/////////////////////////////////////////// // Running convGAN-majority-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: 19s - loss: 0.0510 33/116 [=======>......................] - ETA: 0s - loss: 0.0978  68/116 [================>.............] - ETA: 0s - loss: 0.0895 100/116 [========================>.....] - ETA: 0s - loss: 0.0909 116/116 [==============================] - 0s 2ms/step - loss: 0.0920 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0632 33/116 [=======>......................] - ETA: 0s - loss: 0.0889 62/116 [===============>..............] - ETA: 0s - loss: 0.0995 96/116 [=======================>......] - ETA: 0s - loss: 0.0921 116/116 [==============================] - 0s 2ms/step - loss: 0.0913 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0353 36/116 [========>.....................] - ETA: 0s - loss: 0.0976 67/116 [================>.............] - ETA: 0s - loss: 0.0953 97/116 [========================>.....] - ETA: 0s - loss: 0.0899 116/116 [==============================] - 0s 2ms/step - loss: 0.0907 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0399 30/116 [======>.......................] - ETA: 0s - loss: 0.0786 63/116 [===============>..............] - ETA: 0s - loss: 0.0938 97/116 [========================>.....] - ETA: 0s - loss: 0.0893 116/116 [==============================] - 0s 2ms/step - loss: 0.0889 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0366 33/116 [=======>......................] - ETA: 0s - loss: 0.0773 68/116 [================>.............] - ETA: 0s - loss: 0.0815 101/116 [=========================>....] - ETA: 0s - loss: 0.0851 116/116 [==============================] - 0s 2ms/step - loss: 0.0867 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0246 31/116 [=======>......................] - ETA: 0s - loss: 0.0834 65/116 [===============>..............] - ETA: 0s - loss: 0.0895 98/116 [========================>.....] - ETA: 0s - loss: 0.0853 116/116 [==============================] - 0s 2ms/step - loss: 0.0859 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0370 29/116 [======>.......................] - ETA: 0s - loss: 0.0710 57/116 [=============>................] - ETA: 0s - loss: 0.0889 85/116 [====================>.........] - ETA: 0s - loss: 0.0863 116/116 [==============================] - 0s 2ms/step - loss: 0.0867 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0312 31/116 [=======>......................] - ETA: 0s - loss: 0.0834 63/116 [===============>..............] - ETA: 0s - loss: 0.0799 97/116 [========================>.....] - ETA: 0s - loss: 0.0914 116/116 [==============================] - 0s 2ms/step - loss: 0.0844 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1040 33/116 [=======>......................] - ETA: 0s - loss: 0.0801 66/116 [================>.............] - ETA: 0s - loss: 0.0951 99/116 [========================>.....] - ETA: 0s - loss: 0.0870 116/116 [==============================] - 0s 2ms/step - loss: 0.0836 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0166 34/116 [=======>......................] - ETA: 0s - loss: 0.0790 64/116 [===============>..............] - ETA: 0s - loss: 0.0768 94/116 [=======================>......] - ETA: 0s - loss: 0.0756 116/116 [==============================] - 0s 2ms/step - loss: 0.0824 -> 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: 275, 13 LR fn, tp: 1, 8 LR f1 score: 0.533 LR cohens kappa score: 0.513 LR average precision score: 0.876 -> 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: 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: 0, 9 KNN f1 score: 0.750 KNN cohens kappa score: 0.740 ------ 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: 21s - loss: 0.0801 37/116 [========>.....................] - ETA: 0s - loss: 0.0666  73/116 [=================>............] - ETA: 0s - loss: 0.0657 110/116 [===========================>..] - ETA: 0s - loss: 0.0750 116/116 [==============================] - 0s 1ms/step - loss: 0.0744 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2249 36/116 [========>.....................] - ETA: 0s - loss: 0.0499 72/116 [=================>............] - ETA: 0s - loss: 0.0693 108/116 [==========================>...] - ETA: 0s - loss: 0.0728 116/116 [==============================] - 0s 1ms/step - loss: 0.0730 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1034 38/116 [========>.....................] - ETA: 0s - loss: 0.0702 75/116 [==================>...........] - ETA: 0s - loss: 0.0733 111/116 [===========================>..] - ETA: 0s - loss: 0.0722 116/116 [==============================] - 0s 1ms/step - loss: 0.0722 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0266 37/116 [========>.....................] - ETA: 0s - loss: 0.0879 74/116 [==================>...........] - ETA: 0s - loss: 0.0766 115/116 [============================>.] - ETA: 0s - loss: 0.0719 116/116 [==============================] - 0s 1ms/step - loss: 0.0718 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.3760 11/116 [=>............................] - ETA: 0s - loss: 0.0791 40/116 [=========>....................] - ETA: 0s - loss: 0.0825 81/116 [===================>..........] - ETA: 0s - loss: 0.0724 116/116 [==============================] - 0s 2ms/step - loss: 0.0693 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0107 37/116 [========>.....................] - ETA: 0s - loss: 0.0682 79/116 [===================>..........] - ETA: 0s - loss: 0.0665 116/116 [==============================] - 0s 1ms/step - loss: 0.0700 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0578 42/116 [=========>....................] - ETA: 0s - loss: 0.0483 85/116 [====================>.........] - ETA: 0s - loss: 0.0654 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0145 41/116 [=========>....................] - ETA: 0s - loss: 0.0585 83/116 [====================>.........] - ETA: 0s - loss: 0.0602 116/116 [==============================] - 0s 1ms/step - loss: 0.0683 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1089 41/116 [=========>....................] - ETA: 0s - loss: 0.0566 80/116 [===================>..........] - ETA: 0s - loss: 0.0612 116/116 [==============================] - 0s 1ms/step - loss: 0.0662 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0720 43/116 [==========>...................] - ETA: 0s - loss: 0.0580 84/116 [====================>.........] - ETA: 0s - loss: 0.0678 116/116 [==============================] - 0s 1ms/step - loss: 0.0659 -> 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: 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: 285, 3 GB fn, tp: 1, 8 GB f1 score: 0.800 GB cohens kappa score: 0.793 -> 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 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: 22s - loss: 0.0072 32/116 [=======>......................] - ETA: 0s - loss: 0.0748  65/116 [===============>..............] - ETA: 0s - loss: 0.0868 97/116 [========================>.....] - ETA: 0s - loss: 0.0751 116/116 [==============================] - 0s 2ms/step - loss: 0.0735 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0216 33/116 [=======>......................] - ETA: 0s - loss: 0.0833 64/116 [===============>..............] - ETA: 0s - loss: 0.0695 97/116 [========================>.....] - ETA: 0s - loss: 0.0729 116/116 [==============================] - 0s 2ms/step - loss: 0.0715 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0391 34/116 [=======>......................] - ETA: 0s - loss: 0.0717 67/116 [================>.............] - ETA: 0s - loss: 0.0758 101/116 [=========================>....] - ETA: 0s - loss: 0.0731 116/116 [==============================] - 0s 2ms/step - loss: 0.0701 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0079 34/116 [=======>......................] - ETA: 0s - loss: 0.0631 66/116 [================>.............] - ETA: 0s - loss: 0.0661 98/116 [========================>.....] - ETA: 0s - loss: 0.0693 116/116 [==============================] - 0s 2ms/step - loss: 0.0701 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0387 32/116 [=======>......................] - ETA: 0s - loss: 0.0673 63/116 [===============>..............] - ETA: 0s - loss: 0.0744 94/116 [=======================>......] - ETA: 0s - loss: 0.0702 116/116 [==============================] - 0s 2ms/step - loss: 0.0692 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0874 33/116 [=======>......................] - ETA: 0s - loss: 0.0610 63/116 [===============>..............] - ETA: 0s - loss: 0.0546 95/116 [=======================>......] - ETA: 0s - loss: 0.0692 116/116 [==============================] - 0s 2ms/step - loss: 0.0687 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0299 32/116 [=======>......................] - ETA: 0s - loss: 0.0678 65/116 [===============>..............] - ETA: 0s - loss: 0.0713 100/116 [========================>.....] - ETA: 0s - loss: 0.0712 116/116 [==============================] - 0s 1ms/step - loss: 0.0696 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2908 32/116 [=======>......................] - ETA: 0s - loss: 0.0850 64/116 [===============>..............] - ETA: 0s - loss: 0.0694 96/116 [=======================>......] - ETA: 0s - loss: 0.0672 116/116 [==============================] - 0s 2ms/step - loss: 0.0660 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0179 37/116 [========>.....................] - ETA: 0s - loss: 0.0680 69/116 [================>.............] - ETA: 0s - loss: 0.0766 100/116 [========================>.....] - ETA: 0s - loss: 0.0707 116/116 [==============================] - 0s 2ms/step - loss: 0.0651 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1692 36/116 [========>.....................] - ETA: 0s - loss: 0.0644 68/116 [================>.............] - ETA: 0s - loss: 0.0744 102/116 [=========================>....] - ETA: 0s - loss: 0.0684 116/116 [==============================] - 0s 2ms/step - loss: 0.0676 -> test with GAN.predict GAN tn, fp: 277, 11 GAN fn, tp: 1, 8 GAN f1 score: 0.571 GAN cohens kappa score: 0.553 -> 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: 0.587 -> test with 'RF' RF tn, fp: 286, 2 RF fn, tp: 4, 5 RF f1 score: 0.625 RF cohens kappa score: 0.615 -> 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: 277, 11 KNN fn, tp: 1, 8 KNN f1 score: 0.571 KNN cohens kappa score: 0.553 ------ 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: 19s - loss: 0.0876 39/116 [=========>....................] - ETA: 0s - loss: 0.0756  75/116 [==================>...........] - ETA: 0s - loss: 0.0741 111/116 [===========================>..] - ETA: 0s - loss: 0.0780 116/116 [==============================] - 0s 1ms/step - loss: 0.0785 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0191 37/116 [========>.....................] - ETA: 0s - loss: 0.0569 69/116 [================>.............] - ETA: 0s - loss: 0.0597 101/116 [=========================>....] - ETA: 0s - loss: 0.0721 116/116 [==============================] - 0s 2ms/step - loss: 0.0754 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0424 36/116 [========>.....................] - ETA: 0s - loss: 0.0610 67/116 [================>.............] - ETA: 0s - loss: 0.0762 99/116 [========================>.....] - ETA: 0s - loss: 0.0703 116/116 [==============================] - 0s 2ms/step - loss: 0.0755 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0217 36/116 [========>.....................] - ETA: 0s - loss: 0.0530 73/116 [=================>............] - ETA: 0s - loss: 0.0580 110/116 [===========================>..] - ETA: 0s - loss: 0.0717 116/116 [==============================] - 0s 1ms/step - loss: 0.0742 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0300 35/116 [========>.....................] - ETA: 0s - loss: 0.0601 73/116 [=================>............] - ETA: 0s - loss: 0.0766 111/116 [===========================>..] - ETA: 0s - loss: 0.0744 116/116 [==============================] - 0s 1ms/step - loss: 0.0732 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0071 39/116 [=========>....................] - ETA: 0s - loss: 0.0844 76/116 [==================>...........] - ETA: 0s - loss: 0.0812 109/116 [===========================>..] - ETA: 0s - loss: 0.0739 116/116 [==============================] - 0s 1ms/step - loss: 0.0720 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0398 35/116 [========>.....................] - ETA: 0s - loss: 0.0607 69/116 [================>.............] - ETA: 0s - loss: 0.0646 101/116 [=========================>....] - ETA: 0s - loss: 0.0724 116/116 [==============================] - 0s 2ms/step - loss: 0.0729 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2263 38/116 [========>.....................] - ETA: 0s - loss: 0.0645 70/116 [=================>............] - ETA: 0s - loss: 0.0723 101/116 [=========================>....] - ETA: 0s - loss: 0.0747 116/116 [==============================] - 0s 2ms/step - loss: 0.0724 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0389 35/116 [========>.....................] - ETA: 0s - loss: 0.0692 72/116 [=================>............] - ETA: 0s - loss: 0.0673 108/116 [==========================>...] - ETA: 0s - loss: 0.0713 116/116 [==============================] - 0s 1ms/step - loss: 0.0704 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2030 36/116 [========>.....................] - ETA: 0s - loss: 0.0595 72/116 [=================>............] - ETA: 0s - loss: 0.0710 107/116 [==========================>...] - ETA: 0s - loss: 0.0699 116/116 [==============================] - 0s 1ms/step - loss: 0.0694 -> 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: 281, 7 LR fn, tp: 0, 9 LR f1 score: 0.720 LR cohens kappa score: 0.709 LR average precision score: 0.771 -> 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: 4, 5 GB f1 score: 0.714 GB cohens kappa score: 0.708 -> 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 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: 19s - loss: 0.0736 38/116 [========>.....................] - ETA: 0s - loss: 0.0821  74/116 [==================>...........] - ETA: 0s - loss: 0.0858 110/116 [===========================>..] - ETA: 0s - loss: 0.0823 116/116 [==============================] - 0s 1ms/step - loss: 0.0807 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0460 35/116 [========>.....................] - ETA: 0s - loss: 0.0727 71/116 [=================>............] - ETA: 0s - loss: 0.0786 106/116 [==========================>...] - ETA: 0s - loss: 0.0831 116/116 [==============================] - 0s 1ms/step - loss: 0.0793 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0640 33/116 [=======>......................] - ETA: 0s - loss: 0.0987 67/116 [================>.............] - ETA: 0s - loss: 0.0957 102/116 [=========================>....] - ETA: 0s - loss: 0.0807 116/116 [==============================] - 0s 1ms/step - loss: 0.0778 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0157 39/116 [=========>....................] - ETA: 0s - loss: 0.0762 78/116 [===================>..........] - ETA: 0s - loss: 0.0853 113/116 [============================>.] - ETA: 0s - loss: 0.0792 116/116 [==============================] - 0s 1ms/step - loss: 0.0783 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1219 38/116 [========>.....................] - ETA: 0s - loss: 0.0805 75/116 [==================>...........] - ETA: 0s - loss: 0.0724 112/116 [===========================>..] - ETA: 0s - loss: 0.0733 116/116 [==============================] - 0s 1ms/step - loss: 0.0764 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2731 37/116 [========>.....................] - ETA: 0s - loss: 0.0737 75/116 [==================>...........] - ETA: 0s - loss: 0.0747 113/116 [============================>.] - ETA: 0s - loss: 0.0765 116/116 [==============================] - 0s 1ms/step - loss: 0.0762 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1061 38/116 [========>.....................] - ETA: 0s - loss: 0.0782 75/116 [==================>...........] - ETA: 0s - loss: 0.0715 109/116 [===========================>..] - ETA: 0s - loss: 0.0716 116/116 [==============================] - 0s 1ms/step - loss: 0.0747 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0442 39/116 [=========>....................] - ETA: 0s - loss: 0.0681 76/116 [==================>...........] - ETA: 0s - loss: 0.0821 113/116 [============================>.] - ETA: 0s - loss: 0.0762 116/116 [==============================] - 0s 1ms/step - loss: 0.0763 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1021 39/116 [=========>....................] - ETA: 0s - loss: 0.0668 77/116 [==================>...........] - ETA: 0s - loss: 0.0714 115/116 [============================>.] - ETA: 0s - loss: 0.0739 116/116 [==============================] - 0s 1ms/step - loss: 0.0738 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0057 39/116 [=========>....................] - ETA: 0s - loss: 0.0706 73/116 [=================>............] - ETA: 0s - loss: 0.0647 109/116 [===========================>..] - ETA: 0s - loss: 0.0745 116/116 [==============================] - 0s 1ms/step - loss: 0.0727 -> test with GAN.predict GAN tn, fp: 273, 15 GAN fn, tp: 0, 8 GAN f1 score: 0.516 GAN cohens kappa score: 0.496 -> 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: 0.689 -> 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: 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: 20s - loss: 0.0392 36/116 [========>.....................] - ETA: 0s - loss: 0.0744  72/116 [=================>............] - ETA: 0s - loss: 0.0822 108/116 [==========================>...] - ETA: 0s - loss: 0.0899 116/116 [==============================] - 0s 1ms/step - loss: 0.0890 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0466 37/116 [========>.....................] - ETA: 0s - loss: 0.0854 72/116 [=================>............] - ETA: 0s - loss: 0.0898 109/116 [===========================>..] - ETA: 0s - loss: 0.0882 116/116 [==============================] - 0s 1ms/step - loss: 0.0875 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1701 35/116 [========>.....................] - ETA: 0s - loss: 0.0893 70/116 [=================>............] - ETA: 0s - loss: 0.0907 104/116 [=========================>....] - ETA: 0s - loss: 0.0851 116/116 [==============================] - 0s 1ms/step - loss: 0.0860 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0119 34/116 [=======>......................] - ETA: 0s - loss: 0.0858 70/116 [=================>............] - ETA: 0s - loss: 0.0928 105/116 [==========================>...] - ETA: 0s - loss: 0.0845 116/116 [==============================] - 0s 1ms/step - loss: 0.0838 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0175 32/116 [=======>......................] - ETA: 0s - loss: 0.1113 64/116 [===============>..............] - ETA: 0s - loss: 0.0949 99/116 [========================>.....] - ETA: 0s - loss: 0.0911 116/116 [==============================] - 0s 2ms/step - loss: 0.0844 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0343 38/116 [========>.....................] - ETA: 0s - loss: 0.0970 74/116 [==================>...........] - ETA: 0s - loss: 0.0860 110/116 [===========================>..] - ETA: 0s - loss: 0.0839 116/116 [==============================] - 0s 1ms/step - loss: 0.0818 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1001 36/116 [========>.....................] - ETA: 0s - loss: 0.0797 70/116 [=================>............] - ETA: 0s - loss: 0.0793 105/116 [==========================>...] - ETA: 0s - loss: 0.0806 116/116 [==============================] - 0s 1ms/step - loss: 0.0800 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.4191 35/116 [========>.....................] - ETA: 0s - loss: 0.0779 69/116 [================>.............] - ETA: 0s - loss: 0.0832 102/116 [=========================>....] - ETA: 0s - loss: 0.0805 116/116 [==============================] - 0s 1ms/step - loss: 0.0784 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0181 35/116 [========>.....................] - ETA: 0s - loss: 0.1065 72/116 [=================>............] - ETA: 0s - loss: 0.0937 107/116 [==========================>...] - ETA: 0s - loss: 0.0795 116/116 [==============================] - 0s 1ms/step - loss: 0.0782 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0344 34/116 [=======>......................] - ETA: 0s - loss: 0.0835 71/116 [=================>............] - ETA: 0s - loss: 0.0822 108/116 [==========================>...] - ETA: 0s - loss: 0.0782 116/116 [==============================] - 0s 1ms/step - loss: 0.0774 -> test with GAN.predict GAN tn, fp: 276, 12 GAN fn, tp: 1, 8 GAN f1 score: 0.552 GAN cohens kappa score: 0.532 -> 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: 0.655 -> 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: 286, 2 GB fn, tp: 1, 8 GB f1 score: 0.842 GB cohens kappa score: 0.837 -> 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 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: 0.0272 37/116 [========>.....................] - ETA: 0s - loss: 0.0671  73/116 [=================>............] - ETA: 0s - loss: 0.0684 110/116 [===========================>..] - ETA: 0s - loss: 0.0775 116/116 [==============================] - 0s 1ms/step - loss: 0.0776 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0180 37/116 [========>.....................] - ETA: 0s - loss: 0.0812 75/116 [==================>...........] - ETA: 0s - loss: 0.0765 113/116 [============================>.] - ETA: 0s - loss: 0.0742 116/116 [==============================] - 0s 1ms/step - loss: 0.0746 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0417 39/116 [=========>....................] - ETA: 0s - loss: 0.0851 77/116 [==================>...........] - ETA: 0s - loss: 0.0800 114/116 [============================>.] - ETA: 0s - loss: 0.0747 116/116 [==============================] - 0s 1ms/step - loss: 0.0751 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0207 38/116 [========>.....................] - ETA: 0s - loss: 0.0847 76/116 [==================>...........] - ETA: 0s - loss: 0.0816 114/116 [============================>.] - ETA: 0s - loss: 0.0727 116/116 [==============================] - 0s 1ms/step - loss: 0.0725 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2582 38/116 [========>.....................] - ETA: 0s - loss: 0.0718 75/116 [==================>...........] - ETA: 0s - loss: 0.0723 111/116 [===========================>..] - ETA: 0s - loss: 0.0705 116/116 [==============================] - 0s 1ms/step - loss: 0.0695 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0506 40/116 [=========>....................] - ETA: 0s - loss: 0.0863 79/116 [===================>..........] - ETA: 0s - loss: 0.0660 116/116 [==============================] - ETA: 0s - loss: 0.0678 116/116 [==============================] - 0s 1ms/step - loss: 0.0678 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0269 38/116 [========>.....................] - ETA: 0s - loss: 0.0775 74/116 [==================>...........] - ETA: 0s - loss: 0.0759 110/116 [===========================>..] - ETA: 0s - loss: 0.0653 116/116 [==============================] - 0s 1ms/step - loss: 0.0643 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0177 32/116 [=======>......................] - ETA: 0s - loss: 0.0840 61/116 [==============>...............] - ETA: 0s - loss: 0.0761 92/116 [======================>.......] - ETA: 0s - loss: 0.0666 116/116 [==============================] - 0s 2ms/step - loss: 0.0629 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0890 39/116 [=========>....................] - ETA: 0s - loss: 0.0686 72/116 [=================>............] - ETA: 0s - loss: 0.0662 108/116 [==========================>...] - ETA: 0s - loss: 0.0601 116/116 [==============================] - 0s 1ms/step - loss: 0.0625 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0261 37/116 [========>.....................] - ETA: 0s - loss: 0.0568 75/116 [==================>...........] - ETA: 0s - loss: 0.0595 113/116 [============================>.] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 1ms/step - loss: 0.0603 -> test with GAN.predict GAN tn, fp: 277, 11 GAN fn, tp: 2, 7 GAN f1 score: 0.519 GAN cohens kappa score: 0.498 -> test with 'LR' LR tn, fp: 271, 17 LR fn, tp: 1, 8 LR f1 score: 0.471 LR cohens kappa score: 0.446 LR average precision score: 0.343 -> test with 'RF' RF tn, fp: 283, 5 RF fn, tp: 6, 3 RF f1 score: 0.353 RF cohens kappa score: 0.334 -> test with 'GB' GB tn, fp: 283, 5 GB fn, tp: 6, 3 GB f1 score: 0.353 GB cohens kappa score: 0.334 -> 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 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: 0.0376 39/116 [=========>....................] - ETA: 0s - loss: 0.0903  71/116 [=================>............] - ETA: 0s - loss: 0.0833 111/116 [===========================>..] - ETA: 0s - loss: 0.0873 116/116 [==============================] - 0s 1ms/step - loss: 0.0859 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0903 39/116 [=========>....................] - ETA: 0s - loss: 0.0659 77/116 [==================>...........] - ETA: 0s - loss: 0.0764 115/116 [============================>.] - ETA: 0s - loss: 0.0848 116/116 [==============================] - 0s 1ms/step - loss: 0.0847 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0585 41/116 [=========>....................] - ETA: 0s - loss: 0.0868 80/116 [===================>..........] - ETA: 0s - loss: 0.0864 116/116 [==============================] - 0s 1ms/step - loss: 0.0830 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0267 41/116 [=========>....................] - ETA: 0s - loss: 0.1050 78/116 [===================>..........] - ETA: 0s - loss: 0.0880 116/116 [==============================] - 0s 1ms/step - loss: 0.0822 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1661 40/116 [=========>....................] - ETA: 0s - loss: 0.0836 83/116 [====================>.........] - ETA: 0s - loss: 0.0737 116/116 [==============================] - 0s 1ms/step - loss: 0.0811 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0286 41/116 [=========>....................] - ETA: 0s - loss: 0.0866 81/116 [===================>..........] - ETA: 0s - loss: 0.0873 116/116 [==============================] - 0s 1ms/step - loss: 0.0816 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0183 40/116 [=========>....................] - ETA: 0s - loss: 0.0824 77/116 [==================>...........] - ETA: 0s - loss: 0.0830 116/116 [==============================] - ETA: 0s - loss: 0.0802 116/116 [==============================] - 0s 1ms/step - loss: 0.0802 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0367 38/116 [========>.....................] - ETA: 0s - loss: 0.0837 77/116 [==================>...........] - ETA: 0s - loss: 0.0817 115/116 [============================>.] - ETA: 0s - loss: 0.0799 116/116 [==============================] - 0s 1ms/step - loss: 0.0798 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0486 40/116 [=========>....................] - ETA: 0s - loss: 0.0758 79/116 [===================>..........] - ETA: 0s - loss: 0.0805 116/116 [==============================] - 0s 1ms/step - loss: 0.0798 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1113 40/116 [=========>....................] - ETA: 0s - loss: 0.0673 79/116 [===================>..........] - ETA: 0s - loss: 0.0652 116/116 [==============================] - 0s 1ms/step - loss: 0.0762 -> 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: 1, 8 LR f1 score: 0.667 LR cohens kappa score: 0.654 LR average precision score: 0.741 -> test with 'RF' RF tn, fp: 288, 0 RF fn, tp: 2, 7 RF f1 score: 0.875 RF cohens kappa score: 0.872 -> 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: 18s - loss: 0.0547 38/116 [========>.....................] - ETA: 0s - loss: 0.0942  76/116 [==================>...........] - ETA: 0s - loss: 0.0856 111/116 [===========================>..] - ETA: 0s - loss: 0.0936 116/116 [==============================] - 0s 1ms/step - loss: 0.0926 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0186 36/116 [========>.....................] - ETA: 0s - loss: 0.0833 75/116 [==================>...........] - ETA: 0s - loss: 0.0981 113/116 [============================>.] - ETA: 0s - loss: 0.0916 116/116 [==============================] - 0s 1ms/step - loss: 0.0908 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1832 37/116 [========>.....................] - ETA: 0s - loss: 0.0733 68/116 [================>.............] - ETA: 0s - loss: 0.0850 98/116 [========================>.....] - ETA: 0s - loss: 0.0874 116/116 [==============================] - 0s 2ms/step - loss: 0.0895 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1133 39/116 [=========>....................] - ETA: 0s - loss: 0.0865 77/116 [==================>...........] - ETA: 0s - loss: 0.0861 115/116 [============================>.] - ETA: 0s - loss: 0.0882 116/116 [==============================] - 0s 1ms/step - loss: 0.0888 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0572 40/116 [=========>....................] - ETA: 0s - loss: 0.1102 78/116 [===================>..........] - ETA: 0s - loss: 0.0955 116/116 [==============================] - 0s 1ms/step - loss: 0.0873 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0906 37/116 [========>.....................] - ETA: 0s - loss: 0.0992 74/116 [==================>...........] - ETA: 0s - loss: 0.0847 110/116 [===========================>..] - ETA: 0s - loss: 0.0886 116/116 [==============================] - 0s 1ms/step - loss: 0.0880 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2560 40/116 [=========>....................] - ETA: 0s - loss: 0.0884 80/116 [===================>..........] - ETA: 0s - loss: 0.0831 116/116 [==============================] - 0s 1ms/step - loss: 0.0846 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0204 39/116 [=========>....................] - ETA: 0s - loss: 0.0795 77/116 [==================>...........] - ETA: 0s - loss: 0.0780 115/116 [============================>.] - ETA: 0s - loss: 0.0839 116/116 [==============================] - 0s 1ms/step - loss: 0.0846 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0720 40/116 [=========>....................] - ETA: 0s - loss: 0.0806 78/116 [===================>..........] - ETA: 0s - loss: 0.0831 114/116 [============================>.] - ETA: 0s - loss: 0.0843 116/116 [==============================] - 0s 1ms/step - loss: 0.0836 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0262 39/116 [=========>....................] - ETA: 0s - loss: 0.0897 77/116 [==================>...........] - ETA: 0s - loss: 0.0850 116/116 [==============================] - 0s 1ms/step - loss: 0.0831 -> test with GAN.predict GAN tn, fp: 274, 14 GAN fn, tp: 0, 9 GAN f1 score: 0.562 GAN cohens kappa score: 0.543 -> 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: 0.878 -> 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: 2, 7 GB f1 score: 0.737 GB cohens kappa score: 0.728 -> 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 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: 0.2000 39/116 [=========>....................] - ETA: 0s - loss: 0.0774  78/116 [===================>..........] - ETA: 0s - loss: 0.0745 116/116 [==============================] - ETA: 0s - loss: 0.0723 116/116 [==============================] - 0s 1ms/step - loss: 0.0723 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0813 39/116 [=========>....................] - ETA: 0s - loss: 0.0649 79/116 [===================>..........] - ETA: 0s - loss: 0.0687 116/116 [==============================] - 0s 1ms/step - loss: 0.0727 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0896 40/116 [=========>....................] - ETA: 0s - loss: 0.0511 78/116 [===================>..........] - ETA: 0s - loss: 0.0595 116/116 [==============================] - ETA: 0s - loss: 0.0707 116/116 [==============================] - 0s 1ms/step - loss: 0.0707 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1048 40/116 [=========>....................] - ETA: 0s - loss: 0.0811 80/116 [===================>..........] - ETA: 0s - loss: 0.0757 116/116 [==============================] - 0s 1ms/step - loss: 0.0687 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0550 39/116 [=========>....................] - ETA: 0s - loss: 0.0615 76/116 [==================>...........] - ETA: 0s - loss: 0.0614 116/116 [==============================] - ETA: 0s - loss: 0.0681 116/116 [==============================] - 0s 1ms/step - loss: 0.0681 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0176 39/116 [=========>....................] - ETA: 0s - loss: 0.0748 77/116 [==================>...........] - ETA: 0s - loss: 0.0656 115/116 [============================>.] - ETA: 0s - loss: 0.0662 116/116 [==============================] - 0s 1ms/step - loss: 0.0679 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1177 38/116 [========>.....................] - ETA: 0s - loss: 0.0774 78/116 [===================>..........] - ETA: 0s - loss: 0.0735 116/116 [==============================] - ETA: 0s - loss: 0.0671 116/116 [==============================] - 0s 1ms/step - loss: 0.0671 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0177 40/116 [=========>....................] - ETA: 0s - loss: 0.0650 79/116 [===================>..........] - ETA: 0s - loss: 0.0612 116/116 [==============================] - 0s 1ms/step - loss: 0.0676 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1616 40/116 [=========>....................] - ETA: 0s - loss: 0.0694 78/116 [===================>..........] - ETA: 0s - loss: 0.0693 112/116 [===========================>..] - ETA: 0s - loss: 0.0662 116/116 [==============================] - 0s 1ms/step - loss: 0.0656 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2012 37/116 [========>.....................] - ETA: 0s - loss: 0.0522 69/116 [================>.............] - ETA: 0s - loss: 0.0568 108/116 [==========================>...] - ETA: 0s - loss: 0.0672 116/116 [==============================] - 0s 1ms/step - loss: 0.0647 -> test with GAN.predict GAN tn, fp: 278, 10 GAN fn, tp: 0, 8 GAN f1 score: 0.615 GAN cohens kappa score: 0.600 -> 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: 0.614 -> test with 'RF' RF tn, fp: 287, 1 RF fn, tp: 6, 2 RF f1 score: 0.364 RF cohens kappa score: 0.354 -> test with 'GB' GB tn, fp: 286, 2 GB fn, tp: 5, 3 GB f1 score: 0.462 GB cohens kappa score: 0.450 -> 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: 18s - loss: 0.0281 42/116 [=========>....................] - ETA: 0s - loss: 0.0725  79/116 [===================>..........] - ETA: 0s - loss: 0.0837 115/116 [============================>.] - ETA: 0s - loss: 0.0821 116/116 [==============================] - 0s 1ms/step - loss: 0.0823 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0394 38/116 [========>.....................] - ETA: 0s - loss: 0.0607 75/116 [==================>...........] - ETA: 0s - loss: 0.0768 113/116 [============================>.] - ETA: 0s - loss: 0.0829 116/116 [==============================] - 0s 1ms/step - loss: 0.0816 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0179 42/116 [=========>....................] - ETA: 0s - loss: 0.0730 83/116 [====================>.........] - ETA: 0s - loss: 0.0810 116/116 [==============================] - 0s 1ms/step - loss: 0.0818 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0763 39/116 [=========>....................] - ETA: 0s - loss: 0.0706 76/116 [==================>...........] - ETA: 0s - loss: 0.0797 114/116 [============================>.] - ETA: 0s - loss: 0.0796 116/116 [==============================] - 0s 1ms/step - loss: 0.0790 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0248 40/116 [=========>....................] - ETA: 0s - loss: 0.0666 77/116 [==================>...........] - ETA: 0s - loss: 0.0739 115/116 [============================>.] - ETA: 0s - loss: 0.0779 116/116 [==============================] - 0s 1ms/step - loss: 0.0778 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2806 36/116 [========>.....................] - ETA: 0s - loss: 0.0633 72/116 [=================>............] - ETA: 0s - loss: 0.0727 106/116 [==========================>...] - ETA: 0s - loss: 0.0765 116/116 [==============================] - 0s 1ms/step - loss: 0.0756 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2936 39/116 [=========>....................] - ETA: 0s - loss: 0.0694 76/116 [==================>...........] - ETA: 0s - loss: 0.0760 115/116 [============================>.] - ETA: 0s - loss: 0.0747 116/116 [==============================] - 0s 1ms/step - loss: 0.0765 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1070 40/116 [=========>....................] - ETA: 0s - loss: 0.0720 77/116 [==================>...........] - ETA: 0s - loss: 0.0729 115/116 [============================>.] - ETA: 0s - loss: 0.0743 116/116 [==============================] - 0s 1ms/step - loss: 0.0742 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0266 41/116 [=========>....................] - ETA: 0s - loss: 0.0622 81/116 [===================>..........] - ETA: 0s - loss: 0.0695 116/116 [==============================] - 0s 1ms/step - loss: 0.0733 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1200 39/116 [=========>....................] - ETA: 0s - loss: 0.0721 77/116 [==================>...........] - ETA: 0s - loss: 0.0668 114/116 [============================>.] - ETA: 0s - loss: 0.0727 116/116 [==============================] - 0s 1ms/step - loss: 0.0723 -> test with GAN.predict GAN tn, fp: 272, 16 GAN fn, tp: 1, 8 GAN f1 score: 0.485 GAN cohens kappa score: 0.461 -> 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: 0.673 -> 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: 3, 6 GB f1 score: 0.706 GB cohens kappa score: 0.697 -> 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: 21s - loss: 0.2115 37/116 [========>.....................] - ETA: 0s - loss: 0.0821  77/116 [==================>...........] - ETA: 0s - loss: 0.0805 115/116 [============================>.] - ETA: 0s - loss: 0.0755 116/116 [==============================] - 0s 1ms/step - loss: 0.0756 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0131 39/116 [=========>....................] - ETA: 0s - loss: 0.0744 78/116 [===================>..........] - ETA: 0s - loss: 0.0758 115/116 [============================>.] - ETA: 0s - loss: 0.0756 116/116 [==============================] - 0s 1ms/step - loss: 0.0756 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0428 36/116 [========>.....................] - ETA: 0s - loss: 0.0708 73/116 [=================>............] - ETA: 0s - loss: 0.0764 111/116 [===========================>..] - ETA: 0s - loss: 0.0744 116/116 [==============================] - 0s 1ms/step - loss: 0.0730 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0177 40/116 [=========>....................] - ETA: 0s - loss: 0.0682 79/116 [===================>..........] - ETA: 0s - loss: 0.0701 116/116 [==============================] - 0s 1ms/step - loss: 0.0720 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0129 39/116 [=========>....................] - ETA: 0s - loss: 0.0807 75/116 [==================>...........] - ETA: 0s - loss: 0.0786 113/116 [============================>.] - ETA: 0s - loss: 0.0725 116/116 [==============================] - 0s 1ms/step - loss: 0.0714 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1297 38/116 [========>.....................] - ETA: 0s - loss: 0.0783 73/116 [=================>............] - ETA: 0s - loss: 0.0632 104/116 [=========================>....] - ETA: 0s - loss: 0.0671 116/116 [==============================] - 0s 1ms/step - loss: 0.0701 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1273 34/116 [=======>......................] - ETA: 0s - loss: 0.0738 69/116 [================>.............] - ETA: 0s - loss: 0.0678 106/116 [==========================>...] - ETA: 0s - loss: 0.0718 116/116 [==============================] - 0s 1ms/step - loss: 0.0693 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0163 40/116 [=========>....................] - ETA: 0s - loss: 0.0600 79/116 [===================>..........] - ETA: 0s - loss: 0.0676 116/116 [==============================] - 0s 1ms/step - loss: 0.0684 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0132 39/116 [=========>....................] - ETA: 0s - loss: 0.0563 78/116 [===================>..........] - ETA: 0s - loss: 0.0623 116/116 [==============================] - ETA: 0s - loss: 0.0664 116/116 [==============================] - 0s 1ms/step - loss: 0.0664 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0656 39/116 [=========>....................] - ETA: 0s - loss: 0.0829 78/116 [===================>..........] - ETA: 0s - loss: 0.0690 116/116 [==============================] - ETA: 0s - loss: 0.0665 116/116 [==============================] - 0s 1ms/step - loss: 0.0665 -> test with GAN.predict GAN tn, fp: 274, 14 GAN fn, tp: 0, 9 GAN f1 score: 0.562 GAN cohens kappa score: 0.543 -> 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: 0.708 -> 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: 286, 2 GB fn, tp: 3, 6 GB f1 score: 0.706 GB cohens kappa score: 0.697 -> test with 'KNN' KNN tn, fp: 277, 11 KNN fn, tp: 1, 8 KNN f1 score: 0.571 KNN cohens kappa score: 0.553 ------ 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: 21s - loss: 0.0241 39/116 [=========>....................] - ETA: 0s - loss: 0.0846  76/116 [==================>...........] - ETA: 0s - loss: 0.0844 115/116 [============================>.] - ETA: 0s - loss: 0.0826 116/116 [==============================] - 0s 1ms/step - loss: 0.0825 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0257 38/116 [========>.....................] - ETA: 0s - loss: 0.0800 76/116 [==================>...........] - ETA: 0s - loss: 0.0815 113/116 [============================>.] - ETA: 0s - loss: 0.0812 116/116 [==============================] - 0s 1ms/step - loss: 0.0799 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0602 34/116 [=======>......................] - ETA: 0s - loss: 0.0687 64/116 [===============>..............] - ETA: 0s - loss: 0.0758 98/116 [========================>.....] - ETA: 0s - loss: 0.0820 116/116 [==============================] - 0s 2ms/step - loss: 0.0793 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0197 39/116 [=========>....................] - ETA: 0s - loss: 0.0834 78/116 [===================>..........] - ETA: 0s - loss: 0.0835 115/116 [============================>.] - ETA: 0s - loss: 0.0780 116/116 [==============================] - 0s 1ms/step - loss: 0.0779 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0153 37/116 [========>.....................] - ETA: 0s - loss: 0.0655 74/116 [==================>...........] - ETA: 0s - loss: 0.0683 112/116 [===========================>..] - ETA: 0s - loss: 0.0782 116/116 [==============================] - 0s 1ms/step - loss: 0.0773 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1583 38/116 [========>.....................] - ETA: 0s - loss: 0.0659 73/116 [=================>............] - ETA: 0s - loss: 0.0742 110/116 [===========================>..] - ETA: 0s - loss: 0.0718 116/116 [==============================] - 0s 1ms/step - loss: 0.0755 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0164 39/116 [=========>....................] - ETA: 0s - loss: 0.0730 76/116 [==================>...........] - ETA: 0s - loss: 0.0732 114/116 [============================>.] - ETA: 0s - loss: 0.0738 116/116 [==============================] - 0s 1ms/step - loss: 0.0740 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0613 38/116 [========>.....................] - ETA: 0s - loss: 0.0487 76/116 [==================>...........] - ETA: 0s - loss: 0.0610 112/116 [===========================>..] - ETA: 0s - loss: 0.0742 116/116 [==============================] - 0s 1ms/step - loss: 0.0741 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0306 38/116 [========>.....................] - ETA: 0s - loss: 0.0757 76/116 [==================>...........] - ETA: 0s - loss: 0.0692 112/116 [===========================>..] - ETA: 0s - loss: 0.0730 116/116 [==============================] - 0s 1ms/step - loss: 0.0727 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0173 39/116 [=========>....................] - ETA: 0s - loss: 0.0779 76/116 [==================>...........] - ETA: 0s - loss: 0.0778 114/116 [============================>.] - ETA: 0s - loss: 0.0714 116/116 [==============================] - 0s 1ms/step - loss: 0.0711 -> 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: 281, 7 LR fn, tp: 1, 8 LR f1 score: 0.667 LR cohens kappa score: 0.654 LR average precision score: 0.813 -> 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: 284, 4 KNN fn, tp: 0, 9 KNN f1 score: 0.818 KNN cohens kappa score: 0.811 ------ 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: 21s - loss: 0.2269 35/116 [========>.....................] - ETA: 0s - loss: 0.0845  73/116 [=================>............] - ETA: 0s - loss: 0.0841 113/116 [============================>.] - ETA: 0s - loss: 0.0812 116/116 [==============================] - 0s 1ms/step - loss: 0.0821 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0408 37/116 [========>.....................] - ETA: 0s - loss: 0.0944 76/116 [==================>...........] - ETA: 0s - loss: 0.0793 114/116 [============================>.] - ETA: 0s - loss: 0.0808 116/116 [==============================] - 0s 1ms/step - loss: 0.0802 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0215 42/116 [=========>....................] - ETA: 0s - loss: 0.0546 78/116 [===================>..........] - ETA: 0s - loss: 0.0729 100/116 [========================>.....] - ETA: 0s - loss: 0.0723 116/116 [==============================] - 0s 2ms/step - loss: 0.0779 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0483 28/116 [======>.......................] - ETA: 0s - loss: 0.0631 55/116 [=============>................] - ETA: 0s - loss: 0.0737 76/116 [==================>...........] - ETA: 0s - loss: 0.0826 97/116 [========================>.....] - ETA: 0s - loss: 0.0786 116/116 [==============================] - 0s 2ms/step - loss: 0.0793 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0244 29/116 [======>.......................] - ETA: 0s - loss: 0.0819 54/116 [============>.................] - ETA: 0s - loss: 0.0832 82/116 [====================>.........] - ETA: 0s - loss: 0.0762 110/116 [===========================>..] - ETA: 0s - loss: 0.0746 116/116 [==============================] - 0s 2ms/step - loss: 0.0763 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0314 28/116 [======>.......................] - ETA: 0s - loss: 0.0676 57/116 [=============>................] - ETA: 0s - loss: 0.0762 84/116 [====================>.........] - ETA: 0s - loss: 0.0758 108/116 [==========================>...] - ETA: 0s - loss: 0.0718 116/116 [==============================] - 0s 2ms/step - loss: 0.0749 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0659 30/116 [======>.......................] - ETA: 0s - loss: 0.0846 59/116 [==============>...............] - ETA: 0s - loss: 0.0675 86/116 [=====================>........] - ETA: 0s - loss: 0.0664 113/116 [============================>.] - ETA: 0s - loss: 0.0717 116/116 [==============================] - 0s 2ms/step - loss: 0.0726 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0883 31/116 [=======>......................] - ETA: 0s - loss: 0.0631 63/116 [===============>..............] - ETA: 0s - loss: 0.0578 99/116 [========================>.....] - ETA: 0s - loss: 0.0756 116/116 [==============================] - 0s 2ms/step - loss: 0.0718 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0083 24/116 [=====>........................] - ETA: 0s - loss: 0.0624 49/116 [===========>..................] - ETA: 0s - loss: 0.0523 74/116 [==================>...........] - ETA: 0s - loss: 0.0548 94/116 [=======================>......] - ETA: 0s - loss: 0.0697 116/116 [==============================] - 0s 2ms/step - loss: 0.0710 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0250 26/116 [=====>........................] - ETA: 0s - loss: 0.0883 55/116 [=============>................] - ETA: 0s - loss: 0.0679 84/116 [====================>.........] - ETA: 0s - loss: 0.0758 114/116 [============================>.] - ETA: 0s - loss: 0.0699 116/116 [==============================] - 0s 2ms/step - loss: 0.0696 -> test with GAN.predict GAN tn, fp: 281, 7 GAN fn, tp: 0, 9 GAN f1 score: 0.720 GAN cohens kappa score: 0.709 -> 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: 0.765 -> 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: 280, 8 KNN fn, tp: 1, 8 KNN f1 score: 0.640 KNN cohens kappa score: 0.625 ------ 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: 23s - loss: 0.1531 41/116 [=========>....................] - ETA: 0s - loss: 0.0677  79/116 [===================>..........] - ETA: 0s - loss: 0.0722 115/116 [============================>.] - ETA: 0s - loss: 0.0757 116/116 [==============================] - 0s 1ms/step - loss: 0.0756 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0659 38/116 [========>.....................] - ETA: 0s - loss: 0.0900 76/116 [==================>...........] - ETA: 0s - loss: 0.0799 115/116 [============================>.] - ETA: 0s - loss: 0.0742 116/116 [==============================] - 0s 1ms/step - loss: 0.0741 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0743 40/116 [=========>....................] - ETA: 0s - loss: 0.0760 80/116 [===================>..........] - ETA: 0s - loss: 0.0825 116/116 [==============================] - 0s 1ms/step - loss: 0.0736 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0203 40/116 [=========>....................] - ETA: 0s - loss: 0.0737 77/116 [==================>...........] - ETA: 0s - loss: 0.0724 114/116 [============================>.] - ETA: 0s - loss: 0.0726 116/116 [==============================] - 0s 1ms/step - loss: 0.0726 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0308 39/116 [=========>....................] - ETA: 0s - loss: 0.0742 77/116 [==================>...........] - ETA: 0s - loss: 0.0727 111/116 [===========================>..] - ETA: 0s - loss: 0.0701 116/116 [==============================] - 0s 1ms/step - loss: 0.0705 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0163 36/116 [========>.....................] - ETA: 0s - loss: 0.0593 74/116 [==================>...........] - ETA: 0s - loss: 0.0592 113/116 [============================>.] - ETA: 0s - loss: 0.0699 116/116 [==============================] - 0s 1ms/step - loss: 0.0689 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0506 40/116 [=========>....................] - ETA: 0s - loss: 0.0593 78/116 [===================>..........] - ETA: 0s - loss: 0.0630 116/116 [==============================] - 0s 1ms/step - loss: 0.0699 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.3316 40/116 [=========>....................] - ETA: 0s - loss: 0.0789 79/116 [===================>..........] - ETA: 0s - loss: 0.0670 114/116 [============================>.] - ETA: 0s - loss: 0.0675 116/116 [==============================] - 0s 1ms/step - loss: 0.0688 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.3351 38/116 [========>.....................] - ETA: 0s - loss: 0.0679 72/116 [=================>............] - ETA: 0s - loss: 0.0686 111/116 [===========================>..] - ETA: 0s - loss: 0.0686 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0100 39/116 [=========>....................] - ETA: 0s - loss: 0.0672 76/116 [==================>...........] - ETA: 0s - loss: 0.0698 113/116 [============================>.] - ETA: 0s - loss: 0.0677 116/116 [==============================] - 0s 1ms/step - loss: 0.0672 -> 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: 275, 13 LR fn, tp: 0, 8 LR f1 score: 0.552 LR cohens kappa score: 0.533 LR average precision score: 0.304 -> test with 'RF' RF tn, fp: 284, 4 RF fn, tp: 2, 6 RF f1 score: 0.667 RF cohens kappa score: 0.656 -> test with 'GB' GB tn, fp: 282, 6 GB fn, tp: 1, 7 GB f1 score: 0.667 GB cohens kappa score: 0.655 -> 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 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: 26s - loss: 0.0502 29/116 [======>.......................] - ETA: 0s - loss: 0.0929  56/116 [=============>................] - ETA: 0s - loss: 0.0911 81/116 [===================>..........] - ETA: 0s - loss: 0.0831 98/116 [========================>.....] - ETA: 0s - loss: 0.0843 116/116 [==============================] - 0s 2ms/step - loss: 0.0830 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0258 22/116 [====>.........................] - ETA: 0s - loss: 0.0724 38/116 [========>.....................] - ETA: 0s - loss: 0.0786 54/116 [============>.................] - ETA: 0s - loss: 0.0803 71/116 [=================>............] - ETA: 0s - loss: 0.0811 91/116 [======================>.......] - ETA: 0s - loss: 0.0775 113/116 [============================>.] - ETA: 0s - loss: 0.0814 116/116 [==============================] - 0s 3ms/step - loss: 0.0821 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1194 23/116 [====>.........................] - ETA: 0s - loss: 0.0640 44/116 [==========>...................] - ETA: 0s - loss: 0.0676 60/116 [==============>...............] - ETA: 0s - loss: 0.0736 75/116 [==================>...........] - ETA: 0s - loss: 0.0746 88/116 [=====================>........] - ETA: 0s - loss: 0.0764 106/116 [==========================>...] - ETA: 0s - loss: 0.0777 116/116 [==============================] - 0s 3ms/step - loss: 0.0807 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0360 18/116 [===>..........................] - ETA: 0s - loss: 0.0655 34/116 [=======>......................] - ETA: 0s - loss: 0.0902 50/116 [===========>..................] - ETA: 0s - loss: 0.0918 67/116 [================>.............] - ETA: 0s - loss: 0.0883 82/116 [====================>.........] - ETA: 0s - loss: 0.0910 99/116 [========================>.....] - ETA: 0s - loss: 0.0815 116/116 [==============================] - 0s 3ms/step - loss: 0.0792 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0084 20/116 [====>.........................] - ETA: 0s - loss: 0.0959 36/116 [========>.....................] - ETA: 0s - loss: 0.0842 59/116 [==============>...............] - ETA: 0s - loss: 0.0887 80/116 [===================>..........] - ETA: 0s - loss: 0.0875 101/116 [=========================>....] - ETA: 0s - loss: 0.0786 116/116 [==============================] - 0s 3ms/step - loss: 0.0785 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0257 18/116 [===>..........................] - ETA: 0s - loss: 0.0713 33/116 [=======>......................] - ETA: 0s - loss: 0.0883 52/116 [============>.................] - ETA: 0s - loss: 0.0859 72/116 [=================>............] - ETA: 0s - loss: 0.0822 94/116 [=======================>......] - ETA: 0s - loss: 0.0842 116/116 [==============================] - 0s 3ms/step - loss: 0.0777 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1209 26/116 [=====>........................] - ETA: 0s - loss: 0.0678 48/116 [===========>..................] - ETA: 0s - loss: 0.0758 69/116 [================>.............] - ETA: 0s - loss: 0.0697 89/116 [======================>.......] - ETA: 0s - loss: 0.0692 110/116 [===========================>..] - ETA: 0s - loss: 0.0784 116/116 [==============================] - 0s 2ms/step - loss: 0.0779 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0564 25/116 [=====>........................] - ETA: 0s - loss: 0.0814 48/116 [===========>..................] - ETA: 0s - loss: 0.1026 71/116 [=================>............] - ETA: 0s - loss: 0.0898 92/116 [======================>.......] - ETA: 0s - loss: 0.0821 116/116 [==============================] - 0s 2ms/step - loss: 0.0765 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2265 29/116 [======>.......................] - ETA: 0s - loss: 0.0733 52/116 [============>.................] - ETA: 0s - loss: 0.0806 82/116 [====================>.........] - ETA: 0s - loss: 0.0750 112/116 [===========================>..] - ETA: 0s - loss: 0.0760 116/116 [==============================] - 0s 2ms/step - loss: 0.0762 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0092 25/116 [=====>........................] - ETA: 0s - loss: 0.0537 49/116 [===========>..................] - ETA: 0s - loss: 0.0817 76/116 [==================>...........] - ETA: 0s - loss: 0.0772 106/116 [==========================>...] - ETA: 0s - loss: 0.0770 116/116 [==============================] - 0s 2ms/step - loss: 0.0759 -> 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: 275, 13 LR fn, tp: 0, 9 LR f1 score: 0.581 LR cohens kappa score: 0.562 LR average precision score: 0.714 -> 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: 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 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: 0.1457 39/116 [=========>....................] - ETA: 0s - loss: 0.0739  78/116 [===================>..........] - ETA: 0s - loss: 0.0724 116/116 [==============================] - 0s 1ms/step - loss: 0.0709 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0197 39/116 [=========>....................] - ETA: 0s - loss: 0.0611 78/116 [===================>..........] - ETA: 0s - loss: 0.0656 116/116 [==============================] - ETA: 0s - loss: 0.0682 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0368 42/116 [=========>....................] - ETA: 0s - loss: 0.0742 82/116 [====================>.........] - ETA: 0s - loss: 0.0618 116/116 [==============================] - 0s 1ms/step - loss: 0.0691 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0225 34/116 [=======>......................] - ETA: 0s - loss: 0.0521 66/116 [================>.............] - ETA: 0s - loss: 0.0567 101/116 [=========================>....] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0331 39/116 [=========>....................] - ETA: 0s - loss: 0.0678 78/116 [===================>..........] - ETA: 0s - loss: 0.0594 116/116 [==============================] - 0s 1ms/step - loss: 0.0673 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0637 33/116 [=======>......................] - ETA: 0s - loss: 0.0541 72/116 [=================>............] - ETA: 0s - loss: 0.0647 108/116 [==========================>...] - ETA: 0s - loss: 0.0636 116/116 [==============================] - 0s 1ms/step - loss: 0.0665 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0134 42/116 [=========>....................] - ETA: 0s - loss: 0.0595 78/116 [===================>..........] - ETA: 0s - loss: 0.0642 116/116 [==============================] - 0s 1ms/step - loss: 0.0660 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0221 41/116 [=========>....................] - ETA: 0s - loss: 0.0623 79/116 [===================>..........] - ETA: 0s - loss: 0.0607 116/116 [==============================] - ETA: 0s - loss: 0.0653 116/116 [==============================] - 0s 1ms/step - loss: 0.0653 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0306 37/116 [========>.....................] - ETA: 0s - loss: 0.0671 75/116 [==================>...........] - ETA: 0s - loss: 0.0633 108/116 [==========================>...] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 1ms/step - loss: 0.0651 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0264 34/116 [=======>......................] - ETA: 0s - loss: 0.0847 71/116 [=================>............] - ETA: 0s - loss: 0.0682 107/116 [==========================>...] - ETA: 0s - loss: 0.0611 116/116 [==============================] - 0s 1ms/step - loss: 0.0631 -> test with GAN.predict GAN tn, fp: 274, 14 GAN fn, tp: 0, 9 GAN f1 score: 0.562 GAN cohens kappa score: 0.543 -> 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: 0.623 -> 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: 277, 11 KNN fn, tp: 0, 9 KNN f1 score: 0.621 KNN cohens kappa score: 0.604 ------ 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: 0.0899 37/116 [========>.....................] - ETA: 0s - loss: 0.1073  69/116 [================>.............] - ETA: 0s - loss: 0.0863 108/116 [==========================>...] - ETA: 0s - loss: 0.0846 116/116 [==============================] - 0s 1ms/step - loss: 0.0830 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2157 35/116 [========>.....................] - ETA: 0s - loss: 0.0791 67/116 [================>.............] - ETA: 0s - loss: 0.0747 102/116 [=========================>....] - ETA: 0s - loss: 0.0792 116/116 [==============================] - 0s 1ms/step - loss: 0.0789 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1671 35/116 [========>.....................] - ETA: 0s - loss: 0.0833 68/116 [================>.............] - ETA: 0s - loss: 0.0775 89/116 [======================>.......] - ETA: 0s - loss: 0.0754 116/116 [==============================] - 0s 2ms/step - loss: 0.0785 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.3553 32/116 [=======>......................] - ETA: 0s - loss: 0.0581 66/116 [================>.............] - ETA: 0s - loss: 0.0702 101/116 [=========================>....] - ETA: 0s - loss: 0.0732 116/116 [==============================] - 0s 2ms/step - loss: 0.0762 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0870 37/116 [========>.....................] - ETA: 0s - loss: 0.0657 68/116 [================>.............] - ETA: 0s - loss: 0.0778 100/116 [========================>.....] - ETA: 0s - loss: 0.0786 116/116 [==============================] - 0s 2ms/step - loss: 0.0749 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0071 32/116 [=======>......................] - ETA: 0s - loss: 0.0598 69/116 [================>.............] - ETA: 0s - loss: 0.0689 102/116 [=========================>....] - ETA: 0s - loss: 0.0761 116/116 [==============================] - 0s 2ms/step - loss: 0.0760 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0379 35/116 [========>.....................] - ETA: 0s - loss: 0.0761 68/116 [================>.............] - ETA: 0s - loss: 0.0800 102/116 [=========================>....] - ETA: 0s - loss: 0.0746 116/116 [==============================] - 0s 2ms/step - loss: 0.0740 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0384 36/116 [========>.....................] - ETA: 0s - loss: 0.0599 73/116 [=================>............] - ETA: 0s - loss: 0.0662 111/116 [===========================>..] - ETA: 0s - loss: 0.0729 116/116 [==============================] - 0s 1ms/step - loss: 0.0734 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0212 34/116 [=======>......................] - ETA: 0s - loss: 0.0562 61/116 [==============>...............] - ETA: 0s - loss: 0.0693 99/116 [========================>.....] - ETA: 0s - loss: 0.0713 116/116 [==============================] - 0s 2ms/step - loss: 0.0727 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0672 33/116 [=======>......................] - ETA: 0s - loss: 0.0808 68/116 [================>.............] - ETA: 0s - loss: 0.0741 104/116 [=========================>....] - ETA: 0s - loss: 0.0725 116/116 [==============================] - 0s 1ms/step - loss: 0.0714 -> test with GAN.predict GAN tn, fp: 279, 9 GAN fn, tp: 2, 7 GAN f1 score: 0.560 GAN cohens kappa score: 0.542 -> 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: 0.615 -> 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: 21s - loss: 0.0619 39/116 [=========>....................] - ETA: 0s - loss: 0.0976  80/116 [===================>..........] - ETA: 0s - loss: 0.0815 116/116 [==============================] - 0s 1ms/step - loss: 0.0833 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0235 42/116 [=========>....................] - ETA: 0s - loss: 0.0577 80/116 [===================>..........] - ETA: 0s - loss: 0.0748 114/116 [============================>.] - ETA: 0s - loss: 0.0813 116/116 [==============================] - 0s 1ms/step - loss: 0.0809 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2452 34/116 [=======>......................] - ETA: 0s - loss: 0.0679 68/116 [================>.............] - ETA: 0s - loss: 0.0760 108/116 [==========================>...] - ETA: 0s - loss: 0.0811 116/116 [==============================] - 0s 1ms/step - loss: 0.0798 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0294 42/116 [=========>....................] - ETA: 0s - loss: 0.0847 83/116 [====================>.........] - ETA: 0s - loss: 0.0752 116/116 [==============================] - 0s 1ms/step - loss: 0.0797 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2461 39/116 [=========>....................] - ETA: 0s - loss: 0.0832 78/116 [===================>..........] - ETA: 0s - loss: 0.0794 113/116 [============================>.] - ETA: 0s - loss: 0.0771 116/116 [==============================] - 0s 1ms/step - loss: 0.0779 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2621 39/116 [=========>....................] - ETA: 0s - loss: 0.0665 73/116 [=================>............] - ETA: 0s - loss: 0.0680 105/116 [==========================>...] - ETA: 0s - loss: 0.0760 116/116 [==============================] - 0s 1ms/step - loss: 0.0773 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0786 41/116 [=========>....................] - ETA: 0s - loss: 0.0861 80/116 [===================>..........] - ETA: 0s - loss: 0.0753 116/116 [==============================] - 0s 1ms/step - loss: 0.0761 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0084 41/116 [=========>....................] - ETA: 0s - loss: 0.0827 81/116 [===================>..........] - ETA: 0s - loss: 0.0765 116/116 [==============================] - 0s 1ms/step - loss: 0.0760 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.3655 42/116 [=========>....................] - ETA: 0s - loss: 0.0788 83/116 [====================>.........] - ETA: 0s - loss: 0.0795 116/116 [==============================] - 0s 1ms/step - loss: 0.0747 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0177 40/116 [=========>....................] - ETA: 0s - loss: 0.0771 81/116 [===================>..........] - ETA: 0s - loss: 0.0713 116/116 [==============================] - 0s 1ms/step - loss: 0.0738 -> 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: 0.668 -> 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: 281, 7 KNN fn, tp: 1, 8 KNN f1 score: 0.667 KNN cohens kappa score: 0.654 ------ 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: 18s - loss: 0.0148 40/116 [=========>....................] - ETA: 0s - loss: 0.0825  78/116 [===================>..........] - ETA: 0s - loss: 0.0773 115/116 [============================>.] - ETA: 0s - loss: 0.0797 116/116 [==============================] - 0s 1ms/step - loss: 0.0796 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0490 38/116 [========>.....................] - ETA: 0s - loss: 0.0704 76/116 [==================>...........] - ETA: 0s - loss: 0.0814 116/116 [==============================] - 0s 1ms/step - loss: 0.0791 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0256 40/116 [=========>....................] - ETA: 0s - loss: 0.0767 79/116 [===================>..........] - ETA: 0s - loss: 0.0804 116/116 [==============================] - 0s 1ms/step - loss: 0.0779 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2742 39/116 [=========>....................] - ETA: 0s - loss: 0.0927 79/116 [===================>..........] - ETA: 0s - loss: 0.0798 116/116 [==============================] - ETA: 0s - loss: 0.0777 116/116 [==============================] - 0s 1ms/step - loss: 0.0777 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1105 25/116 [=====>........................] - ETA: 0s - loss: 0.0729 61/116 [==============>...............] - ETA: 0s - loss: 0.0801 100/116 [========================>.....] - ETA: 0s - loss: 0.0781 116/116 [==============================] - 0s 2ms/step - loss: 0.0775 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0088 39/116 [=========>....................] - ETA: 0s - loss: 0.0725 78/116 [===================>..........] - ETA: 0s - loss: 0.0739 116/116 [==============================] - ETA: 0s - loss: 0.0749 116/116 [==============================] - 0s 1ms/step - loss: 0.0749 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2657 41/116 [=========>....................] - ETA: 0s - loss: 0.0718 79/116 [===================>..........] - ETA: 0s - loss: 0.0664 116/116 [==============================] - 0s 1ms/step - loss: 0.0749 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0320 41/116 [=========>....................] - ETA: 0s - loss: 0.0679 78/116 [===================>..........] - ETA: 0s - loss: 0.0783 116/116 [==============================] - 0s 1ms/step - loss: 0.0740 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1506 41/116 [=========>....................] - ETA: 0s - loss: 0.1004 80/116 [===================>..........] - ETA: 0s - loss: 0.0862 116/116 [==============================] - 0s 1ms/step - loss: 0.0740 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0155 39/116 [=========>....................] - ETA: 0s - loss: 0.0591 79/116 [===================>..........] - ETA: 0s - loss: 0.0682 116/116 [==============================] - 0s 1ms/step - loss: 0.0739 -> test with GAN.predict GAN tn, fp: 271, 17 GAN fn, tp: 0, 8 GAN f1 score: 0.485 GAN cohens kappa score: 0.463 -> 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: 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: 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: 25s - loss: 0.0743 38/116 [========>.....................] - ETA: 0s - loss: 0.0884  73/116 [=================>............] - ETA: 0s - loss: 0.0850 110/116 [===========================>..] - ETA: 0s - loss: 0.0791 116/116 [==============================] - 0s 1ms/step - loss: 0.0778 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0363 38/116 [========>.....................] - ETA: 0s - loss: 0.0710 69/116 [================>.............] - ETA: 0s - loss: 0.0761 101/116 [=========================>....] - ETA: 0s - loss: 0.0811 116/116 [==============================] - 0s 1ms/step - loss: 0.0768 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0358 38/116 [========>.....................] - ETA: 0s - loss: 0.0754 74/116 [==================>...........] - ETA: 0s - loss: 0.0704 109/116 [===========================>..] - ETA: 0s - loss: 0.0745 116/116 [==============================] - 0s 1ms/step - loss: 0.0754 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0418 35/116 [========>.....................] - ETA: 0s - loss: 0.0607 66/116 [================>.............] - ETA: 0s - loss: 0.0581 101/116 [=========================>....] - ETA: 0s - loss: 0.0697 116/116 [==============================] - 0s 2ms/step - loss: 0.0750 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0339 37/116 [========>.....................] - ETA: 0s - loss: 0.0802 74/116 [==================>...........] - ETA: 0s - loss: 0.0665 112/116 [===========================>..] - ETA: 0s - loss: 0.0746 116/116 [==============================] - 0s 1ms/step - loss: 0.0734 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0166 38/116 [========>.....................] - ETA: 0s - loss: 0.0877 74/116 [==================>...........] - ETA: 0s - loss: 0.0885 110/116 [===========================>..] - ETA: 0s - loss: 0.0775 116/116 [==============================] - 0s 1ms/step - loss: 0.0759 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0169 37/116 [========>.....................] - ETA: 0s - loss: 0.0686 73/116 [=================>............] - ETA: 0s - loss: 0.0739 109/116 [===========================>..] - ETA: 0s - loss: 0.0715 116/116 [==============================] - 0s 1ms/step - loss: 0.0724 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0503 38/116 [========>.....................] - ETA: 0s - loss: 0.0653 73/116 [=================>............] - ETA: 0s - loss: 0.0600 109/116 [===========================>..] - ETA: 0s - loss: 0.0714 116/116 [==============================] - 0s 1ms/step - loss: 0.0727 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0322 35/116 [========>.....................] - ETA: 0s - loss: 0.0769 68/116 [================>.............] - ETA: 0s - loss: 0.0814 103/116 [=========================>....] - ETA: 0s - loss: 0.0745 116/116 [==============================] - 0s 1ms/step - loss: 0.0710 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2495 24/116 [=====>........................] - ETA: 0s - loss: 0.0789 61/116 [==============>...............] - ETA: 0s - loss: 0.0667 99/116 [========================>.....] - ETA: 0s - loss: 0.0719 116/116 [==============================] - 0s 2ms/step - loss: 0.0698 -> 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: 271, 17 LR fn, tp: 0, 9 LR f1 score: 0.514 LR cohens kappa score: 0.491 LR average precision score: 0.716 -> 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: 0.0136 42/116 [=========>....................] - ETA: 0s - loss: 0.1155  81/116 [===================>..........] - ETA: 0s - loss: 0.0971 116/116 [==============================] - 0s 1ms/step - loss: 0.0884 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1570 37/116 [========>.....................] - ETA: 0s - loss: 0.0740 74/116 [==================>...........] - ETA: 0s - loss: 0.0831 112/116 [===========================>..] - ETA: 0s - loss: 0.0844 116/116 [==============================] - 0s 1ms/step - loss: 0.0864 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0356 39/116 [=========>....................] - ETA: 0s - loss: 0.0876 69/116 [================>.............] - ETA: 0s - loss: 0.0871 104/116 [=========================>....] - ETA: 0s - loss: 0.0870 116/116 [==============================] - 0s 1ms/step - loss: 0.0864 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0154 38/116 [========>.....................] - ETA: 0s - loss: 0.0974 77/116 [==================>...........] - ETA: 0s - loss: 0.0836 116/116 [==============================] - 0s 1ms/step - loss: 0.0844 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0466 38/116 [========>.....................] - ETA: 0s - loss: 0.0786 77/116 [==================>...........] - ETA: 0s - loss: 0.0751 115/116 [============================>.] - ETA: 0s - loss: 0.0827 116/116 [==============================] - 0s 1ms/step - loss: 0.0827 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0196 39/116 [=========>....................] - ETA: 0s - loss: 0.0865 76/116 [==================>...........] - ETA: 0s - loss: 0.0843 115/116 [============================>.] - ETA: 0s - loss: 0.0828 116/116 [==============================] - 0s 1ms/step - loss: 0.0827 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0141 40/116 [=========>....................] - ETA: 0s - loss: 0.0868 80/116 [===================>..........] - ETA: 0s - loss: 0.0815 116/116 [==============================] - 0s 1ms/step - loss: 0.0825 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0163 41/116 [=========>....................] - ETA: 0s - loss: 0.0896 81/116 [===================>..........] - ETA: 0s - loss: 0.0752 116/116 [==============================] - 0s 1ms/step - loss: 0.0797 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0168 39/116 [=========>....................] - ETA: 0s - loss: 0.0937 78/116 [===================>..........] - ETA: 0s - loss: 0.0822 116/116 [==============================] - 0s 1ms/step - loss: 0.0817 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2440 40/116 [=========>....................] - ETA: 0s - loss: 0.0965 78/116 [===================>..........] - ETA: 0s - loss: 0.0795 116/116 [==============================] - 0s 1ms/step - loss: 0.0781 -> 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: 279, 9 LR fn, tp: 1, 8 LR f1 score: 0.615 LR cohens kappa score: 0.600 LR average precision score: 0.790 -> 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: 284, 4 KNN fn, tp: 0, 9 KNN f1 score: 0.818 KNN cohens kappa score: 0.811 ------ 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: 17s - loss: 0.1223 41/116 [=========>....................] - ETA: 0s - loss: 0.0839  81/116 [===================>..........] - ETA: 0s - loss: 0.0823 113/116 [============================>.] - ETA: 0s - loss: 0.0802 116/116 [==============================] - 0s 1ms/step - loss: 0.0794 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0130 40/116 [=========>....................] - ETA: 0s - loss: 0.0782 78/116 [===================>..........] - ETA: 0s - loss: 0.0795 116/116 [==============================] - 0s 1ms/step - loss: 0.0782 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0324 41/116 [=========>....................] - ETA: 0s - loss: 0.0804 81/116 [===================>..........] - ETA: 0s - loss: 0.0737 116/116 [==============================] - 0s 1ms/step - loss: 0.0784 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0629 43/116 [==========>...................] - ETA: 0s - loss: 0.0695 84/116 [====================>.........] - ETA: 0s - loss: 0.0667 116/116 [==============================] - 0s 1ms/step - loss: 0.0764 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1508 42/116 [=========>....................] - ETA: 0s - loss: 0.0808 83/116 [====================>.........] - ETA: 0s - loss: 0.0793 116/116 [==============================] - 0s 1ms/step - loss: 0.0758 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0237 41/116 [=========>....................] - ETA: 0s - loss: 0.0780 82/116 [====================>.........] - ETA: 0s - loss: 0.0736 116/116 [==============================] - 0s 1ms/step - loss: 0.0743 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1141 41/116 [=========>....................] - ETA: 0s - loss: 0.0780 79/116 [===================>..........] - ETA: 0s - loss: 0.0833 116/116 [==============================] - ETA: 0s - loss: 0.0739 116/116 [==============================] - 0s 1ms/step - loss: 0.0739 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0146 41/116 [=========>....................] - ETA: 0s - loss: 0.0893 81/116 [===================>..........] - ETA: 0s - loss: 0.0814 116/116 [==============================] - 0s 1ms/step - loss: 0.0728 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0559 42/116 [=========>....................] - ETA: 0s - loss: 0.0733 82/116 [====================>.........] - ETA: 0s - loss: 0.0659 116/116 [==============================] - 0s 1ms/step - loss: 0.0713 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2322 41/116 [=========>....................] - ETA: 0s - loss: 0.0673 82/116 [====================>.........] - ETA: 0s - loss: 0.0739 116/116 [==============================] - 0s 1ms/step - loss: 0.0705 -> 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: 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: 1, 8 RF f1 score: 0.889 RF cohens kappa score: 0.885 -> 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: 23s - loss: 0.0367 41/116 [=========>....................] - ETA: 0s - loss: 0.0893  82/116 [====================>.........] - ETA: 0s - loss: 0.0882 116/116 [==============================] - 0s 1ms/step - loss: 0.0800 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0962 38/116 [========>.....................] - ETA: 0s - loss: 0.0564 78/116 [===================>..........] - ETA: 0s - loss: 0.0810 116/116 [==============================] - 0s 1ms/step - loss: 0.0791 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0237 40/116 [=========>....................] - ETA: 0s - loss: 0.0854 78/116 [===================>..........] - ETA: 0s - loss: 0.0770 114/116 [============================>.] - ETA: 0s - loss: 0.0768 116/116 [==============================] - 0s 1ms/step - loss: 0.0781 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0150 41/116 [=========>....................] - ETA: 0s - loss: 0.0995 81/116 [===================>..........] - ETA: 0s - loss: 0.0836 116/116 [==============================] - 0s 1ms/step - loss: 0.0779 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1093 42/116 [=========>....................] - ETA: 0s - loss: 0.0780 85/116 [====================>.........] - ETA: 0s - loss: 0.0791 116/116 [==============================] - 0s 1ms/step - loss: 0.0775 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0148 42/116 [=========>....................] - ETA: 0s - loss: 0.0650 82/116 [====================>.........] - ETA: 0s - loss: 0.0772 116/116 [==============================] - 0s 1ms/step - loss: 0.0763 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0151 38/116 [========>.....................] - ETA: 0s - loss: 0.0591 75/116 [==================>...........] - ETA: 0s - loss: 0.0695 113/116 [============================>.] - ETA: 0s - loss: 0.0765 116/116 [==============================] - 0s 1ms/step - loss: 0.0755 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0307 38/116 [========>.....................] - ETA: 0s - loss: 0.0707 78/116 [===================>..........] - ETA: 0s - loss: 0.0713 112/116 [===========================>..] - ETA: 0s - loss: 0.0737 116/116 [==============================] - 0s 1ms/step - loss: 0.0740 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1172 32/116 [=======>......................] - ETA: 0s - loss: 0.0815 68/116 [================>.............] - ETA: 0s - loss: 0.0794 105/116 [==========================>...] - ETA: 0s - loss: 0.0749 116/116 [==============================] - 0s 1ms/step - loss: 0.0743 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0110 36/116 [========>.....................] - ETA: 0s - loss: 0.0780 71/116 [=================>............] - ETA: 0s - loss: 0.0749 106/116 [==========================>...] - ETA: 0s - loss: 0.0764 116/116 [==============================] - 0s 1ms/step - loss: 0.0747 -> test with GAN.predict GAN tn, fp: 282, 6 GAN fn, tp: 2, 7 GAN f1 score: 0.636 GAN cohens kappa score: 0.623 -> 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: 0.589 -> 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: 4, 5 GB f1 score: 0.667 GB cohens kappa score: 0.658 -> 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 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: 0.0062 41/116 [=========>....................] - ETA: 0s - loss: 0.0662  81/116 [===================>..........] - ETA: 0s - loss: 0.0717 116/116 [==============================] - 0s 1ms/step - loss: 0.0779 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0280 41/116 [=========>....................] - ETA: 0s - loss: 0.0696 81/116 [===================>..........] - ETA: 0s - loss: 0.0824 116/116 [==============================] - 0s 1ms/step - loss: 0.0764 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0225 39/116 [=========>....................] - ETA: 0s - loss: 0.0755 80/116 [===================>..........] - ETA: 0s - loss: 0.0771 116/116 [==============================] - 0s 1ms/step - loss: 0.0749 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0155 40/116 [=========>....................] - ETA: 0s - loss: 0.0711 79/116 [===================>..........] - ETA: 0s - loss: 0.0762 116/116 [==============================] - 0s 1ms/step - loss: 0.0751 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1543 41/116 [=========>....................] - ETA: 0s - loss: 0.0606 81/116 [===================>..........] - ETA: 0s - loss: 0.0660 116/116 [==============================] - 0s 1ms/step - loss: 0.0722 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2359 40/116 [=========>....................] - ETA: 0s - loss: 0.0913 80/116 [===================>..........] - ETA: 0s - loss: 0.0791 116/116 [==============================] - 0s 1ms/step - loss: 0.0719 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0408 40/116 [=========>....................] - ETA: 0s - loss: 0.0833 79/116 [===================>..........] - ETA: 0s - loss: 0.0779 116/116 [==============================] - 0s 1ms/step - loss: 0.0703 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0979 40/116 [=========>....................] - ETA: 0s - loss: 0.0738 81/116 [===================>..........] - ETA: 0s - loss: 0.0795 116/116 [==============================] - 0s 1ms/step - loss: 0.0700 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0829 41/116 [=========>....................] - ETA: 0s - loss: 0.0723 79/116 [===================>..........] - ETA: 0s - loss: 0.0726 116/116 [==============================] - 0s 1ms/step - loss: 0.0694 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0150 39/116 [=========>....................] - ETA: 0s - loss: 0.0684 78/116 [===================>..........] - ETA: 0s - loss: 0.0748 116/116 [==============================] - 0s 1ms/step - loss: 0.0692 -> test with GAN.predict GAN tn, fp: 269, 19 GAN fn, tp: 1, 7 GAN f1 score: 0.412 GAN cohens kappa score: 0.386 -> 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: 0.354 -> test with 'RF' RF tn, fp: 285, 3 RF fn, tp: 3, 5 RF f1 score: 0.625 RF cohens kappa score: 0.615 -> 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: 281, 17 LR fn, tp: 2, 9 LR f1 score: 0.720 LR cohens kappa score: 0.709 LR average precision score: 0.878 average: LR tn, fp: 275.72, 12.28 LR fn, tp: 0.28, 8.52 LR f1 score: 0.582 LR cohens kappa score: 0.564 LR average precision score: 0.663 minimum: LR tn, fp: 271, 7 LR fn, tp: 0, 7 LR f1 score: 0.471 LR cohens kappa score: 0.446 LR average precision score: 0.304 -----[ RF ]----- maximum: RF tn, fp: 288, 5 RF fn, tp: 6, 8 RF f1 score: 0.889 RF cohens kappa score: 0.885 average: RF tn, fp: 286.48, 1.52 RF fn, tp: 3.24, 5.56 RF f1 score: 0.691 RF cohens kappa score: 0.684 minimum: RF tn, fp: 283, 0 RF fn, tp: 1, 2 RF f1 score: 0.353 RF cohens kappa score: 0.334 -----[ GB ]----- maximum: GB tn, fp: 288, 6 GB fn, tp: 6, 9 GB f1 score: 0.842 GB cohens kappa score: 0.837 average: GB tn, fp: 285.76, 2.24 GB fn, tp: 2.64, 6.16 GB f1 score: 0.713 GB cohens kappa score: 0.705 minimum: GB tn, fp: 282, 0 GB fn, tp: 0, 3 GB f1 score: 0.353 GB cohens kappa score: 0.334 -----[ KNN ]----- maximum: KNN tn, fp: 285, 15 KNN fn, tp: 2, 9 KNN f1 score: 0.857 KNN cohens kappa score: 0.852 average: KNN tn, fp: 278.64, 9.36 KNN fn, tp: 0.28, 8.52 KNN f1 score: 0.650 KNN cohens kappa score: 0.636 minimum: KNN tn, fp: 273, 3 KNN fn, tp: 0, 6 KNN f1 score: 0.444 KNN cohens kappa score: 0.422 -----[ GAN ]----- maximum: GAN tn, fp: 283, 19 GAN fn, tp: 3, 9 GAN f1 score: 0.727 GAN cohens kappa score: 0.717 average: GAN tn, fp: 276.52, 11.48 GAN fn, tp: 0.72, 8.08 GAN f1 score: 0.578 GAN cohens kappa score: 0.560 minimum: GAN tn, fp: 269, 5 GAN fn, tp: 0, 6 GAN f1 score: 0.412 GAN cohens kappa score: 0.386