/////////////////////////////////////////// // Running convGAN-proximary-full on folding_kddcup-guess_passwd_vs_satan /////////////////////////////////////////// Load 'data_input/folding_kddcup-guess_passwd_vs_satan' 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 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 19s - loss: 7.0652e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.6435e-09  81/128 [=================>............] - ETA: 0s - loss: 1.2533e-09 121/128 [===========================>..] - ETA: 0s - loss: 1.2663e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.2313e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.1774e-10 38/128 [=======>......................] - ETA: 0s - loss: 7.0285e-10 78/128 [=================>............] - ETA: 0s - loss: 7.2479e-10 115/128 [=========================>....] - ETA: 0s - loss: 7.9558e-10 128/128 [==============================] - 0s 1ms/step - loss: 7.4268e-10 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.1410e-10 42/128 [========>.....................] - ETA: 0s - loss: 1.0717e-09 82/128 [==================>...........] - ETA: 0s - loss: 6.7645e-10 122/128 [===========================>..] - ETA: 0s - loss: 5.6362e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.6138e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 4.5857e-10 41/128 [========>.....................] - ETA: 0s - loss: 6.7881e-10 77/128 [=================>............] - ETA: 0s - loss: 5.3630e-10 114/128 [=========================>....] - ETA: 0s - loss: 5.1417e-10 128/128 [==============================] - 0s 1ms/step - loss: 4.7986e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.9163e-10 38/128 [=======>......................] - ETA: 0s - loss: 5.3152e-10 79/128 [=================>............] - ETA: 0s - loss: 5.4913e-10 117/128 [==========================>...] - ETA: 0s - loss: 4.4493e-10 128/128 [==============================] - 0s 1ms/step - loss: 4.2106e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.4203e-10 41/128 [========>.....................] - ETA: 0s - loss: 3.6794e-10 81/128 [=================>............] - ETA: 0s - loss: 4.3249e-10 119/128 [==========================>...] - ETA: 0s - loss: 3.7311e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.7901e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 2.1066e-10 41/128 [========>.....................] - ETA: 0s - loss: 2.0863e-10 82/128 [==================>...........] - ETA: 0s - loss: 2.5179e-10 122/128 [===========================>..] - ETA: 0s - loss: 3.5137e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.5143e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 9.8251e-11 36/128 [=======>......................] - ETA: 0s - loss: 2.6981e-10 76/128 [================>.............] - ETA: 0s - loss: 2.3972e-10 115/128 [=========================>....] - ETA: 0s - loss: 2.2029e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.2808e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 6.6714e-11 40/128 [========>.....................] - ETA: 0s - loss: 4.4518e-10 80/128 [=================>............] - ETA: 0s - loss: 3.1828e-10 119/128 [==========================>...] - ETA: 0s - loss: 3.2178e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.1093e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 6.7895e-11 40/128 [========>.....................] - ETA: 0s - loss: 1.4793e-10 79/128 [=================>............] - ETA: 0s - loss: 1.6612e-10 117/128 [==========================>...] - ETA: 0s - loss: 2.8204e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.9258e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 26s - loss: 1.1255e-10 37/128 [=======>......................] - ETA: 0s - loss: 6.1950e-08  72/128 [===============>..............] - ETA: 0s - loss: 3.1966e-08 106/128 [=======================>......] - ETA: 0s - loss: 2.1760e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.8181e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 8.0143e-11 39/128 [========>.....................] - ETA: 0s - loss: 1.5643e-09 75/128 [================>.............] - ETA: 0s - loss: 8.8103e-10 115/128 [=========================>....] - ETA: 0s - loss: 6.4674e-10 128/128 [==============================] - 0s 1ms/step - loss: 6.1967e-10 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.7673e-11 39/128 [========>.....................] - ETA: 0s - loss: 1.5731e-09 73/128 [================>.............] - ETA: 0s - loss: 9.0072e-10 113/128 [=========================>....] - ETA: 0s - loss: 6.4246e-10 128/128 [==============================] - 0s 1ms/step - loss: 6.1193e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 9.8568e-12 35/128 [=======>......................] - ETA: 0s - loss: 2.7596e-10 71/128 [===============>..............] - ETA: 0s - loss: 2.1110e-10 106/128 [=======================>......] - ETA: 0s - loss: 2.0782e-10 128/128 [==============================] - 0s 1ms/step - loss: 6.0445e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.1186e-10 38/128 [=======>......................] - ETA: 0s - loss: 1.4883e-10 73/128 [================>.............] - ETA: 0s - loss: 1.9396e-10 108/128 [========================>.....] - ETA: 0s - loss: 6.6505e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.9715e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 4.3534e-11 40/128 [========>.....................] - ETA: 0s - loss: 2.1209e-10 77/128 [=================>............] - ETA: 0s - loss: 1.5320e-10 112/128 [=========================>....] - ETA: 0s - loss: 6.4989e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.9024e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.0161e-09 36/128 [=======>......................] - ETA: 0s - loss: 1.6350e-09 70/128 [===============>..............] - ETA: 0s - loss: 9.6737e-10 106/128 [=======================>......] - ETA: 0s - loss: 6.8127e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.8387e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.5107e-10 37/128 [=======>......................] - ETA: 0s - loss: 1.7496e-10 74/128 [================>.............] - ETA: 0s - loss: 8.4623e-10 109/128 [========================>.....] - ETA: 0s - loss: 6.1641e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.7773e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.7873e-10 30/128 [======>.......................] - ETA: 0s - loss: 2.2560e-10 59/128 [============>.................] - ETA: 0s - loss: 1.7597e-10 98/128 [=====================>........] - ETA: 0s - loss: 1.5824e-10 128/128 [==============================] - 0s 2ms/step - loss: 5.7167e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 2.4767e-10 37/128 [=======>......................] - ETA: 0s - loss: 1.5199e-09 73/128 [================>.............] - ETA: 0s - loss: 8.8163e-10 109/128 [========================>.....] - ETA: 0s - loss: 6.4546e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.6579e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 19s - loss: 1.8359e-09 42/128 [========>.....................] - ETA: 0s - loss: 6.2573e-09  83/128 [==================>...........] - ETA: 0s - loss: 3.7198e-09 122/128 [===========================>..] - ETA: 0s - loss: 3.0157e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.9381e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.0454e-09 40/128 [========>.....................] - ETA: 0s - loss: 9.7892e-10 80/128 [=================>............] - ETA: 0s - loss: 9.4472e-10 119/128 [==========================>...] - ETA: 0s - loss: 1.3160e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.2863e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 8.4306e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.4209e-09 81/128 [=================>............] - ETA: 0s - loss: 1.3349e-09 120/128 [===========================>..] - ETA: 0s - loss: 1.1849e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.1687e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 6.8482e-10 36/128 [=======>......................] - ETA: 0s - loss: 1.4192e-09 72/128 [===============>..............] - ETA: 0s - loss: 1.1151e-09 108/128 [========================>.....] - ETA: 0s - loss: 1.0464e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.1172e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 9.6030e-10 40/128 [========>.....................] - ETA: 0s - loss: 7.8048e-10 81/128 [=================>............] - ETA: 0s - loss: 1.2178e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.0488e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0360e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 7.3791e-10 40/128 [========>.....................] - ETA: 0s - loss: 1.2592e-09 79/128 [=================>............] - ETA: 0s - loss: 1.0279e-09 119/128 [==========================>...] - ETA: 0s - loss: 1.0253e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0014e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 7.1867e-10 43/128 [=========>....................] - ETA: 0s - loss: 7.4961e-10 81/128 [=================>............] - ETA: 0s - loss: 7.2063e-10 122/128 [===========================>..] - ETA: 0s - loss: 7.2343e-10 128/128 [==============================] - 0s 1ms/step - loss: 9.6224e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 7.9178e-10 42/128 [========>.....................] - ETA: 0s - loss: 8.9481e-10 83/128 [==================>...........] - ETA: 0s - loss: 1.0338e-09 120/128 [===========================>..] - ETA: 0s - loss: 9.2117e-10 128/128 [==============================] - 0s 1ms/step - loss: 9.0594e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 9.0026e-10 40/128 [========>.....................] - ETA: 0s - loss: 1.2148e-09 80/128 [=================>............] - ETA: 0s - loss: 9.3558e-10 120/128 [===========================>..] - ETA: 0s - loss: 9.0207e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.8684e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.9806e-10 40/128 [========>.....................] - ETA: 0s - loss: 6.3795e-10 81/128 [=================>............] - ETA: 0s - loss: 7.1418e-10 122/128 [===========================>..] - ETA: 0s - loss: 8.6271e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.5460e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 1 KNN fn, tp: 0, 11 KNN f1 score: 0.957 KNN cohens kappa score: 0.955 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 19s - loss: 2.3824e-09 42/128 [========>.....................] - ETA: 0s - loss: 4.7044e-09  84/128 [==================>...........] - ETA: 0s - loss: 3.4384e-09 125/128 [============================>.] - ETA: 0s - loss: 3.0728e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.0561e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.3399e-09 36/128 [=======>......................] - ETA: 0s - loss: 3.7245e-09 72/128 [===============>..............] - ETA: 0s - loss: 3.0089e-09 107/128 [========================>.....] - ETA: 0s - loss: 2.8772e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.7369e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.2800e-09 40/128 [========>.....................] - ETA: 0s - loss: 2.1140e-09 80/128 [=================>............] - ETA: 0s - loss: 2.7690e-09 119/128 [==========================>...] - ETA: 0s - loss: 2.5924e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.5265e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 4.2231e-09 40/128 [========>.....................] - ETA: 0s - loss: 3.7242e-09 80/128 [=================>............] - ETA: 0s - loss: 2.7228e-09 120/128 [===========================>..] - ETA: 0s - loss: 2.3946e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.3627e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.8716e-09 41/128 [========>.....................] - ETA: 0s - loss: 2.1079e-09 79/128 [=================>............] - ETA: 0s - loss: 1.8560e-09 121/128 [===========================>..] - ETA: 0s - loss: 1.7654e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.2483e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.7309e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.5170e-09 80/128 [=================>............] - ETA: 0s - loss: 1.5942e-09 119/128 [==========================>...] - ETA: 0s - loss: 2.1202e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.1559e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.2211e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.6087e-09 83/128 [==================>...........] - ETA: 0s - loss: 2.4092e-09 123/128 [===========================>..] - ETA: 0s - loss: 2.0908e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.0579e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.1012e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.3383e-09 80/128 [=================>............] - ETA: 0s - loss: 2.1692e-09 120/128 [===========================>..] - ETA: 0s - loss: 2.0205e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.9886e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 9.9728e-10 42/128 [========>.....................] - ETA: 0s - loss: 1.5521e-09 82/128 [==================>...........] - ETA: 0s - loss: 2.1981e-09 123/128 [===========================>..] - ETA: 0s - loss: 1.9322e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.9106e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.1330e-09 42/128 [========>.....................] - ETA: 0s - loss: 2.7922e-09 83/128 [==================>...........] - ETA: 0s - loss: 2.0962e-09 124/128 [============================>.] - ETA: 0s - loss: 1.8570e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.8448e-09 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1228 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 20s - loss: 4.0775e-09 40/128 [========>.....................] - ETA: 0s - loss: 4.3599e-09  81/128 [=================>............] - ETA: 0s - loss: 8.9048e-09 122/128 [===========================>..] - ETA: 0s - loss: 7.5389e-09 128/128 [==============================] - 0s 1ms/step - loss: 7.4208e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 5.8716e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.7496e-09 81/128 [=================>............] - ETA: 0s - loss: 3.7067e-09 122/128 [===========================>..] - ETA: 0s - loss: 4.0096e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.0500e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 3.7828e-09 41/128 [========>.....................] - ETA: 0s - loss: 4.0490e-09 82/128 [==================>...........] - ETA: 0s - loss: 4.0131e-09 122/128 [===========================>..] - ETA: 0s - loss: 3.8101e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.8148e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.1511e-09 40/128 [========>.....................] - ETA: 0s - loss: 3.7698e-09 78/128 [=================>............] - ETA: 0s - loss: 3.6883e-09 119/128 [==========================>...] - ETA: 0s - loss: 3.6728e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.6322e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.4225e-09 42/128 [========>.....................] - ETA: 0s - loss: 3.1484e-09 81/128 [=================>............] - ETA: 0s - loss: 3.7109e-09 121/128 [===========================>..] - ETA: 0s - loss: 3.5283e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.5037e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 6.3797e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.3123e-09 81/128 [=================>............] - ETA: 0s - loss: 3.4523e-09 121/128 [===========================>..] - ETA: 0s - loss: 3.4304e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.3696e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 6.5691e-09 42/128 [========>.....................] - ETA: 0s - loss: 3.5943e-09 80/128 [=================>............] - ETA: 0s - loss: 3.3526e-09 117/128 [==========================>...] - ETA: 0s - loss: 3.2607e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.2507e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.4527e-09 42/128 [========>.....................] - ETA: 0s - loss: 2.9768e-09 82/128 [==================>...........] - ETA: 0s - loss: 3.1636e-09 116/128 [==========================>...] - ETA: 0s - loss: 3.1673e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.1613e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 3.3838e-09 32/128 [======>.......................] - ETA: 0s - loss: 2.8206e-09 70/128 [===============>..............] - ETA: 0s - loss: 3.0762e-09 110/128 [========================>.....] - ETA: 0s - loss: 3.0816e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.0503e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 2.8851e-09 40/128 [========>.....................] - ETA: 0s - loss: 3.1905e-09 82/128 [==================>...........] - ETA: 0s - loss: 3.1326e-09 124/128 [============================>.] - ETA: 0s - loss: 2.9653e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.9550e-09 -> test with GAN.predict GAN tn, fp: 317, 0 GAN fn, tp: 0, 9 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 317, 0 LR fn, tp: 0, 9 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 317, 0 RF fn, tp: 0, 9 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 317, 0 GB fn, tp: 0, 9 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 0 KNN fn, tp: 0, 9 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 21s - loss: 1.0512e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.0739e-09  83/128 [==================>...........] - ETA: 0s - loss: 1.2339e-09 123/128 [===========================>..] - ETA: 0s - loss: 1.0943e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0863e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.8160e-09 42/128 [========>.....................] - ETA: 0s - loss: 7.7659e-10 82/128 [==================>...........] - ETA: 0s - loss: 7.6377e-10 123/128 [===========================>..] - ETA: 0s - loss: 1.0274e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0165e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 7.4252e-10 41/128 [========>.....................] - ETA: 0s - loss: 7.0837e-10 79/128 [=================>............] - ETA: 0s - loss: 7.1757e-10 118/128 [==========================>...] - ETA: 0s - loss: 8.9642e-10 128/128 [==============================] - 0s 1ms/step - loss: 9.4923e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 7.2671e-10 39/128 [========>.....................] - ETA: 0s - loss: 1.2465e-09 77/128 [=================>............] - ETA: 0s - loss: 8.9100e-10 117/128 [==========================>...] - ETA: 0s - loss: 7.9202e-10 128/128 [==============================] - 0s 1ms/step - loss: 7.7724e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 7.8384e-10 37/128 [=======>......................] - ETA: 0s - loss: 1.1164e-09 77/128 [=================>............] - ETA: 0s - loss: 8.5107e-10 117/128 [==========================>...] - ETA: 0s - loss: 7.3486e-10 128/128 [==============================] - 0s 1ms/step - loss: 7.4738e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 6.4737e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.1377e-09 82/128 [==================>...........] - ETA: 0s - loss: 8.4215e-10 120/128 [===========================>..] - ETA: 0s - loss: 7.3621e-10 128/128 [==============================] - 0s 1ms/step - loss: 7.2249e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.7562e-10 36/128 [=======>......................] - ETA: 0s - loss: 1.1054e-09 68/128 [==============>...............] - ETA: 0s - loss: 8.7140e-10 101/128 [======================>.......] - ETA: 0s - loss: 7.5473e-10 128/128 [==============================] - 0s 1ms/step - loss: 7.0405e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.0298e-10 42/128 [========>.....................] - ETA: 0s - loss: 1.0807e-09 83/128 [==================>...........] - ETA: 0s - loss: 8.0376e-10 124/128 [============================>.] - ETA: 0s - loss: 6.8863e-10 128/128 [==============================] - 0s 1ms/step - loss: 6.8448e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 7.0610e-10 41/128 [========>.....................] - ETA: 0s - loss: 5.4836e-10 80/128 [=================>............] - ETA: 0s - loss: 7.8203e-10 120/128 [===========================>..] - ETA: 0s - loss: 6.7758e-10 128/128 [==============================] - 0s 1ms/step - loss: 6.6534e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 3.5385e-10 42/128 [========>.....................] - ETA: 0s - loss: 4.9278e-10 83/128 [==================>...........] - ETA: 0s - loss: 4.8260e-10 125/128 [============================>.] - ETA: 0s - loss: 6.5703e-10 128/128 [==============================] - 0s 1ms/step - loss: 6.5188e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 21s - loss: 1.5280e-09 42/128 [========>.....................] - ETA: 0s - loss: 2.0646e-09  83/128 [==================>...........] - ETA: 0s - loss: 1.3698e-08 122/128 [===========================>..] - ETA: 0s - loss: 9.7648e-09 128/128 [==============================] - 0s 1ms/step - loss: 9.4255e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.3955e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.6909e-09 81/128 [=================>............] - ETA: 0s - loss: 1.5715e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.5211e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4999e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.3747e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.3904e-09 81/128 [=================>............] - ETA: 0s - loss: 1.3737e-09 121/128 [===========================>..] - ETA: 0s - loss: 1.4874e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4905e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.7683e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.4088e-09 79/128 [=================>............] - ETA: 0s - loss: 1.5940e-09 112/128 [=========================>....] - ETA: 0s - loss: 1.4963e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4816e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.3180e-09 35/128 [=======>......................] - ETA: 0s - loss: 1.4411e-09 75/128 [================>.............] - ETA: 0s - loss: 1.3255e-09 112/128 [=========================>....] - ETA: 0s - loss: 1.4928e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4721e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 6.7075e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.2350e-09 81/128 [=================>............] - ETA: 0s - loss: 1.3071e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.4690e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4632e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.0679e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.2271e-09 81/128 [=================>............] - ETA: 0s - loss: 1.5194e-09 121/128 [===========================>..] - ETA: 0s - loss: 1.4513e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4543e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.8802e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.2883e-09 82/128 [==================>...........] - ETA: 0s - loss: 1.3167e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.4119e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4436e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.1600e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.2759e-09 80/128 [=================>............] - ETA: 0s - loss: 1.5170e-09 120/128 [===========================>..] - ETA: 0s - loss: 1.4395e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4339e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.5465e-10 40/128 [========>.....................] - ETA: 0s - loss: 1.6435e-09 80/128 [=================>............] - ETA: 0s - loss: 1.4972e-09 115/128 [=========================>....] - ETA: 0s - loss: 1.4388e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4243e-09 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 1 KNN fn, tp: 0, 11 KNN f1 score: 0.957 KNN cohens kappa score: 0.955 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 23s - loss: 1.4440e-09 40/128 [========>.....................] - ETA: 0s - loss: 2.3862e-09  81/128 [=================>............] - ETA: 0s - loss: 3.7894e-09 122/128 [===========================>..] - ETA: 0s - loss: 2.9761e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.9042e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.7418e-09 40/128 [========>.....................] - ETA: 0s - loss: 8.0377e-10 81/128 [=================>............] - ETA: 0s - loss: 9.1136e-10 121/128 [===========================>..] - ETA: 0s - loss: 1.2299e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.2057e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 6.7400e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.1454e-09 76/128 [================>.............] - ETA: 0s - loss: 1.0012e-09 109/128 [========================>.....] - ETA: 0s - loss: 1.1310e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0646e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.4555e-10 39/128 [========>.....................] - ETA: 0s - loss: 6.8073e-10 78/128 [=================>............] - ETA: 0s - loss: 7.7507e-10 118/128 [==========================>...] - ETA: 0s - loss: 9.5469e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.0297e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 7.2851e-10 42/128 [========>.....................] - ETA: 0s - loss: 9.2890e-10 82/128 [==================>...........] - ETA: 0s - loss: 1.0544e-09 121/128 [===========================>..] - ETA: 0s - loss: 9.5848e-10 128/128 [==============================] - 0s 1ms/step - loss: 9.4165e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 6.8515e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.2043e-09 82/128 [==================>...........] - ETA: 0s - loss: 9.9784e-10 123/128 [===========================>..] - ETA: 0s - loss: 9.2092e-10 128/128 [==============================] - 0s 1ms/step - loss: 9.0759e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 4.5829e-10 41/128 [========>.....................] - ETA: 0s - loss: 6.6684e-10 80/128 [=================>............] - ETA: 0s - loss: 7.7083e-10 121/128 [===========================>..] - ETA: 0s - loss: 8.9448e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.8432e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 6.7309e-10 42/128 [========>.....................] - ETA: 0s - loss: 7.4895e-10 80/128 [=================>............] - ETA: 0s - loss: 1.0405e-09 120/128 [===========================>..] - ETA: 0s - loss: 8.7976e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.6336e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 5.4358e-10 40/128 [========>.....................] - ETA: 0s - loss: 5.5526e-10 80/128 [=================>............] - ETA: 0s - loss: 7.0694e-10 119/128 [==========================>...] - ETA: 0s - loss: 8.5254e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3075e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 5.5745e-10 38/128 [=======>......................] - ETA: 0s - loss: 1.1665e-09 79/128 [=================>............] - ETA: 0s - loss: 9.3943e-10 117/128 [==========================>...] - ETA: 0s - loss: 8.0203e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.2380e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 23s - loss: 1.1086e-10 42/128 [========>.....................] - ETA: 0s - loss: 3.7055e-10  83/128 [==================>...........] - ETA: 0s - loss: 0.0130  121/128 [===========================>..] - ETA: 0s - loss: 0.0089 128/128 [==============================] - 0s 1ms/step - loss: 0.0085 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 7.4247e-12 42/128 [========>.....................] - ETA: 0s - loss: 2.8608e-11 80/128 [=================>............] - ETA: 0s - loss: 3.5425e-10 119/128 [==========================>...] - ETA: 0s - loss: 2.4445e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3342e-10 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 6.0788e-12 33/128 [======>.......................] - ETA: 0s - loss: 3.9154e-11 71/128 [===============>..............] - ETA: 0s - loss: 4.0217e-10 107/128 [========================>.....] - ETA: 0s - loss: 2.7308e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3323e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 4.2676e-11 42/128 [========>.....................] - ETA: 0s - loss: 2.3632e-11 83/128 [==================>...........] - ETA: 0s - loss: 3.4218e-10 121/128 [===========================>..] - ETA: 0s - loss: 2.4378e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3306e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 3.2273e-12 42/128 [========>.....................] - ETA: 0s - loss: 6.4702e-10 84/128 [==================>...........] - ETA: 0s - loss: 3.3514e-10 125/128 [============================>.] - ETA: 0s - loss: 2.3626e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3287e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 4.1858e-11 39/128 [========>.....................] - ETA: 0s - loss: 2.1549e-11 79/128 [=================>............] - ETA: 0s - loss: 2.3646e-11 120/128 [===========================>..] - ETA: 0s - loss: 2.4500e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3269e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.6698e-11 43/128 [=========>....................] - ETA: 0s - loss: 6.3610e-10 85/128 [==================>...........] - ETA: 0s - loss: 3.3609e-10 123/128 [===========================>..] - ETA: 0s - loss: 2.3993e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3249e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.4630e-11 41/128 [========>.....................] - ETA: 0s - loss: 2.1227e-11 81/128 [=================>............] - ETA: 0s - loss: 3.4810e-10 122/128 [===========================>..] - ETA: 0s - loss: 2.4087e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3229e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.1556e-11 41/128 [========>.....................] - ETA: 0s - loss: 2.7147e-11 83/128 [==================>...........] - ETA: 0s - loss: 3.4242e-10 123/128 [===========================>..] - ETA: 0s - loss: 2.3914e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3209e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 3.6549e-12 42/128 [========>.....................] - ETA: 0s - loss: 2.2954e-11 83/128 [==================>...........] - ETA: 0s - loss: 2.2857e-11 124/128 [============================>.] - ETA: 0s - loss: 2.3687e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.3187e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1228 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 24s - loss: 2.8385e-09 37/128 [=======>......................] - ETA: 0s - loss: 7.2612e-06  67/128 [==============>...............] - ETA: 0s - loss: 4.0168e-06 97/128 [=====================>........] - ETA: 0s - loss: 2.7779e-06 126/128 [============================>.] - ETA: 0s - loss: 2.1406e-06 128/128 [==============================] - 0s 2ms/step - loss: 2.1205e-06 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 5.3842e-09 33/128 [======>.......................] - ETA: 0s - loss: 5.9206e-09 67/128 [==============>...............] - ETA: 0s - loss: 7.0521e-09 104/128 [=======================>......] - ETA: 0s - loss: 3.6036e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.0207e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.0486e-09 36/128 [=======>......................] - ETA: 0s - loss: 5.9200e-09 70/128 [===============>..............] - ETA: 0s - loss: 4.9794e-09 104/128 [=======================>......] - ETA: 0s - loss: 4.7677e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.6488e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.0720e-09 36/128 [=======>......................] - ETA: 0s - loss: 5.9250e-09 71/128 [===============>..............] - ETA: 0s - loss: 4.7595e-09 107/128 [========================>.....] - ETA: 0s - loss: 2.8117e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.4246e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.6001e-09 36/128 [=======>......................] - ETA: 0s - loss: 3.3578e-09 71/128 [===============>..............] - ETA: 0s - loss: 3.1713e-09 105/128 [=======================>......] - ETA: 0s - loss: 2.5691e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.2271e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 4.1158e-09 39/128 [========>.....................] - ETA: 0s - loss: 2.9772e-09 75/128 [================>.............] - ETA: 0s - loss: 2.8783e-09 114/128 [=========================>....] - ETA: 0s - loss: 3.0377e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.0723e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.3838e-09 37/128 [=======>......................] - ETA: 0s - loss: 3.3892e-09 73/128 [================>.............] - ETA: 0s - loss: 4.0195e-09 109/128 [========================>.....] - ETA: 0s - loss: 2.2242e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9490e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.6261e-09 37/128 [=======>......................] - ETA: 0s - loss: 3.0477e-09 72/128 [===============>..............] - ETA: 0s - loss: 3.0882e-09 107/128 [========================>.....] - ETA: 0s - loss: 2.0571e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.8155e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 8.7774e-10 35/128 [=======>......................] - ETA: 0s - loss: 5.4914e-08 70/128 [===============>..............] - ETA: 0s - loss: 2.8819e-08 105/128 [=======================>......] - ETA: 0s - loss: 2.0161e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.7222e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 2.0105e-09 35/128 [=======>......................] - ETA: 0s - loss: 2.8101e-09 69/128 [===============>..............] - ETA: 0s - loss: 2.6771e-08 100/128 [======================>.......] - ETA: 0s - loss: 1.9238e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.6206e-08 -> test with GAN.predict GAN tn, fp: 317, 0 GAN fn, tp: 0, 9 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 317, 0 LR fn, tp: 0, 9 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 317, 0 RF fn, tp: 0, 9 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 317, 0 GB fn, tp: 0, 9 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 0 KNN fn, tp: 0, 9 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 19s - loss: 1.1125e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.4027e-09  82/128 [==================>...........] - ETA: 0s - loss: 9.5507e-09 123/128 [===========================>..] - ETA: 0s - loss: 6.7993e-09 128/128 [==============================] - 0s 1ms/step - loss: 6.6350e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 5.9582e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.0250e-08 80/128 [=================>............] - ETA: 0s - loss: 5.8022e-09 119/128 [==========================>...] - ETA: 0s - loss: 4.7212e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.4802e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.2635e-08 36/128 [=======>......................] - ETA: 0s - loss: 1.4712e-09 68/128 [==============>...............] - ETA: 0s - loss: 1.5191e-09 107/128 [========================>.....] - ETA: 0s - loss: 4.1179e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.6049e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 4.5685e-10 42/128 [========>.....................] - ETA: 0s - loss: 2.0213e-09 82/128 [==================>...........] - ETA: 0s - loss: 1.9897e-09 122/128 [===========================>..] - ETA: 0s - loss: 3.2069e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.1055e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 8.2621e-10 38/128 [=======>......................] - ETA: 0s - loss: 1.7171e-09 74/128 [================>.............] - ETA: 0s - loss: 1.5891e-09 110/128 [========================>.....] - ETA: 0s - loss: 3.0147e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.7285e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 2.3073e-10 42/128 [========>.....................] - ETA: 0s - loss: 4.2406e-09 82/128 [==================>...........] - ETA: 0s - loss: 2.9205e-09 122/128 [===========================>..] - ETA: 0s - loss: 2.5183e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.4548e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 4.6584e-10 41/128 [========>.....................] - ETA: 0s - loss: 3.8503e-09 79/128 [=================>............] - ETA: 0s - loss: 2.4220e-09 120/128 [===========================>..] - ETA: 0s - loss: 2.3148e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.2319e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 3.5218e-10 42/128 [========>.....................] - ETA: 0s - loss: 3.9153e-09 83/128 [==================>...........] - ETA: 0s - loss: 2.6416e-09 124/128 [============================>.] - ETA: 0s - loss: 2.0711e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.0531e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 5.4544e-10 36/128 [=======>......................] - ETA: 0s - loss: 1.0923e-09 76/128 [================>.............] - ETA: 0s - loss: 1.0667e-09 116/128 [==========================>...] - ETA: 0s - loss: 1.8216e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.9059e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 7.0788e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.2138e-09 82/128 [==================>...........] - ETA: 0s - loss: 2.1301e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.8108e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.7772e-09 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 1 KNN fn, tp: 0, 11 KNN f1 score: 0.957 KNN cohens kappa score: 0.955 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 21s - loss: 4.1303e-09 41/128 [========>.....................] - ETA: 0s - loss: 0.0669  81/128 [=================>............] - ETA: 0s - loss: 0.0343 122/128 [===========================>..] - ETA: 0s - loss: 0.0227 128/128 [==============================] - 0s 1ms/step - loss: 0.0218 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 4.2182e-07 42/128 [========>.....................] - ETA: 0s - loss: 3.0616e-07 78/128 [=================>............] - ETA: 0s - loss: 3.0284e-07 110/128 [========================>.....] - ETA: 0s - loss: 2.8913e-07 128/128 [==============================] - 0s 1ms/step - loss: 2.8601e-07 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.1788e-07 33/128 [======>.......................] - ETA: 0s - loss: 2.5635e-07 73/128 [================>.............] - ETA: 0s - loss: 2.4998e-07 112/128 [=========================>....] - ETA: 0s - loss: 2.4402e-07 128/128 [==============================] - 0s 1ms/step - loss: 2.3693e-07 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 8.9473e-08 42/128 [========>.....................] - ETA: 0s - loss: 1.9200e-07 81/128 [=================>............] - ETA: 0s - loss: 2.0658e-07 119/128 [==========================>...] - ETA: 0s - loss: 2.0021e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.9819e-07 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.0109e-07 41/128 [========>.....................] - ETA: 0s - loss: 1.7302e-07 80/128 [=================>............] - ETA: 0s - loss: 1.6720e-07 119/128 [==========================>...] - ETA: 0s - loss: 1.6737e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.6651e-07 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 3.0140e-07 42/128 [========>.....................] - ETA: 0s - loss: 1.5593e-07 81/128 [=================>............] - ETA: 0s - loss: 1.4975e-07 121/128 [===========================>..] - ETA: 0s - loss: 1.4313e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.4107e-07 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.3679e-07 43/128 [=========>....................] - ETA: 0s - loss: 1.3744e-07 85/128 [==================>...........] - ETA: 0s - loss: 1.2835e-07 124/128 [============================>.] - ETA: 0s - loss: 1.2054e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.2005e-07 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 4.9952e-08 37/128 [=======>......................] - ETA: 0s - loss: 1.0576e-07 77/128 [=================>............] - ETA: 0s - loss: 1.0436e-07 114/128 [=========================>....] - ETA: 0s - loss: 1.0248e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.0261e-07 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.7293e-07 41/128 [========>.....................] - ETA: 0s - loss: 9.2644e-08 81/128 [=================>............] - ETA: 0s - loss: 9.4115e-08 122/128 [===========================>..] - ETA: 0s - loss: 8.8266e-08 128/128 [==============================] - 0s 1ms/step - loss: 8.8122e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.9407e-08 41/128 [========>.....................] - ETA: 0s - loss: 8.0545e-08 82/128 [==================>...........] - ETA: 0s - loss: 7.6692e-08 121/128 [===========================>..] - ETA: 0s - loss: 7.4742e-08 128/128 [==============================] - 0s 1ms/step - loss: 7.5897e-08 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 23s - loss: 1.1647e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.7304e-09  81/128 [=================>............] - ETA: 0s - loss: 3.2490e-09 121/128 [===========================>..] - ETA: 0s - loss: 1.7517e-05 128/128 [==============================] - 0s 1ms/step - loss: 1.6680e-05 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 6.6315e-08 41/128 [========>.....................] - ETA: 0s - loss: 8.8047e-06 77/128 [=================>............] - ETA: 0s - loss: 4.6986e-06 115/128 [=========================>....] - ETA: 0s - loss: 3.1496e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.8510e-06 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.9090e-09 41/128 [========>.....................] - ETA: 0s - loss: 6.2021e-06 82/128 [==================>...........] - ETA: 0s - loss: 3.1075e-06 123/128 [===========================>..] - ETA: 0s - loss: 2.0739e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.0073e-06 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.1616e-08 41/128 [========>.....................] - ETA: 0s - loss: 6.0252e-09 79/128 [=================>............] - ETA: 0s - loss: 2.4777e-06 113/128 [=========================>....] - ETA: 0s - loss: 1.7363e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.5446e-06 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.1434e-08 35/128 [=======>......................] - ETA: 0s - loss: 7.8181e-09 73/128 [================>.............] - ETA: 0s - loss: 2.1371e-06 114/128 [=========================>....] - ETA: 0s - loss: 1.3710e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.2304e-06 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.1662e-08 42/128 [========>.....................] - ETA: 0s - loss: 6.6640e-09 81/128 [=================>............] - ETA: 0s - loss: 6.0866e-09 119/128 [==========================>...] - ETA: 0s - loss: 1.0824e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.0140e-06 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.1169e-08 39/128 [========>.....................] - ETA: 0s - loss: 6.8291e-09 79/128 [=================>............] - ETA: 0s - loss: 5.8823e-09 118/128 [==========================>...] - ETA: 0s - loss: 9.1572e-07 128/128 [==============================] - 0s 1ms/step - loss: 8.5078e-07 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.1007e-08 39/128 [========>.....................] - ETA: 0s - loss: 2.3497e-06 78/128 [=================>............] - ETA: 0s - loss: 1.1779e-06 118/128 [==========================>...] - ETA: 0s - loss: 7.8075e-07 128/128 [==============================] - 0s 1ms/step - loss: 7.2517e-07 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 5.0428e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.9316e-06 81/128 [=================>............] - ETA: 0s - loss: 9.8146e-07 122/128 [===========================>..] - ETA: 0s - loss: 6.5345e-07 128/128 [==============================] - 0s 1ms/step - loss: 6.2739e-07 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 3.2929e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.6877e-06 81/128 [=================>............] - ETA: 0s - loss: 8.5678e-07 122/128 [===========================>..] - ETA: 0s - loss: 5.7086e-07 128/128 [==============================] - 0s 1ms/step - loss: 5.4813e-07 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 20s - loss: 2.6636e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.9389e-09  82/128 [==================>...........] - ETA: 0s - loss: 1.4544e-05 121/128 [===========================>..] - ETA: 0s - loss: 9.8636e-06 128/128 [==============================] - 0s 1ms/step - loss: 9.3904e-06 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.8135e-09 39/128 [========>.....................] - ETA: 0s - loss: 5.5031e-09 79/128 [=================>............] - ETA: 0s - loss: 1.1975e-06 120/128 [===========================>..] - ETA: 0s - loss: 7.8986e-07 128/128 [==============================] - 0s 1ms/step - loss: 7.4594e-07 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.8323e-09 42/128 [========>.....................] - ETA: 0s - loss: 3.1609e-09 83/128 [==================>...........] - ETA: 0s - loss: 4.0258e-09 121/128 [===========================>..] - ETA: 0s - loss: 5.7737e-07 128/128 [==============================] - 0s 1ms/step - loss: 5.4989e-07 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.5581e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.3877e-06 81/128 [=================>............] - ETA: 0s - loss: 6.8987e-07 117/128 [==========================>...] - ETA: 0s - loss: 4.7878e-07 128/128 [==============================] - 0s 1ms/step - loss: 4.4121e-07 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.2147e-09 40/128 [========>.....................] - ETA: 0s - loss: 4.5247e-09 79/128 [=================>............] - ETA: 0s - loss: 3.6212e-09 116/128 [==========================>...] - ETA: 0s - loss: 3.9382e-07 128/128 [==============================] - 0s 1ms/step - loss: 3.5972e-07 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 2.2887e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.2252e-09 80/128 [=================>............] - ETA: 0s - loss: 4.7361e-07 120/128 [===========================>..] - ETA: 0s - loss: 3.1677e-07 128/128 [==============================] - 0s 1ms/step - loss: 2.9976e-07 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 2.3356e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.2427e-09 81/128 [=================>............] - ETA: 0s - loss: 3.4685e-09 121/128 [===========================>..] - ETA: 0s - loss: 2.6748e-07 128/128 [==============================] - 0s 1ms/step - loss: 2.5476e-07 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 3.3947e-09 40/128 [========>.....................] - ETA: 0s - loss: 2.8938e-09 79/128 [=================>............] - ETA: 0s - loss: 3.5037e-07 111/128 [=========================>....] - ETA: 0s - loss: 2.5056e-07 128/128 [==============================] - 0s 1ms/step - loss: 2.1922e-07 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.2073e-09 40/128 [========>.....................] - ETA: 0s - loss: 2.3438e-09 78/128 [=================>............] - ETA: 0s - loss: 3.0999e-07 117/128 [==========================>...] - ETA: 0s - loss: 2.0760e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.9129e-07 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 9.8104e-10 41/128 [========>.....................] - ETA: 0s - loss: 5.1777e-07 82/128 [==================>...........] - ETA: 0s - loss: 2.6027e-07 123/128 [===========================>..] - ETA: 0s - loss: 1.7435e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.6880e-07 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1228 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 22s - loss: 1.6707e-10 42/128 [========>.....................] - ETA: 0s - loss: 7.6904e-10  81/128 [=================>............] - ETA: 0s - loss: 5.5079e-10 121/128 [===========================>..] - ETA: 0s - loss: 4.6977e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.8579e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.7190e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.2920e-10 82/128 [==================>...........] - ETA: 0s - loss: 3.1384e-10 118/128 [==========================>...] - ETA: 0s - loss: 2.2949e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.1613e-10 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.8776e-11 38/128 [=======>......................] - ETA: 0s - loss: 1.0601e-10 78/128 [=================>............] - ETA: 0s - loss: 7.1239e-11 118/128 [==========================>...] - ETA: 0s - loss: 5.8619e-11 128/128 [==============================] - 0s 1ms/step - loss: 2.0691e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 4.4184e-11 41/128 [========>.....................] - ETA: 0s - loss: 3.1417e-11 81/128 [=================>............] - ETA: 0s - loss: 6.6787e-11 114/128 [=========================>....] - ETA: 0s - loss: 2.2538e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.0512e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 9.9657e-12 40/128 [========>.....................] - ETA: 0s - loss: 3.2652e-11 81/128 [=================>............] - ETA: 0s - loss: 2.9774e-10 120/128 [===========================>..] - ETA: 0s - loss: 2.1333e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.0314e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 3.4222e-11 39/128 [========>.....................] - ETA: 0s - loss: 3.3197e-11 80/128 [=================>............] - ETA: 0s - loss: 3.4980e-11 120/128 [===========================>..] - ETA: 0s - loss: 2.1132e-10 128/128 [==============================] - 0s 1ms/step - loss: 2.0115e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 2.6490e-11 41/128 [========>.....................] - ETA: 0s - loss: 3.1142e-11 82/128 [==================>...........] - ETA: 0s - loss: 3.4197e-11 119/128 [==========================>...] - ETA: 0s - loss: 1.9194e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.9929e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.6170e-11 36/128 [=======>......................] - ETA: 0s - loss: 3.5801e-11 72/128 [===============>..............] - ETA: 0s - loss: 2.9537e-10 108/128 [========================>.....] - ETA: 0s - loss: 2.2677e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.9727e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 3.0396e-11 34/128 [======>.......................] - ETA: 0s - loss: 9.3405e-11 68/128 [==============>...............] - ETA: 0s - loss: 3.3849e-10 107/128 [========================>.....] - ETA: 0s - loss: 2.2654e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.9495e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 2.5381e-11 39/128 [========>.....................] - ETA: 0s - loss: 3.0162e-11 78/128 [=================>............] - ETA: 0s - loss: 2.9698e-10 117/128 [==========================>...] - ETA: 0s - loss: 2.0777e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.9326e-10 -> test with GAN.predict GAN tn, fp: 317, 0 GAN fn, tp: 0, 9 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 317, 0 LR fn, tp: 0, 9 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 317, 0 RF fn, tp: 0, 9 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 317, 0 GB fn, tp: 0, 9 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 0 KNN fn, tp: 0, 9 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 22s - loss: 7.9322e-10 33/128 [======>.......................] - ETA: 0s - loss: 7.1365e-04  64/128 [==============>...............] - ETA: 0s - loss: 3.6799e-04 99/128 [======================>.......] - ETA: 0s - loss: 2.3790e-04 128/128 [==============================] - 0s 2ms/step - loss: 1.8531e-04 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 4.9383e-09 39/128 [========>.....................] - ETA: 0s - loss: 1.2522e-05 79/128 [=================>............] - ETA: 0s - loss: 6.2000e-06 113/128 [=========================>....] - ETA: 0s - loss: 4.3411e-06 128/128 [==============================] - 0s 1ms/step - loss: 3.8613e-06 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.9327e-08 30/128 [======>.......................] - ETA: 0s - loss: 1.6332e-08 62/128 [=============>................] - ETA: 0s - loss: 4.5455e-06 94/128 [=====================>........] - ETA: 0s - loss: 3.0055e-06 128/128 [==============================] - ETA: 0s - loss: 2.2314e-06 128/128 [==============================] - 0s 2ms/step - loss: 2.2314e-06 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.1871e-08 34/128 [======>.......................] - ETA: 0s - loss: 1.4784e-08 69/128 [===============>..............] - ETA: 0s - loss: 3.1521e-06 103/128 [=======================>......] - ETA: 0s - loss: 2.1183e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.7232e-06 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.5873e-08 35/128 [=======>......................] - ETA: 0s - loss: 3.1165e-08 71/128 [===============>..............] - ETA: 0s - loss: 2.5519e-06 103/128 [=======================>......] - ETA: 0s - loss: 1.7637e-06 128/128 [==============================] - 0s 2ms/step - loss: 1.4321e-06 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.0858e-08 32/128 [======>.......................] - ETA: 0s - loss: 4.8719e-06 62/128 [=============>................] - ETA: 0s - loss: 2.5223e-06 98/128 [=====================>........] - ETA: 0s - loss: 1.5996e-06 128/128 [==============================] - 0s 2ms/step - loss: 1.2358e-06 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.1806e-09 37/128 [=======>......................] - ETA: 0s - loss: 1.4131e-08 76/128 [================>.............] - ETA: 0s - loss: 1.8192e-06 111/128 [=========================>....] - ETA: 0s - loss: 1.2495e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.0953e-06 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 9.1155e-09 39/128 [========>.....................] - ETA: 0s - loss: 3.1584e-06 75/128 [================>.............] - ETA: 0s - loss: 1.6464e-06 111/128 [=========================>....] - ETA: 0s - loss: 1.1199e-06 128/128 [==============================] - 0s 1ms/step - loss: 9.7964e-07 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 3.3164e-08 38/128 [=======>......................] - ETA: 0s - loss: 8.7137e-09 74/128 [================>.............] - ETA: 0s - loss: 1.5081e-06 108/128 [========================>.....] - ETA: 0s - loss: 1.0367e-06 128/128 [==============================] - 0s 1ms/step - loss: 8.8463e-07 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 2.8104e-09 31/128 [======>.......................] - ETA: 0s - loss: 9.1427e-09 67/128 [==============>...............] - ETA: 0s - loss: 8.0250e-09 103/128 [=======================>......] - ETA: 0s - loss: 9.9589e-07 128/128 [==============================] - 0s 2ms/step - loss: 8.0834e-07 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 50s - loss: 5.3069e-11 42/128 [========>.....................] - ETA: 0s - loss: 0.1202  82/128 [==================>...........] - ETA: 0s - loss: 0.0618 123/128 [===========================>..] - ETA: 0s - loss: 0.0425 128/128 [==============================] - 1s 1ms/step - loss: 0.0411 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.3768e-10 41/128 [========>.....................] - ETA: 0s - loss: 2.0119e-09 81/128 [=================>............] - ETA: 0s - loss: 1.2846e-09 122/128 [===========================>..] - ETA: 0s - loss: 8.6550e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3225e-10 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.1327e-11 42/128 [========>.....................] - ETA: 0s - loss: 3.3071e-11 77/128 [=================>............] - ETA: 0s - loss: 1.1031e-09 110/128 [========================>.....] - ETA: 0s - loss: 9.6507e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3988e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.7000e-11 39/128 [========>.....................] - ETA: 0s - loss: 4.0272e-11 80/128 [=================>............] - ETA: 0s - loss: 1.3103e-09 120/128 [===========================>..] - ETA: 0s - loss: 8.8626e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3876e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 4.2331e-11 41/128 [========>.....................] - ETA: 0s - loss: 2.0347e-09 81/128 [=================>............] - ETA: 0s - loss: 1.2949e-09 120/128 [===========================>..] - ETA: 0s - loss: 8.8486e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3759e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 6.9406e-11 41/128 [========>.....................] - ETA: 0s - loss: 3.3327e-11 80/128 [=================>............] - ETA: 0s - loss: 3.5278e-11 119/128 [==========================>...] - ETA: 0s - loss: 8.9060e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3637e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 6.3635e-11 39/128 [========>.....................] - ETA: 0s - loss: 4.0259e-11 79/128 [=================>............] - ETA: 0s - loss: 3.6400e-11 119/128 [==========================>...] - ETA: 0s - loss: 8.8953e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3508e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.4958e-11 40/128 [========>.....................] - ETA: 0s - loss: 3.9519e-11 80/128 [=================>............] - ETA: 0s - loss: 1.3038e-09 119/128 [==========================>...] - ETA: 0s - loss: 8.8773e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3374e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 2.6633e-11 42/128 [========>.....................] - ETA: 0s - loss: 4.0171e-11 82/128 [==================>...........] - ETA: 0s - loss: 1.2722e-09 123/128 [===========================>..] - ETA: 0s - loss: 8.5876e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3236e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 4.8744e-11 42/128 [========>.....................] - ETA: 0s - loss: 3.7706e-11 82/128 [==================>...........] - ETA: 0s - loss: 1.0247e-09 118/128 [==========================>...] - ETA: 0s - loss: 8.9245e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3096e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 24s - loss: 3.2350e-11 41/128 [========>.....................] - ETA: 0s - loss: 5.2977e-10  82/128 [==================>...........] - ETA: 0s - loss: 8.5991e-10 123/128 [===========================>..] - ETA: 0s - loss: 9.5074e-10 128/128 [==============================] - 0s 1ms/step - loss: 9.2014e-10 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.0581e-12 40/128 [========>.....................] - ETA: 0s - loss: 8.9032e-11 80/128 [=================>............] - ETA: 0s - loss: 4.7096e-11 120/128 [===========================>..] - ETA: 0s - loss: 1.3312e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.2583e-10 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.1135e-12 41/128 [========>.....................] - ETA: 0s - loss: 2.8885e-10 80/128 [=================>............] - ETA: 0s - loss: 1.5535e-10 121/128 [===========================>..] - ETA: 0s - loss: 1.2587e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.1990e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.5610e-12 41/128 [========>.....................] - ETA: 0s - loss: 3.5287e-10 81/128 [=================>............] - ETA: 0s - loss: 1.7963e-10 121/128 [===========================>..] - ETA: 0s - loss: 1.2091e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.1531e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 3.4296e-11 42/128 [========>.....................] - ETA: 0s - loss: 2.8046e-12 80/128 [=================>............] - ETA: 0s - loss: 2.8373e-12 121/128 [===========================>..] - ETA: 0s - loss: 2.0310e-11 128/128 [==============================] - 0s 1ms/step - loss: 1.1174e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 2.1238e-12 32/128 [======>.......................] - ETA: 0s - loss: 3.4592e-12 65/128 [==============>...............] - ETA: 0s - loss: 3.0351e-11 97/128 [=====================>........] - ETA: 0s - loss: 1.4440e-10 128/128 [==============================] - 0s 2ms/step - loss: 1.1055e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 7.5082e-13 41/128 [========>.....................] - ETA: 0s - loss: 3.2875e-10 81/128 [=================>............] - ETA: 0s - loss: 1.6754e-10 121/128 [===========================>..] - ETA: 0s - loss: 1.1495e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.0948e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 7.6667e-13 39/128 [========>.....................] - ETA: 0s - loss: 3.4688e-10 78/128 [=================>............] - ETA: 0s - loss: 1.7511e-10 118/128 [==========================>...] - ETA: 0s - loss: 1.1677e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.0857e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.3942e-12 37/128 [=======>......................] - ETA: 0s - loss: 4.4166e-11 72/128 [===============>..............] - ETA: 0s - loss: 1.8617e-10 106/128 [=======================>......] - ETA: 0s - loss: 1.2880e-10 128/128 [==============================] - 0s 1ms/step - loss: 1.0769e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 6.7932e-13 41/128 [========>.....................] - ETA: 0s - loss: 7.5227e-12 81/128 [=================>............] - ETA: 0s - loss: 2.2736e-11 121/128 [===========================>..] - ETA: 0s - loss: 1.5989e-11 128/128 [==============================] - 0s 1ms/step - loss: 1.0685e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 27s - loss: 3.9529e-09 38/128 [=======>......................] - ETA: 0s - loss: 5.6325e-09  76/128 [================>.............] - ETA: 0s - loss: 5.4210e-09 113/128 [=========================>....] - ETA: 0s - loss: 5.4664e-09 128/128 [==============================] - 0s 1ms/step - loss: 5.4786e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 6.2202e-09 39/128 [========>.....................] - ETA: 0s - loss: 4.3330e-09 75/128 [================>.............] - ETA: 0s - loss: 4.9906e-09 112/128 [=========================>....] - ETA: 0s - loss: 4.8509e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.9583e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 4.5780e-09 37/128 [=======>......................] - ETA: 0s - loss: 4.2812e-09 73/128 [================>.............] - ETA: 0s - loss: 4.6193e-09 108/128 [========================>.....] - ETA: 0s - loss: 4.5411e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.5869e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.3595e-08 38/128 [=======>......................] - ETA: 0s - loss: 4.4644e-09 74/128 [================>.............] - ETA: 0s - loss: 4.2527e-09 110/128 [========================>.....] - ETA: 0s - loss: 4.3124e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.2959e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 3.6091e-09 36/128 [=======>......................] - ETA: 0s - loss: 3.9330e-09 73/128 [================>.............] - ETA: 0s - loss: 4.0449e-09 109/128 [========================>.....] - ETA: 0s - loss: 4.1451e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.0664e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 3.1537e-09 34/128 [======>.......................] - ETA: 0s - loss: 3.5259e-09 71/128 [===============>..............] - ETA: 0s - loss: 4.2467e-09 106/128 [=======================>......] - ETA: 0s - loss: 4.0462e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.9117e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.9421e-09 37/128 [=======>......................] - ETA: 0s - loss: 3.5829e-09 73/128 [================>.............] - ETA: 0s - loss: 3.5661e-09 109/128 [========================>.....] - ETA: 0s - loss: 3.8529e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.7604e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 3.9964e-09 37/128 [=======>......................] - ETA: 0s - loss: 3.4748e-09 73/128 [================>.............] - ETA: 0s - loss: 3.6912e-09 109/128 [========================>.....] - ETA: 0s - loss: 3.6162e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.6290e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 3.3420e-09 42/128 [========>.....................] - ETA: 0s - loss: 3.4038e-09 84/128 [==================>...........] - ETA: 0s - loss: 3.3771e-09 128/128 [==============================] - ETA: 0s - loss: 3.5189e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.5189e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 3.7662e-09 39/128 [========>.....................] - ETA: 0s - loss: 3.2784e-09 76/128 [================>.............] - ETA: 0s - loss: 3.6241e-09 93/128 [====================>.........] - ETA: 0s - loss: 3.5566e-09 128/128 [==============================] - 0s 2ms/step - loss: 3.4140e-09 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1228 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 21s - loss: 2.8392e-10 34/128 [======>.......................] - ETA: 0s - loss: 9.8471e-10  73/128 [================>.............] - ETA: 0s - loss: 5.8505e-09 112/128 [=========================>....] - ETA: 0s - loss: 3.8625e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.4223e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.0726e-10 38/128 [=======>......................] - ETA: 0s - loss: 8.4221e-10 78/128 [=================>............] - ETA: 0s - loss: 7.3790e-10 118/128 [==========================>...] - ETA: 0s - loss: 6.1135e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.7249e-10 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 6.9183e-11 35/128 [=======>......................] - ETA: 0s - loss: 3.6903e-10 69/128 [===============>..............] - ETA: 0s - loss: 2.4423e-10 103/128 [=======================>......] - ETA: 0s - loss: 5.9458e-10 128/128 [==============================] - 0s 1ms/step - loss: 5.0884e-10 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.1753e-10 39/128 [========>.....................] - ETA: 0s - loss: 1.4106e-10 77/128 [=================>............] - ETA: 0s - loss: 2.7157e-10 114/128 [=========================>....] - ETA: 0s - loss: 2.9672e-10 128/128 [==============================] - 0s 1ms/step - loss: 4.6569e-10 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.4712e-10 40/128 [========>.....................] - ETA: 0s - loss: 9.9011e-11 78/128 [=================>............] - ETA: 0s - loss: 5.3491e-10 117/128 [==========================>...] - ETA: 0s - loss: 4.4508e-10 128/128 [==============================] - 0s 1ms/step - loss: 4.3160e-10 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 3.2018e-10 37/128 [=======>......................] - ETA: 0s - loss: 1.4119e-10 76/128 [================>.............] - ETA: 0s - loss: 2.9985e-10 112/128 [=========================>....] - ETA: 0s - loss: 4.5587e-10 128/128 [==============================] - 0s 1ms/step - loss: 4.1048e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 4.1774e-11 39/128 [========>.....................] - ETA: 0s - loss: 3.3577e-10 78/128 [=================>............] - ETA: 0s - loss: 2.7028e-10 116/128 [==========================>...] - ETA: 0s - loss: 2.0143e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.8841e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 8.3003e-11 41/128 [========>.....................] - ETA: 0s - loss: 2.0289e-10 80/128 [=================>............] - ETA: 0s - loss: 4.6084e-10 119/128 [==========================>...] - ETA: 0s - loss: 3.9214e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.7283e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 2.5384e-11 39/128 [========>.....................] - ETA: 0s - loss: 1.8332e-10 78/128 [=================>............] - ETA: 0s - loss: 4.6413e-10 118/128 [==========================>...] - ETA: 0s - loss: 3.3117e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.5887e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 2.6712e-11 41/128 [========>.....................] - ETA: 0s - loss: 2.8591e-10 80/128 [=================>............] - ETA: 0s - loss: 5.0017e-10 119/128 [==========================>...] - ETA: 0s - loss: 3.6636e-10 128/128 [==============================] - 0s 1ms/step - loss: 3.4677e-10 -> test with GAN.predict GAN tn, fp: 317, 0 GAN fn, tp: 0, 9 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 316, 1 LR fn, tp: 0, 9 LR f1 score: 0.947 LR cohens kappa score: 0.946 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 317, 0 RF fn, tp: 0, 9 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 317, 0 GB fn, tp: 0, 9 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 316, 1 KNN fn, tp: 0, 9 KNN f1 score: 0.947 KNN cohens kappa score: 0.946 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 22s - loss: 4.0080e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.8264e-09  81/128 [=================>............] - ETA: 0s - loss: 4.8390e-09 120/128 [===========================>..] - ETA: 0s - loss: 9.7124e-09 128/128 [==============================] - 0s 1ms/step - loss: 9.1791e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 6.4131e-10 41/128 [========>.....................] - ETA: 0s - loss: 4.8787e-10 80/128 [=================>............] - ETA: 0s - loss: 1.2522e-09 119/128 [==========================>...] - ETA: 0s - loss: 1.3875e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.3077e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 8.1106e-11 39/128 [========>.....................] - ETA: 0s - loss: 1.4337e-10 78/128 [=================>............] - ETA: 0s - loss: 9.5434e-10 117/128 [==========================>...] - ETA: 0s - loss: 1.2678e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.1758e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.0416e-10 40/128 [========>.....................] - ETA: 0s - loss: 1.5282e-10 78/128 [=================>............] - ETA: 0s - loss: 8.0497e-10 114/128 [=========================>....] - ETA: 0s - loss: 1.1848e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0740e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.5984e-10 30/128 [======>.......................] - ETA: 0s - loss: 3.8958e-10 62/128 [=============>................] - ETA: 0s - loss: 1.2021e-09 101/128 [======================>.......] - ETA: 0s - loss: 1.2183e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0013e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 6.0779e-11 41/128 [========>.....................] - ETA: 0s - loss: 1.2479e-09 80/128 [=================>............] - ETA: 0s - loss: 6.8531e-10 119/128 [==========================>...] - ETA: 0s - loss: 1.0037e-09 128/128 [==============================] - 0s 1ms/step - loss: 9.4580e-10 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 5.3565e-11 40/128 [========>.....................] - ETA: 0s - loss: 9.8268e-10 78/128 [=================>............] - ETA: 0s - loss: 5.5624e-10 117/128 [==========================>...] - ETA: 0s - loss: 9.6704e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.9768e-10 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 6.2998e-11 40/128 [========>.....................] - ETA: 0s - loss: 8.8508e-10 80/128 [=================>............] - ETA: 0s - loss: 1.2440e-09 119/128 [==========================>...] - ETA: 0s - loss: 9.1430e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.6164e-10 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 4.6482e-11 42/128 [========>.....................] - ETA: 0s - loss: 1.0730e-10 85/128 [==================>...........] - ETA: 0s - loss: 7.9754e-10 126/128 [============================>.] - ETA: 0s - loss: 8.3881e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.3221e-10 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.5124e-11 41/128 [========>.....................] - ETA: 0s - loss: 8.5290e-10 80/128 [=================>............] - ETA: 0s - loss: 4.8675e-10 119/128 [==========================>...] - ETA: 0s - loss: 8.5410e-10 128/128 [==============================] - 0s 1ms/step - loss: 8.0473e-10 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 1 KNN fn, tp: 0, 11 KNN f1 score: 0.957 KNN cohens kappa score: 0.955 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 21s - loss: 1.6411e-09 34/128 [======>.......................] - ETA: 0s - loss: 8.7902e-10  65/128 [==============>...............] - ETA: 0s - loss: 1.5067e-04 98/128 [=====================>........] - ETA: 0s - loss: 9.9937e-05 128/128 [==============================] - 0s 2ms/step - loss: 8.3984e-05 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.1529e-08 35/128 [=======>......................] - ETA: 0s - loss: 1.1837e-05 71/128 [===============>..............] - ETA: 0s - loss: 5.8453e-06 106/128 [=======================>......] - ETA: 0s - loss: 3.9587e-06 128/128 [==============================] - 0s 1ms/step - loss: 3.3026e-06 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.2219e-08 39/128 [========>.....................] - ETA: 0s - loss: 9.7135e-08 70/128 [===============>..............] - ETA: 0s - loss: 5.7898e-08 101/128 [======================>.......] - ETA: 0s - loss: 4.2481e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.5155e-06 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.0929e-08 34/128 [======>.......................] - ETA: 0s - loss: 7.7107e-06 66/128 [==============>...............] - ETA: 0s - loss: 3.9755e-06 103/128 [=======================>......] - ETA: 0s - loss: 2.5490e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.0665e-06 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 4.4965e-09 35/128 [=======>......................] - ETA: 0s - loss: 5.9240e-08 65/128 [==============>...............] - ETA: 0s - loss: 3.3268e-06 99/128 [======================>.......] - ETA: 0s - loss: 2.1868e-06 128/128 [==============================] - 0s 2ms/step - loss: 1.7039e-06 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 3.7834e-09 40/128 [========>.....................] - ETA: 0s - loss: 4.5539e-06 79/128 [=================>............] - ETA: 0s - loss: 2.3072e-06 117/128 [==========================>...] - ETA: 0s - loss: 1.5591e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.4452e-06 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.5330e-09 39/128 [========>.....................] - ETA: 0s - loss: 3.5080e-08 78/128 [=================>............] - ETA: 0s - loss: 1.8543e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.3491e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.2421e-06 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.5154e-09 40/128 [========>.....................] - ETA: 0s - loss: 2.7587e-08 79/128 [=================>............] - ETA: 0s - loss: 1.5720e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.1589e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.0671e-06 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.5924e-09 38/128 [=======>......................] - ETA: 0s - loss: 2.8276e-09 76/128 [================>.............] - ETA: 0s - loss: 1.5488e-06 114/128 [=========================>....] - ETA: 0s - loss: 1.0339e-06 128/128 [==============================] - 0s 1ms/step - loss: 9.2752e-07 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.0993e-10 39/128 [========>.....................] - ETA: 0s - loss: 1.9121e-09 78/128 [=================>............] - ETA: 0s - loss: 1.3091e-06 117/128 [==========================>...] - ETA: 0s - loss: 8.7942e-07 128/128 [==============================] - 0s 1ms/step - loss: 8.0971e-07 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 20s - loss: 3.1947e-10 40/128 [========>.....................] - ETA: 0s - loss: 4.5475e-09  78/128 [=================>............] - ETA: 0s - loss: 1.9018e-04 116/128 [==========================>...] - ETA: 0s - loss: 1.2915e-04 128/128 [==============================] - 0s 1ms/step - loss: 1.1787e-04 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 3.7418e-10 34/128 [======>.......................] - ETA: 0s - loss: 4.3054e-10 72/128 [===============>..............] - ETA: 0s - loss: 7.4109e-06 111/128 [=========================>....] - ETA: 0s - loss: 4.8561e-06 128/128 [==============================] - 0s 1ms/step - loss: 4.2425e-06 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 8.8633e-08 41/128 [========>.....................] - ETA: 0s - loss: 4.0523e-09 79/128 [=================>............] - ETA: 0s - loss: 2.7412e-09 119/128 [==========================>...] - ETA: 0s - loss: 3.0255e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.8327e-06 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.6961e-09 41/128 [========>.....................] - ETA: 0s - loss: 8.9487e-08 81/128 [=================>............] - ETA: 0s - loss: 3.4289e-06 120/128 [===========================>..] - ETA: 0s - loss: 2.3159e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.1871e-06 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.2798e-09 40/128 [========>.....................] - ETA: 0s - loss: 5.6448e-06 79/128 [=================>............] - ETA: 0s - loss: 2.8604e-06 118/128 [==========================>...] - ETA: 0s - loss: 1.9176e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.7821e-06 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.3521e-09 40/128 [========>.....................] - ETA: 0s - loss: 4.7024e-06 70/128 [===============>..............] - ETA: 0s - loss: 2.6898e-06 103/128 [=======================>......] - ETA: 0s - loss: 1.8327e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.5006e-06 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 2.3765e-09 39/128 [========>.....................] - ETA: 0s - loss: 5.3600e-09 79/128 [=================>............] - ETA: 0s - loss: 2.0504e-06 118/128 [==========================>...] - ETA: 0s - loss: 1.3883e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.2894e-06 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.2524e-09 40/128 [========>.....................] - ETA: 0s - loss: 3.9079e-08 79/128 [=================>............] - ETA: 0s - loss: 2.1669e-08 118/128 [==========================>...] - ETA: 0s - loss: 1.6300e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.1113e-06 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 3.7317e-10 40/128 [========>.....................] - ETA: 0s - loss: 3.0849e-06 78/128 [=================>............] - ETA: 0s - loss: 1.5989e-06 117/128 [==========================>...] - ETA: 0s - loss: 1.0695e-06 128/128 [==============================] - 0s 1ms/step - loss: 9.8465e-07 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 3.2008e-10 41/128 [========>.....................] - ETA: 0s - loss: 5.4109e-09 80/128 [=================>............] - ETA: 0s - loss: 1.3040e-06 120/128 [===========================>..] - ETA: 0s - loss: 8.7901e-07 128/128 [==============================] - 0s 1ms/step - loss: 8.3001e-07 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1229 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 21s - loss: 1.4707e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.5333e-04  79/128 [=================>............] - ETA: 0s - loss: 1.8340e-04 119/128 [==========================>...] - ETA: 0s - loss: 1.4413e-04 128/128 [==============================] - 0s 1ms/step - loss: 1.3494e-04 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 3.0647e-09 41/128 [========>.....................] - ETA: 0s - loss: 2.5371e-09 79/128 [=================>............] - ETA: 0s - loss: 1.0121e-05 117/128 [==========================>...] - ETA: 0s - loss: 7.3757e-06 128/128 [==============================] - 0s 1ms/step - loss: 6.7898e-06 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.8150e-09 40/128 [========>.....................] - ETA: 0s - loss: 2.4452e-09 77/128 [=================>............] - ETA: 0s - loss: 6.6043e-06 115/128 [=========================>....] - ETA: 0s - loss: 4.4229e-06 128/128 [==============================] - 0s 1ms/step - loss: 4.0021e-06 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.8317e-09 39/128 [========>.....................] - ETA: 0s - loss: 2.6589e-09 75/128 [================>.............] - ETA: 0s - loss: 4.1072e-07 113/128 [=========================>....] - ETA: 0s - loss: 3.2011e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.8463e-06 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.8884e-09 40/128 [========>.....................] - ETA: 0s - loss: 3.2848e-09 79/128 [=================>............] - ETA: 0s - loss: 3.2097e-06 120/128 [===========================>..] - ETA: 0s - loss: 2.3030e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.1747e-06 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 5.1654e-09 42/128 [========>.....................] - ETA: 0s - loss: 5.0876e-07 88/128 [===================>..........] - ETA: 0s - loss: 2.5113e-06 111/128 [=========================>....] - ETA: 0s - loss: 1.9922e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.7406e-06 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 6.8942e-09 44/128 [=========>....................] - ETA: 0s - loss: 5.7513e-09 89/128 [===================>..........] - ETA: 0s - loss: 1.8562e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.4364e-06 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 6.4276e-09 41/128 [========>.....................] - ETA: 0s - loss: 6.7222e-09 79/128 [=================>............] - ETA: 0s - loss: 2.1330e-07 125/128 [============================>.] - ETA: 0s - loss: 1.2377e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.2174e-06 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 6.3452e-09 43/128 [=========>....................] - ETA: 0s - loss: 3.5350e-07 84/128 [==================>...........] - ETA: 0s - loss: 1.8407e-07 120/128 [===========================>..] - ETA: 0s - loss: 1.1184e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.0563e-06 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 6.0887e-09 39/128 [========>.....................] - ETA: 0s - loss: 5.9798e-09 78/128 [=================>............] - ETA: 0s - loss: 1.3305e-06 119/128 [==========================>...] - ETA: 0s - loss: 9.8294e-07 128/128 [==============================] - 0s 1ms/step - loss: 9.2066e-07 -> test with GAN.predict GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 318, 0 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 318, 0 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1228 synthetic samples -> retrain GAN for predict Epoch 1/10 1/128 [..............................] - ETA: 22s - loss: 2.6818e-10 36/128 [=======>......................] - ETA: 0s - loss: 9.0138e-10  67/128 [==============>...............] - ETA: 0s - loss: 0.0762  102/128 [======================>.......] - ETA: 0s - loss: 0.0501 128/128 [==============================] - 0s 1ms/step - loss: 0.0401 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 6.2488e-06 38/128 [=======>......................] - ETA: 0s - loss: 4.3737e-06 73/128 [================>.............] - ETA: 0s - loss: 4.9266e-06 108/128 [========================>.....] - ETA: 0s - loss: 4.3684e-06 128/128 [==============================] - 0s 1ms/step - loss: 4.0713e-06 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.1505e-06 38/128 [=======>......................] - ETA: 0s - loss: 3.8408e-06 76/128 [================>.............] - ETA: 0s - loss: 2.9102e-06 109/128 [========================>.....] - ETA: 0s - loss: 2.6641e-06 128/128 [==============================] - 0s 1ms/step - loss: 2.5313e-06 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.1570e-06 35/128 [=======>......................] - ETA: 0s - loss: 2.3247e-06 69/128 [===============>..............] - ETA: 0s - loss: 1.8012e-06 104/128 [=======================>......] - ETA: 0s - loss: 1.9093e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.9138e-06 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 9.7444e-07 34/128 [======>.......................] - ETA: 0s - loss: 2.2908e-06 69/128 [===============>..............] - ETA: 0s - loss: 1.7457e-06 103/128 [=======================>......] - ETA: 0s - loss: 1.4618e-06 128/128 [==============================] - 0s 2ms/step - loss: 1.5287e-06 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 8.9771e-06 35/128 [=======>......................] - ETA: 0s - loss: 2.0051e-06 72/128 [===============>..............] - ETA: 0s - loss: 1.3553e-06 105/128 [=======================>......] - ETA: 0s - loss: 1.1576e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.0503e-06 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 2.3777e-07 36/128 [=======>......................] - ETA: 0s - loss: 6.0123e-07 72/128 [===============>..............] - ETA: 0s - loss: 4.9694e-07 107/128 [========================>.....] - ETA: 0s - loss: 3.9743e-07 128/128 [==============================] - 0s 1ms/step - loss: 3.7616e-07 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.5518e-07 34/128 [======>.......................] - ETA: 0s - loss: 1.6705e-07 66/128 [==============>...............] - ETA: 0s - loss: 1.7814e-07 103/128 [=======================>......] - ETA: 0s - loss: 1.7018e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.8248e-07 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 6.4778e-08 36/128 [=======>......................] - ETA: 0s - loss: 1.0797e-07 72/128 [===============>..............] - ETA: 0s - loss: 1.2320e-07 108/128 [========================>.....] - ETA: 0s - loss: 1.2322e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.1478e-07 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 5.3125e-08 35/128 [=======>......................] - ETA: 0s - loss: 9.2837e-08 59/128 [============>.................] - ETA: 0s - loss: 8.8362e-08 85/128 [==================>...........] - ETA: 0s - loss: 7.7919e-08 113/128 [=========================>....] - ETA: 0s - loss: 7.5708e-08 128/128 [==============================] - 0s 2ms/step - loss: 8.0943e-08 -> test with GAN.predict GAN tn, fp: 317, 0 GAN fn, tp: 0, 9 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 -> test with 'LR' LR tn, fp: 317, 0 LR fn, tp: 0, 9 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 -> test with 'RF' RF tn, fp: 317, 0 RF fn, tp: 0, 9 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 317, 0 GB fn, tp: 0, 9 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 317, 0 KNN fn, tp: 0, 9 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 318, 1 LR fn, tp: 0, 11 LR f1 score: 1.000 LR cohens kappa score: 1.000 LR average precision score: 1.000 average: LR tn, fp: 317.76, 0.04 LR fn, tp: 0.0, 10.6 LR f1 score: 0.998 LR cohens kappa score: 0.998 LR average precision score: 1.000 minimum: LR tn, fp: 316, 0 LR fn, tp: 0, 9 LR f1 score: 0.947 LR cohens kappa score: 0.946 LR average precision score: 1.000 -----[ RF ]----- maximum: RF tn, fp: 318, 0 RF fn, tp: 0, 11 RF f1 score: 1.000 RF cohens kappa score: 1.000 average: RF tn, fp: 317.8, 0.0 RF fn, tp: 0.0, 10.6 RF f1 score: 1.000 RF cohens kappa score: 1.000 minimum: RF tn, fp: 317, 0 RF fn, tp: 0, 9 RF f1 score: 1.000 RF cohens kappa score: 1.000 -----[ GB ]----- maximum: GB tn, fp: 318, 0 GB fn, tp: 0, 11 GB f1 score: 1.000 GB cohens kappa score: 1.000 average: GB tn, fp: 317.8, 0.0 GB fn, tp: 0.0, 10.6 GB f1 score: 1.000 GB cohens kappa score: 1.000 minimum: GB tn, fp: 317, 0 GB fn, tp: 0, 9 GB f1 score: 1.000 GB cohens kappa score: 1.000 -----[ KNN ]----- maximum: KNN tn, fp: 318, 1 KNN fn, tp: 0, 11 KNN f1 score: 1.000 KNN cohens kappa score: 1.000 average: KNN tn, fp: 317.6, 0.2 KNN fn, tp: 0.0, 10.6 KNN f1 score: 0.991 KNN cohens kappa score: 0.991 minimum: KNN tn, fp: 316, 0 KNN fn, tp: 0, 9 KNN f1 score: 0.947 KNN cohens kappa score: 0.946 -----[ GAN ]----- maximum: GAN tn, fp: 318, 0 GAN fn, tp: 0, 11 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 average: GAN tn, fp: 317.8, 0.0 GAN fn, tp: 0.0, 10.6 GAN f1 score: 1.000 GAN cohens kappa score: 1.000 minimum: GAN tn, fp: 317, 0 GAN fn, tp: 0, 9 GAN f1 score: 1.000 GAN cohens kappa score: 1.000