/////////////////////////////////////////// // Running convGAN-majority-full on folding_yeast6 /////////////////////////////////////////// Load 'data_input/folding_yeast6' 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 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0325 42/116 [=========>....................] - ETA: 0s - loss: 0.0923  83/116 [====================>.........] - ETA: 0s - loss: 0.0684 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0017 41/116 [=========>....................] - ETA: 0s - loss: 0.0540 79/116 [===================>..........] - ETA: 0s - loss: 0.0656 116/116 [==============================] - 0s 1ms/step - loss: 0.0663 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1729 42/116 [=========>....................] - ETA: 0s - loss: 0.0515 83/116 [====================>.........] - ETA: 0s - loss: 0.0622 116/116 [==============================] - 0s 1ms/step - loss: 0.0676 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0199 42/116 [=========>....................] - ETA: 0s - loss: 0.0681 82/116 [====================>.........] - ETA: 0s - loss: 0.0648 116/116 [==============================] - 0s 1ms/step - loss: 0.0681 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0034 41/116 [=========>....................] - ETA: 0s - loss: 0.0905 77/116 [==================>...........] - ETA: 0s - loss: 0.0687 113/116 [============================>.] - ETA: 0s - loss: 0.0668 116/116 [==============================] - 0s 1ms/step - loss: 0.0662 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0106 42/116 [=========>....................] - ETA: 0s - loss: 0.0557 84/116 [====================>.........] - ETA: 0s - loss: 0.0663 116/116 [==============================] - 0s 1ms/step - loss: 0.0643 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0061 43/116 [==========>...................] - ETA: 0s - loss: 0.0716 82/116 [====================>.........] - ETA: 0s - loss: 0.0626 116/116 [==============================] - 0s 1ms/step - loss: 0.0634 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0148 41/116 [=========>....................] - ETA: 0s - loss: 0.0518 81/116 [===================>..........] - ETA: 0s - loss: 0.0581 116/116 [==============================] - 0s 1ms/step - loss: 0.0650 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0111 42/116 [=========>....................] - ETA: 0s - loss: 0.0808 78/116 [===================>..........] - ETA: 0s - loss: 0.0663 112/116 [===========================>..] - ETA: 0s - loss: 0.0654 116/116 [==============================] - 0s 1ms/step - loss: 0.0648 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0128 35/116 [========>.....................] - ETA: 0s - loss: 0.0465 77/116 [==================>...........] - ETA: 0s - loss: 0.0488 116/116 [==============================] - 0s 1ms/step - loss: 0.0633 -> test with GAN.predict GAN tn, fp: 280, 10 GAN fn, tp: 1, 6 GAN f1 score: 0.522 GAN cohens kappa score: 0.506 -> test with 'LR' LR tn, fp: 271, 19 LR fn, tp: 1, 6 LR f1 score: 0.375 LR cohens kappa score: 0.351 LR average precision score: 0.691 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 3, 4 RF f1 score: 0.615 RF cohens kappa score: 0.607 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 4, 3 GB f1 score: 0.462 GB cohens kappa score: 0.450 -> test with 'KNN' KNN tn, fp: 274, 16 KNN fn, tp: 1, 6 KNN f1 score: 0.414 KNN cohens kappa score: 0.392 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.5048 42/116 [=========>....................] - ETA: 0s - loss: 0.0595  83/116 [====================>.........] - ETA: 0s - loss: 0.0557 116/116 [==============================] - 0s 1ms/step - loss: 0.0591 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0515 39/116 [=========>....................] - ETA: 0s - loss: 0.0614 79/116 [===================>..........] - ETA: 0s - loss: 0.0613 116/116 [==============================] - 0s 1ms/step - loss: 0.0565 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0044 41/116 [=========>....................] - ETA: 0s - loss: 0.0434 82/116 [====================>.........] - ETA: 0s - loss: 0.0575 116/116 [==============================] - 0s 1ms/step - loss: 0.0554 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1211 41/116 [=========>....................] - ETA: 0s - loss: 0.0591 82/116 [====================>.........] - ETA: 0s - loss: 0.0547 116/116 [==============================] - 0s 1ms/step - loss: 0.0554 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0630 42/116 [=========>....................] - ETA: 0s - loss: 0.0512 83/116 [====================>.........] - ETA: 0s - loss: 0.0496 116/116 [==============================] - 0s 1ms/step - loss: 0.0533 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0130 41/116 [=========>....................] - ETA: 0s - loss: 0.0403 82/116 [====================>.........] - ETA: 0s - loss: 0.0457 116/116 [==============================] - 0s 1ms/step - loss: 0.0527 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0081 40/116 [=========>....................] - ETA: 0s - loss: 0.0499 76/116 [==================>...........] - ETA: 0s - loss: 0.0532 110/116 [===========================>..] - ETA: 0s - loss: 0.0541 116/116 [==============================] - 0s 1ms/step - loss: 0.0536 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0216 34/116 [=======>......................] - ETA: 0s - loss: 0.0474 70/116 [=================>............] - ETA: 0s - loss: 0.0569 110/116 [===========================>..] - ETA: 0s - loss: 0.0533 116/116 [==============================] - 0s 1ms/step - loss: 0.0523 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0209 39/116 [=========>....................] - ETA: 0s - loss: 0.0531 76/116 [==================>...........] - ETA: 0s - loss: 0.0545 116/116 [==============================] - 0s 1ms/step - loss: 0.0503 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0118 43/116 [==========>...................] - ETA: 0s - loss: 0.0387 81/116 [===================>..........] - ETA: 0s - loss: 0.0510 116/116 [==============================] - 0s 1ms/step - loss: 0.0525 -> test with GAN.predict GAN tn, fp: 279, 11 GAN fn, tp: 3, 4 GAN f1 score: 0.364 GAN cohens kappa score: 0.343 -> test with 'LR' LR tn, fp: 268, 22 LR fn, tp: 2, 5 LR f1 score: 0.294 LR cohens kappa score: 0.267 LR average precision score: 0.425 -> test with 'RF' RF tn, fp: 286, 4 RF fn, tp: 3, 4 RF f1 score: 0.533 RF cohens kappa score: 0.521 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 3, 4 GB f1 score: 0.533 GB cohens kappa score: 0.521 -> test with 'KNN' KNN tn, fp: 274, 16 KNN fn, tp: 3, 4 KNN f1 score: 0.296 KNN cohens kappa score: 0.271 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0382 35/116 [========>.....................] - ETA: 0s - loss: 0.0640  70/116 [=================>............] - ETA: 0s - loss: 0.0766 108/116 [==========================>...] - ETA: 0s - loss: 0.0787 116/116 [==============================] - 0s 1ms/step - loss: 0.0779 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0494 35/116 [========>.....................] - ETA: 0s - loss: 0.0614 71/116 [=================>............] - ETA: 0s - loss: 0.0617 110/116 [===========================>..] - ETA: 0s - loss: 0.0705 116/116 [==============================] - 0s 1ms/step - loss: 0.0731 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0249 36/116 [========>.....................] - ETA: 0s - loss: 0.0672 71/116 [=================>............] - ETA: 0s - loss: 0.0671 108/116 [==========================>...] - ETA: 0s - loss: 0.0726 116/116 [==============================] - 0s 1ms/step - loss: 0.0732 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0310 37/116 [========>.....................] - ETA: 0s - loss: 0.0752 71/116 [=================>............] - ETA: 0s - loss: 0.0726 103/116 [=========================>....] - ETA: 0s - loss: 0.0720 116/116 [==============================] - 0s 2ms/step - loss: 0.0753 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0158 31/116 [=======>......................] - ETA: 0s - loss: 0.0761 66/116 [================>.............] - ETA: 0s - loss: 0.0724 101/116 [=========================>....] - ETA: 0s - loss: 0.0690 116/116 [==============================] - 0s 2ms/step - loss: 0.0713 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1786 37/116 [========>.....................] - ETA: 0s - loss: 0.0624 72/116 [=================>............] - ETA: 0s - loss: 0.0694 104/116 [=========================>....] - ETA: 0s - loss: 0.0748 116/116 [==============================] - 0s 1ms/step - loss: 0.0703 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0086 37/116 [========>.....................] - ETA: 0s - loss: 0.0561 72/116 [=================>............] - ETA: 0s - loss: 0.0682 104/116 [=========================>....] - ETA: 0s - loss: 0.0705 116/116 [==============================] - 0s 1ms/step - loss: 0.0703 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2089 41/116 [=========>....................] - ETA: 0s - loss: 0.0673 77/116 [==================>...........] - ETA: 0s - loss: 0.0698 110/116 [===========================>..] - ETA: 0s - loss: 0.0730 116/116 [==============================] - 0s 1ms/step - loss: 0.0735 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1529 41/116 [=========>....................] - ETA: 0s - loss: 0.0904 77/116 [==================>...........] - ETA: 0s - loss: 0.0784 111/116 [===========================>..] - ETA: 0s - loss: 0.0666 116/116 [==============================] - 0s 1ms/step - loss: 0.0671 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0292 35/116 [========>.....................] - ETA: 0s - loss: 0.0489 71/116 [=================>............] - ETA: 0s - loss: 0.0558 105/116 [==========================>...] - ETA: 0s - loss: 0.0679 116/116 [==============================] - 0s 1ms/step - loss: 0.0663 -> test with GAN.predict GAN tn, fp: 284, 6 GAN fn, tp: 3, 4 GAN f1 score: 0.471 GAN cohens kappa score: 0.455 -> test with 'LR' LR tn, fp: 266, 24 LR fn, tp: 1, 6 LR f1 score: 0.324 LR cohens kappa score: 0.297 LR average precision score: 0.309 -> test with 'RF' RF tn, fp: 290, 0 RF fn, tp: 3, 4 RF f1 score: 0.727 RF cohens kappa score: 0.723 -> test with 'GB' GB tn, fp: 289, 1 GB fn, tp: 2, 5 GB f1 score: 0.769 GB cohens kappa score: 0.764 -> test with 'KNN' KNN tn, fp: 278, 12 KNN fn, tp: 1, 6 KNN f1 score: 0.480 KNN cohens kappa score: 0.462 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0099 38/116 [========>.....................] - ETA: 0s - loss: 0.0406  78/116 [===================>..........] - ETA: 0s - loss: 0.0619 116/116 [==============================] - 0s 1ms/step - loss: 0.0629 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0457 40/116 [=========>....................] - ETA: 0s - loss: 0.0771 80/116 [===================>..........] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 1ms/step - loss: 0.0631 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0108 38/116 [========>.....................] - ETA: 0s - loss: 0.0645 78/116 [===================>..........] - ETA: 0s - loss: 0.0663 116/116 [==============================] - 0s 1ms/step - loss: 0.0618 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0490 41/116 [=========>....................] - ETA: 0s - loss: 0.0647 82/116 [====================>.........] - ETA: 0s - loss: 0.0595 116/116 [==============================] - 0s 1ms/step - loss: 0.0611 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0198 42/116 [=========>....................] - ETA: 0s - loss: 0.0523 82/116 [====================>.........] - ETA: 0s - loss: 0.0586 116/116 [==============================] - 0s 1ms/step - loss: 0.0589 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1889 42/116 [=========>....................] - ETA: 0s - loss: 0.0578 83/116 [====================>.........] - ETA: 0s - loss: 0.0596 116/116 [==============================] - 0s 1ms/step - loss: 0.0596 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0445 39/116 [=========>....................] - ETA: 0s - loss: 0.0617 77/116 [==================>...........] - ETA: 0s - loss: 0.0556 111/116 [===========================>..] - ETA: 0s - loss: 0.0597 116/116 [==============================] - 0s 1ms/step - loss: 0.0585 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0064 37/116 [========>.....................] - ETA: 0s - loss: 0.0393 76/116 [==================>...........] - ETA: 0s - loss: 0.0592 112/116 [===========================>..] - ETA: 0s - loss: 0.0574 116/116 [==============================] - 0s 1ms/step - loss: 0.0588 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0294 40/116 [=========>....................] - ETA: 0s - loss: 0.0893 80/116 [===================>..........] - ETA: 0s - loss: 0.0671 116/116 [==============================] - 0s 1ms/step - loss: 0.0598 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0195 41/116 [=========>....................] - ETA: 0s - loss: 0.0637 80/116 [===================>..........] - ETA: 0s - loss: 0.0530 116/116 [==============================] - 0s 1ms/step - loss: 0.0603 -> test with GAN.predict GAN tn, fp: 287, 3 GAN fn, tp: 4, 3 GAN f1 score: 0.462 GAN cohens kappa score: 0.450 -> test with 'LR' LR tn, fp: 275, 15 LR fn, tp: 2, 5 LR f1 score: 0.370 LR cohens kappa score: 0.348 LR average precision score: 0.620 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 4, 3 RF f1 score: 0.545 RF cohens kappa score: 0.538 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 4, 3 GB f1 score: 0.429 GB cohens kappa score: 0.415 -> test with 'KNN' KNN tn, fp: 282, 8 KNN fn, tp: 1, 6 KNN f1 score: 0.571 KNN cohens kappa score: 0.558 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 16s - loss: 0.0157 38/116 [========>.....................] - ETA: 0s - loss: 0.0677  79/116 [===================>..........] - ETA: 0s - loss: 0.0687 116/116 [==============================] - 0s 1ms/step - loss: 0.0686 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0086 41/116 [=========>....................] - ETA: 0s - loss: 0.0576 80/116 [===================>..........] - ETA: 0s - loss: 0.0618 116/116 [==============================] - ETA: 0s - loss: 0.0664 116/116 [==============================] - 0s 1ms/step - loss: 0.0664 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1168 39/116 [=========>....................] - ETA: 0s - loss: 0.0612 77/116 [==================>...........] - ETA: 0s - loss: 0.0623 116/116 [==============================] - 0s 1ms/step - loss: 0.0665 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0106 38/116 [========>.....................] - ETA: 0s - loss: 0.0401 77/116 [==================>...........] - ETA: 0s - loss: 0.0548 111/116 [===========================>..] - ETA: 0s - loss: 0.0620 116/116 [==============================] - 0s 1ms/step - loss: 0.0639 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0745 37/116 [========>.....................] - ETA: 0s - loss: 0.0616 73/116 [=================>............] - ETA: 0s - loss: 0.0578 112/116 [===========================>..] - ETA: 0s - loss: 0.0628 116/116 [==============================] - 0s 1ms/step - loss: 0.0631 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0539 36/116 [========>.....................] - ETA: 0s - loss: 0.0535 76/116 [==================>...........] - ETA: 0s - loss: 0.0549 114/116 [============================>.] - ETA: 0s - loss: 0.0622 116/116 [==============================] - 0s 1ms/step - loss: 0.0624 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0522 36/116 [========>.....................] - ETA: 0s - loss: 0.0646 74/116 [==================>...........] - ETA: 0s - loss: 0.0637 110/116 [===========================>..] - ETA: 0s - loss: 0.0621 116/116 [==============================] - 0s 1ms/step - loss: 0.0625 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0574 37/116 [========>.....................] - ETA: 0s - loss: 0.0590 74/116 [==================>...........] - ETA: 0s - loss: 0.0611 113/116 [============================>.] - ETA: 0s - loss: 0.0637 116/116 [==============================] - 0s 1ms/step - loss: 0.0626 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0768 37/116 [========>.....................] - ETA: 0s - loss: 0.0708 69/116 [================>.............] - ETA: 0s - loss: 0.0614 103/116 [=========================>....] - ETA: 0s - loss: 0.0622 116/116 [==============================] - 0s 1ms/step - loss: 0.0597 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1747 38/116 [========>.....................] - ETA: 0s - loss: 0.0719 75/116 [==================>...........] - ETA: 0s - loss: 0.0653 112/116 [===========================>..] - ETA: 0s - loss: 0.0623 116/116 [==============================] - 0s 1ms/step - loss: 0.0612 -> test with GAN.predict GAN tn, fp: 284, 5 GAN fn, tp: 2, 5 GAN f1 score: 0.588 GAN cohens kappa score: 0.576 -> test with 'LR' LR tn, fp: 257, 32 LR fn, tp: 0, 7 LR f1 score: 0.304 LR cohens kappa score: 0.275 LR average precision score: 0.604 -> test with 'RF' RF tn, fp: 287, 2 RF fn, tp: 2, 5 RF f1 score: 0.714 RF cohens kappa score: 0.707 -> test with 'GB' GB tn, fp: 286, 3 GB fn, tp: 2, 5 GB f1 score: 0.667 GB cohens kappa score: 0.658 -> test with 'KNN' KNN tn, fp: 271, 18 KNN fn, tp: 1, 6 KNN f1 score: 0.387 KNN cohens kappa score: 0.364 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0174 43/116 [==========>...................] - ETA: 0s - loss: 0.0746  85/116 [====================>.........] - ETA: 0s - loss: 0.0571 116/116 [==============================] - 0s 1ms/step - loss: 0.0543 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1193 34/116 [=======>......................] - ETA: 0s - loss: 0.0283 74/116 [==================>...........] - ETA: 0s - loss: 0.0474 114/116 [============================>.] - ETA: 0s - loss: 0.0497 116/116 [==============================] - 0s 1ms/step - loss: 0.0491 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.3540 42/116 [=========>....................] - ETA: 0s - loss: 0.0720 82/116 [====================>.........] - ETA: 0s - loss: 0.0579 116/116 [==============================] - 0s 1ms/step - loss: 0.0481 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0796 41/116 [=========>....................] - ETA: 0s - loss: 0.0372 82/116 [====================>.........] - ETA: 0s - loss: 0.0462 116/116 [==============================] - 0s 1ms/step - loss: 0.0505 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0836 40/116 [=========>....................] - ETA: 0s - loss: 0.0521 79/116 [===================>..........] - ETA: 0s - loss: 0.0523 116/116 [==============================] - 0s 1ms/step - loss: 0.0491 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0086 40/116 [=========>....................] - ETA: 0s - loss: 0.0400 81/116 [===================>..........] - ETA: 0s - loss: 0.0514 116/116 [==============================] - 0s 1ms/step - loss: 0.0470 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0188 42/116 [=========>....................] - ETA: 0s - loss: 0.0414 82/116 [====================>.........] - ETA: 0s - loss: 0.0476 116/116 [==============================] - 0s 1ms/step - loss: 0.0476 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0132 41/116 [=========>....................] - ETA: 0s - loss: 0.0383 81/116 [===================>..........] - ETA: 0s - loss: 0.0446 116/116 [==============================] - 0s 1ms/step - loss: 0.0468 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0115 41/116 [=========>....................] - ETA: 0s - loss: 0.0501 82/116 [====================>.........] - ETA: 0s - loss: 0.0487 116/116 [==============================] - 0s 1ms/step - loss: 0.0449 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0183 35/116 [========>.....................] - ETA: 0s - loss: 0.0489 67/116 [================>.............] - ETA: 0s - loss: 0.0411 107/116 [==========================>...] - ETA: 0s - loss: 0.0402 116/116 [==============================] - 0s 1ms/step - loss: 0.0467 -> test with GAN.predict GAN tn, fp: 280, 10 GAN fn, tp: 2, 5 GAN f1 score: 0.455 GAN cohens kappa score: 0.436 -> test with 'LR' LR tn, fp: 277, 13 LR fn, tp: 1, 6 LR f1 score: 0.462 LR cohens kappa score: 0.442 LR average precision score: 0.669 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 3, 4 RF f1 score: 0.571 RF cohens kappa score: 0.561 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 3, 4 GB f1 score: 0.533 GB cohens kappa score: 0.521 -> test with 'KNN' KNN tn, fp: 279, 11 KNN fn, tp: 2, 5 KNN f1 score: 0.435 KNN cohens kappa score: 0.416 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.0153 41/116 [=========>....................] - ETA: 0s - loss: 0.0787  82/116 [====================>.........] - ETA: 0s - loss: 0.0736 116/116 [==============================] - 0s 1ms/step - loss: 0.0868 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0783 41/116 [=========>....................] - ETA: 0s - loss: 0.0750 82/116 [====================>.........] - ETA: 0s - loss: 0.0873 116/116 [==============================] - 0s 1ms/step - loss: 0.0859 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1277 42/116 [=========>....................] - ETA: 0s - loss: 0.0885 82/116 [====================>.........] - ETA: 0s - loss: 0.0842 116/116 [==============================] - 0s 1ms/step - loss: 0.0787 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0055 41/116 [=========>....................] - ETA: 0s - loss: 0.0687 81/116 [===================>..........] - ETA: 0s - loss: 0.0791 116/116 [==============================] - 0s 1ms/step - loss: 0.0787 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0100 38/116 [========>.....................] - ETA: 0s - loss: 0.0532 78/116 [===================>..........] - ETA: 0s - loss: 0.0699 116/116 [==============================] - 0s 1ms/step - loss: 0.0759 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0334 41/116 [=========>....................] - ETA: 0s - loss: 0.0918 80/116 [===================>..........] - ETA: 0s - loss: 0.0706 116/116 [==============================] - 0s 1ms/step - loss: 0.0734 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0301 42/116 [=========>....................] - ETA: 0s - loss: 0.0560 83/116 [====================>.........] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 1ms/step - loss: 0.0754 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0971 42/116 [=========>....................] - ETA: 0s - loss: 0.0762 83/116 [====================>.........] - ETA: 0s - loss: 0.0745 116/116 [==============================] - 0s 1ms/step - loss: 0.0744 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2248 41/116 [=========>....................] - ETA: 0s - loss: 0.0926 82/116 [====================>.........] - ETA: 0s - loss: 0.0779 116/116 [==============================] - 0s 1ms/step - loss: 0.0740 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1185 35/116 [========>.....................] - ETA: 0s - loss: 0.0538 69/116 [================>.............] - ETA: 0s - loss: 0.0696 106/116 [==========================>...] - ETA: 0s - loss: 0.0682 116/116 [==============================] - 0s 1ms/step - loss: 0.0722 -> test with GAN.predict GAN tn, fp: 275, 15 GAN fn, tp: 1, 6 GAN f1 score: 0.429 GAN cohens kappa score: 0.408 -> test with 'LR' LR tn, fp: 261, 29 LR fn, tp: 0, 7 LR f1 score: 0.326 LR cohens kappa score: 0.298 LR average precision score: 0.293 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 3, 4 RF f1 score: 0.615 RF cohens kappa score: 0.607 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 0, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 272, 18 KNN fn, tp: 0, 7 KNN f1 score: 0.438 KNN cohens kappa score: 0.416 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0378 42/116 [=========>....................] - ETA: 0s - loss: 0.0748  83/116 [====================>.........] - ETA: 0s - loss: 0.0604 116/116 [==============================] - 0s 1ms/step - loss: 0.0617 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0675 39/116 [=========>....................] - ETA: 0s - loss: 0.0645 79/116 [===================>..........] - ETA: 0s - loss: 0.0715 116/116 [==============================] - 0s 1ms/step - loss: 0.0627 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0067 40/116 [=========>....................] - ETA: 0s - loss: 0.0606 78/116 [===================>..........] - ETA: 0s - loss: 0.0623 116/116 [==============================] - 0s 1ms/step - loss: 0.0604 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0435 41/116 [=========>....................] - ETA: 0s - loss: 0.0565 81/116 [===================>..........] - ETA: 0s - loss: 0.0573 116/116 [==============================] - 0s 1ms/step - loss: 0.0578 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0099 42/116 [=========>....................] - ETA: 0s - loss: 0.0698 83/116 [====================>.........] - ETA: 0s - loss: 0.0662 116/116 [==============================] - 0s 1ms/step - loss: 0.0605 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1095 41/116 [=========>....................] - ETA: 0s - loss: 0.0576 80/116 [===================>..........] - ETA: 0s - loss: 0.0626 116/116 [==============================] - 0s 1ms/step - loss: 0.0585 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1753 35/116 [========>.....................] - ETA: 0s - loss: 0.0540 73/116 [=================>............] - ETA: 0s - loss: 0.0503 109/116 [===========================>..] - ETA: 0s - loss: 0.0624 116/116 [==============================] - 0s 1ms/step - loss: 0.0611 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0670 42/116 [=========>....................] - ETA: 0s - loss: 0.0601 80/116 [===================>..........] - ETA: 0s - loss: 0.0515 116/116 [==============================] - 0s 1ms/step - loss: 0.0581 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0096 35/116 [========>.....................] - ETA: 0s - loss: 0.0638 70/116 [=================>............] - ETA: 0s - loss: 0.0666 102/116 [=========================>....] - ETA: 0s - loss: 0.0628 116/116 [==============================] - 0s 1ms/step - loss: 0.0629 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0674 40/116 [=========>....................] - ETA: 0s - loss: 0.0695 79/116 [===================>..........] - ETA: 0s - loss: 0.0659 116/116 [==============================] - 0s 1ms/step - loss: 0.0584 -> test with GAN.predict GAN tn, fp: 282, 8 GAN fn, tp: 2, 5 GAN f1 score: 0.500 GAN cohens kappa score: 0.484 -> test with 'LR' LR tn, fp: 264, 26 LR fn, tp: 1, 6 LR f1 score: 0.308 LR cohens kappa score: 0.280 LR average precision score: 0.536 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 3, 4 RF f1 score: 0.615 RF cohens kappa score: 0.607 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 3, 4 GB f1 score: 0.533 GB cohens kappa score: 0.521 -> test with 'KNN' KNN tn, fp: 274, 16 KNN fn, tp: 2, 5 KNN f1 score: 0.357 KNN cohens kappa score: 0.334 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0154 42/116 [=========>....................] - ETA: 0s - loss: 0.0650  83/116 [====================>.........] - ETA: 0s - loss: 0.0536 116/116 [==============================] - 0s 1ms/step - loss: 0.0519 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0435 42/116 [=========>....................] - ETA: 0s - loss: 0.0285 82/116 [====================>.........] - ETA: 0s - loss: 0.0541 116/116 [==============================] - 0s 1ms/step - loss: 0.0507 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0051 44/116 [==========>...................] - ETA: 0s - loss: 0.0516 85/116 [====================>.........] - ETA: 0s - loss: 0.0478 116/116 [==============================] - 0s 1ms/step - loss: 0.0523 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1251 42/116 [=========>....................] - ETA: 0s - loss: 0.0477 83/116 [====================>.........] - ETA: 0s - loss: 0.0538 116/116 [==============================] - 0s 1ms/step - loss: 0.0556 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0285 41/116 [=========>....................] - ETA: 0s - loss: 0.0407 82/116 [====================>.........] - ETA: 0s - loss: 0.0449 116/116 [==============================] - 0s 1ms/step - loss: 0.0518 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1378 41/116 [=========>....................] - ETA: 0s - loss: 0.0506 80/116 [===================>..........] - ETA: 0s - loss: 0.0557 116/116 [==============================] - 0s 1ms/step - loss: 0.0506 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0321 40/116 [=========>....................] - ETA: 0s - loss: 0.0409 81/116 [===================>..........] - ETA: 0s - loss: 0.0472 116/116 [==============================] - 0s 1ms/step - loss: 0.0533 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0054 41/116 [=========>....................] - ETA: 0s - loss: 0.0524 82/116 [====================>.........] - ETA: 0s - loss: 0.0504 116/116 [==============================] - 0s 1ms/step - loss: 0.0507 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0065 38/116 [========>.....................] - ETA: 0s - loss: 0.0586 72/116 [=================>............] - ETA: 0s - loss: 0.0489 106/116 [==========================>...] - ETA: 0s - loss: 0.0470 116/116 [==============================] - 0s 1ms/step - loss: 0.0483 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0264 41/116 [=========>....................] - ETA: 0s - loss: 0.0474 79/116 [===================>..........] - ETA: 0s - loss: 0.0499 116/116 [==============================] - 0s 1ms/step - loss: 0.0492 -> test with GAN.predict GAN tn, fp: 284, 6 GAN fn, tp: 2, 5 GAN f1 score: 0.556 GAN cohens kappa score: 0.542 -> test with 'LR' LR tn, fp: 269, 21 LR fn, tp: 2, 5 LR f1 score: 0.303 LR cohens kappa score: 0.276 LR average precision score: 0.576 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 5, 2 RF f1 score: 0.400 RF cohens kappa score: 0.391 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 5, 2 GB f1 score: 0.333 GB cohens kappa score: 0.320 -> test with 'KNN' KNN tn, fp: 276, 14 KNN fn, tp: 3, 4 KNN f1 score: 0.320 KNN cohens kappa score: 0.296 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 41s - loss: 0.1905 40/116 [=========>....................] - ETA: 0s - loss: 0.0578  78/116 [===================>..........] - ETA: 0s - loss: 0.0604 114/116 [============================>.] - ETA: 0s - loss: 0.0625 116/116 [==============================] - 1s 1ms/step - loss: 0.0620 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0272 39/116 [=========>....................] - ETA: 0s - loss: 0.0671 76/116 [==================>...........] - ETA: 0s - loss: 0.0676 108/116 [==========================>...] - ETA: 0s - loss: 0.0645 116/116 [==============================] - 0s 1ms/step - loss: 0.0619 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0353 42/116 [=========>....................] - ETA: 0s - loss: 0.0477 80/116 [===================>..........] - ETA: 0s - loss: 0.0531 116/116 [==============================] - 0s 1ms/step - loss: 0.0603 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0049 41/116 [=========>....................] - ETA: 0s - loss: 0.0693 85/116 [====================>.........] - ETA: 0s - loss: 0.0593 116/116 [==============================] - 0s 1ms/step - loss: 0.0586 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0533 38/116 [========>.....................] - ETA: 0s - loss: 0.0399 76/116 [==================>...........] - ETA: 0s - loss: 0.0609 116/116 [==============================] - ETA: 0s - loss: 0.0585 116/116 [==============================] - 0s 1ms/step - loss: 0.0585 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0070 38/116 [========>.....................] - ETA: 0s - loss: 0.0652 76/116 [==================>...........] - ETA: 0s - loss: 0.0581 112/116 [===========================>..] - ETA: 0s - loss: 0.0593 116/116 [==============================] - 0s 1ms/step - loss: 0.0588 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1955 42/116 [=========>....................] - ETA: 0s - loss: 0.0615 75/116 [==================>...........] - ETA: 0s - loss: 0.0618 114/116 [============================>.] - ETA: 0s - loss: 0.0594 116/116 [==============================] - 0s 1ms/step - loss: 0.0589 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0852 38/116 [========>.....................] - ETA: 0s - loss: 0.0508 75/116 [==================>...........] - ETA: 0s - loss: 0.0569 112/116 [===========================>..] - ETA: 0s - loss: 0.0593 116/116 [==============================] - 0s 1ms/step - loss: 0.0584 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0697 38/116 [========>.....................] - ETA: 0s - loss: 0.0596 74/116 [==================>...........] - ETA: 0s - loss: 0.0646 110/116 [===========================>..] - ETA: 0s - loss: 0.0609 116/116 [==============================] - 0s 1ms/step - loss: 0.0606 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0196 35/116 [========>.....................] - ETA: 0s - loss: 0.0634 68/116 [================>.............] - ETA: 0s - loss: 0.0672 101/116 [=========================>....] - ETA: 0s - loss: 0.0591 116/116 [==============================] - 0s 2ms/step - loss: 0.0589 -> test with GAN.predict GAN tn, fp: 284, 5 GAN fn, tp: 2, 5 GAN f1 score: 0.588 GAN cohens kappa score: 0.576 -> test with 'LR' LR tn, fp: 276, 13 LR fn, tp: 1, 6 LR f1 score: 0.462 LR cohens kappa score: 0.442 LR average precision score: 0.488 -> test with 'RF' RF tn, fp: 289, 0 RF fn, tp: 6, 1 RF f1 score: 0.250 RF cohens kappa score: 0.246 -> test with 'GB' GB tn, fp: 288, 1 GB fn, tp: 4, 3 GB f1 score: 0.545 GB cohens kappa score: 0.537 -> test with 'KNN' KNN tn, fp: 282, 7 KNN fn, tp: 2, 5 KNN f1 score: 0.526 KNN cohens kappa score: 0.512 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0028 42/116 [=========>....................] - ETA: 0s - loss: 0.0640  83/116 [====================>.........] - ETA: 0s - loss: 0.0652 116/116 [==============================] - 0s 1ms/step - loss: 0.0583 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2149 41/116 [=========>....................] - ETA: 0s - loss: 0.0822 80/116 [===================>..........] - ETA: 0s - loss: 0.0568 116/116 [==============================] - 0s 1ms/step - loss: 0.0554 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0017 41/116 [=========>....................] - ETA: 0s - loss: 0.0571 82/116 [====================>.........] - ETA: 0s - loss: 0.0505 116/116 [==============================] - 0s 1ms/step - loss: 0.0530 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0032 36/116 [========>.....................] - ETA: 0s - loss: 0.0372 69/116 [================>.............] - ETA: 0s - loss: 0.0504 103/116 [=========================>....] - ETA: 0s - loss: 0.0523 116/116 [==============================] - 0s 1ms/step - loss: 0.0527 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0148 42/116 [=========>....................] - ETA: 0s - loss: 0.0425 82/116 [====================>.........] - ETA: 0s - loss: 0.0554 116/116 [==============================] - 0s 1ms/step - loss: 0.0525 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0158 39/116 [=========>....................] - ETA: 0s - loss: 0.0431 75/116 [==================>...........] - ETA: 0s - loss: 0.0473 115/116 [============================>.] - ETA: 0s - loss: 0.0516 116/116 [==============================] - 0s 1ms/step - loss: 0.0514 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0109 42/116 [=========>....................] - ETA: 0s - loss: 0.0516 83/116 [====================>.........] - ETA: 0s - loss: 0.0494 116/116 [==============================] - 0s 1ms/step - loss: 0.0529 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0052 42/116 [=========>....................] - ETA: 0s - loss: 0.0462 81/116 [===================>..........] - ETA: 0s - loss: 0.0576 116/116 [==============================] - 0s 1ms/step - loss: 0.0525 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0338 41/116 [=========>....................] - ETA: 0s - loss: 0.0417 77/116 [==================>...........] - ETA: 0s - loss: 0.0560 116/116 [==============================] - 0s 1ms/step - loss: 0.0540 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0294 40/116 [=========>....................] - ETA: 0s - loss: 0.0465 80/116 [===================>..........] - ETA: 0s - loss: 0.0546 116/116 [==============================] - 0s 1ms/step - loss: 0.0514 -> test with GAN.predict GAN tn, fp: 285, 5 GAN fn, tp: 2, 5 GAN f1 score: 0.588 GAN cohens kappa score: 0.576 -> test with 'LR' LR tn, fp: 269, 21 LR fn, tp: 1, 6 LR f1 score: 0.353 LR cohens kappa score: 0.328 LR average precision score: 0.651 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 3, 4 RF f1 score: 0.667 RF cohens kappa score: 0.660 -> test with 'GB' GB tn, fp: 288, 2 GB fn, tp: 3, 4 GB f1 score: 0.615 GB cohens kappa score: 0.607 -> test with 'KNN' KNN tn, fp: 281, 9 KNN fn, tp: 1, 6 KNN f1 score: 0.545 KNN cohens kappa score: 0.530 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0282 43/116 [==========>...................] - ETA: 0s - loss: 0.0637  85/116 [====================>.........] - ETA: 0s - loss: 0.0632 116/116 [==============================] - 0s 1ms/step - loss: 0.0752 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0165 37/116 [========>.....................] - ETA: 0s - loss: 0.0704 70/116 [=================>............] - ETA: 0s - loss: 0.0683 109/116 [===========================>..] - ETA: 0s - loss: 0.0673 116/116 [==============================] - 0s 1ms/step - loss: 0.0737 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0348 42/116 [=========>....................] - ETA: 0s - loss: 0.0595 83/116 [====================>.........] - ETA: 0s - loss: 0.0551 116/116 [==============================] - 0s 1ms/step - loss: 0.0686 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0080 42/116 [=========>....................] - ETA: 0s - loss: 0.0585 82/116 [====================>.........] - ETA: 0s - loss: 0.0732 116/116 [==============================] - 0s 1ms/step - loss: 0.0719 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0185 42/116 [=========>....................] - ETA: 0s - loss: 0.0679 82/116 [====================>.........] - ETA: 0s - loss: 0.0659 116/116 [==============================] - 0s 1ms/step - loss: 0.0696 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0773 41/116 [=========>....................] - ETA: 0s - loss: 0.0750 82/116 [====================>.........] - ETA: 0s - loss: 0.0742 116/116 [==============================] - 0s 1ms/step - loss: 0.0668 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1069 41/116 [=========>....................] - ETA: 0s - loss: 0.0652 81/116 [===================>..........] - ETA: 0s - loss: 0.0606 116/116 [==============================] - 0s 1ms/step - loss: 0.0672 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0101 41/116 [=========>....................] - ETA: 0s - loss: 0.0655 81/116 [===================>..........] - ETA: 0s - loss: 0.0658 116/116 [==============================] - 0s 1ms/step - loss: 0.0664 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1889 41/116 [=========>....................] - ETA: 0s - loss: 0.0706 82/116 [====================>.........] - ETA: 0s - loss: 0.0616 116/116 [==============================] - 0s 1ms/step - loss: 0.0647 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0261 41/116 [=========>....................] - ETA: 0s - loss: 0.0631 81/116 [===================>..........] - ETA: 0s - loss: 0.0656 116/116 [==============================] - 0s 1ms/step - loss: 0.0651 -> test with GAN.predict GAN tn, fp: 275, 15 GAN fn, tp: 0, 7 GAN f1 score: 0.483 GAN cohens kappa score: 0.464 -> test with 'LR' LR tn, fp: 262, 28 LR fn, tp: 0, 7 LR f1 score: 0.333 LR cohens kappa score: 0.306 LR average precision score: 0.793 -> test with 'RF' RF tn, fp: 286, 4 RF fn, tp: 3, 4 RF f1 score: 0.533 RF cohens kappa score: 0.521 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 3, 4 GB f1 score: 0.533 GB cohens kappa score: 0.521 -> test with 'KNN' KNN tn, fp: 267, 23 KNN fn, tp: 0, 7 KNN f1 score: 0.378 KNN cohens kappa score: 0.354 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0228 32/116 [=======>......................] - ETA: 0s - loss: 0.0560  69/116 [================>.............] - ETA: 0s - loss: 0.0608 109/116 [===========================>..] - ETA: 0s - loss: 0.0619 116/116 [==============================] - 0s 1ms/step - loss: 0.0610 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0926 38/116 [========>.....................] - ETA: 0s - loss: 0.0585 76/116 [==================>...........] - ETA: 0s - loss: 0.0577 116/116 [==============================] - 0s 1ms/step - loss: 0.0553 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0109 42/116 [=========>....................] - ETA: 0s - loss: 0.0626 83/116 [====================>.........] - ETA: 0s - loss: 0.0623 116/116 [==============================] - 0s 1ms/step - loss: 0.0549 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1438 41/116 [=========>....................] - ETA: 0s - loss: 0.0502 82/116 [====================>.........] - ETA: 0s - loss: 0.0591 116/116 [==============================] - 0s 1ms/step - loss: 0.0544 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0112 41/116 [=========>....................] - ETA: 0s - loss: 0.0633 76/116 [==================>...........] - ETA: 0s - loss: 0.0575 111/116 [===========================>..] - ETA: 0s - loss: 0.0551 116/116 [==============================] - 0s 1ms/step - loss: 0.0544 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0079 39/116 [=========>....................] - ETA: 0s - loss: 0.0552 80/116 [===================>..........] - ETA: 0s - loss: 0.0582 116/116 [==============================] - 0s 1ms/step - loss: 0.0548 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0156 40/116 [=========>....................] - ETA: 0s - loss: 0.0626 80/116 [===================>..........] - ETA: 0s - loss: 0.0499 116/116 [==============================] - 0s 1ms/step - loss: 0.0525 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1336 42/116 [=========>....................] - ETA: 0s - loss: 0.0536 82/116 [====================>.........] - ETA: 0s - loss: 0.0491 116/116 [==============================] - 0s 1ms/step - loss: 0.0556 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0440 42/116 [=========>....................] - ETA: 0s - loss: 0.0579 82/116 [====================>.........] - ETA: 0s - loss: 0.0537 116/116 [==============================] - 0s 1ms/step - loss: 0.0527 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0221 42/116 [=========>....................] - ETA: 0s - loss: 0.0707 83/116 [====================>.........] - ETA: 0s - loss: 0.0545 116/116 [==============================] - 0s 1ms/step - loss: 0.0511 -> test with GAN.predict GAN tn, fp: 283, 7 GAN fn, tp: 3, 4 GAN f1 score: 0.444 GAN cohens kappa score: 0.428 -> test with 'LR' LR tn, fp: 275, 15 LR fn, tp: 2, 5 LR f1 score: 0.370 LR cohens kappa score: 0.348 LR average precision score: 0.419 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 3, 4 RF f1 score: 0.615 RF cohens kappa score: 0.607 -> test with 'GB' GB tn, fp: 288, 2 GB fn, tp: 3, 4 GB f1 score: 0.615 GB cohens kappa score: 0.607 -> test with 'KNN' KNN tn, fp: 280, 10 KNN fn, tp: 3, 4 KNN f1 score: 0.381 KNN cohens kappa score: 0.361 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0540 40/116 [=========>....................] - ETA: 0s - loss: 0.0823  81/116 [===================>..........] - ETA: 0s - loss: 0.0812 116/116 [==============================] - 0s 1ms/step - loss: 0.0777 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0238 41/116 [=========>....................] - ETA: 0s - loss: 0.0544 79/116 [===================>..........] - ETA: 0s - loss: 0.0576 116/116 [==============================] - 0s 1ms/step - loss: 0.0739 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0386 39/116 [=========>....................] - ETA: 0s - loss: 0.0765 80/116 [===================>..........] - ETA: 0s - loss: 0.0705 116/116 [==============================] - 0s 1ms/step - loss: 0.0715 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0474 41/116 [=========>....................] - ETA: 0s - loss: 0.0688 76/116 [==================>...........] - ETA: 0s - loss: 0.0694 111/116 [===========================>..] - ETA: 0s - loss: 0.0719 116/116 [==============================] - 0s 1ms/step - loss: 0.0734 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0304 37/116 [========>.....................] - ETA: 0s - loss: 0.0598 75/116 [==================>...........] - ETA: 0s - loss: 0.0577 116/116 [==============================] - 0s 1ms/step - loss: 0.0692 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2570 40/116 [=========>....................] - ETA: 0s - loss: 0.0841 79/116 [===================>..........] - ETA: 0s - loss: 0.0751 116/116 [==============================] - 0s 1ms/step - loss: 0.0703 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1121 41/116 [=========>....................] - ETA: 0s - loss: 0.0676 83/116 [====================>.........] - ETA: 0s - loss: 0.0701 116/116 [==============================] - 0s 1ms/step - loss: 0.0699 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0450 41/116 [=========>....................] - ETA: 0s - loss: 0.0626 82/116 [====================>.........] - ETA: 0s - loss: 0.0650 116/116 [==============================] - 0s 1ms/step - loss: 0.0692 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0298 41/116 [=========>....................] - ETA: 0s - loss: 0.0925 81/116 [===================>..........] - ETA: 0s - loss: 0.0835 116/116 [==============================] - 0s 1ms/step - loss: 0.0745 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0034 42/116 [=========>....................] - ETA: 0s - loss: 0.0767 82/116 [====================>.........] - ETA: 0s - loss: 0.0729 116/116 [==============================] - 0s 1ms/step - loss: 0.0697 -> test with GAN.predict GAN tn, fp: 280, 10 GAN fn, tp: 2, 5 GAN f1 score: 0.455 GAN cohens kappa score: 0.436 -> test with 'LR' LR tn, fp: 264, 26 LR fn, tp: 1, 6 LR f1 score: 0.308 LR cohens kappa score: 0.280 LR average precision score: 0.442 -> test with 'RF' RF tn, fp: 286, 4 RF fn, tp: 3, 4 RF f1 score: 0.533 RF cohens kappa score: 0.521 -> test with 'GB' GB tn, fp: 281, 9 GB fn, tp: 3, 4 GB f1 score: 0.400 GB cohens kappa score: 0.381 -> test with 'KNN' KNN tn, fp: 273, 17 KNN fn, tp: 2, 5 KNN f1 score: 0.345 KNN cohens kappa score: 0.321 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 15s - loss: 0.0093 37/116 [========>.....................] - ETA: 0s - loss: 0.0854  79/116 [===================>..........] - ETA: 0s - loss: 0.0863 115/116 [============================>.] - ETA: 0s - loss: 0.0821 116/116 [==============================] - 0s 1ms/step - loss: 0.0820 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0087 34/116 [=======>......................] - ETA: 0s - loss: 0.0781 67/116 [================>.............] - ETA: 0s - loss: 0.0785 98/116 [========================>.....] - ETA: 0s - loss: 0.0773 116/116 [==============================] - 0s 2ms/step - loss: 0.0754 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0500 44/116 [==========>...................] - ETA: 0s - loss: 0.0655 82/116 [====================>.........] - ETA: 0s - loss: 0.0774 116/116 [==============================] - 0s 1ms/step - loss: 0.0763 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1682 39/116 [=========>....................] - ETA: 0s - loss: 0.1028 78/116 [===================>..........] - ETA: 0s - loss: 0.0739 116/116 [==============================] - ETA: 0s - loss: 0.0720 116/116 [==============================] - 0s 1ms/step - loss: 0.0720 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0191 38/116 [========>.....................] - ETA: 0s - loss: 0.0686 76/116 [==================>...........] - ETA: 0s - loss: 0.0733 114/116 [============================>.] - ETA: 0s - loss: 0.0713 116/116 [==============================] - 0s 1ms/step - loss: 0.0716 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0220 37/116 [========>.....................] - ETA: 0s - loss: 0.0764 76/116 [==================>...........] - ETA: 0s - loss: 0.0704 113/116 [============================>.] - ETA: 0s - loss: 0.0717 116/116 [==============================] - 0s 1ms/step - loss: 0.0706 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2317 37/116 [========>.....................] - ETA: 0s - loss: 0.0775 74/116 [==================>...........] - ETA: 0s - loss: 0.0744 116/116 [==============================] - ETA: 0s - loss: 0.0690 116/116 [==============================] - 0s 1ms/step - loss: 0.0690 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0595 37/116 [========>.....................] - ETA: 0s - loss: 0.0769 76/116 [==================>...........] - ETA: 0s - loss: 0.0710 113/116 [============================>.] - ETA: 0s - loss: 0.0709 116/116 [==============================] - 0s 1ms/step - loss: 0.0709 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0872 40/116 [=========>....................] - ETA: 0s - loss: 0.0742 80/116 [===================>..........] - ETA: 0s - loss: 0.0689 116/116 [==============================] - 0s 1ms/step - loss: 0.0691 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0068 37/116 [========>.....................] - ETA: 0s - loss: 0.0503 72/116 [=================>............] - ETA: 0s - loss: 0.0662 111/116 [===========================>..] - ETA: 0s - loss: 0.0692 116/116 [==============================] - 0s 1ms/step - loss: 0.0675 -> test with GAN.predict GAN tn, fp: 283, 6 GAN fn, tp: 4, 3 GAN f1 score: 0.375 GAN cohens kappa score: 0.358 -> test with 'LR' LR tn, fp: 273, 16 LR fn, tp: 1, 6 LR f1 score: 0.414 LR cohens kappa score: 0.392 LR average precision score: 0.502 -> test with 'RF' RF tn, fp: 288, 1 RF fn, tp: 6, 1 RF f1 score: 0.222 RF cohens kappa score: 0.214 -> test with 'GB' GB tn, fp: 287, 2 GB fn, tp: 4, 3 GB f1 score: 0.500 GB cohens kappa score: 0.490 -> test with 'KNN' KNN tn, fp: 278, 11 KNN fn, tp: 1, 6 KNN f1 score: 0.500 KNN cohens kappa score: 0.483 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.0144 42/116 [=========>....................] - ETA: 0s - loss: 0.0611  83/116 [====================>.........] - ETA: 0s - loss: 0.0627 116/116 [==============================] - 0s 1ms/step - loss: 0.0645 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0043 40/116 [=========>....................] - ETA: 0s - loss: 0.0459 80/116 [===================>..........] - ETA: 0s - loss: 0.0448 116/116 [==============================] - 0s 1ms/step - loss: 0.0637 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0225 42/116 [=========>....................] - ETA: 0s - loss: 0.0964 83/116 [====================>.........] - ETA: 0s - loss: 0.0629 116/116 [==============================] - 0s 1ms/step - loss: 0.0639 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.5400 41/116 [=========>....................] - ETA: 0s - loss: 0.0773 79/116 [===================>..........] - ETA: 0s - loss: 0.0680 116/116 [==============================] - 0s 1ms/step - loss: 0.0581 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1331 40/116 [=========>....................] - ETA: 0s - loss: 0.0473 79/116 [===================>..........] - ETA: 0s - loss: 0.0533 113/116 [============================>.] - ETA: 0s - loss: 0.0583 116/116 [==============================] - 0s 1ms/step - loss: 0.0572 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0066 35/116 [========>.....................] - ETA: 0s - loss: 0.0623 73/116 [=================>............] - ETA: 0s - loss: 0.0620 113/116 [============================>.] - ETA: 0s - loss: 0.0544 116/116 [==============================] - 0s 1ms/step - loss: 0.0550 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0561 40/116 [=========>....................] - ETA: 0s - loss: 0.0637 81/116 [===================>..........] - ETA: 0s - loss: 0.0551 116/116 [==============================] - 0s 1ms/step - loss: 0.0562 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0190 42/116 [=========>....................] - ETA: 0s - loss: 0.0697 77/116 [==================>...........] - ETA: 0s - loss: 0.0606 115/116 [============================>.] - ETA: 0s - loss: 0.0558 116/116 [==============================] - 0s 1ms/step - loss: 0.0554 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0737 41/116 [=========>....................] - ETA: 0s - loss: 0.0438 81/116 [===================>..........] - ETA: 0s - loss: 0.0459 116/116 [==============================] - 0s 1ms/step - loss: 0.0559 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0141 41/116 [=========>....................] - ETA: 0s - loss: 0.0450 80/116 [===================>..........] - ETA: 0s - loss: 0.0574 116/116 [==============================] - 0s 1ms/step - loss: 0.0579 -> test with GAN.predict GAN tn, fp: 288, 2 GAN fn, tp: 4, 3 GAN f1 score: 0.500 GAN cohens kappa score: 0.490 -> test with 'LR' LR tn, fp: 276, 14 LR fn, tp: 1, 6 LR f1 score: 0.444 LR cohens kappa score: 0.424 LR average precision score: 0.741 -> test with 'RF' RF tn, fp: 290, 0 RF fn, tp: 3, 4 RF f1 score: 0.727 RF cohens kappa score: 0.723 -> test with 'GB' GB tn, fp: 288, 2 GB fn, tp: 1, 6 GB f1 score: 0.800 GB cohens kappa score: 0.795 -> test with 'KNN' KNN tn, fp: 279, 11 KNN fn, tp: 1, 6 KNN f1 score: 0.500 KNN cohens kappa score: 0.483 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0092 41/116 [=========>....................] - ETA: 0s - loss: 0.0729  82/116 [====================>.........] - ETA: 0s - loss: 0.0770 116/116 [==============================] - 0s 1ms/step - loss: 0.0783 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1526 41/116 [=========>....................] - ETA: 0s - loss: 0.0822 78/116 [===================>..........] - ETA: 0s - loss: 0.0846 116/116 [==============================] - 0s 1ms/step - loss: 0.0832 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0717 41/116 [=========>....................] - ETA: 0s - loss: 0.0746 81/116 [===================>..........] - ETA: 0s - loss: 0.0732 115/116 [============================>.] - ETA: 0s - loss: 0.0737 116/116 [==============================] - 0s 1ms/step - loss: 0.0745 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2795 39/116 [=========>....................] - ETA: 0s - loss: 0.0819 74/116 [==================>...........] - ETA: 0s - loss: 0.0772 115/116 [============================>.] - ETA: 0s - loss: 0.0728 116/116 [==============================] - 0s 1ms/step - loss: 0.0732 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0710 42/116 [=========>....................] - ETA: 0s - loss: 0.0698 81/116 [===================>..........] - ETA: 0s - loss: 0.0742 116/116 [==============================] - 0s 1ms/step - loss: 0.0710 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.3352 41/116 [=========>....................] - ETA: 0s - loss: 0.0798 81/116 [===================>..........] - ETA: 0s - loss: 0.0735 116/116 [==============================] - 0s 1ms/step - loss: 0.0730 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0122 42/116 [=========>....................] - ETA: 0s - loss: 0.0667 83/116 [====================>.........] - ETA: 0s - loss: 0.0687 116/116 [==============================] - 0s 1ms/step - loss: 0.0700 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0062 41/116 [=========>....................] - ETA: 0s - loss: 0.0571 82/116 [====================>.........] - ETA: 0s - loss: 0.0709 116/116 [==============================] - 0s 1ms/step - loss: 0.0704 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0658 42/116 [=========>....................] - ETA: 0s - loss: 0.0712 81/116 [===================>..........] - ETA: 0s - loss: 0.0724 116/116 [==============================] - 0s 1ms/step - loss: 0.0702 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0119 41/116 [=========>....................] - ETA: 0s - loss: 0.0640 81/116 [===================>..........] - ETA: 0s - loss: 0.0696 116/116 [==============================] - 0s 1ms/step - loss: 0.0682 -> test with GAN.predict GAN tn, fp: 282, 8 GAN fn, tp: 2, 5 GAN f1 score: 0.500 GAN cohens kappa score: 0.484 -> test with 'LR' LR tn, fp: 265, 25 LR fn, tp: 0, 7 LR f1 score: 0.359 LR cohens kappa score: 0.333 LR average precision score: 0.290 -> test with 'RF' RF tn, fp: 286, 4 RF fn, tp: 3, 4 RF f1 score: 0.533 RF cohens kappa score: 0.521 -> test with 'GB' GB tn, fp: 285, 5 GB fn, tp: 3, 4 GB f1 score: 0.500 GB cohens kappa score: 0.486 -> test with 'KNN' KNN tn, fp: 274, 16 KNN fn, tp: 1, 6 KNN f1 score: 0.414 KNN cohens kappa score: 0.392 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.0955 42/116 [=========>....................] - ETA: 0s - loss: 0.0523  78/116 [===================>..........] - ETA: 0s - loss: 0.0654 116/116 [==============================] - 0s 1ms/step - loss: 0.0657 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0108 40/116 [=========>....................] - ETA: 0s - loss: 0.0509 80/116 [===================>..........] - ETA: 0s - loss: 0.0537 116/116 [==============================] - 0s 1ms/step - loss: 0.0599 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0116 41/116 [=========>....................] - ETA: 0s - loss: 0.0393 81/116 [===================>..........] - ETA: 0s - loss: 0.0577 116/116 [==============================] - 0s 1ms/step - loss: 0.0588 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0329 41/116 [=========>....................] - ETA: 0s - loss: 0.0548 75/116 [==================>...........] - ETA: 0s - loss: 0.0595 108/116 [==========================>...] - ETA: 0s - loss: 0.0632 116/116 [==============================] - 0s 1ms/step - loss: 0.0627 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0140 38/116 [========>.....................] - ETA: 0s - loss: 0.0717 76/116 [==================>...........] - ETA: 0s - loss: 0.0558 116/116 [==============================] - 0s 1ms/step - loss: 0.0588 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0629 42/116 [=========>....................] - ETA: 0s - loss: 0.0471 83/116 [====================>.........] - ETA: 0s - loss: 0.0554 116/116 [==============================] - 0s 1ms/step - loss: 0.0597 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1409 41/116 [=========>....................] - ETA: 0s - loss: 0.0605 82/116 [====================>.........] - ETA: 0s - loss: 0.0617 116/116 [==============================] - 0s 1ms/step - loss: 0.0581 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0550 41/116 [=========>....................] - ETA: 0s - loss: 0.0704 81/116 [===================>..........] - ETA: 0s - loss: 0.0580 116/116 [==============================] - 0s 1ms/step - loss: 0.0581 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0727 41/116 [=========>....................] - ETA: 0s - loss: 0.0538 79/116 [===================>..........] - ETA: 0s - loss: 0.0543 116/116 [==============================] - 0s 1ms/step - loss: 0.0568 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0095 41/116 [=========>....................] - ETA: 0s - loss: 0.0723 82/116 [====================>.........] - ETA: 0s - loss: 0.0533 116/116 [==============================] - 0s 1ms/step - loss: 0.0580 -> test with GAN.predict GAN tn, fp: 278, 12 GAN fn, tp: 1, 6 GAN f1 score: 0.480 GAN cohens kappa score: 0.462 -> test with 'LR' LR tn, fp: 262, 28 LR fn, tp: 1, 6 LR f1 score: 0.293 LR cohens kappa score: 0.264 LR average precision score: 0.554 -> test with 'RF' RF tn, fp: 286, 4 RF fn, tp: 1, 6 RF f1 score: 0.706 RF cohens kappa score: 0.697 -> test with 'GB' GB tn, fp: 284, 6 GB fn, tp: 2, 5 GB f1 score: 0.556 GB cohens kappa score: 0.542 -> test with 'KNN' KNN tn, fp: 270, 20 KNN fn, tp: 1, 6 KNN f1 score: 0.364 KNN cohens kappa score: 0.339 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 22s - loss: 0.0394 41/116 [=========>....................] - ETA: 0s - loss: 0.0654  81/116 [===================>..........] - ETA: 0s - loss: 0.0660 116/116 [==============================] - 0s 1ms/step - loss: 0.0658 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2063 42/116 [=========>....................] - ETA: 0s - loss: 0.0530 82/116 [====================>.........] - ETA: 0s - loss: 0.0552 116/116 [==============================] - 0s 1ms/step - loss: 0.0645 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0117 38/116 [========>.....................] - ETA: 0s - loss: 0.0529 78/116 [===================>..........] - ETA: 0s - loss: 0.0615 116/116 [==============================] - ETA: 0s - loss: 0.0630 116/116 [==============================] - 0s 1ms/step - loss: 0.0630 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0127 43/116 [==========>...................] - ETA: 0s - loss: 0.0724 83/116 [====================>.........] - ETA: 0s - loss: 0.0690 116/116 [==============================] - 0s 1ms/step - loss: 0.0635 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0116 41/116 [=========>....................] - ETA: 0s - loss: 0.0610 82/116 [====================>.........] - ETA: 0s - loss: 0.0599 116/116 [==============================] - 0s 1ms/step - loss: 0.0621 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0544 40/116 [=========>....................] - ETA: 0s - loss: 0.0470 82/116 [====================>.........] - ETA: 0s - loss: 0.0535 116/116 [==============================] - 0s 1ms/step - loss: 0.0605 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0243 42/116 [=========>....................] - ETA: 0s - loss: 0.0729 82/116 [====================>.........] - ETA: 0s - loss: 0.0659 116/116 [==============================] - 0s 1ms/step - loss: 0.0625 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0199 42/116 [=========>....................] - ETA: 0s - loss: 0.0615 83/116 [====================>.........] - ETA: 0s - loss: 0.0567 116/116 [==============================] - 0s 1ms/step - loss: 0.0606 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0064 42/116 [=========>....................] - ETA: 0s - loss: 0.0497 83/116 [====================>.........] - ETA: 0s - loss: 0.0674 116/116 [==============================] - 0s 1ms/step - loss: 0.0594 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0054 39/116 [=========>....................] - ETA: 0s - loss: 0.0674 79/116 [===================>..........] - ETA: 0s - loss: 0.0642 116/116 [==============================] - 0s 1ms/step - loss: 0.0589 -> test with GAN.predict GAN tn, fp: 283, 7 GAN fn, tp: 2, 5 GAN f1 score: 0.526 GAN cohens kappa score: 0.512 -> test with 'LR' LR tn, fp: 271, 19 LR fn, tp: 1, 6 LR f1 score: 0.375 LR cohens kappa score: 0.351 LR average precision score: 0.646 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 4, 3 RF f1 score: 0.545 RF cohens kappa score: 0.538 -> test with 'GB' GB tn, fp: 289, 1 GB fn, tp: 4, 3 GB f1 score: 0.545 GB cohens kappa score: 0.538 -> test with 'KNN' KNN tn, fp: 279, 11 KNN fn, tp: 2, 5 KNN f1 score: 0.435 KNN cohens kappa score: 0.416 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 16s - loss: 0.0087 44/116 [==========>...................] - ETA: 0s - loss: 0.0428  87/116 [=====================>........] - ETA: 0s - loss: 0.0507 116/116 [==============================] - 0s 1ms/step - loss: 0.0563 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0063 45/116 [==========>...................] - ETA: 0s - loss: 0.0520 89/116 [======================>.......] - ETA: 0s - loss: 0.0495 116/116 [==============================] - 0s 1ms/step - loss: 0.0565 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0306 44/116 [==========>...................] - ETA: 0s - loss: 0.0655 85/116 [====================>.........] - ETA: 0s - loss: 0.0518 116/116 [==============================] - 0s 1ms/step - loss: 0.0558 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0627 36/116 [========>.....................] - ETA: 0s - loss: 0.0961 74/116 [==================>...........] - ETA: 0s - loss: 0.0713 108/116 [==========================>...] - ETA: 0s - loss: 0.0587 116/116 [==============================] - 0s 1ms/step - loss: 0.0587 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0204 45/116 [==========>...................] - ETA: 0s - loss: 0.0385 86/116 [=====================>........] - ETA: 0s - loss: 0.0468 116/116 [==============================] - 0s 1ms/step - loss: 0.0549 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0063 44/116 [==========>...................] - ETA: 0s - loss: 0.0763 87/116 [=====================>........] - ETA: 0s - loss: 0.0622 116/116 [==============================] - 0s 1ms/step - loss: 0.0553 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0333 43/116 [==========>...................] - ETA: 0s - loss: 0.0461 81/116 [===================>..........] - ETA: 0s - loss: 0.0509 116/116 [==============================] - 0s 1ms/step - loss: 0.0530 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1172 45/116 [==========>...................] - ETA: 0s - loss: 0.0613 90/116 [======================>.......] - ETA: 0s - loss: 0.0555 116/116 [==============================] - 0s 1ms/step - loss: 0.0558 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0071 41/116 [=========>....................] - ETA: 0s - loss: 0.0424 85/116 [====================>.........] - ETA: 0s - loss: 0.0538 116/116 [==============================] - 0s 1ms/step - loss: 0.0557 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0414 44/116 [==========>...................] - ETA: 0s - loss: 0.0500 87/116 [=====================>........] - ETA: 0s - loss: 0.0464 116/116 [==============================] - 0s 1ms/step - loss: 0.0521 -> test with GAN.predict GAN tn, fp: 284, 5 GAN fn, tp: 4, 3 GAN f1 score: 0.400 GAN cohens kappa score: 0.384 -> test with 'LR' LR tn, fp: 272, 17 LR fn, tp: 2, 5 LR f1 score: 0.345 LR cohens kappa score: 0.320 LR average precision score: 0.670 -> test with 'RF' RF tn, fp: 288, 1 RF fn, tp: 4, 3 RF f1 score: 0.545 RF cohens kappa score: 0.537 -> test with 'GB' GB tn, fp: 288, 1 GB fn, tp: 4, 3 GB f1 score: 0.545 GB cohens kappa score: 0.537 -> test with 'KNN' KNN tn, fp: 279, 10 KNN fn, tp: 2, 5 KNN f1 score: 0.455 KNN cohens kappa score: 0.436 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.0086 42/116 [=========>....................] - ETA: 0s - loss: 0.0695  83/116 [====================>.........] - ETA: 0s - loss: 0.0660 116/116 [==============================] - ETA: 0s - loss: 0.0619 116/116 [==============================] - 0s 1ms/step - loss: 0.0619 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0049 34/116 [=======>......................] - ETA: 0s - loss: 0.0689 71/116 [=================>............] - ETA: 0s - loss: 0.0651 112/116 [===========================>..] - ETA: 0s - loss: 0.0650 116/116 [==============================] - 0s 1ms/step - loss: 0.0634 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0114 42/116 [=========>....................] - ETA: 0s - loss: 0.0641 84/116 [====================>.........] - ETA: 0s - loss: 0.0652 116/116 [==============================] - 0s 1ms/step - loss: 0.0602 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0121 42/116 [=========>....................] - ETA: 0s - loss: 0.0609 83/116 [====================>.........] - ETA: 0s - loss: 0.0487 116/116 [==============================] - 0s 1ms/step - loss: 0.0581 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0108 40/116 [=========>....................] - ETA: 0s - loss: 0.0492 81/116 [===================>..........] - ETA: 0s - loss: 0.0607 116/116 [==============================] - 0s 1ms/step - loss: 0.0605 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0654 42/116 [=========>....................] - ETA: 0s - loss: 0.0579 82/116 [====================>.........] - ETA: 0s - loss: 0.0584 116/116 [==============================] - 0s 1ms/step - loss: 0.0603 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0345 42/116 [=========>....................] - ETA: 0s - loss: 0.0626 80/116 [===================>..........] - ETA: 0s - loss: 0.0591 116/116 [==============================] - 0s 1ms/step - loss: 0.0585 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0194 40/116 [=========>....................] - ETA: 0s - loss: 0.0585 80/116 [===================>..........] - ETA: 0s - loss: 0.0584 116/116 [==============================] - 0s 1ms/step - loss: 0.0610 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0114 43/116 [==========>...................] - ETA: 0s - loss: 0.0618 80/116 [===================>..........] - ETA: 0s - loss: 0.0603 116/116 [==============================] - 0s 1ms/step - loss: 0.0578 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0336 41/116 [=========>....................] - ETA: 0s - loss: 0.0407 81/116 [===================>..........] - ETA: 0s - loss: 0.0537 116/116 [==============================] - 0s 1ms/step - loss: 0.0575 -> test with GAN.predict GAN tn, fp: 282, 8 GAN fn, tp: 1, 6 GAN f1 score: 0.571 GAN cohens kappa score: 0.558 -> test with 'LR' LR tn, fp: 270, 20 LR fn, tp: 0, 7 LR f1 score: 0.412 LR cohens kappa score: 0.389 LR average precision score: 0.505 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 3, 4 RF f1 score: 0.571 RF cohens kappa score: 0.561 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 2, 5 GB f1 score: 0.625 GB cohens kappa score: 0.615 -> test with 'KNN' KNN tn, fp: 272, 18 KNN fn, tp: 1, 6 KNN f1 score: 0.387 KNN cohens kappa score: 0.364 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0293 37/116 [========>.....................] - ETA: 0s - loss: 0.0603  81/116 [===================>..........] - ETA: 0s - loss: 0.0780 116/116 [==============================] - 0s 1ms/step - loss: 0.0724 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0389 41/116 [=========>....................] - ETA: 0s - loss: 0.0802 82/116 [====================>.........] - ETA: 0s - loss: 0.0695 116/116 [==============================] - 0s 1ms/step - loss: 0.0714 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0389 40/116 [=========>....................] - ETA: 0s - loss: 0.0717 80/116 [===================>..........] - ETA: 0s - loss: 0.0654 116/116 [==============================] - 0s 1ms/step - loss: 0.0722 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1047 38/116 [========>.....................] - ETA: 0s - loss: 0.0773 78/116 [===================>..........] - ETA: 0s - loss: 0.0736 116/116 [==============================] - 0s 1ms/step - loss: 0.0703 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2928 41/116 [=========>....................] - ETA: 0s - loss: 0.0705 82/116 [====================>.........] - ETA: 0s - loss: 0.0744 116/116 [==============================] - 0s 1ms/step - loss: 0.0708 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0592 37/116 [========>.....................] - ETA: 0s - loss: 0.0561 77/116 [==================>...........] - ETA: 0s - loss: 0.0646 115/116 [============================>.] - ETA: 0s - loss: 0.0686 116/116 [==============================] - 0s 1ms/step - loss: 0.0688 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0527 33/116 [=======>......................] - ETA: 0s - loss: 0.0617 71/116 [=================>............] - ETA: 0s - loss: 0.0646 109/116 [===========================>..] - ETA: 0s - loss: 0.0663 116/116 [==============================] - 0s 1ms/step - loss: 0.0679 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0470 32/116 [=======>......................] - ETA: 0s - loss: 0.0641 62/116 [===============>..............] - ETA: 0s - loss: 0.0641 95/116 [=======================>......] - ETA: 0s - loss: 0.0685 116/116 [==============================] - 0s 2ms/step - loss: 0.0692 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0113 34/116 [=======>......................] - ETA: 0s - loss: 0.0741 65/116 [===============>..............] - ETA: 0s - loss: 0.0694 97/116 [========================>.....] - ETA: 0s - loss: 0.0620 116/116 [==============================] - 0s 2ms/step - loss: 0.0680 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0122 34/116 [=======>......................] - ETA: 0s - loss: 0.0502 70/116 [=================>............] - ETA: 0s - loss: 0.0736 108/116 [==========================>...] - ETA: 0s - loss: 0.0631 116/116 [==============================] - 0s 1ms/step - loss: 0.0656 -> test with GAN.predict GAN tn, fp: 285, 5 GAN fn, tp: 3, 4 GAN f1 score: 0.500 GAN cohens kappa score: 0.486 -> test with 'LR' LR tn, fp: 272, 18 LR fn, tp: 3, 4 LR f1 score: 0.276 LR cohens kappa score: 0.249 LR average precision score: 0.245 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 3, 4 RF f1 score: 0.667 RF cohens kappa score: 0.660 -> test with 'GB' GB tn, fp: 289, 1 GB fn, tp: 3, 4 GB f1 score: 0.667 GB cohens kappa score: 0.660 -> test with 'KNN' KNN tn, fp: 279, 11 KNN fn, tp: 3, 4 KNN f1 score: 0.364 KNN cohens kappa score: 0.343 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.0054 38/116 [========>.....................] - ETA: 0s - loss: 0.0531  77/116 [==================>...........] - ETA: 0s - loss: 0.0573 115/116 [============================>.] - ETA: 0s - loss: 0.0636 116/116 [==============================] - 0s 1ms/step - loss: 0.0632 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0700 41/116 [=========>....................] - ETA: 0s - loss: 0.0414 82/116 [====================>.........] - ETA: 0s - loss: 0.0438 116/116 [==============================] - 0s 1ms/step - loss: 0.0640 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0032 39/116 [=========>....................] - ETA: 0s - loss: 0.0662 79/116 [===================>..........] - ETA: 0s - loss: 0.0624 116/116 [==============================] - 0s 1ms/step - loss: 0.0630 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0260 40/116 [=========>....................] - ETA: 0s - loss: 0.0505 80/116 [===================>..........] - ETA: 0s - loss: 0.0621 116/116 [==============================] - 0s 1ms/step - loss: 0.0667 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0031 37/116 [========>.....................] - ETA: 0s - loss: 0.0496 78/116 [===================>..........] - ETA: 0s - loss: 0.0539 116/116 [==============================] - 0s 1ms/step - loss: 0.0582 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0957 42/116 [=========>....................] - ETA: 0s - loss: 0.0599 83/116 [====================>.........] - ETA: 0s - loss: 0.0654 116/116 [==============================] - 0s 1ms/step - loss: 0.0610 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1456 40/116 [=========>....................] - ETA: 0s - loss: 0.0536 80/116 [===================>..........] - ETA: 0s - loss: 0.0565 116/116 [==============================] - 0s 1ms/step - loss: 0.0590 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0708 41/116 [=========>....................] - ETA: 0s - loss: 0.0780 81/116 [===================>..........] - ETA: 0s - loss: 0.0595 116/116 [==============================] - 0s 1ms/step - loss: 0.0589 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1368 41/116 [=========>....................] - ETA: 0s - loss: 0.0800 81/116 [===================>..........] - ETA: 0s - loss: 0.0668 116/116 [==============================] - 0s 1ms/step - loss: 0.0586 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0459 41/116 [=========>....................] - ETA: 0s - loss: 0.0419 82/116 [====================>.........] - ETA: 0s - loss: 0.0440 116/116 [==============================] - 0s 1ms/step - loss: 0.0573 -> test with GAN.predict GAN tn, fp: 282, 8 GAN fn, tp: 0, 7 GAN f1 score: 0.636 GAN cohens kappa score: 0.624 -> test with 'LR' LR tn, fp: 268, 22 LR fn, tp: 0, 7 LR f1 score: 0.389 LR cohens kappa score: 0.365 LR average precision score: 0.773 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 0, 7 RF f1 score: 0.875 RF cohens kappa score: 0.872 -> test with 'GB' GB tn, fp: 288, 2 GB fn, tp: 0, 7 GB f1 score: 0.875 GB cohens kappa score: 0.872 -> test with 'KNN' KNN tn, fp: 278, 12 KNN fn, tp: 0, 7 KNN f1 score: 0.538 KNN cohens kappa score: 0.522 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 22s - loss: 0.1037 41/116 [=========>....................] - ETA: 0s - loss: 0.0607  83/116 [====================>.........] - ETA: 0s - loss: 0.0628 116/116 [==============================] - 0s 1ms/step - loss: 0.0617 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1633 41/116 [=========>....................] - ETA: 0s - loss: 0.0881 82/116 [====================>.........] - ETA: 0s - loss: 0.0678 116/116 [==============================] - 0s 1ms/step - loss: 0.0599 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0069 41/116 [=========>....................] - ETA: 0s - loss: 0.0723 82/116 [====================>.........] - ETA: 0s - loss: 0.0582 116/116 [==============================] - 0s 1ms/step - loss: 0.0584 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0635 42/116 [=========>....................] - ETA: 0s - loss: 0.0632 81/116 [===================>..........] - ETA: 0s - loss: 0.0653 116/116 [==============================] - 0s 1ms/step - loss: 0.0592 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0323 36/116 [========>.....................] - ETA: 0s - loss: 0.0465 70/116 [=================>............] - ETA: 0s - loss: 0.0608 103/116 [=========================>....] - ETA: 0s - loss: 0.0610 116/116 [==============================] - 0s 1ms/step - loss: 0.0597 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1660 41/116 [=========>....................] - ETA: 0s - loss: 0.0552 79/116 [===================>..........] - ETA: 0s - loss: 0.0621 116/116 [==============================] - 0s 1ms/step - loss: 0.0577 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0476 40/116 [=========>....................] - ETA: 0s - loss: 0.0468 80/116 [===================>..........] - ETA: 0s - loss: 0.0645 116/116 [==============================] - 0s 1ms/step - loss: 0.0595 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0388 40/116 [=========>....................] - ETA: 0s - loss: 0.0609 80/116 [===================>..........] - ETA: 0s - loss: 0.0600 116/116 [==============================] - 0s 1ms/step - loss: 0.0592 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0320 42/116 [=========>....................] - ETA: 0s - loss: 0.0478 84/116 [====================>.........] - ETA: 0s - loss: 0.0527 116/116 [==============================] - 0s 1ms/step - loss: 0.0565 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0061 42/116 [=========>....................] - ETA: 0s - loss: 0.0448 84/116 [====================>.........] - ETA: 0s - loss: 0.0524 116/116 [==============================] - 0s 1ms/step - loss: 0.0571 -> test with GAN.predict GAN tn, fp: 286, 4 GAN fn, tp: 4, 3 GAN f1 score: 0.429 GAN cohens kappa score: 0.415 -> test with 'LR' LR tn, fp: 264, 26 LR fn, tp: 2, 5 LR f1 score: 0.263 LR cohens kappa score: 0.234 LR average precision score: 0.451 -> test with 'RF' RF tn, fp: 290, 0 RF fn, tp: 5, 2 RF f1 score: 0.444 RF cohens kappa score: 0.439 -> test with 'GB' GB tn, fp: 290, 0 GB fn, tp: 5, 2 GB f1 score: 0.444 GB cohens kappa score: 0.439 -> test with 'KNN' KNN tn, fp: 276, 14 KNN fn, tp: 2, 5 KNN f1 score: 0.385 KNN cohens kappa score: 0.363 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0212 42/116 [=========>....................] - ETA: 0s - loss: 0.0467  84/116 [====================>.........] - ETA: 0s - loss: 0.0448 116/116 [==============================] - 0s 1ms/step - loss: 0.0506 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0105 44/116 [==========>...................] - ETA: 0s - loss: 0.0567 88/116 [=====================>........] - ETA: 0s - loss: 0.0525 116/116 [==============================] - 0s 1ms/step - loss: 0.0520 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0042 39/116 [=========>....................] - ETA: 0s - loss: 0.0402 83/116 [====================>.........] - ETA: 0s - loss: 0.0375 116/116 [==============================] - 0s 1ms/step - loss: 0.0489 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0163 44/116 [==========>...................] - ETA: 0s - loss: 0.0426 88/116 [=====================>........] - ETA: 0s - loss: 0.0504 116/116 [==============================] - 0s 1ms/step - loss: 0.0496 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1148 40/116 [=========>....................] - ETA: 0s - loss: 0.0413 76/116 [==================>...........] - ETA: 0s - loss: 0.0485 111/116 [===========================>..] - ETA: 0s - loss: 0.0488 116/116 [==============================] - 0s 1ms/step - loss: 0.0493 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0031 42/116 [=========>....................] - ETA: 0s - loss: 0.0340 86/116 [=====================>........] - ETA: 0s - loss: 0.0512 116/116 [==============================] - 0s 1ms/step - loss: 0.0482 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0875 43/116 [==========>...................] - ETA: 0s - loss: 0.0617 84/116 [====================>.........] - ETA: 0s - loss: 0.0524 116/116 [==============================] - 0s 1ms/step - loss: 0.0509 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0017 43/116 [==========>...................] - ETA: 0s - loss: 0.0624 81/116 [===================>..........] - ETA: 0s - loss: 0.0460 116/116 [==============================] - 0s 1ms/step - loss: 0.0490 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1950 43/116 [==========>...................] - ETA: 0s - loss: 0.0509 86/116 [=====================>........] - ETA: 0s - loss: 0.0472 116/116 [==============================] - 0s 1ms/step - loss: 0.0474 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0222 43/116 [==========>...................] - ETA: 0s - loss: 0.0454 86/116 [=====================>........] - ETA: 0s - loss: 0.0514 116/116 [==============================] - 0s 1ms/step - loss: 0.0487 -> test with GAN.predict GAN tn, fp: 282, 7 GAN fn, tp: 3, 4 GAN f1 score: 0.444 GAN cohens kappa score: 0.428 -> test with 'LR' LR tn, fp: 273, 16 LR fn, tp: 2, 5 LR f1 score: 0.357 LR cohens kappa score: 0.334 LR average precision score: 0.442 -> test with 'RF' RF tn, fp: 289, 0 RF fn, tp: 4, 3 RF f1 score: 0.600 RF cohens kappa score: 0.594 -> test with 'GB' GB tn, fp: 285, 4 GB fn, tp: 5, 2 GB f1 score: 0.308 GB cohens kappa score: 0.292 -> test with 'KNN' KNN tn, fp: 278, 11 KNN fn, tp: 2, 5 KNN f1 score: 0.435 KNN cohens kappa score: 0.416 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 277, 32 LR fn, tp: 3, 7 LR f1 score: 0.462 LR cohens kappa score: 0.442 LR average precision score: 0.793 average: LR tn, fp: 268.8, 21.0 LR fn, tp: 1.12, 5.88 LR f1 score: 0.353 LR cohens kappa score: 0.328 LR average precision score: 0.533 minimum: LR tn, fp: 257, 13 LR fn, tp: 0, 4 LR f1 score: 0.263 LR cohens kappa score: 0.234 LR average precision score: 0.245 -----[ RF ]----- maximum: RF tn, fp: 290, 4 RF fn, tp: 6, 7 RF f1 score: 0.875 RF cohens kappa score: 0.872 average: RF tn, fp: 288.0, 1.8 RF fn, tp: 3.32, 3.68 RF f1 score: 0.575 RF cohens kappa score: 0.567 minimum: RF tn, fp: 286, 0 RF fn, tp: 0, 1 RF f1 score: 0.222 RF cohens kappa score: 0.214 -----[ GB ]----- maximum: GB tn, fp: 290, 9 GB fn, tp: 5, 7 GB f1 score: 0.875 GB cohens kappa score: 0.872 average: GB tn, fp: 286.76, 3.04 GB fn, tp: 3.0, 4.0 GB f1 score: 0.564 GB cohens kappa score: 0.554 minimum: GB tn, fp: 281, 0 GB fn, tp: 0, 2 GB f1 score: 0.308 GB cohens kappa score: 0.292 -----[ KNN ]----- maximum: KNN tn, fp: 282, 23 KNN fn, tp: 3, 7 KNN f1 score: 0.571 KNN cohens kappa score: 0.558 average: KNN tn, fp: 276.2, 13.6 KNN fn, tp: 1.52, 5.48 KNN f1 score: 0.426 KNN cohens kappa score: 0.406 minimum: KNN tn, fp: 267, 7 KNN fn, tp: 0, 4 KNN f1 score: 0.296 KNN cohens kappa score: 0.271 -----[ GAN ]----- maximum: GAN tn, fp: 288, 15 GAN fn, tp: 4, 7 GAN f1 score: 0.636 GAN cohens kappa score: 0.624 average: GAN tn, fp: 282.28, 7.52 GAN fn, tp: 2.28, 4.72 GAN f1 score: 0.491 GAN cohens kappa score: 0.475 minimum: GAN tn, fp: 275, 2 GAN fn, tp: 0, 3 GAN f1 score: 0.364 GAN cohens kappa score: 0.343