................] - ETA: 0s - loss: 0.0678 72/116 [=================>............] - ETA: 0s - loss: 0.0864 109/116 [===========================>..] - ETA: 0s - loss: 0.0837 116/116 [==============================] - 0s 1ms/step - loss: 0.0845 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1590 33/116 [=======>......................] - ETA: 0s - loss: 0.0764 66/116 [================>.............] - ETA: 0s - loss: 0.0795 105/116 [==========================>...] - ETA: 0s - loss: 0.0758 116/116 [==============================] - 0s 1ms/step - loss: 0.0815 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0878 39/116 [=========>....................] - ETA: 0s - loss: 0.0711 77/116 [==================>...........] - ETA: 0s - loss: 0.0825 114/116 [============================>.] - ETA: 0s - loss: 0.0769 116/116 [==============================] - 0s 1ms/step - loss: 0.0784 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0306 36/116 [========>.....................] - ETA: 0s - loss: 0.0713 71/116 [=================>............] - ETA: 0s - loss: 0.0777 107/116 [==========================>...] - ETA: 0s - loss: 0.0748 116/116 [==============================] - 0s 1ms/step - loss: 0.0762 -> test with GAN.predict GAN tn, fp: 282, 6 GAN fn, tp: 3, 6 GAN f1 score: 0.571 GAN cohens kappa score: 0.556 -> test with 'LR' LR tn, fp: 280, 8 LR fn, tp: 0, 9 LR f1 score: 0.692 LR cohens kappa score: 0.680 LR average precision score: 0.761 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 6, 3 RF f1 score: 0.500 RF cohens kappa score: 0.492 -> test with 'GB' GB tn, fp: 288, 0 GB fn, tp: 4, 5 GB f1 score: 0.714 GB cohens kappa score: 0.708 -> 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 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: 20s - loss: 0.4361 35/116 [========>.....................] - ETA: 0s - loss: 0.3313  75/116 [==================>...........] - ETA: 0s - loss: 0.2958 113/116 [============================>.] - ETA: 0s - loss: 0.2576 116/116 [==============================] - 0s 1ms/step - loss: 0.2551 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2639 41/116 [=========>....................] - ETA: 0s - loss: 0.1474 80/116 [===================>..........] - ETA: 0s - loss: 0.1456 116/116 [==============================] - 0s 1ms/step - loss: 0.1367 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2829 41/116 [=========>....................] - ETA: 0s - loss: 0.1053 82/116 [====================>.........] - ETA: 0s - loss: 0.1037 116/116 [==============================] - 0s 1ms/step - loss: 0.1061 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1240 42/116 [=========>....................] - ETA: 0s - loss: 0.0886 82/116 [====================>.........] - ETA: 0s - loss: 0.1001 116/116 [==============================] - 0s 1ms/step - loss: 0.0950 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1288 38/116 [========>.....................] - ETA: 0s - loss: 0.0916 76/116 [==================>...........] - ETA: 0s - loss: 0.0925 116/116 [==============================] - ETA: 0s - loss: 0.0883 116/116 [==============================] - 0s 1ms/step - loss: 0.0883 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0439 41/116 [=========>....................] - ETA: 0s - loss: 0.0982 81/116 [===================>..........] - ETA: 0s - loss: 0.0840 116/116 [==============================] - 0s 1ms/step - loss: 0.0827 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0761 41/116 [=========>....................] - ETA: 0s - loss: 0.0721 82/116 [====================>.........] - ETA: 0s - loss: 0.0779 116/116 [==============================] - 0s 1ms/step - loss: 0.0798 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0387 42/116 [=========>....................] - ETA: 0s - loss: 0.0952 83/116 [====================>.........] - ETA: 0s - loss: 0.0837 116/116 [==============================] - 0s 1ms/step - loss: 0.0773 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0154 39/116 [=========>....................] - ETA: 0s - loss: 0.0663 78/116 [===================>..........] - ETA: 0s - loss: 0.0735 116/116 [==============================] - 0s 1ms/step - loss: 0.0739 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0863 40/116 [=========>....................] - ETA: 0s - loss: 0.0761 79/116 [===================>..........] - ETA: 0s - loss: 0.0806 116/116 [==============================] - 0s 1ms/step - loss: 0.0715 -> test with GAN.predict GAN tn, fp: 272, 16 GAN fn, tp: 0, 8 GAN f1 score: 0.500 GAN cohens kappa score: 0.479 -> 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: 0.703 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 3, 5 RF f1 score: 0.667 RF cohens kappa score: 0.658 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 2, 6 GB f1 score: 0.750 GB cohens kappa score: 0.743 -> test with 'KNN' KNN tn, fp: 275, 13 KNN fn, tp: 0, 8 KNN f1 score: 0.552 KNN cohens kappa score: 0.533 ====== 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: 18s - loss: 0.3734 42/116 [=========>....................] - ETA: 0s - loss: 0.2742  83/116 [====================>.........] - ETA: 0s - loss: 0.2499 116/116 [==============================] - 0s 1ms/step - loss: 0.2250 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2634 41/116 [=========>....................] - ETA: 0s - loss: 0.1525 82/116 [====================>.........] - ETA: 0s - loss: 0.1464 116/116 [==============================] - 0s 1ms/step - loss: 0.1374 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1667 41/116 [=========>....................] - ETA: 0s - loss: 0.1102 82/116 [====================>.........] - ETA: 0s - loss: 0.1132 116/116 [==============================] - 0s 1ms/step - loss: 0.1097 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0358 37/116 [========>.....................] - ETA: 0s - loss: 0.0930 71/116 [=================>............] - ETA: 0s - loss: 0.0953 106/116 [==========================>...] - ETA: 0s - loss: 0.0918 116/116 [==============================] - 0s 1ms/step - loss: 0.0949 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0369 40/116 [=========>....................] - ETA: 0s - loss: 0.0815 80/116 [===================>..........] - ETA: 0s - loss: 0.0916 116/116 [==============================] - 0s 1ms/step - loss: 0.0874 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0190 38/116 [========>.....................] - ETA: 0s - loss: 0.0939 73/116 [=================>............] - ETA: 0s - loss: 0.0908 106/116 [==========================>...] - ETA: 0s - loss: 0.0853 116/116 [==============================] - 0s 1ms/step - loss: 0.0857 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0438 42/116 [=========>....................] - ETA: 0s - loss: 0.0856 83/116 [====================>.........] - ETA: 0s - loss: 0.0811 116/116 [==============================] - 0s 1ms/step - loss: 0.0820 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0284 41/116 [=========>....................] - ETA: 0s - loss: 0.0805 81/116 [===================>..........] - ETA: 0s - loss: 0.0811 116/116 [==============================] - 0s 1ms/step - loss: 0.0772 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0908 41/116 [=========>....................] - ETA: 0s - loss: 0.0736 79/116 [===================>..........] - ETA: 0s - loss: 0.0754 116/116 [==============================] - 0s 1ms/step - loss: 0.0760 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.4501 42/116 [=========>....................] - ETA: 0s - loss: 0.0790 83/116 [====================>.........] - ETA: 0s - loss: 0.0724 116/116 [==============================] - 0s 1ms/step - loss: 0.0737 -> test with GAN.predict GAN tn, fp: 277, 11 GAN fn, tp: 0, 9 GAN f1 score: 0.621 GAN cohens kappa score: 0.604 -> test with 'LR' LR tn, fp: 275, 13 LR fn, tp: 0, 9 LR f1 score: 0.581 LR cohens kappa score: 0.562 LR average precision score: 0.703 -> 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: 1, 8 GB f1 score: 0.889 GB cohens kappa score: 0.885 -> test with 'KNN' KNN tn, fp: 279, 9 KNN fn, tp: 0, 9 KNN f1 score: 0.667 KNN cohens kappa score: 0.653 ------ 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: 18s - loss: 0.3317 42/116 [=========>....................] - ETA: 0s - loss: 0.2651  81/116 [===================>..........] - ETA: 0s - loss: 0.2289 116/116 [==============================] - 0s 1ms/step - loss: 0.2127 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1379 39/116 [=========>....................] - ETA: 0s - loss: 0.1582 78/116 [===================>..........] - ETA: 0s - loss: 0.1408 116/116 [==============================] - 0s 1ms/step - loss: 0.1225 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0662 41/116 [=========>....................] - ETA: 0s - loss: 0.0821 82/116 [====================>.........] - ETA: 0s - loss: 0.0907 116/116 [==============================] - 0s 1ms/step - loss: 0.0886 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1906 42/116 [=========>....................] - ETA: 0s - loss: 0.0778 82/116 [====================>.........] - ETA: 0s - loss: 0.0675 116/116 [==============================] - 0s 1ms/step - loss: 0.0745 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0107 41/116 [=========>....................] - ETA: 0s - loss: 0.0741 80/116 [===================>..........] - ETA: 0s - loss: 0.0629 116/116 [==============================] - 0s 1ms/step - loss: 0.0683 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0688 39/116 [=========>....................] - ETA: 0s - loss: 0.0663 79/116 [===================>..........] - ETA: 0s - loss: 0.0621 116/116 [==============================] - 0s 1ms/step - loss: 0.0637 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0446 41/116 [=========>....................] - ETA: 0s - loss: 0.0659 81/116 [===================>..........] - ETA: 0s - loss: 0.0598 116/116 [==============================] - 0s 1ms/step - loss: 0.0611 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0115 41/116 [=========>....................] - ETA: 0s - loss: 0.0609 82/116 [====================>.........] - ETA: 0s - loss: 0.0609 116/116 [==============================] - 0s 1ms/step - loss: 0.0586 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1719 41/116 [=========>....................] - ETA: 0s - loss: 0.0599 82/116 [====================>.........] - ETA: 0s - loss: 0.0577 116/116 [==============================] - 0s 1ms/step - loss: 0.0567 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0913 41/116 [=========>....................] - ETA: 0s - loss: 0.0565 81/116 [===================>..........] - ETA: 0s - loss: 0.0558 116/116 [==============================] - 0s 1ms/step - loss: 0.0549 -> test with GAN.predict GAN tn, fp: 273, 15 GAN fn, tp: 1, 8 GAN f1 score: 0.500 GAN cohens kappa score: 0.477 -> test with 'LR' LR tn, fp: 270, 18 LR fn, tp: 1, 8 LR f1 score: 0.457 LR cohens kappa score: 0.432 LR average precision score: 0.320 -> test with 'RF' RF tn, fp: 282, 6 RF fn, tp: 6, 3 RF f1 score: 0.333 RF cohens kappa score: 0.312 -> test with 'GB' GB tn, fp: 282, 6 GB fn, tp: 6, 3 GB f1 score: 0.333 GB cohens kappa score: 0.312 -> test with 'KNN' KNN tn, fp: 273, 15 KNN fn, tp: 1, 8 KNN f1 score: 0.500 KNN cohens kappa score: 0.477 ------ 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: 18s - loss: 0.4024 39/116 [=========>....................] - ETA: 0s - loss: 0.2628  81/116 [===================>..........] - ETA: 0s - loss: 0.2131 116/116 [==============================] - 0s 1ms/step - loss: 0.1934 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0799 41/116 [=========>....................] - ETA: 0s - loss: 0.1359 81/116 [===================>..........] - ETA: 0s - loss: 0.1322 116/116 [==============================] - 0s 1ms/step - loss: 0.1263 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.4314 42/116 [=========>....................] - ETA: 0s - loss: 0.1319 81/116 [===================>..........] - ETA: 0s - loss: 0.1158 116/116 [==============================] - 0s 1ms/step - loss: 0.1069 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1604 41/116 [=========>....................] - ETA: 0s - loss: 0.1041 83/116 [====================>.........] - ETA: 0s - loss: 0.1013 116/116 [==============================] - 0s 1ms/step - loss: 0.0979 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1867 39/116 [=========>....................] - ETA: 0s - loss: 0.0867 78/116 [===================>..........] - ETA: 0s - loss: 0.0834 113/116 [============================>.] - ETA: 0s - loss: 0.0933 116/116 [==============================] - 0s 1ms/step - loss: 0.0923 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0541 36/116 [========>.....................] - ETA: 0s - loss: 0.0857 75/116 [==================>...........] - ETA: 0s - loss: 0.0876 114/116 [============================>.] - ETA: 0s - loss: 0.0883 116/116 [==============================] - 0s 1ms/step - loss: 0.0888 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0213 42/116 [=========>....................] - ETA: 0s - loss: 0.0674 81/116 [===================>..........] - ETA: 0s - loss: 0.0785 116/116 [==============================] - 0s 1ms/step - loss: 0.0864 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0652 38/116 [========>.....................] - ETA: 0s - loss: 0.0831 74/116 [==================>...........] - ETA: 0s - loss: 0.0814 114/116 [============================>.] - ETA: 0s - loss: 0.0844 116/116 [==============================] - 0s 1ms/step - loss: 0.0842 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0657 42/116 [=========>....................] - ETA: 0s - loss: 0.0672 81/116 [===================>..........] - ETA: 0s - loss: 0.0810 116/116 [==============================] - 0s 1ms/step - loss: 0.0815 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1210 42/116 [=========>....................] - ETA: 0s - loss: 0.0859 80/116 [===================>..........] - ETA: 0s - loss: 0.0810 116/116 [==============================] - 0s 1ms/step - loss: 0.0800 -> test with GAN.predict GAN tn, fp: 281, 7 GAN fn, tp: 1, 8 GAN f1 score: 0.667 GAN cohens kappa score: 0.654 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 0, 9 LR f1 score: 0.720 LR cohens kappa score: 0.709 LR average precision score: 0.762 -> 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: 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 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: 0.3830 37/116 [========>.....................] - ETA: 0s - loss: 0.1648  74/116 [==================>...........] - ETA: 0s - loss: 0.1554 115/116 [============================>.] - ETA: 0s - loss: 0.1416 116/116 [==============================] - 0s 1ms/step - loss: 0.1413 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2550 39/116 [=========>....................] - ETA: 0s - loss: 0.1083 80/116 [===================>..........] - ETA: 0s - loss: 0.1077 116/116 [==============================] - 0s 1ms/step - loss: 0.1063 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1065 39/116 [=========>....................] - ETA: 0s - loss: 0.1050 79/116 [===================>..........] - ETA: 0s - loss: 0.1046 116/116 [==============================] - 0s 1ms/step - loss: 0.0956 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0350 42/116 [=========>....................] - ETA: 0s - loss: 0.0916 83/116 [====================>.........] - ETA: 0s - loss: 0.0882 116/116 [==============================] - 0s 1ms/step - loss: 0.0900 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2414 41/116 [=========>....................] - ETA: 0s - loss: 0.0706 77/116 [==================>...........] - ETA: 0s - loss: 0.0798 116/116 [==============================] - 0s 1ms/step - loss: 0.0848 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1867 38/116 [========>.....................] - ETA: 0s - loss: 0.0734 79/116 [===================>..........] - ETA: 0s - loss: 0.0820 116/116 [==============================] - 0s 1ms/step - loss: 0.0820 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1595 42/116 [=========>....................] - ETA: 0s - loss: 0.0691 80/116 [===================>..........] - ETA: 0s - loss: 0.0703 116/116 [==============================] - 0s 1ms/step - loss: 0.0803 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0348 42/116 [=========>....................] - ETA: 0s - loss: 0.0916 83/116 [====================>.........] - ETA: 0s - loss: 0.0837 116/116 [==============================] - 0s 1ms/step - loss: 0.0786 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0319 42/116 [=========>....................] - ETA: 0s - loss: 0.0731 80/116 [===================>..........] - ETA: 0s - loss: 0.0713 116/116 [==============================] - 0s 1ms/step - loss: 0.0762 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0447 41/116 [=========>....................] - ETA: 0s - loss: 0.0699 81/116 [===================>..........] - ETA: 0s - loss: 0.0655 116/116 [==============================] - 0s 1ms/step - loss: 0.0742 -> test with GAN.predict GAN tn, fp: 277, 11 GAN fn, tp: 0, 9 GAN f1 score: 0.621 GAN cohens kappa score: 0.604 -> 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: 0.878 -> 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: 277, 11 KNN fn, tp: 0, 9 KNN f1 score: 0.621 KNN cohens kappa score: 0.604 ------ 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: 17s - loss: 0.2900 41/116 [=========>....................] - ETA: 0s - loss: 0.2157  82/116 [====================>.........] - ETA: 0s - loss: 0.1839 116/116 [==============================] - 0s 1ms/step - loss: 0.1665 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1874 41/116 [=========>....................] - ETA: 0s - loss: 0.1226 81/116 [===================>..........] - ETA: 0s - loss: 0.1120 116/116 [==============================] - 0s 1ms/step - loss: 0.1067 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0910 36/116 [========>.....................] - ETA: 0s - loss: 0.1158 72/116 [=================>............] - ETA: 0s - loss: 0.0915 110/116 [===========================>..] - ETA: 0s - loss: 0.0896 116/116 [==============================] - 0s 1ms/step - loss: 0.0934 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0112 40/116 [=========>....................] - ETA: 0s - loss: 0.0905 80/116 [===================>..........] - ETA: 0s - loss: 0.0979 116/116 [==============================] - 0s 1ms/step - loss: 0.0870 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2915 40/116 [=========>....................] - ETA: 0s - loss: 0.0835 79/116 [===================>..........] - ETA: 0s - loss: 0.0789 116/116 [==============================] - 0s 1ms/step - loss: 0.0824 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1384 42/116 [=========>....................] - ETA: 0s - loss: 0.0707 83/116 [====================>.........] - ETA: 0s - loss: 0.0801 116/116 [==============================] - 0s 1ms/step - loss: 0.0785 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0203 42/116 [=========>....................] - ETA: 0s - loss: 0.0632 83/116 [====================>.........] - ETA: 0s - loss: 0.0689 116/116 [==============================] - 0s 1ms/step - loss: 0.0760 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0165 41/116 [=========>....................] - ETA: 0s - loss: 0.0672 82/116 [====================>.........] - ETA: 0s - loss: 0.0760 116/116 [==============================] - 0s 1ms/step - loss: 0.0757 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0110 41/116 [=========>....................] - ETA: 0s - loss: 0.0841 83/116 [====================>.........] - ETA: 0s - loss: 0.0844 116/116 [==============================] - 0s 1ms/step - loss: 0.0718 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0710 43/116 [==========>...................] - ETA: 0s - loss: 0.0794 83/116 [====================>.........] - ETA: 0s - loss: 0.0727 116/116 [==============================] - 0s 1ms/step - loss: 0.0715 -> 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: 277, 11 LR fn, tp: 0, 8 LR f1 score: 0.593 LR cohens kappa score: 0.576 LR average precision score: 0.607 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 5, 3 RF f1 score: 0.545 RF cohens kappa score: 0.539 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 4, 4 GB f1 score: 0.571 GB cohens kappa score: 0.561 -> test with 'KNN' KNN tn, fp: 281, 7 KNN fn, tp: 0, 8 KNN f1 score: 0.696 KNN cohens kappa score: 0.685 ====== 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: 17s - loss: 0.2337 41/116 [=========>....................] - ETA: 0s - loss: 0.1194  82/116 [====================>.........] - ETA: 0s - loss: 0.1019 116/116 [==============================] - 0s 1ms/step - loss: 0.1030 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0292 42/116 [=========>....................] - ETA: 0s - loss: 0.0881 77/116 [==================>...........] - ETA: 0s - loss: 0.0843 116/116 [==============================] - ETA: 0s - loss: 0.0801 116/116 [==============================] - 0s 1ms/step - loss: 0.0801 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1152 41/116 [=========>....................] - ETA: 0s - loss: 0.0824 82/116 [====================>.........] - ETA: 0s - loss: 0.0766 116/116 [==============================] - 0s 1ms/step - loss: 0.0730 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0173 43/116 [==========>...................] - ETA: 0s - loss: 0.0590 85/116 [====================>.........] - ETA: 0s - loss: 0.0691 116/116 [==============================] - 0s 1ms/step - loss: 0.0689 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0106 43/116 [==========>...................] - ETA: 0s - loss: 0.0637 85/116 [====================>.........] - ETA: 0s - loss: 0.0649 116/116 [==============================] - 0s 1ms/step - loss: 0.0661 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0117 43/116 [==========>...................] - ETA: 0s - loss: 0.0733 83/116 [====================>.........] - ETA: 0s - loss: 0.0638 116/116 [==============================] - 0s 1ms/step - loss: 0.0641 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0255 41/116 [=========>....................] - ETA: 0s - loss: 0.0503 81/116 [===================>..........] - ETA: 0s - loss: 0.0555 116/116 [==============================] - 0s 1ms/step - loss: 0.0614 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0123 39/116 [=========>....................] - ETA: 0s - loss: 0.0374 77/116 [==================>...........] - ETA: 0s - loss: 0.0585 115/116 [============================>.] - ETA: 0s - loss: 0.0602 116/116 [==============================] - 0s 1ms/step - loss: 0.0601 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0268 43/116 [==========>...................] - ETA: 0s - loss: 0.0532 83/116 [====================>.........] - ETA: 0s - loss: 0.0523 116/116 [==============================] - 0s 1ms/step - loss: 0.0599 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1948 42/116 [=========>....................] - ETA: 0s - loss: 0.0620 83/116 [====================>.........] - ETA: 0s - loss: 0.0575 116/116 [==============================] - 0s 1ms/step - loss: 0.0590 -> test with GAN.predict GAN tn, fp: 274, 14 GAN fn, tp: 1, 8 GAN f1 score: 0.516 GAN cohens kappa score: 0.494 -> 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: 0.710 -> 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: 276, 12 KNN fn, tp: 0, 9 KNN f1 score: 0.600 KNN cohens kappa score: 0.582 ------ 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: 17s - loss: 0.2515 44/116 [==========>...................] - ETA: 0s - loss: 0.2723  85/116 [====================>.........] - ETA: 0s - loss: 0.2329 116/116 [==============================] - 0s 1ms/step - loss: 0.2160 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.3647 43/116 [==========>...................] - ETA: 0s - loss: 0.1527 85/116 [====================>.........] - ETA: 0s - loss: 0.1370 116/116 [==============================] - 0s 1ms/step - loss: 0.1291 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1168 42/116 [=========>....................] - ETA: 0s - loss: 0.1061 84/116 [====================>.........] - ETA: 0s - loss: 0.0989 116/116 [==============================] - 0s 1ms/step - loss: 0.0985 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0291 36/116 [========>.....................] - ETA: 0s - loss: 0.0933 71/116 [=================>............] - ETA: 0s - loss: 0.0853 108/116 [==========================>...] - ETA: 0s - loss: 0.0853 116/116 [==============================] - 0s 1ms/step - loss: 0.0837 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0294 41/116 [=========>....................] - ETA: 0s - loss: 0.0882 81/116 [===================>..........] - ETA: 0s - loss: 0.0766 116/116 [==============================] - 0s 1ms/step - loss: 0.0757 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1930 41/116 [=========>....................] - ETA: 0s - loss: 0.0693 82/116 [====================>.........] - ETA: 0s - loss: 0.0747 116/116 [==============================] - 0s 1ms/step - loss: 0.0702 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0121 38/116 [========>.....................] - ETA: 0s - loss: 0.0683 78/116 [===================>..........] - ETA: 0s - loss: 0.0595 116/116 [==============================] - 0s 1ms/step - loss: 0.0661 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2856 40/116 [=========>....................] - ETA: 0s - loss: 0.0735 80/116 [===================>..........] - ETA: 0s - loss: 0.0673 116/116 [==============================] - 0s 1ms/step - loss: 0.0625 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0436 38/116 [========>.....................] - ETA: 0s - loss: 0.0662 78/116 [===================>..........] - ETA: 0s - loss: 0.0613 116/116 [==============================] - 0s 1ms/step - loss: 0.0612 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0393 43/116 [==========>...................] - ETA: 0s - loss: 0.0742 84/116 [====================>.........] - ETA: 0s - loss: 0.0657 116/116 [==============================] - 0s 1ms/step - loss: 0.0593 -> test with GAN.predict GAN tn, fp: 274, 14 GAN fn, tp: 1, 8 GAN f1 score: 0.516 GAN cohens kappa score: 0.494 -> 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: 0.684 -> 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: 285, 3 GB fn, tp: 3, 6 GB f1 score: 0.667 GB cohens kappa score: 0.656 -> test with 'KNN' KNN tn, fp: 276, 12 KNN fn, tp: 1, 8 KNN f1 score: 0.552 KNN cohens kappa score: 0.532 ------ 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: 17s - loss: 0.2704 42/116 [=========>....................] - ETA: 0s - loss: 0.1515  83/116 [====================>.........] - ETA: 0s - loss: 0.1346 116/116 [==============================] - 0s 1ms/step - loss: 0.1284 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1175 43/116 [==========>...................] - ETA: 0s - loss: 0.1003 84/116 [====================>.........] - ETA: 0s - loss: 0.0934 116/116 [==============================] - 0s 1ms/step - loss: 0.0958 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0757 41/116 [=========>....................] - ETA: 0s - loss: 0.0914 81/116 [===================>..........] - ETA: 0s - loss: 0.0843 116/116 [==============================] - 0s 1ms/step - loss: 0.0859 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1742 42/116 [=========>....................] - ETA: 0s - loss: 0.0709 83/116 [====================>.........] - ETA: 0s - loss: 0.0861 116/116 [==============================] - 0s 1ms/step - loss: 0.0812 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0271 42/116 [=========>....................] - ETA: 0s - loss: 0.0766 81/116 [===================>..........] - ETA: 0s - loss: 0.0824 116/116 [==============================] - 0s 1ms/step - loss: 0.0773 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1256 40/116 [=========>....................] - ETA: 0s - loss: 0.0779 75/116 [==================>...........] - ETA: 0s - loss: 0.0749 115/116 [============================>.] - ETA: 0s - loss: 0.0746 116/116 [==============================] - 0s 1ms/step - loss: 0.0746 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0246 40/116 [=========>....................] - ETA: 0s - loss: 0.0743 80/116 [===================>..........] - ETA: 0s - loss: 0.0696 116/116 [==============================] - 0s 1ms/step - loss: 0.0730 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1707 39/116 [=========>....................] - ETA: 0s - loss: 0.0843 78/116 [===================>..........] - ETA: 0s - loss: 0.0745 116/116 [==============================] - 0s 1ms/step - loss: 0.0707 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2234 41/116 [=========>....................] - ETA: 0s - loss: 0.0869 81/116 [===================>..........] - ETA: 0s - loss: 0.0765 116/116 [==============================] - 0s 1ms/step - loss: 0.0691 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0125 42/116 [=========>....................] - ETA: 0s - loss: 0.0612 83/116 [====================>.........] - ETA: 0s - loss: 0.0699 116/116 [==============================] - 0s 1ms/step - loss: 0.0686 -> 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: 0.817 -> 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: 2, 7 GB f1 score: 0.875 GB cohens kappa score: 0.872 -> test with 'KNN' KNN tn, fp: 285, 3 KNN fn, tp: 0, 9 KNN f1 score: 0.857 KNN cohens kappa score: 0.852 ------ 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: 0.5103 42/116 [=========>....................] - ETA: 0s - loss: 0.3051  82/116 [====================>.........] - ETA: 0s - loss: 0.2739 116/116 [==============================] - 0s 1ms/step - loss: 0.2486 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2211 41/116 [=========>....................] - ETA: 0s - loss: 0.1568 80/116 [===================>..........] - ETA: 0s - loss: 0.1408 116/116 [==============================] - 0s 1ms/step - loss: 0.1348 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2647 42/116 [=========>....................] - ETA: 0s - loss: 0.1154 83/116 [====================>.........] - ETA: 0s - loss: 0.1113 116/116 [==============================] - 0s 1ms/step - loss: 0.1064 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0742 42/116 [=========>....................] - ETA: 0s - loss: 0.0896 83/116 [====================>.........] - ETA: 0s - loss: 0.0957 116/116 [==============================] - 0s 1ms/step - loss: 0.0922 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0274 41/116 [=========>....................] - ETA: 0s - loss: 0.0962 81/116 [===================>..........] - ETA: 0s - loss: 0.0834 116/116 [==============================] - 0s 1ms/step - loss: 0.0846 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0213 41/116 [=========>....................] - ETA: 0s - loss: 0.0823 83/116 [====================>.........] - ETA: 0s - loss: 0.0799 116/116 [==============================] - 0s 1ms/step - loss: 0.0795 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1779 40/116 [=========>....................] - ETA: 0s - loss: 0.0832 82/116 [====================>.........] - ETA: 0s - loss: 0.0722 116/116 [==============================] - 0s 1ms/step - loss: 0.0759 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0946 42/116 [=========>....................] - ETA: 0s - loss: 0.0758 83/116 [====================>.........] - ETA: 0s - loss: 0.0776 116/116 [==============================] - 0s 1ms/step - loss: 0.0725 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0348 37/116 [========>.....................] - ETA: 0s - loss: 0.0651 78/116 [===================>..........] - ETA: 0s - loss: 0.0692 115/116 [============================>.] - ETA: 0s - loss: 0.0707 116/116 [==============================] - 0s 1ms/step - loss: 0.0706 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0933 41/116 [=========>....................] - ETA: 0s - loss: 0.0825 81/116 [===================>..........] - ETA: 0s - loss: 0.0707 116/116 [==============================] - 0s 1ms/step - loss: 0.0688 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 1, 8 GAN f1 score: 0.593 GAN cohens kappa score: 0.575 -> 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: 0.758 -> 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: 4, 5 GB f1 score: 0.714 GB cohens kappa score: 0.708 -> 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 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: 0.3570 42/116 [=========>....................] - ETA: 0s - loss: 0.2799  84/116 [====================>.........] - ETA: 0s - loss: 0.2391 116/116 [==============================] - 0s 1ms/step - loss: 0.2123 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1142 42/116 [=========>....................] - ETA: 0s - loss: 0.1340 84/116 [====================>.........] - ETA: 0s - loss: 0.1154 116/116 [==============================] - 0s 1ms/step - loss: 0.1225 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0451 41/116 [=========>....................] - ETA: 0s - loss: 0.1031 76/116 [==================>...........] - ETA: 0s - loss: 0.0888 112/116 [===========================>..] - ETA: 0s - loss: 0.1010 116/116 [==============================] - 0s 1ms/step - loss: 0.0999 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0434 41/116 [=========>....................] - ETA: 0s - loss: 0.0969 77/116 [==================>...........] - ETA: 0s - loss: 0.0793 116/116 [==============================] - 0s 1ms/step - loss: 0.0870 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0200 34/116 [=======>......................] - ETA: 0s - loss: 0.0987 67/116 [================>.............] - ETA: 0s - loss: 0.0881 108/116 [==========================>...] - ETA: 0s - loss: 0.0811 116/116 [==============================] - 0s 1ms/step - loss: 0.0803 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1271 43/116 [==========>...................] - ETA: 0s - loss: 0.0734 82/116 [====================>.........] - ETA: 0s - loss: 0.0749 116/116 [==============================] - 0s 1ms/step - loss: 0.0765 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0992 42/116 [=========>....................] - ETA: 0s - loss: 0.0744 83/116 [====================>.........] - ETA: 0s - loss: 0.0714 116/116 [==============================] - 0s 1ms/step - loss: 0.0723 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0078 42/116 [=========>....................] - ETA: 0s - loss: 0.0737 82/116 [====================>.........] - ETA: 0s - loss: 0.0708 116/116 [==============================] - 0s 1ms/step - loss: 0.0695 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0213 41/116 [=========>....................] - ETA: 0s - loss: 0.0688 82/116 [====================>.........] - ETA: 0s - loss: 0.0690 116/116 [==============================] - 0s 1ms/step - loss: 0.0679 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0517 38/116 [========>.....................] - ETA: 0s - loss: 0.0651 74/116 [==================>...........] - ETA: 0s - loss: 0.0709 108/116 [==========================>...] - ETA: 0s - loss: 0.0675 116/116 [==============================] - 0s 1ms/step - loss: 0.0659 -> test with GAN.predict GAN tn, fp: 274, 14 GAN fn, tp: 0, 8 GAN f1 score: 0.533 GAN cohens kappa score: 0.514 -> 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: 0.349 -> 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: 275, 13 KNN fn, tp: 0, 8 KNN f1 score: 0.552 KNN cohens kappa score: 0.533 ====== 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: 18s - loss: 0.3488 43/116 [==========>...................] - ETA: 0s - loss: 0.2442  84/116 [====================>.........] - ETA: 0s - loss: 0.2245 116/116 [==============================] - 0s 1ms/step - loss: 0.2118 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1434 42/116 [=========>....................] - ETA: 0s - loss: 0.1477 83/116 [====================>.........] - ETA: 0s - loss: 0.1389 116/116 [==============================] - 0s 1ms/step - loss: 0.1317 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0803 39/116 [=========>....................] - ETA: 0s - loss: 0.0924 81/116 [===================>..........] - ETA: 0s - loss: 0.1030 116/116 [==============================] - 0s 1ms/step - loss: 0.1066 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0562 39/116 [=========>....................] - ETA: 0s - loss: 0.1104 80/116 [===================>..........] - ETA: 0s - loss: 0.0944 116/116 [==============================] - 0s 1ms/step - loss: 0.0937 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0695 42/116 [=========>....................] - ETA: 0s - loss: 0.0864 81/116 [===================>..........] - ETA: 0s - loss: 0.0897 116/116 [==============================] - 0s 1ms/step - loss: 0.0874 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0311 39/116 [=========>....................] - ETA: 0s - loss: 0.0857 80/116 [===================>..........] - ETA: 0s - loss: 0.0807 116/116 [==============================] - 0s 1ms/step - loss: 0.0844 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0581 38/116 [========>.....................] - ETA: 0s - loss: 0.0842 79/116 [===================>..........] - ETA: 0s - loss: 0.0892 116/116 [==============================] - 0s 1ms/step - loss: 0.0795 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0421 40/116 [=========>....................] - ETA: 0s - loss: 0.0572 77/116 [==================>...........] - ETA: 0s - loss: 0.0599 116/116 [==============================] - 0s 1ms/step - loss: 0.0765 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0496 43/116 [==========>...................] - ETA: 0s - loss: 0.0853 84/116 [====================>.........] - ETA: 0s - loss: 0.0727 116/116 [==============================] - 0s 1ms/step - loss: 0.0758 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0316 41/116 [=========>....................] - ETA: 0s - loss: 0.0734 79/116 [===================>..........] - ETA: 0s - loss: 0.0765 116/116 [==============================] - 0s 1ms/step - loss: 0.0730 -> test with GAN.predict GAN tn, fp: 271, 17 GAN fn, tp: 0, 9 GAN f1 score: 0.514 GAN cohens kappa score: 0.491 -> test with 'LR' LR tn, fp: 275, 13 LR fn, tp: 0, 9 LR f1 score: 0.581 LR cohens kappa score: 0.562 LR average precision score: 0.748 -> 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: 277, 11 KNN fn, tp: 0, 9 KNN f1 score: 0.621 KNN cohens kappa score: 0.604 ------ 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: 18s - loss: 0.5631 41/116 [=========>....................] - ETA: 0s - loss: 0.3563  83/116 [====================>.........] - ETA: 0s - loss: 0.2859 116/116 [==============================] - 0s 1ms/step - loss: 0.2502 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0833 43/116 [==========>...................] - ETA: 0s - loss: 0.1367 85/116 [====================>.........] - ETA: 0s - loss: 0.1264 116/116 [==============================] - 0s 1ms/step - loss: 0.1199 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0363 41/116 [=========>....................] - ETA: 0s - loss: 0.0946 81/116 [===================>..........] - ETA: 0s - loss: 0.0944 116/116 [==============================] - 0s 1ms/step - loss: 0.0899 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1015 41/116 [=========>....................] - ETA: 0s - loss: 0.0887 82/116 [====================>.........] - ETA: 0s - loss: 0.0751 116/116 [==============================] - 0s 1ms/step - loss: 0.0777 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0908 41/116 [=========>....................] - ETA: 0s - loss: 0.0673 82/116 [====================>.........] - ETA: 0s - loss: 0.0697 116/116 [==============================] - 0s 1ms/step - loss: 0.0719 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0162 42/116 [=========>....................] - ETA: 0s - loss: 0.0611 84/116 [====================>.........] - ETA: 0s - loss: 0.0693 116/116 [==============================] - 0s 1ms/step - loss: 0.0693 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0718 40/116 [=========>....................] - ETA: 0s - loss: 0.0575 79/116 [===================>..........] - ETA: 0s - loss: 0.0695 116/116 [==============================] - 0s 1ms/step - loss: 0.0657 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0401 43/116 [==========>...................] - ETA: 0s - loss: 0.0622 84/116 [====================>.........] - ETA: 0s - loss: 0.0575 116/116 [==============================] - 0s 1ms/step - loss: 0.0622 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0342 39/116 [=========>....................] - ETA: 0s - loss: 0.0634 73/116 [=================>............] - ETA: 0s - loss: 0.0627 107/116 [==========================>...] - ETA: 0s - loss: 0.0640 116/116 [==============================] - 0s 1ms/step - loss: 0.0639 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0266 43/116 [==========>...................] - ETA: 0s - loss: 0.0731 83/116 [====================>.........] - ETA: 0s - loss: 0.0640 116/116 [==============================] - 0s 1ms/step - loss: 0.0596 -> test with GAN.predict GAN tn, fp: 270, 18 GAN fn, tp: 1, 8 GAN f1 score: 0.457 GAN cohens kappa score: 0.432 -> test with 'LR' LR tn, fp: 271, 17 LR fn, tp: 0, 9 LR f1 score: 0.514 LR cohens kappa score: 0.491 LR average precision score: 0.625 -> 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: 287, 1 GB fn, tp: 2, 7 GB f1 score: 0.824 GB cohens kappa score: 0.818 -> 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 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: 18s - loss: 0.2390 42/116 [=========>....................] - ETA: 0s - loss: 0.2663  80/116 [===================>..........] - ETA: 0s - loss: 0.2305 114/116 [============================>.] - ETA: 0s - loss: 0.2121 116/116 [==============================] - 0s 1ms/step - loss: 0.2114 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2798 34/116 [=======>......................] - ETA: 0s - loss: 0.1385 73/116 [=================>............] - ETA: 0s - loss: 0.1432 114/116 [============================>.] - ETA: 0s - loss: 0.1385 116/116 [==============================] - 0s 1ms/step - loss: 0.1378 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1008 40/116 [=========>....................] - ETA: 0s - loss: 0.1217 81/116 [===================>..........] - ETA: 0s - loss: 0.1147 116/116 [==============================] - 0s 1ms/step - loss: 0.1138 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1171 41/116 [=========>....................] - ETA: 0s - loss: 0.1055 81/116 [===================>..........] - ETA: 0s - loss: 0.0969 116/116 [==============================] - 0s 1ms/step - loss: 0.1002 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0253 41/116 [=========>....................] - ETA: 0s - loss: 0.0801 82/116 [====================>.........] - ETA: 0s - loss: 0.0902 116/116 [==============================] - 0s 1ms/step - loss: 0.0920 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0386 41/116 [=========>....................] - ETA: 0s - loss: 0.0803 81/116 [===================>..........] - ETA: 0s - loss: 0.0752 116/116 [==============================] - 0s 1ms/step - loss: 0.0857 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1226 39/116 [=========>....................] - ETA: 0s - loss: 0.0993 80/116 [===================>..........] - ETA: 0s - loss: 0.0849 116/116 [==============================] - 0s 1ms/step - loss: 0.0812 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0484 42/116 [=========>....................] - ETA: 0s - loss: 0.0760 81/116 [===================>..........] - ETA: 0s - loss: 0.0742 116/116 [==============================] - 0s 1ms/step - loss: 0.0786 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0312 44/116 [==========>...................] - ETA: 0s - loss: 0.0812 85/116 [====================>.........] - ETA: 0s - loss: 0.0811 116/116 [==============================] - 0s 1ms/step - loss: 0.0753 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0421 41/116 [=========>....................] - ETA: 0s - loss: 0.0791 82/116 [====================>.........] - ETA: 0s - loss: 0.0757 116/116 [==============================] - 0s 1ms/step - loss: 0.0726 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 3, 6 GAN f1 score: 0.500 GAN cohens kappa score: 0.480 -> test with 'LR' LR tn, fp: 278, 10 LR fn, tp: 2, 7 LR f1 score: 0.538 LR cohens kappa score: 0.519 LR average precision score: 0.650 -> 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: 0, 9 KNN f1 score: 0.667 KNN cohens kappa score: 0.653 ------ 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: 19s - loss: 0.3221 41/116 [=========>....................] - ETA: 0s - loss: 0.3398  81/116 [===================>..........] - ETA: 0s - loss: 0.3006 116/116 [==============================] - 0s 1ms/step - loss: 0.2687 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2994 41/116 [=========>....................] - ETA: 0s - loss: 0.1628 81/116 [===================>..........] - ETA: 0s - loss: 0.1627 116/116 [==============================] - 0s 1ms/step - loss: 0.1477 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2950 40/116 [=========>....................] - ETA: 0s - loss: 0.1158 80/116 [===================>..........] - ETA: 0s - loss: 0.1128 116/116 [==============================] - ETA: 0s - loss: 0.1131 116/116 [==============================] - 0s 1ms/step - loss: 0.1131 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2107 39/116 [=========>....................] - ETA: 0s - loss: 0.1016 79/116 [===================>..........] - ETA: 0s - loss: 0.0972 116/116 [==============================] - 0s 1ms/step - loss: 0.0970 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0490 41/116 [=========>....................] - ETA: 0s - loss: 0.1057 81/116 [===================>..........] - ETA: 0s - loss: 0.0940 116/116 [==============================] - 0s 1ms/step - loss: 0.0895 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0885 42/116 [=========>....................] - ETA: 0s - loss: 0.0781 82/116 [====================>.........] - ETA: 0s - loss: 0.0887 116/116 [==============================] - 0s 1ms/step - loss: 0.0836 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1438 37/116 [========>.....................] - ETA: 0s - loss: 0.0748 74/116 [==================>...........] - ETA: 0s - loss: 0.0750 116/116 [==============================] - ETA: 0s - loss: 0.0794 116/116 [==============================] - 0s 1ms/step - loss: 0.0794 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0344 40/116 [=========>....................] - ETA: 0s - loss: 0.0759 81/116 [===================>..........] - ETA: 0s - loss: 0.0721 116/116 [==============================] - 0s 1ms/step - loss: 0.0765 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0282 40/116 [=========>....................] - ETA: 0s - loss: 0.0774 80/116 [===================>..........] - ETA: 0s - loss: 0.0736 116/116 [==============================] - 0s 1ms/step - loss: 0.0745 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0369 41/116 [=========>....................] - ETA: 0s - loss: 0.0697 81/116 [===================>..........] - ETA: 0s - loss: 0.0756 116/116 [==============================] - 0s 1ms/step - loss: 0.0710 -> test with GAN.predict GAN tn, fp: 280, 8 GAN fn, tp: 0, 9 GAN f1 score: 0.692 GAN cohens kappa score: 0.680 -> test with 'LR' LR tn, fp: 280, 8 LR fn, tp: 0, 9 LR f1 score: 0.692 LR cohens kappa score: 0.680 LR average precision score: 0.696 -> 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: 287, 1 GB fn, tp: 3, 6 GB f1 score: 0.750 GB cohens kappa score: 0.743 -> test with 'KNN' KNN tn, fp: 282, 6 KNN fn, tp: 1, 8 KNN f1 score: 0.696 KNN cohens kappa score: 0.684 ------ 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: 17s - loss: 0.2197 42/116 [=========>....................] - ETA: 0s - loss: 0.2801  84/116 [====================>.........] - ETA: 0s - loss: 0.2500 116/116 [==============================] - 0s 1ms/step - loss: 0.2320 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1336 38/116 [========>.....................] - ETA: 0s - loss: 0.1643 77/116 [==================>...........] - ETA: 0s - loss: 0.1587 116/116 [==============================] - 0s 1ms/step - loss: 0.1532 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1881 39/116 [=========>....................] - ETA: 0s - loss: 0.1241 77/116 [==================>...........] - ETA: 0s - loss: 0.1196 116/116 [==============================] - 0s 1ms/step - loss: 0.1217 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0878 43/116 [==========>...................] - ETA: 0s - loss: 0.1005 84/116 [====================>.........] - ETA: 0s - loss: 0.1084 116/116 [==============================] - 0s 1ms/step - loss: 0.1079 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0660 42/116 [=========>....................] - ETA: 0s - loss: 0.0884 82/116 [====================>.........] - ETA: 0s - loss: 0.1013 116/116 [==============================] - 0s 1ms/step - loss: 0.1010 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0700 41/116 [=========>....................] - ETA: 0s - loss: 0.1162 82/116 [====================>.........] - ETA: 0s - loss: 0.0938 116/116 [==============================] - 0s 1ms/step - loss: 0.0978 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.4742 41/116 [=========>....................] - ETA: 0s - loss: 0.1292 81/116 [===================>..........] - ETA: 0s - loss: 0.1014 116/116 [==============================] - 0s 1ms/step - loss: 0.0922 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.3748 42/116 [=========>....................] - ETA: 0s - loss: 0.1025 82/116 [====================>.........] - ETA: 0s - loss: 0.0896 116/116 [==============================] - 0s 1ms/step - loss: 0.0891 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2381 41/116 [=========>....................] - ETA: 0s - loss: 0.0924 82/116 [====================>.........] - ETA: 0s - loss: 0.0893 116/116 [==============================] - 0s 1ms/step - loss: 0.0866 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.4065 42/116 [=========>....................] - ETA: 0s - loss: 0.0833 82/116 [====================>.........] - ETA: 0s - loss: 0.0799 116/116 [==============================] - 0s 1ms/step - loss: 0.0852 -> test with GAN.predict GAN tn, fp: 276, 12 GAN fn, tp: 0, 8 GAN f1 score: 0.571 GAN cohens kappa score: 0.554 -> test with 'LR' LR tn, fp: 272, 16 LR fn, tp: 0, 8 LR f1 score: 0.500 LR cohens kappa score: 0.479 LR average precision score: 0.640 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 1, 7 RF f1 score: 0.933 RF cohens kappa score: 0.932 -> 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: 273, 15 KNN fn, tp: 0, 8 KNN f1 score: 0.516 KNN cohens kappa score: 0.496 ====== 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: 21s - loss: 0.3688 42/116 [=========>....................] - ETA: 0s - loss: 0.3654  83/116 [====================>.........] - ETA: 0s - loss: 0.2998 116/116 [==============================] - 0s 1ms/step - loss: 0.2671 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2327 40/116 [=========>....................] - ETA: 0s - loss: 0.1493 81/116 [===================>..........] - ETA: 0s - loss: 0.1420 116/116 [==============================] - 0s 1ms/step - loss: 0.1368 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1644 39/116 [=========>....................] - ETA: 0s - loss: 0.1137 81/116 [===================>..........] - ETA: 0s - loss: 0.1129 116/116 [==============================] - 0s 1ms/step - loss: 0.1068 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1838 42/116 [=========>....................] - ETA: 0s - loss: 0.1018 84/116 [====================>.........] - ETA: 0s - loss: 0.0982 116/116 [==============================] - 0s 1ms/step - loss: 0.0942 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1060 38/116 [========>.....................] - ETA: 0s - loss: 0.0885 77/116 [==================>...........] - ETA: 0s - loss: 0.0870 116/116 [==============================] - ETA: 0s - loss: 0.0871 116/116 [==============================] - 0s 1ms/step - loss: 0.0871 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0999 39/116 [=========>....................] - ETA: 0s - loss: 0.0959 75/116 [==================>...........] - ETA: 0s - loss: 0.0813 113/116 [============================>.] - ETA: 0s - loss: 0.0851 116/116 [==============================] - 0s 1ms/step - loss: 0.0840 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0381 37/116 [========>.....................] - ETA: 0s - loss: 0.0926 76/116 [==================>...........] - ETA: 0s - loss: 0.0836 116/116 [==============================] - ETA: 0s - loss: 0.0790 116/116 [==============================] - 0s 1ms/step - loss: 0.0790 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0287 40/116 [=========>....................] - ETA: 0s - loss: 0.0844 79/116 [===================>..........] - ETA: 0s - loss: 0.0823 116/116 [==============================] - 0s 1ms/step - loss: 0.0814 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1329 41/116 [=========>....................] - ETA: 0s - loss: 0.0848 81/116 [===================>..........] - ETA: 0s - loss: 0.0774 116/116 [==============================] - 0s 1ms/step - loss: 0.0753 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0183 42/116 [=========>....................] - ETA: 0s - loss: 0.0694 82/116 [====================>.........] - ETA: 0s - loss: 0.0707 116/116 [==============================] - 0s 1ms/step - loss: 0.0723 -> test with GAN.predict GAN tn, fp: 272, 16 GAN fn, tp: 0, 9 GAN f1 score: 0.529 GAN cohens kappa score: 0.507 -> 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: 0.710 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 1, 8 RF f1 score: 0.889 RF cohens kappa score: 0.885 -> test with 'GB' GB tn, fp: 284, 4 GB fn, tp: 0, 9 GB f1 score: 0.818 GB cohens kappa score: 0.811 -> 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 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: 18s - loss: 0.5454 41/116 [=========>....................] - ETA: 0s - loss: 0.3585  82/116 [====================>.........] - ETA: 0s - loss: 0.2861 116/116 [==============================] - 0s 1ms/step - loss: 0.2482 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0838 42/116 [=========>....................] - ETA: 0s - loss: 0.1260 82/116 [====================>.........] - ETA: 0s - loss: 0.1199 116/116 [==============================] - 0s 1ms/step - loss: 0.1158 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0416 42/116 [=========>....................] - ETA: 0s - loss: 0.0817 81/116 [===================>..........] - ETA: 0s - loss: 0.0857 116/116 [==============================] - 0s 1ms/step - loss: 0.0841 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0437 41/116 [=========>....................] - ETA: 0s - loss: 0.0762 82/116 [====================>.........] - ETA: 0s - loss: 0.0727 116/116 [==============================] - 0s 1ms/step - loss: 0.0715 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1181 40/116 [=========>....................] - ETA: 0s - loss: 0.0555 79/116 [===================>..........] - ETA: 0s - loss: 0.0628 116/116 [==============================] - 0s 1ms/step - loss: 0.0649 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0290 41/116 [=========>....................] - ETA: 0s - loss: 0.0651 82/116 [====================>.........] - ETA: 0s - loss: 0.0591 116/116 [==============================] - ETA: 0s - loss: 0.0609 116/116 [==============================] - 0s 1ms/step - loss: 0.0609 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0147 35/116 [========>.....................] - ETA: 0s - loss: 0.0351 66/116 [================>.............] - ETA: 0s - loss: 0.0505 105/116 [==========================>...] - ETA: 0s - loss: 0.0528 116/116 [==============================] - 0s 1ms/step - loss: 0.0562 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0321 41/116 [=========>....................] - ETA: 0s - loss: 0.0422 80/116 [===================>..........] - ETA: 0s - loss: 0.0529 116/116 [==============================] - 0s 1ms/step - loss: 0.0541 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0665 40/116 [=========>....................] - ETA: 0s - loss: 0.0508 81/116 [===================>..........] - ETA: 0s - loss: 0.0514 116/116 [==============================] - 0s 1ms/step - loss: 0.0519 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0444 41/116 [=========>....................] - ETA: 0s - loss: 0.0533 80/116 [===================>..........] - ETA: 0s - loss: 0.0529 116/116 [==============================] - 0s 1ms/step - loss: 0.0506 -> test with GAN.predict GAN tn, fp: 283, 5 GAN fn, tp: 3, 6 GAN f1 score: 0.600 GAN cohens kappa score: 0.586 -> 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: 0.777 -> 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: 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: 0, 9 KNN f1 score: 0.783 KNN cohens kappa score: 0.774 ------ 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: 18s - loss: 0.3089 42/116 [=========>....................] - ETA: 0s - loss: 0.3385  83/116 [====================>.........] - ETA: 0s - loss: 0.2919 116/116 [==============================] - 0s 1ms/step - loss: 0.2608 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0909 42/116 [=========>....................] - ETA: 0s - loss: 0.1550 83/116 [====================>.........] - ETA: 0s - loss: 0.1452 116/116 [==============================] - 0s 1ms/step - loss: 0.1439 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0712 41/116 [=========>....................] - ETA: 0s - loss: 0.1062 81/116 [===================>..........] - ETA: 0s - loss: 0.1183 116/116 [==============================] - 0s 1ms/step - loss: 0.1147 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0801 42/116 [=========>....................] - ETA: 0s - loss: 0.0852 83/116 [====================>.........] - ETA: 0s - loss: 0.0995 116/116 [==============================] - 0s 1ms/step - loss: 0.1042 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0698 42/116 [=========>....................] - ETA: 0s - loss: 0.0856 81/116 [===================>..........] - ETA: 0s - loss: 0.0930 116/116 [==============================] - 0s 1ms/step - loss: 0.0978 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0569 38/116 [========>.....................] - ETA: 0s - loss: 0.1049 79/116 [===================>..........] - ETA: 0s - loss: 0.0994 116/116 [==============================] - 0s 1ms/step - loss: 0.0923 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0688 42/116 [=========>....................] - ETA: 0s - loss: 0.1043 83/116 [====================>.........] - ETA: 0s - loss: 0.0937 116/116 [==============================] - 0s 1ms/step - loss: 0.0885 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0163 41/116 [=========>....................] - ETA: 0s - loss: 0.0952 79/116 [===================>..........] - ETA: 0s - loss: 0.0887 116/116 [==============================] - 0s 1ms/step - loss: 0.0859 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0635 36/116 [========>.....................] - ETA: 0s - loss: 0.0800 71/116 [=================>............] - ETA: 0s - loss: 0.0898 109/116 [===========================>..] - ETA: 0s - loss: 0.0843 116/116 [==============================] - 0s 1ms/step - loss: 0.0828 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0636 41/116 [=========>....................] - ETA: 0s - loss: 0.0925 81/116 [===================>..........] - ETA: 0s - loss: 0.0838 116/116 [==============================] - 0s 1ms/step - loss: 0.0790 -> 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: 277, 11 LR fn, tp: 0, 9 LR f1 score: 0.621 LR cohens kappa score: 0.604 LR average precision score: 0.747 -> 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: 287, 1 GB fn, tp: 2, 7 GB f1 score: 0.824 GB cohens kappa score: 0.818 -> test with 'KNN' KNN tn, fp: 282, 6 KNN fn, tp: 0, 9 KNN f1 score: 0.750 KNN cohens kappa score: 0.740 ------ 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: 21s - loss: 0.3188 40/116 [=========>....................] - ETA: 0s - loss: 0.1700  80/116 [===================>..........] - ETA: 0s - loss: 0.1547 116/116 [==============================] - 0s 1ms/step - loss: 0.1421 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1563 42/116 [=========>....................] - ETA: 0s - loss: 0.1052 81/116 [===================>..........] - ETA: 0s - loss: 0.0927 116/116 [==============================] - 0s 1ms/step - loss: 0.0892 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0460 38/116 [========>.....................] - ETA: 0s - loss: 0.0746 71/116 [=================>............] - ETA: 0s - loss: 0.0733 102/116 [=========================>....] - ETA: 0s - loss: 0.0742 116/116 [==============================] - 0s 2ms/step - loss: 0.0748 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0312 40/116 [=========>....................] - ETA: 0s - loss: 0.0518 80/116 [===================>..........] - ETA: 0s - loss: 0.0650 116/116 [==============================] - 0s 1ms/step - loss: 0.0664 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1667 41/116 [=========>....................] - ETA: 0s - loss: 0.0621 83/116 [====================>.........] - ETA: 0s - loss: 0.0685 116/116 [==============================] - 0s 1ms/step - loss: 0.0624 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0296 42/116 [=========>....................] - ETA: 0s - loss: 0.0759 82/116 [====================>.........] - ETA: 0s - loss: 0.0622 116/116 [==============================] - 0s 1ms/step - loss: 0.0580 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0148 39/116 [=========>....................] - ETA: 0s - loss: 0.0578 80/116 [===================>..........] - ETA: 0s - loss: 0.0579 116/116 [==============================] - 0s 1ms/step - loss: 0.0556 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0529 40/116 [=========>....................] - ETA: 0s - loss: 0.0529 82/116 [====================>.........] - ETA: 0s - loss: 0.0552 116/116 [==============================] - 0s 1ms/step - loss: 0.0550 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0117 43/116 [==========>...................] - ETA: 0s - loss: 0.0548 83/116 [====================>.........] - ETA: 0s - loss: 0.0529 116/116 [==============================] - 0s 1ms/step - loss: 0.0514 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0096 40/116 [=========>....................] - ETA: 0s - loss: 0.0422 80/116 [===================>..........] - ETA: 0s - loss: 0.0471 116/116 [==============================] - 0s 1ms/step - loss: 0.0505 -> test with GAN.predict GAN tn, fp: 284, 4 GAN fn, tp: 3, 6 GAN f1 score: 0.632 GAN cohens kappa score: 0.619 -> test with 'LR' LR tn, fp: 281, 7 LR fn, tp: 3, 6 LR f1 score: 0.545 LR cohens kappa score: 0.529 LR average precision score: 0.600 -> 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: 283, 5 KNN fn, tp: 1, 8 KNN f1 score: 0.727 KNN cohens kappa score: 0.717 ------ 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: 0.3437 42/116 [=========>....................] - ETA: 0s - loss: 0.2813  83/116 [====================>.........] - ETA: 0s - loss: 0.2423 116/116 [==============================] - 0s 1ms/step - loss: 0.2221 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2086 41/116 [=========>....................] - ETA: 0s - loss: 0.1506 81/116 [===================>..........] - ETA: 0s - loss: 0.1379 116/116 [==============================] - 0s 1ms/step - loss: 0.1328 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1675 42/116 [=========>....................] - ETA: 0s - loss: 0.1166 82/116 [====================>.........] - ETA: 0s - loss: 0.1072 116/116 [==============================] - 0s 1ms/step - loss: 0.1051 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0620 43/116 [==========>...................] - ETA: 0s - loss: 0.0887 83/116 [====================>.........] - ETA: 0s - loss: 0.0954 116/116 [==============================] - 0s 1ms/step - loss: 0.0939 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1836 43/116 [==========>...................] - ETA: 0s - loss: 0.0747 80/116 [===================>..........] - ETA: 0s - loss: 0.0832 115/116 [============================>.] - ETA: 0s - loss: 0.0858 116/116 [==============================] - 0s 1ms/step - loss: 0.0861 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0373 38/116 [========>.....................] - ETA: 0s - loss: 0.0820 74/116 [==================>...........] - ETA: 0s - loss: 0.0826 115/116 [============================>.] - ETA: 0s - loss: 0.0824 116/116 [==============================] - 0s 1ms/step - loss: 0.0825 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1426 41/116 [=========>....................] - ETA: 0s - loss: 0.0821 81/116 [===================>..........] - ETA: 0s - loss: 0.0793 116/116 [==============================] - 0s 1ms/step - loss: 0.0776 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2233 42/116 [=========>....................] - ETA: 0s - loss: 0.0872 83/116 [====================>.........] - ETA: 0s - loss: 0.0837 116/116 [==============================] - 0s 1ms/step - loss: 0.0753 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0977 42/116 [=========>....................] - ETA: 0s - loss: 0.0712 83/116 [====================>.........] - ETA: 0s - loss: 0.0746 116/116 [==============================] - 0s 1ms/step - loss: 0.0718 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0173 42/116 [=========>....................] - ETA: 0s - loss: 0.0776 83/116 [====================>.........] - ETA: 0s - loss: 0.0729 116/116 [==============================] - 0s 1ms/step - loss: 0.0722 -> test with GAN.predict GAN tn, fp: 274, 14 GAN fn, tp: 1, 7 GAN f1 score: 0.483 GAN cohens kappa score: 0.462 -> test with 'LR' LR tn, fp: 271, 17 LR fn, tp: 0, 8 LR f1 score: 0.485 LR cohens kappa score: 0.463 LR average precision score: 0.435 -> 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: 1, 7 KNN f1 score: 0.500 KNN cohens kappa score: 0.480 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 281, 18 LR fn, tp: 3, 9 LR f1 score: 0.720 LR cohens kappa score: 0.709 LR average precision score: 0.897 average: LR tn, fp: 275.72, 12.28 LR fn, tp: 0.36, 8.44 LR f1 score: 0.577 LR cohens kappa score: 0.559 LR average precision score: 0.675 minimum: LR tn, fp: 270, 7 LR fn, tp: 0, 6 LR f1 score: 0.457 LR cohens kappa score: 0.432 LR average precision score: 0.320 -----[ RF ]----- maximum: RF tn, fp: 288, 6 RF fn, tp: 6, 8 RF f1 score: 0.941 RF cohens kappa score: 0.939 average: RF tn, fp: 286.52, 1.48 RF fn, tp: 3.12, 5.68 RF f1 score: 0.705 RF cohens kappa score: 0.698 minimum: RF tn, fp: 282, 0 RF fn, tp: 1, 3 RF f1 score: 0.333 RF cohens kappa score: 0.312 -----[ GB ]----- maximum: GB tn, fp: 288, 6 GB fn, tp: 6, 9 GB f1 score: 0.889 GB cohens kappa score: 0.885 average: GB tn, fp: 285.76, 2.24 GB fn, tp: 2.44, 6.36 GB f1 score: 0.731 GB cohens kappa score: 0.723 minimum: GB tn, fp: 282, 0 GB fn, tp: 0, 3 GB f1 score: 0.333 GB cohens kappa score: 0.312 -----[ KNN ]----- maximum: KNN tn, fp: 285, 15 KNN fn, tp: 1, 9 KNN f1 score: 0.857 KNN cohens kappa score: 0.852 average: KNN tn, fp: 278.12, 9.88 KNN fn, tp: 0.24, 8.56 KNN f1 score: 0.640 KNN cohens kappa score: 0.624 minimum: KNN tn, fp: 273, 3 KNN fn, tp: 0, 7 KNN f1 score: 0.500 KNN cohens kappa score: 0.477 -----[ GAN ]----- maximum: GAN tn, fp: 284, 18 GAN fn, tp: 3, 9 GAN f1 score: 0.696 GAN cohens kappa score: 0.684 average: GAN tn, fp: 277.0, 11.0 GAN fn, tp: 1.0, 7.8 GAN f1 score: 0.571 GAN cohens kappa score: 0.553 minimum: GAN tn, fp: 270, 4 GAN fn, tp: 0, 6 GAN f1 score: 0.457 GAN cohens kappa score: 0.432