/////////////////////////////////////////// // Running convGAN-majority-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: 21s - loss: 2.4243e-08 42/128 [========>.....................] - ETA: 0s - loss: 9.9360e-08  83/128 [==================>...........] - ETA: 0s - loss: 6.3626e-08 124/128 [============================>.] - ETA: 0s - loss: 5.6233e-08 128/128 [==============================] - 0s 1ms/step - loss: 5.5476e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.0856e-08 40/128 [========>.....................] - ETA: 0s - loss: 2.3554e-08 80/128 [=================>............] - ETA: 0s - loss: 3.0265e-08 119/128 [==========================>...] - ETA: 0s - loss: 5.2924e-08 128/128 [==============================] - 0s 1ms/step - loss: 5.1415e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.8917e-08 39/128 [========>.....................] - ETA: 0s - loss: 2.3360e-08 75/128 [================>.............] - ETA: 0s - loss: 2.9798e-08 113/128 [=========================>....] - ETA: 0s - loss: 2.6238e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.7757e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.7698e-08 39/128 [========>.....................] - ETA: 0s - loss: 3.2471e-08 78/128 [=================>............] - ETA: 0s - loss: 6.0322e-08 118/128 [==========================>...] - ETA: 0s - loss: 4.6482e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.4365e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.5613e-08 40/128 [========>.....................] - ETA: 0s - loss: 1.7690e-08 77/128 [=================>............] - ETA: 0s - loss: 2.3751e-08 116/128 [==========================>...] - ETA: 0s - loss: 4.3455e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.1250e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.8071e-08 41/128 [========>.....................] - ETA: 0s - loss: 1.6670e-08 78/128 [=================>............] - ETA: 0s - loss: 1.6297e-08 119/128 [==========================>...] - ETA: 0s - loss: 3.9696e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.8361e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.5320e-08 41/128 [========>.....................] - ETA: 0s - loss: 1.5641e-08 83/128 [==================>...........] - ETA: 0s - loss: 4.7305e-08 120/128 [===========================>..] - ETA: 0s - loss: 3.6929e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.5788e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.3329e-08 34/128 [======>.......................] - ETA: 0s - loss: 1.3615e-08 72/128 [===============>..............] - ETA: 0s - loss: 1.3442e-08 107/128 [========================>.....] - ETA: 0s - loss: 3.7099e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.3547e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.0254e-08 41/128 [========>.....................] - ETA: 0s - loss: 6.1959e-08 75/128 [================>.............] - ETA: 0s - loss: 3.9528e-08 111/128 [=========================>....] - ETA: 0s - loss: 3.4321e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.1475e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.8515e-09 42/128 [========>.....................] - ETA: 0s - loss: 2.0848e-08 81/128 [=================>............] - ETA: 0s - loss: 1.6462e-08 122/128 [===========================>..] - ETA: 0s - loss: 3.0370e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.9663e-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 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: 22s - loss: 1.3771e-08 41/128 [========>.....................] - ETA: 0s - loss: 1.7569e-07  81/128 [=================>............] - ETA: 0s - loss: 9.8110e-08 122/128 [===========================>..] - ETA: 0s - loss: 7.0480e-08 128/128 [==============================] - 0s 1ms/step - loss: 6.8178e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.2908e-08 34/128 [======>.......................] - ETA: 0s - loss: 1.3413e-08 67/128 [==============>...............] - ETA: 0s - loss: 9.3114e-08 100/128 [======================>.......] - ETA: 0s - loss: 7.5738e-08 128/128 [==============================] - 0s 2ms/step - loss: 6.2536e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.6887e-08 38/128 [=======>......................] - ETA: 0s - loss: 1.4193e-08 77/128 [=================>............] - ETA: 0s - loss: 1.5107e-08 116/128 [==========================>...] - ETA: 0s - loss: 2.2052e-08 128/128 [==============================] - 0s 1ms/step - loss: 5.7526e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 9.5687e-09 39/128 [========>.....................] - ETA: 0s - loss: 1.2725e-07 78/128 [=================>............] - ETA: 0s - loss: 7.2087e-08 116/128 [==========================>...] - ETA: 0s - loss: 5.8935e-08 128/128 [==============================] - 0s 1ms/step - loss: 5.4792e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 3.1454e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.2695e-08 80/128 [=================>............] - ETA: 0s - loss: 2.1588e-08 119/128 [==========================>...] - ETA: 0s - loss: 1.8914e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.8893e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.0898e-08 42/128 [========>.....................] - ETA: 0s - loss: 1.1298e-08 82/128 [==================>...........] - ETA: 0s - loss: 6.3656e-08 119/128 [==========================>...] - ETA: 0s - loss: 4.7644e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.5198e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.3179e-06 41/128 [========>.....................] - ETA: 0s - loss: 1.0639e-07 81/128 [=================>............] - ETA: 0s - loss: 5.9606e-08 121/128 [===========================>..] - ETA: 0s - loss: 4.3613e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.2030e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.5283e-08 43/128 [=========>....................] - ETA: 0s - loss: 8.2224e-08 79/128 [=================>............] - ETA: 0s - loss: 4.9024e-08 111/128 [=========================>....] - ETA: 0s - loss: 4.2091e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.9055e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 9.5104e-09 41/128 [========>.....................] - ETA: 0s - loss: 9.1778e-09 80/128 [=================>............] - ETA: 0s - loss: 9.5674e-09 119/128 [==========================>...] - ETA: 0s - loss: 3.7854e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.6413e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.0434e-08 40/128 [========>.....................] - ETA: 0s - loss: 1.0465e-08 80/128 [=================>............] - ETA: 0s - loss: 4.3411e-08 120/128 [===========================>..] - ETA: 0s - loss: 3.5251e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.3855e-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 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: 20s - loss: 8.5580e-09 41/128 [========>.....................] - ETA: 0s - loss: 5.1168e-08  82/128 [==================>...........] - ETA: 0s - loss: 2.9975e-08 122/128 [===========================>..] - ETA: 0s - loss: 4.3461e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.1894e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 3.1430e-09 42/128 [========>.....................] - ETA: 0s - loss: 4.6651e-08 80/128 [=================>............] - ETA: 0s - loss: 2.7789e-08 118/128 [==========================>...] - ETA: 0s - loss: 2.1735e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.0531e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.0152e-09 41/128 [========>.....................] - ETA: 0s - loss: 6.2461e-09 81/128 [=================>............] - ETA: 0s - loss: 2.7128e-08 122/128 [===========================>..] - ETA: 0s - loss: 2.0173e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9539e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.7928e-09 40/128 [========>.....................] - ETA: 0s - loss: 8.6576e-09 78/128 [=================>............] - ETA: 0s - loss: 7.4546e-09 114/128 [=========================>....] - ETA: 0s - loss: 6.2976e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.8615e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.9208e-09 40/128 [========>.....................] - ETA: 0s - loss: 6.0689e-09 80/128 [=================>............] - ETA: 0s - loss: 6.3204e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.8374e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.7761e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 4.5434e-09 39/128 [========>.....................] - ETA: 0s - loss: 4.1621e-09 80/128 [=================>............] - ETA: 0s - loss: 5.9022e-09 120/128 [===========================>..] - ETA: 0s - loss: 1.7746e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.6940e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 4.9434e-09 42/128 [========>.....................] - ETA: 0s - loss: 7.2190e-09 82/128 [==================>...........] - ETA: 0s - loss: 6.5016e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.6705e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.6156e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.8521e-09 42/128 [========>.....................] - ETA: 0s - loss: 3.5910e-08 81/128 [=================>............] - ETA: 0s - loss: 2.0396e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.6111e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.5405e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 4.2530e-09 39/128 [========>.....................] - ETA: 0s - loss: 6.6039e-09 70/128 [===============>..............] - ETA: 0s - loss: 6.2467e-09 102/128 [======================>.......] - ETA: 0s - loss: 5.4268e-09 128/128 [==============================] - 0s 2ms/step - loss: 1.4731e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 4.0715e-09 37/128 [=======>......................] - ETA: 0s - loss: 6.5639e-09 71/128 [===============>..............] - ETA: 0s - loss: 2.2351e-08 109/128 [========================>.....] - ETA: 0s - loss: 1.5770e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.4072e-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: 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: 20s - loss: 7.1210e-08 41/128 [========>.....................] - ETA: 0s - loss: 1.3869e-07  78/128 [=================>............] - ETA: 0s - loss: 8.0149e-08 119/128 [==========================>...] - ETA: 0s - loss: 5.8140e-08 128/128 [==============================] - 0s 1ms/step - loss: 5.5302e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.4268e-08 39/128 [========>.....................] - ETA: 0s - loss: 1.3126e-07 78/128 [=================>............] - ETA: 0s - loss: 7.2606e-08 117/128 [==========================>...] - ETA: 0s - loss: 5.4481e-08 128/128 [==============================] - 0s 1ms/step - loss: 5.1465e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 9.9646e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.2073e-07 81/128 [=================>............] - ETA: 0s - loss: 6.7977e-08 122/128 [===========================>..] - ETA: 0s - loss: 4.9722e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.8156e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 5.7670e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.5484e-08 81/128 [=================>............] - ETA: 0s - loss: 6.3124e-08 121/128 [===========================>..] - ETA: 0s - loss: 4.6803e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.5116e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.4172e-08 40/128 [========>.....................] - ETA: 0s - loss: 1.2828e-08 78/128 [=================>............] - ETA: 0s - loss: 1.1911e-08 116/128 [==========================>...] - ETA: 0s - loss: 4.5158e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.2399e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.3106e-08 42/128 [========>.....................] - ETA: 0s - loss: 9.4694e-08 82/128 [==================>...........] - ETA: 0s - loss: 5.5408e-08 118/128 [==========================>...] - ETA: 0s - loss: 4.2129e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.9847e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.0463e-08 42/128 [========>.....................] - ETA: 0s - loss: 9.2203e-08 82/128 [==================>...........] - ETA: 0s - loss: 5.2741e-08 122/128 [===========================>..] - ETA: 0s - loss: 3.8705e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.7565e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.1443e-08 41/128 [========>.....................] - ETA: 0s - loss: 1.3238e-08 77/128 [=================>............] - ETA: 0s - loss: 1.1810e-08 116/128 [==========================>...] - ETA: 0s - loss: 3.8023e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.5477e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 8.0186e-09 40/128 [========>.....................] - ETA: 0s - loss: 9.1393e-09 80/128 [=================>............] - ETA: 0s - loss: 9.5547e-09 121/128 [===========================>..] - ETA: 0s - loss: 3.3868e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.3533e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 7.8574e-09 35/128 [=======>......................] - ETA: 0s - loss: 9.0068e-09 67/128 [==============>...............] - ETA: 0s - loss: 5.1791e-08 101/128 [======================>.......] - ETA: 0s - loss: 3.7399e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.1505e-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 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: 28s - loss: 3.6196e-08 41/128 [========>.....................] - ETA: 0s - loss: 2.4214e-08  81/128 [=================>............] - ETA: 0s - loss: 1.4161e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.1009e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.0602e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 3.4953e-09 36/128 [=======>......................] - ETA: 0s - loss: 3.8466e-09 43/128 [=========>....................] - ETA: 0s - loss: 2.1720e-08 80/128 [=================>............] - ETA: 0s - loss: 1.3552e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.0001e-08 128/128 [==============================] - 0s 2ms/step - loss: 9.6202e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.2183e-08 42/128 [========>.....................] - ETA: 0s - loss: 2.0862e-08 78/128 [=================>............] - ETA: 0s - loss: 1.2640e-08 94/128 [=====================>........] - ETA: 0s - loss: 1.0967e-08 117/128 [==========================>...] - ETA: 0s - loss: 9.5338e-09 128/128 [==============================] - 0s 2ms/step - loss: 9.0362e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.9821e-09 39/128 [========>.....................] - ETA: 0s - loss: 2.9862e-09 79/128 [=================>............] - ETA: 0s - loss: 3.3175e-09 115/128 [=========================>....] - ETA: 0s - loss: 9.0834e-09 128/128 [==============================] - 0s 1ms/step - loss: 8.5316e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.4924e-08 13/128 [==>...........................] - ETA: 0s - loss: 5.0311e-09 42/128 [========>.....................] - ETA: 0s - loss: 3.5495e-09 82/128 [==================>...........] - ETA: 0s - loss: 1.0857e-08 122/128 [===========================>..] - ETA: 0s - loss: 8.2765e-09 128/128 [==============================] - 0s 2ms/step - loss: 8.0720e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 3.4237e-09 34/128 [======>.......................] - ETA: 0s - loss: 2.7564e-09 53/128 [===========>..................] - ETA: 0s - loss: 2.8130e-09 75/128 [================>.............] - ETA: 0s - loss: 2.9844e-09 113/128 [=========================>....] - ETA: 0s - loss: 8.1754e-09 128/128 [==============================] - 0s 2ms/step - loss: 7.6568e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 2.6235e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.2990e-09 76/128 [================>.............] - ETA: 0s - loss: 1.0331e-08 101/128 [======================>.......] - ETA: 0s - loss: 8.4715e-09 119/128 [==========================>...] - ETA: 0s - loss: 7.5369e-09 128/128 [==============================] - 0s 2ms/step - loss: 7.2451e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 3.0009e-09 41/128 [========>.....................] - ETA: 0s - loss: 2.9755e-09 80/128 [=================>............] - ETA: 0s - loss: 2.8542e-09 115/128 [=========================>....] - ETA: 0s - loss: 7.2894e-09 128/128 [==============================] - 0s 1ms/step - loss: 6.9114e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 2.8491e-09 20/128 [===>..........................] - ETA: 0s - loss: 2.9031e-09 44/128 [=========>....................] - ETA: 0s - loss: 1.3493e-08 82/128 [==================>...........] - ETA: 0s - loss: 8.5652e-09 116/128 [==========================>...] - ETA: 0s - loss: 6.9612e-09 128/128 [==============================] - 0s 2ms/step - loss: 6.5780e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.2369e-10 30/128 [======>.......................] - ETA: 0s - loss: 2.2843e-09 57/128 [============>.................] - ETA: 0s - loss: 2.6300e-09 65/128 [==============>...............] - ETA: 0s - loss: 2.6586e-09 104/128 [=======================>......] - ETA: 0s - loss: 2.7414e-09 128/128 [==============================] - 0s 2ms/step - loss: 6.2821e-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: 27s - loss: 4.7242e-09 38/128 [=======>......................] - ETA: 0s - loss: 1.3864e-08  52/128 [===========>..................] - ETA: 0s - loss: 2.4928e-07 87/128 [===================>..........] - ETA: 0s - loss: 1.5022e-07 125/128 [============================>.] - ETA: 0s - loss: 1.3027e-07 128/128 [==============================] - 0s 2ms/step - loss: 1.2815e-07 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.5075e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.8936e-08 75/128 [================>.............] - ETA: 0s - loss: 1.1352e-08 99/128 [======================>.......] - ETA: 0s - loss: 9.1886e-09 120/128 [===========================>..] - ETA: 0s - loss: 3.1809e-08 128/128 [==============================] - 0s 2ms/step - loss: 3.0116e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 8.8151e-10 42/128 [========>.....................] - ETA: 0s - loss: 1.6005e-08 81/128 [=================>............] - ETA: 0s - loss: 8.9846e-09 122/128 [===========================>..] - ETA: 0s - loss: 6.9506e-09 128/128 [==============================] - 0s 1ms/step - loss: 2.7356e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.6423e-09 38/128 [=======>......................] - ETA: 0s - loss: 2.2909e-09 56/128 [============>.................] - ETA: 0s - loss: 2.0751e-09 88/128 [===================>..........] - ETA: 0s - loss: 8.3077e-09 128/128 [==============================] - ETA: 0s - loss: 2.4998e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.4998e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.2270e-09 40/128 [========>.....................] - ETA: 0s - loss: 2.1309e-09 77/128 [=================>............] - ETA: 0s - loss: 2.1413e-09 109/128 [========================>.....] - ETA: 0s - loss: 2.2246e-08 126/128 [============================>.] - ETA: 0s - loss: 2.3124e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.2934e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.1529e-09 39/128 [========>.....................] - ETA: 0s - loss: 1.2575e-08 79/128 [=================>............] - ETA: 0s - loss: 3.2833e-08 118/128 [==========================>...] - ETA: 0s - loss: 2.2683e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.1160e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.7469e-09 36/128 [=======>......................] - ETA: 0s - loss: 1.3271e-09 44/128 [=========>....................] - ETA: 0s - loss: 1.3248e-09 74/128 [================>.............] - ETA: 0s - loss: 1.8104e-09 113/128 [=========================>....] - ETA: 0s - loss: 2.1692e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.9620e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.2206e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.9251e-09 78/128 [=================>............] - ETA: 0s - loss: 2.4264e-08 95/128 [=====================>........] - ETA: 0s - loss: 2.0150e-08 119/128 [==========================>...] - ETA: 0s - loss: 1.9205e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.8055e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 7.3453e-10 41/128 [========>.....................] - ETA: 0s - loss: 2.0137e-09 81/128 [=================>............] - ETA: 0s - loss: 2.1721e-08 116/128 [==========================>...] - ETA: 0s - loss: 1.8207e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.6785e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.2541e-09 31/128 [======>.......................] - ETA: 0s - loss: 1.3302e-09 53/128 [===========>..................] - ETA: 0s - loss: 1.3257e-09 88/128 [===================>..........] - ETA: 0s - loss: 1.9655e-09 122/128 [===========================>..] - ETA: 0s - loss: 1.6326e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.5711e-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 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: 23s - loss: 4.4417e-10 40/128 [========>.....................] - ETA: 0s - loss: 1.4216e-09  79/128 [=================>............] - ETA: 0s - loss: 4.9627e-09 119/128 [==========================>...] - ETA: 0s - loss: 2.6750e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.5071e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 3.6814e-10 40/128 [========>.....................] - ETA: 0s - loss: 6.4985e-08 77/128 [=================>............] - ETA: 0s - loss: 3.3999e-08 116/128 [==========================>...] - ETA: 0s - loss: 2.4392e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.2293e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.9385e-09 41/128 [========>.....................] - ETA: 0s - loss: 2.9088e-09 74/128 [================>.............] - ETA: 0s - loss: 2.2195e-09 113/128 [=========================>....] - ETA: 0s - loss: 2.3258e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.0715e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.4244e-09 41/128 [========>.....................] - ETA: 0s - loss: 2.6982e-09 80/128 [=================>............] - ETA: 0s - loss: 1.8891e-09 118/128 [==========================>...] - ETA: 0s - loss: 2.0910e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9437e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 3.0356e-10 39/128 [========>.....................] - ETA: 0s - loss: 5.6411e-08 77/128 [=================>............] - ETA: 0s - loss: 2.8750e-08 118/128 [==========================>...] - ETA: 0s - loss: 1.9672e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.8285e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.9965e-10 38/128 [=======>......................] - ETA: 0s - loss: 5.4121e-08 76/128 [================>.............] - ETA: 0s - loss: 2.7233e-08 115/128 [=========================>....] - ETA: 0s - loss: 1.8137e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.7173e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 2.6569e-10 39/128 [========>.....................] - ETA: 0s - loss: 3.4151e-10 78/128 [=================>............] - ETA: 0s - loss: 2.5061e-08 116/128 [==========================>...] - ETA: 0s - loss: 1.7482e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.6145e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 3.1704e-10 39/128 [========>.....................] - ETA: 0s - loss: 1.5321e-09 72/128 [===============>..............] - ETA: 0s - loss: 2.6138e-08 104/128 [=======================>......] - ETA: 0s - loss: 1.8459e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.5151e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 3.4819e-10 39/128 [========>.....................] - ETA: 0s - loss: 4.3562e-10 77/128 [=================>............] - ETA: 0s - loss: 6.5902e-10 115/128 [=========================>....] - ETA: 0s - loss: 1.5704e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.4233e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.4254e-10 41/128 [========>.....................] - ETA: 0s - loss: 2.6734e-10 80/128 [=================>............] - ETA: 0s - loss: 2.0536e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.4201e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3419e-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: 317, 1 LR fn, tp: 0, 11 LR f1 score: 0.957 LR cohens kappa score: 0.955 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: 25s - loss: 9.0315e-09 37/128 [=======>......................] - ETA: 0s - loss: 1.0129e-07  70/128 [===============>..............] - ETA: 0s - loss: 6.6130e-08 106/128 [=======================>......] - ETA: 0s - loss: 4.6030e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.9669e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.1951e-08 34/128 [======>.......................] - ETA: 0s - loss: 6.9707e-09 69/128 [===============>..............] - ETA: 0s - loss: 7.7346e-09 103/128 [=======================>......] - ETA: 0s - loss: 4.1296e-08 128/128 [==============================] - 0s 2ms/step - loss: 3.4707e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 7.5504e-09 34/128 [======>.......................] - ETA: 0s - loss: 1.0312e-07 69/128 [===============>..............] - ETA: 0s - loss: 5.4490e-08 104/128 [=======================>......] - ETA: 0s - loss: 3.8456e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.2723e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 6.7906e-09 35/128 [=======>......................] - ETA: 0s - loss: 6.4141e-09 69/128 [===============>..............] - ETA: 0s - loss: 8.0028e-09 105/128 [=======================>......] - ETA: 0s - loss: 3.5991e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.0922e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 5.0740e-09 35/128 [=======>......................] - ETA: 0s - loss: 6.2165e-09 70/128 [===============>..............] - ETA: 0s - loss: 7.7573e-09 103/128 [=======================>......] - ETA: 0s - loss: 3.4576e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.9253e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 5.9917e-09 35/128 [=======>......................] - ETA: 0s - loss: 8.3879e-08 62/128 [=============>................] - ETA: 0s - loss: 4.9911e-08 92/128 [====================>.........] - ETA: 0s - loss: 3.5700e-08 127/128 [============================>.] - ETA: 0s - loss: 2.7743e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.7721e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.9673e-09 34/128 [======>.......................] - ETA: 0s - loss: 5.9679e-09 67/128 [==============>...............] - ETA: 0s - loss: 7.0851e-09 101/128 [======================>.......] - ETA: 0s - loss: 6.7143e-09 128/128 [==============================] - 0s 2ms/step - loss: 2.6282e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 6.3262e-09 34/128 [======>.......................] - ETA: 0s - loss: 7.6354e-08 65/128 [==============>...............] - ETA: 0s - loss: 4.4066e-08 97/128 [=====================>........] - ETA: 0s - loss: 3.1431e-08 126/128 [============================>.] - ETA: 0s - loss: 2.5516e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.5346e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 5.9044e-09 40/128 [========>.....................] - ETA: 0s - loss: 7.4350e-09 73/128 [================>.............] - ETA: 0s - loss: 6.6958e-09 109/128 [========================>.....] - ETA: 0s - loss: 2.6579e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.3551e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 8.0922e-09 36/128 [=======>......................] - ETA: 0s - loss: 6.3226e-08 71/128 [===============>..............] - ETA: 0s - loss: 3.4870e-08 111/128 [=========================>....] - ETA: 0s - loss: 2.4781e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.2356e-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 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: 26s - loss: 1.9688e-09 39/128 [========>.....................] - ETA: 0s - loss: 6.3770e-08  79/128 [=================>............] - ETA: 0s - loss: 3.2602e-08 116/128 [==========================>...] - ETA: 0s - loss: 2.2935e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.9117e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.5472e-09 42/128 [========>.....................] - ETA: 0s - loss: 5.0148e-09 81/128 [=================>............] - ETA: 0s - loss: 3.2793e-08 114/128 [=========================>....] - ETA: 0s - loss: 2.3804e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.1476e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 7.1081e-10 33/128 [======>.......................] - ETA: 0s - loss: 7.0442e-08 70/128 [===============>..............] - ETA: 0s - loss: 3.3962e-08 108/128 [========================>.....] - ETA: 0s - loss: 2.2581e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9391e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.0924e-09 39/128 [========>.....................] - ETA: 0s - loss: 3.5623e-09 79/128 [=================>............] - ETA: 0s - loss: 2.7988e-08 116/128 [==========================>...] - ETA: 0s - loss: 1.9595e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.8008e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.6118e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.9853e-09 81/128 [=================>............] - ETA: 0s - loss: 2.6934e-09 121/128 [===========================>..] - ETA: 0s - loss: 2.8983e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.6700e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.0071e-09 41/128 [========>.....................] - ETA: 0s - loss: 3.8639e-09 80/128 [=================>............] - ETA: 0s - loss: 2.2951e-08 119/128 [==========================>...] - ETA: 0s - loss: 1.6496e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.5526e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.3028e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.4254e-09 83/128 [==================>...........] - ETA: 0s - loss: 2.0401e-08 121/128 [===========================>..] - ETA: 0s - loss: 1.5109e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.4441e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 9.5944e-10 40/128 [========>.....................] - ETA: 0s - loss: 3.7943e-08 78/128 [=================>............] - ETA: 0s - loss: 2.0113e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.4579e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3497e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 9.0933e-10 40/128 [========>.....................] - ETA: 0s - loss: 3.5908e-08 78/128 [=================>............] - ETA: 0s - loss: 1.9123e-08 115/128 [=========================>....] - ETA: 0s - loss: 1.3877e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.2658e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.0316e-09 39/128 [========>.....................] - ETA: 0s - loss: 1.3508e-09 77/128 [=================>............] - ETA: 0s - loss: 1.8269e-09 115/128 [=========================>....] - ETA: 0s - loss: 2.2936e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.1830e-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 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: 29s - loss: 2.0272e-09 41/128 [========>.....................] - ETA: 0s - loss: 6.6813e-09  81/128 [=================>............] - ETA: 0s - loss: 6.2990e-09 120/128 [===========================>..] - ETA: 0s - loss: 5.2580e-09 128/128 [==============================] - 0s 1ms/step - loss: 5.1650e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 5.5536e-08 35/128 [=======>......................] - ETA: 0s - loss: 3.3754e-09 43/128 [=========>....................] - ETA: 0s - loss: 3.3282e-09 82/128 [==================>...........] - ETA: 0s - loss: 4.7939e-09 120/128 [===========================>..] - ETA: 0s - loss: 5.1013e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.8990e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.3502e-09 37/128 [=======>......................] - ETA: 0s - loss: 6.0332e-09 68/128 [==============>...............] - ETA: 0s - loss: 5.1598e-09 82/128 [==================>...........] - ETA: 0s - loss: 4.5988e-09 117/128 [==========================>...] - ETA: 0s - loss: 4.9835e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.6913e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.6504e-09 33/128 [======>.......................] - ETA: 0s - loss: 3.1241e-09 65/128 [==============>...............] - ETA: 0s - loss: 4.9068e-09 97/128 [=====================>........] - ETA: 0s - loss: 5.3010e-09 116/128 [==========================>...] - ETA: 0s - loss: 4.7109e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.4682e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.2706e-08 41/128 [========>.....................] - ETA: 0s - loss: 5.2426e-09 80/128 [=================>............] - ETA: 0s - loss: 4.0681e-09 116/128 [==========================>...] - ETA: 0s - loss: 3.3636e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.2428e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.5171e-09 8/128 [>.............................] - ETA: 0s - loss: 1.7550e-08 45/128 [=========>....................] - ETA: 0s - loss: 5.0687e-09 84/128 [==================>...........] - ETA: 0s - loss: 4.8586e-09 123/128 [===========================>..] - ETA: 0s - loss: 4.2066e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.1198e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.4468e-09 36/128 [=======>......................] - ETA: 0s - loss: 4.9166e-09 50/128 [==========>...................] - ETA: 0s - loss: 3.9898e-09 79/128 [=================>............] - ETA: 0s - loss: 3.0531e-09 117/128 [==========================>...] - ETA: 0s - loss: 4.1708e-09 128/128 [==============================] - 0s 2ms/step - loss: 3.9495e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.7132e-09 39/128 [========>.....................] - ETA: 0s - loss: 1.4055e-09 73/128 [================>.............] - ETA: 0s - loss: 3.1229e-09 84/128 [==================>...........] - ETA: 0s - loss: 2.9355e-09 117/128 [==========================>...] - ETA: 0s - loss: 3.5346e-09 128/128 [==============================] - 0s 2ms/step - loss: 3.7712e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.5067e-09 40/128 [========>.....................] - ETA: 0s - loss: 4.4357e-09 76/128 [================>.............] - ETA: 0s - loss: 3.7816e-09 109/128 [========================>.....] - ETA: 0s - loss: 4.0190e-09 116/128 [==========================>...] - ETA: 0s - loss: 3.8699e-09 128/128 [==============================] - 0s 2ms/step - loss: 3.6575e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.6676e-09 35/128 [=======>......................] - ETA: 0s - loss: 4.9647e-09 72/128 [===============>..............] - ETA: 0s - loss: 3.7853e-09 110/128 [========================>.....] - ETA: 0s - loss: 3.9024e-09 128/128 [==============================] - 0s 1ms/step - loss: 3.5344e-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 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: 20s - loss: 2.4167e-09 32/128 [======>.......................] - ETA: 0s - loss: 1.0236e-08  70/128 [===============>..............] - ETA: 0s - loss: 8.6875e-08 111/128 [=========================>....] - ETA: 0s - loss: 5.5482e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.8508e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.7607e-10 38/128 [=======>......................] - ETA: 0s - loss: 3.0634e-09 74/128 [================>.............] - ETA: 0s - loss: 2.1740e-09 114/128 [=========================>....] - ETA: 0s - loss: 2.2888e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.0569e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 3.6180e-10 41/128 [========>.....................] - ETA: 0s - loss: 4.5957e-10 81/128 [=================>............] - ETA: 0s - loss: 8.0289e-10 121/128 [===========================>..] - ETA: 0s - loss: 2.0274e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9317e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 6.8724e-10 39/128 [========>.....................] - ETA: 0s - loss: 5.6894e-10 80/128 [=================>............] - ETA: 0s - loss: 4.4036e-10 119/128 [==========================>...] - ETA: 0s - loss: 1.8603e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.8096e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 6.0842e-10 41/128 [========>.....................] - ETA: 0s - loss: 2.4781e-09 80/128 [=================>............] - ETA: 0s - loss: 1.4572e-09 119/128 [==========================>...] - ETA: 0s - loss: 1.7970e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.7005e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 5.8691e-10 40/128 [========>.....................] - ETA: 0s - loss: 2.3919e-09 78/128 [=================>............] - ETA: 0s - loss: 2.5771e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.7348e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.6001e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.4333e-10 40/128 [========>.....................] - ETA: 0s - loss: 5.8267e-10 78/128 [=================>............] - ETA: 0s - loss: 2.3212e-08 118/128 [==========================>...] - ETA: 0s - loss: 1.5634e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.5073e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.2511e-10 41/128 [========>.....................] - ETA: 0s - loss: 4.1212e-08 79/128 [=================>............] - ETA: 0s - loss: 2.1587e-08 118/128 [==========================>...] - ETA: 0s - loss: 1.5286e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.4213e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 2.8919e-09 39/128 [========>.....................] - ETA: 0s - loss: 4.9267e-10 76/128 [================>.............] - ETA: 0s - loss: 4.1623e-10 116/128 [==========================>...] - ETA: 0s - loss: 1.4655e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3411e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 3.2746e-10 41/128 [========>.....................] - ETA: 0s - loss: 3.6954e-08 81/128 [=================>............] - ETA: 0s - loss: 1.8899e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.3363e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.2629e-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: 317, 1 LR fn, tp: 0, 11 LR f1 score: 0.957 LR cohens kappa score: 0.955 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: 26s - loss: 2.3912e-08 41/128 [========>.....................] - ETA: 0s - loss: 4.0882e-08  82/128 [==================>...........] - ETA: 0s - loss: 3.4385e-08 117/128 [==========================>...] - ETA: 0s - loss: 3.2271e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.2253e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.2151e-08 10/128 [=>............................] - ETA: 0s - loss: 2.5935e-08 46/128 [=========>....................] - ETA: 0s - loss: 2.4528e-08 79/128 [=================>............] - ETA: 0s - loss: 2.4575e-08 112/128 [=========================>....] - ETA: 0s - loss: 2.2727e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.8502e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.7718e-08 32/128 [======>.......................] - ETA: 0s - loss: 3.5164e-08 52/128 [===========>..................] - ETA: 0s - loss: 3.0812e-08 92/128 [====================>.........] - ETA: 0s - loss: 2.6002e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.5555e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.4739e-08 37/128 [=======>......................] - ETA: 0s - loss: 3.0951e-08 73/128 [================>.............] - ETA: 0s - loss: 2.5381e-08 81/128 [=================>............] - ETA: 0s - loss: 2.5321e-08 119/128 [==========================>...] - ETA: 0s - loss: 2.3183e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.2916e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.0934e-08 40/128 [========>.....................] - ETA: 0s - loss: 1.9068e-08 77/128 [=================>............] - ETA: 0s - loss: 2.3155e-08 113/128 [=========================>....] - ETA: 0s - loss: 2.0555e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.0735e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 7.7624e-09 42/128 [========>.....................] - ETA: 0s - loss: 2.7196e-08 79/128 [=================>............] - ETA: 0s - loss: 2.2710e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.9407e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.8917e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.2384e-08 31/128 [======>.......................] - ETA: 0s - loss: 1.3939e-08 46/128 [=========>....................] - ETA: 0s - loss: 1.5506e-08 83/128 [==================>...........] - ETA: 0s - loss: 1.5095e-08 123/128 [===========================>..] - ETA: 0s - loss: 1.7614e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.7381e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.5628e-08 33/128 [======>.......................] - ETA: 0s - loss: 1.7700e-08 66/128 [==============>...............] - ETA: 0s - loss: 1.4693e-08 84/128 [==================>...........] - ETA: 0s - loss: 1.7674e-08 121/128 [===========================>..] - ETA: 0s - loss: 1.6245e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.5936e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 6.4139e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.2083e-08 77/128 [=================>............] - ETA: 0s - loss: 1.3212e-08 108/128 [========================>.....] - ETA: 0s - loss: 1.4860e-08 126/128 [============================>.] - ETA: 0s - loss: 1.4678e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.4683e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 4.2741e-09 38/128 [=======>......................] - ETA: 0s - loss: 9.2634e-09 77/128 [=================>............] - ETA: 0s - loss: 1.0922e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.3629e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3602e-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: 24s - loss: 1.1525e-09 35/128 [=======>......................] - ETA: 0s - loss: 1.1356e-07  74/128 [================>.............] - ETA: 0s - loss: 5.6441e-08 110/128 [========================>.....] - ETA: 0s - loss: 5.2792e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.6143e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.7070e-09 40/128 [========>.....................] - ETA: 0s - loss: 4.2315e-09 81/128 [=================>............] - ETA: 0s - loss: 1.8213e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.3566e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.4753e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 3.1163e-10 40/128 [========>.....................] - ETA: 0s - loss: 3.0848e-08 79/128 [=================>............] - ETA: 0s - loss: 1.7451e-08 118/128 [==========================>...] - ETA: 0s - loss: 1.4199e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3713e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.8974e-08 41/128 [========>.....................] - ETA: 0s - loss: 8.1048e-09 80/128 [=================>............] - ETA: 0s - loss: 5.5136e-09 119/128 [==========================>...] - ETA: 0s - loss: 1.3466e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.2764e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.5507e-07 41/128 [========>.....................] - ETA: 0s - loss: 8.4404e-09 81/128 [=================>............] - ETA: 0s - loss: 1.7295e-08 119/128 [==========================>...] - ETA: 0s - loss: 1.2462e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.1926e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.3967e-09 39/128 [========>.....................] - ETA: 0s - loss: 3.4491e-09 79/128 [=================>............] - ETA: 0s - loss: 3.0751e-09 118/128 [==========================>...] - ETA: 0s - loss: 1.1782e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.1180e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.8707e-09 39/128 [========>.....................] - ETA: 0s - loss: 3.5836e-09 77/128 [=================>............] - ETA: 0s - loss: 1.4576e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.0190e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.0464e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 3.0994e-09 40/128 [========>.....................] - ETA: 0s - loss: 4.7836e-09 78/128 [=================>............] - ETA: 0s - loss: 4.0910e-09 118/128 [==========================>...] - ETA: 0s - loss: 1.0352e-08 128/128 [==============================] - 0s 1ms/step - loss: 9.8331e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.8561e-09 34/128 [======>.......................] - ETA: 0s - loss: 2.3609e-08 67/128 [==============>...............] - ETA: 0s - loss: 1.4628e-08 102/128 [======================>.......] - ETA: 0s - loss: 1.0574e-08 128/128 [==============================] - 0s 1ms/step - loss: 9.2561e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 3.4208e-10 38/128 [=======>......................] - ETA: 0s - loss: 4.7387e-09 76/128 [================>.............] - ETA: 0s - loss: 1.2409e-08 115/128 [=========================>....] - ETA: 0s - loss: 9.2362e-09 128/128 [==============================] - 0s 1ms/step - loss: 8.6910e-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 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: 22s - loss: 1.0749e-09 42/128 [========>.....................] - ETA: 0s - loss: 9.0126e-08  82/128 [==================>...........] - ETA: 0s - loss: 5.9764e-08 122/128 [===========================>..] - ETA: 0s - loss: 4.0464e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.9010e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 5.2735e-10 43/128 [=========>....................] - ETA: 0s - loss: 2.1495e-09 79/128 [=================>............] - ETA: 0s - loss: 1.3447e-09 118/128 [==========================>...] - ETA: 0s - loss: 3.7741e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.5207e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 3.8335e-10 40/128 [========>.....................] - ETA: 0s - loss: 3.8363e-10 81/128 [=================>............] - ETA: 0s - loss: 7.6521e-10 121/128 [===========================>..] - ETA: 0s - loss: 3.4315e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.2727e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.5620e-10 38/128 [=======>......................] - ETA: 0s - loss: 7.6592e-08 81/128 [=================>............] - ETA: 0s - loss: 3.6356e-08 123/128 [===========================>..] - ETA: 0s - loss: 3.1135e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.0136e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 9.3938e-11 36/128 [=======>......................] - ETA: 0s - loss: 5.0963e-10 70/128 [===============>..............] - ETA: 0s - loss: 5.3327e-10 108/128 [========================>.....] - ETA: 0s - loss: 3.2914e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.8111e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 3.6823e-10 38/128 [=======>......................] - ETA: 0s - loss: 3.5316e-10 75/128 [================>.............] - ETA: 0s - loss: 4.3818e-08 111/128 [=========================>....] - ETA: 0s - loss: 2.9831e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.6126e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.8118e-10 38/128 [=======>......................] - ETA: 0s - loss: 8.0421e-08 75/128 [================>.............] - ETA: 0s - loss: 4.0892e-08 113/128 [=========================>....] - ETA: 0s - loss: 2.7398e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.4414e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 2.0439e-10 39/128 [========>.....................] - ETA: 0s - loss: 3.7400e-10 77/128 [=================>............] - ETA: 0s - loss: 3.8815e-10 115/128 [=========================>....] - ETA: 0s - loss: 2.5016e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.2665e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.6168e-10 39/128 [========>.....................] - ETA: 0s - loss: 6.8382e-08 79/128 [=================>............] - ETA: 0s - loss: 3.4044e-08 118/128 [==========================>...] - ETA: 0s - loss: 2.2969e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.1339e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.5727e-10 40/128 [========>.....................] - ETA: 0s - loss: 4.9334e-10 77/128 [=================>............] - ETA: 0s - loss: 3.2313e-08 114/128 [=========================>....] - ETA: 0s - loss: 2.2032e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9793e-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 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: 6.2405e-09 37/128 [=======>......................] - ETA: 0s - loss: 6.7893e-09  73/128 [================>.............] - ETA: 0s - loss: 6.5382e-09 107/128 [========================>.....] - ETA: 0s - loss: 6.8166e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.5393e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 7.9277e-09 37/128 [=======>......................] - ETA: 0s - loss: 6.0411e-09 73/128 [================>.............] - ETA: 0s - loss: 7.1135e-09 110/128 [========================>.....] - ETA: 0s - loss: 6.9054e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.4556e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.0050e-09 38/128 [=======>......................] - ETA: 0s - loss: 6.3639e-09 73/128 [================>.............] - ETA: 0s - loss: 6.7354e-09 108/128 [========================>.....] - ETA: 0s - loss: 1.5287e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3753e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 7.6614e-09 35/128 [=======>......................] - ETA: 0s - loss: 5.3164e-09 70/128 [===============>..............] - ETA: 0s - loss: 1.8810e-08 106/128 [=======================>......] - ETA: 0s - loss: 1.4525e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3052e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 4.8754e-09 36/128 [=======>......................] - ETA: 0s - loss: 5.6527e-09 72/128 [===============>..............] - ETA: 0s - loss: 1.6593e-08 105/128 [=======================>......] - ETA: 0s - loss: 1.3548e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.2379e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 2.4455e-09 32/128 [======>.......................] - ETA: 0s - loss: 5.3517e-09 66/128 [==============>...............] - ETA: 0s - loss: 6.3297e-09 100/128 [======================>.......] - ETA: 0s - loss: 1.3541e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.1744e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 6.0017e-08 35/128 [=======>......................] - ETA: 0s - loss: 6.2925e-09 67/128 [==============>...............] - ETA: 0s - loss: 5.8131e-09 99/128 [======================>.......] - ETA: 0s - loss: 1.2860e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.1150e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 4.6911e-09 37/128 [=======>......................] - ETA: 0s - loss: 6.6613e-09 73/128 [================>.............] - ETA: 0s - loss: 5.8007e-09 103/128 [=======================>......] - ETA: 0s - loss: 5.5177e-09 128/128 [==============================] - 0s 2ms/step - loss: 1.0597e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 4.9829e-09 30/128 [======>.......................] - ETA: 0s - loss: 5.0038e-09 62/128 [=============>................] - ETA: 0s - loss: 1.4775e-08 96/128 [=====================>........] - ETA: 0s - loss: 1.1643e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.0114e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 4.2458e-09 38/128 [=======>......................] - ETA: 0s - loss: 4.6202e-09 72/128 [===============>..............] - ETA: 0s - loss: 5.3731e-09 110/128 [========================>.....] - ETA: 0s - loss: 5.1219e-09 128/128 [==============================] - 0s 1ms/step - loss: 9.6442e-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 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: 24s - loss: 2.2146e-09 32/128 [======>.......................] - ETA: 0s - loss: 2.7236e-09  61/128 [=============>................] - ETA: 0s - loss: 2.3787e-09 80/128 [=================>............] - ETA: 0s - loss: 1.0378e-08 119/128 [==========================>...] - ETA: 0s - loss: 7.7599e-09 128/128 [==============================] - 0s 2ms/step - loss: 7.4151e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.2011e-09 37/128 [=======>......................] - ETA: 0s - loss: 2.1030e-09 72/128 [===============>..............] - ETA: 0s - loss: 1.0826e-08 101/128 [======================>.......] - ETA: 0s - loss: 8.3874e-09 122/128 [===========================>..] - ETA: 0s - loss: 7.2831e-09 128/128 [==============================] - 0s 2ms/step - loss: 7.0571e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.0434e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.9274e-09 78/128 [=================>............] - ETA: 0s - loss: 2.1842e-09 113/128 [=========================>....] - ETA: 0s - loss: 7.2418e-09 128/128 [==============================] - 0s 1ms/step - loss: 6.6504e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.9383e-09 23/128 [====>.........................] - ETA: 0s - loss: 1.7632e-09 52/128 [===========>..................] - ETA: 0s - loss: 1.2158e-08 92/128 [====================>.........] - ETA: 0s - loss: 7.9792e-09 128/128 [==============================] - 0s 2ms/step - loss: 6.3497e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 1.0174e-09 35/128 [=======>......................] - ETA: 0s - loss: 2.5464e-09 60/128 [=============>................] - ETA: 0s - loss: 2.3102e-09 80/128 [=================>............] - ETA: 0s - loss: 2.1445e-09 118/128 [==========================>...] - ETA: 0s - loss: 2.0080e-09 128/128 [==============================] - 0s 2ms/step - loss: 6.0075e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.0773e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.7529e-09 76/128 [================>.............] - ETA: 0s - loss: 1.9757e-09 100/128 [======================>.......] - ETA: 0s - loss: 2.0066e-09 121/128 [===========================>..] - ETA: 0s - loss: 1.9400e-09 128/128 [==============================] - 0s 2ms/step - loss: 5.7120e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.4888e-09 38/128 [=======>......................] - ETA: 0s - loss: 1.8478e-09 78/128 [=================>............] - ETA: 0s - loss: 1.7391e-09 114/128 [=========================>....] - ETA: 0s - loss: 5.6927e-09 128/128 [==============================] - 0s 1ms/step - loss: 5.4331e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.7862e-09 16/128 [==>...........................] - ETA: 0s - loss: 1.6337e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.6453e-09 81/128 [=================>............] - ETA: 0s - loss: 7.1693e-09 118/128 [==========================>...] - ETA: 0s - loss: 5.4145e-09 128/128 [==============================] - 0s 2ms/step - loss: 5.1875e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 2.1708e-09 33/128 [======>.......................] - ETA: 0s - loss: 1.6513e-09 52/128 [===========>..................] - ETA: 0s - loss: 1.6403e-09 84/128 [==================>...........] - ETA: 0s - loss: 6.3849e-09 121/128 [===========================>..] - ETA: 0s - loss: 5.0897e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.9461e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.7869e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.1550e-08 76/128 [================>.............] - ETA: 0s - loss: 6.8436e-09 87/128 [===================>..........] - ETA: 0s - loss: 6.1521e-09 118/128 [==========================>...] - ETA: 0s - loss: 4.9901e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.7580e-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 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: 6.6023e-07 42/128 [========>.....................] - ETA: 0s - loss: 1.8769e-08  83/128 [==================>...........] - ETA: 0s - loss: 1.0990e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.4185e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.3401e-07 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.5864e-09 38/128 [=======>......................] - ETA: 0s - loss: 2.1304e-09 73/128 [================>.............] - ETA: 0s - loss: 1.1033e-08 104/128 [=======================>......] - ETA: 0s - loss: 1.5140e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.2560e-07 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.5106e-10 37/128 [=======>......................] - ETA: 0s - loss: 3.8227e-07 77/128 [=================>............] - ETA: 0s - loss: 1.8608e-07 117/128 [==========================>...] - ETA: 0s - loss: 1.2799e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.1790e-07 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 4.5486e-10 40/128 [========>.....................] - ETA: 0s - loss: 3.3366e-07 79/128 [=================>............] - ETA: 0s - loss: 1.7089e-07 118/128 [==========================>...] - ETA: 0s - loss: 1.1943e-07 128/128 [==============================] - 0s 1ms/step - loss: 1.1095e-07 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 7.5377e-10 39/128 [========>.....................] - ETA: 0s - loss: 1.1220e-09 79/128 [=================>............] - ETA: 0s - loss: 2.3657e-09 118/128 [==========================>...] - ETA: 0s - loss: 6.4478e-09 128/128 [==============================] - 0s 1ms/step - loss: 1.0458e-07 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 4.0737e-10 40/128 [========>.....................] - ETA: 0s - loss: 1.2091e-09 79/128 [=================>............] - ETA: 0s - loss: 1.2586e-09 120/128 [===========================>..] - ETA: 0s - loss: 1.0396e-07 128/128 [==============================] - 0s 1ms/step - loss: 9.8263e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 8.8816e-10 41/128 [========>.....................] - ETA: 0s - loss: 3.0321e-09 82/128 [==================>...........] - ETA: 0s - loss: 1.4298e-07 120/128 [===========================>..] - ETA: 0s - loss: 9.7958e-08 128/128 [==============================] - 0s 1ms/step - loss: 9.2554e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 3.7972e-10 39/128 [========>.....................] - ETA: 0s - loss: 2.8060e-07 76/128 [================>.............] - ETA: 0s - loss: 1.4456e-07 113/128 [=========================>....] - ETA: 0s - loss: 9.7673e-08 128/128 [==============================] - 0s 1ms/step - loss: 8.6929e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 4.8372e-10 39/128 [========>.....................] - ETA: 0s - loss: 9.1010e-10 76/128 [================>.............] - ETA: 0s - loss: 6.3001e-09 114/128 [=========================>....] - ETA: 0s - loss: 9.1222e-08 128/128 [==============================] - 0s 1ms/step - loss: 8.1890e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.6325e-09 39/128 [========>.....................] - ETA: 0s - loss: 2.3785e-07 76/128 [================>.............] - ETA: 0s - loss: 1.2251e-07 115/128 [=========================>....] - ETA: 0s - loss: 8.4302e-08 128/128 [==============================] - 0s 1ms/step - loss: 7.6881e-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 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: 25s - loss: 8.2513e-10 40/128 [========>.....................] - ETA: 0s - loss: 8.0090e-10  80/128 [=================>............] - ETA: 0s - loss: 4.0639e-09 120/128 [===========================>..] - ETA: 0s - loss: 3.0281e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.8642e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 9.1916e-10 40/128 [========>.....................] - ETA: 0s - loss: 6.7019e-09 74/128 [================>.............] - ETA: 0s - loss: 4.5792e-08 107/128 [========================>.....] - ETA: 0s - loss: 3.2067e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.7126e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.8474e-10 39/128 [========>.....................] - ETA: 0s - loss: 1.0155e-09 77/128 [=================>............] - ETA: 0s - loss: 4.1755e-08 113/128 [=========================>....] - ETA: 0s - loss: 2.8753e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.5653e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.9540e-09 41/128 [========>.....................] - ETA: 0s - loss: 6.8469e-08 80/128 [=================>............] - ETA: 0s - loss: 3.5550e-08 117/128 [==========================>...] - ETA: 0s - loss: 2.6273e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.4247e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 7.4777e-10 38/128 [=======>......................] - ETA: 0s - loss: 6.9713e-08 76/128 [================>.............] - ETA: 0s - loss: 3.5370e-08 112/128 [=========================>....] - ETA: 0s - loss: 2.4340e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.2973e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 7.8420e-10 39/128 [========>.....................] - ETA: 0s - loss: 6.4443e-08 77/128 [=================>............] - ETA: 0s - loss: 3.5276e-08 115/128 [=========================>....] - ETA: 0s - loss: 2.3908e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.1796e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 9.1299e-10 39/128 [========>.....................] - ETA: 0s - loss: 9.7136e-10 78/128 [=================>............] - ETA: 0s - loss: 3.2946e-08 117/128 [==========================>...] - ETA: 0s - loss: 2.2294e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.0580e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 5.7377e-10 39/128 [========>.....................] - ETA: 0s - loss: 6.1191e-08 78/128 [=================>............] - ETA: 0s - loss: 3.1164e-08 117/128 [==========================>...] - ETA: 0s - loss: 2.1040e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9436e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.4728e-09 41/128 [========>.....................] - ETA: 0s - loss: 4.7066e-09 78/128 [=================>............] - ETA: 0s - loss: 2.9408e-08 117/128 [==========================>...] - ETA: 0s - loss: 1.9892e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.8367e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 4.8170e-10 40/128 [========>.....................] - ETA: 0s - loss: 4.4129e-09 79/128 [=================>............] - ETA: 0s - loss: 2.7377e-08 118/128 [==========================>...] - ETA: 0s - loss: 1.8618e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.7356e-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 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: 24s - loss: 1.9684e-09 40/128 [========>.....................] - ETA: 0s - loss: 6.7866e-09  79/128 [=================>............] - ETA: 0s - loss: 5.0197e-09 118/128 [==========================>...] - ETA: 0s - loss: 1.0922e-06 128/128 [==============================] - 0s 1ms/step - loss: 1.0140e-06 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 4.4535e-11 41/128 [========>.....................] - ETA: 0s - loss: 1.9345e-06 81/128 [=================>............] - ETA: 0s - loss: 1.0348e-06 121/128 [===========================>..] - ETA: 0s - loss: 6.9284e-07 128/128 [==============================] - 0s 1ms/step - loss: 0.0014 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 2.4033e-11 39/128 [========>.....................] - ETA: 0s - loss: 5.5995e-05 77/128 [=================>............] - ETA: 0s - loss: 2.8374e-05 115/128 [=========================>....] - ETA: 0s - loss: 1.9029e-05 128/128 [==============================] - 0s 1ms/step - loss: 1.7220e-05 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 3.4001e-08 38/128 [=======>......................] - ETA: 0s - loss: 2.7624e-08 76/128 [================>.............] - ETA: 0s - loss: 4.8606e-08 113/128 [=========================>....] - ETA: 0s - loss: 4.7793e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.4516e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 8.1472e-08 38/128 [=======>......................] - ETA: 0s - loss: 5.9169e-08 78/128 [=================>............] - ETA: 0s - loss: 4.9786e-08 117/128 [==========================>...] - ETA: 0s - loss: 4.0160e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.8352e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 6.0201e-07 41/128 [========>.....................] - ETA: 0s - loss: 6.7808e-08 83/128 [==================>...........] - ETA: 0s - loss: 4.2559e-08 116/128 [==========================>...] - ETA: 0s - loss: 3.5599e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.3659e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.9306e-08 38/128 [=======>......................] - ETA: 0s - loss: 6.4255e-08 78/128 [=================>............] - ETA: 0s - loss: 4.0073e-08 118/128 [==========================>...] - ETA: 0s - loss: 3.0652e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.9949e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 9.9104e-09 33/128 [======>.......................] - ETA: 0s - loss: 2.9334e-08 70/128 [===============>..............] - ETA: 0s - loss: 3.9003e-08 108/128 [========================>.....] - ETA: 0s - loss: 3.0272e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.7009e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.1293e-08 39/128 [========>.....................] - ETA: 0s - loss: 4.4278e-08 78/128 [=================>............] - ETA: 0s - loss: 2.8986e-08 117/128 [==========================>...] - ETA: 0s - loss: 2.2896e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.4549e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.0020e-08 40/128 [========>.....................] - ETA: 0s - loss: 5.0640e-08 78/128 [=================>............] - ETA: 0s - loss: 3.0542e-08 117/128 [==========================>...] - ETA: 0s - loss: 2.3711e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.2614e-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 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: 27s - loss: 2.6985e-09 38/128 [=======>......................] - ETA: 0s - loss: 2.0468e-09  77/128 [=================>............] - ETA: 0s - loss: 9.0104e-09 115/128 [=========================>....] - ETA: 0s - loss: 6.6825e-09 128/128 [==============================] - 0s 1ms/step - loss: 7.5153e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.4513e-09 37/128 [=======>......................] - ETA: 0s - loss: 7.6603e-09 53/128 [===========>..................] - ETA: 0s - loss: 5.9136e-09 88/128 [===================>..........] - ETA: 0s - loss: 9.2037e-09 128/128 [==============================] - ETA: 0s - loss: 6.9235e-09 128/128 [==============================] - 0s 2ms/step - loss: 6.9235e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.6895e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.3147e-08 74/128 [================>.............] - ETA: 0s - loss: 9.9660e-09 86/128 [===================>..........] - ETA: 0s - loss: 8.8048e-09 119/128 [==========================>...] - ETA: 0s - loss: 6.8472e-09 128/128 [==============================] - 0s 2ms/step - loss: 6.5132e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.4891e-09 41/128 [========>.....................] - ETA: 0s - loss: 2.6091e-09 78/128 [=================>............] - ETA: 0s - loss: 2.1757e-09 114/128 [=========================>....] - ETA: 0s - loss: 6.6865e-09 121/128 [===========================>..] - ETA: 0s - loss: 6.4046e-09 128/128 [==============================] - 0s 2ms/step - loss: 6.1849e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.2100e-09 34/128 [======>.......................] - ETA: 0s - loss: 1.6802e-09 67/128 [==============>...............] - ETA: 0s - loss: 7.6604e-09 101/128 [======================>.......] - ETA: 0s - loss: 5.6418e-09 128/128 [==============================] - 0s 2ms/step - loss: 5.8427e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.2485e-09 26/128 [=====>........................] - ETA: 0s - loss: 1.5169e-09 42/128 [========>.....................] - ETA: 0s - loss: 2.2549e-09 82/128 [==================>...........] - ETA: 0s - loss: 7.7490e-09 120/128 [===========================>..] - ETA: 0s - loss: 5.7735e-09 128/128 [==============================] - 0s 2ms/step - loss: 5.5368e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.8908e-09 33/128 [======>.......................] - ETA: 0s - loss: 1.7013e-09 57/128 [============>.................] - ETA: 0s - loss: 7.4904e-09 76/128 [================>.............] - ETA: 0s - loss: 5.9465e-09 108/128 [========================>.....] - ETA: 0s - loss: 5.9546e-09 128/128 [==============================] - 0s 2ms/step - loss: 5.2666e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 9.1527e-10 35/128 [=======>......................] - ETA: 0s - loss: 4.5715e-09 68/128 [==============>...............] - ETA: 0s - loss: 7.7797e-09 82/128 [==================>...........] - ETA: 0s - loss: 6.6841e-09 109/128 [========================>.....] - ETA: 0s - loss: 5.6447e-09 128/128 [==============================] - 0s 2ms/step - loss: 5.0153e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 2.3883e-08 41/128 [========>.....................] - ETA: 0s - loss: 4.3958e-09 78/128 [=================>............] - ETA: 0s - loss: 3.0149e-09 115/128 [=========================>....] - ETA: 0s - loss: 2.4633e-09 126/128 [============================>.] - ETA: 0s - loss: 4.7624e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.7338e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.3424e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.2543e-09 79/128 [=================>............] - ETA: 0s - loss: 4.9548e-09 118/128 [==========================>...] - ETA: 0s - loss: 4.7894e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.5236e-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: 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: 20s - loss: 3.7052e-09 43/128 [=========>....................] - ETA: 0s - loss: 1.6002e-08  83/128 [==================>...........] - ETA: 0s - loss: 7.8281e-08 123/128 [===========================>..] - ETA: 0s - loss: 5.4126e-08 128/128 [==============================] - 0s 1ms/step - loss: 5.2497e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 2.4287e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.2718e-07 80/128 [=================>............] - ETA: 0s - loss: 6.5786e-08 121/128 [===========================>..] - ETA: 0s - loss: 4.6345e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.5906e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 5.1237e-09 41/128 [========>.....................] - ETA: 0s - loss: 4.6210e-09 82/128 [==================>...........] - ETA: 0s - loss: 5.8815e-08 123/128 [===========================>..] - ETA: 0s - loss: 4.3178e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.1865e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 2.8002e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.0467e-08 79/128 [=================>............] - ETA: 0s - loss: 5.7756e-08 120/128 [===========================>..] - ETA: 0s - loss: 4.0505e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.8357e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 2.1573e-09 40/128 [========>.....................] - ETA: 0s - loss: 7.6091e-09 80/128 [=================>............] - ETA: 0s - loss: 5.3599e-09 121/128 [===========================>..] - ETA: 0s - loss: 3.7002e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.5402e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 2.8767e-09 42/128 [========>.....................] - ETA: 0s - loss: 8.7533e-08 82/128 [==================>...........] - ETA: 0s - loss: 4.8222e-08 123/128 [===========================>..] - ETA: 0s - loss: 3.3540e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.2533e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 3.9740e-09 41/128 [========>.....................] - ETA: 0s - loss: 6.2005e-09 81/128 [=================>............] - ETA: 0s - loss: 4.3168e-08 121/128 [===========================>..] - ETA: 0s - loss: 3.1429e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.0016e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.4833e-09 41/128 [========>.....................] - ETA: 0s - loss: 2.8528e-09 81/128 [=================>............] - ETA: 0s - loss: 3.9925e-08 121/128 [===========================>..] - ETA: 0s - loss: 2.9001e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.7811e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.2566e-09 41/128 [========>.....................] - ETA: 0s - loss: 7.2684e-08 82/128 [==================>...........] - ETA: 0s - loss: 3.8215e-08 122/128 [===========================>..] - ETA: 0s - loss: 2.6642e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.5734e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.8765e-09 29/128 [=====>........................] - ETA: 0s - loss: 2.3391e-09 60/128 [=============>................] - ETA: 0s - loss: 4.9301e-09 92/128 [====================>.........] - ETA: 0s - loss: 3.2015e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.3836e-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: 317, 1 LR fn, tp: 0, 11 LR f1 score: 0.957 LR cohens kappa score: 0.955 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: 25s - loss: 3.2256e-09 40/128 [========>.....................] - ETA: 0s - loss: 5.2520e-08  77/128 [=================>............] - ETA: 0s - loss: 5.2097e-08 92/128 [====================>.........] - ETA: 0s - loss: 4.3624e-08 125/128 [============================>.] - ETA: 0s - loss: 3.2153e-08 128/128 [==============================] - 0s 2ms/step - loss: 3.1627e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 8.4959e-11 40/128 [========>.....................] - ETA: 0s - loss: 1.6450e-10 79/128 [=================>............] - ETA: 0s - loss: 2.3223e-08 115/128 [=========================>....] - ETA: 0s - loss: 1.6150e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.4631e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 1.7604e-10 28/128 [=====>........................] - ETA: 0s - loss: 6.1635e-08 66/128 [==============>...............] - ETA: 0s - loss: 2.6293e-08 102/128 [======================>.......] - ETA: 0s - loss: 1.7270e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.3995e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.8358e-10 37/128 [=======>......................] - ETA: 0s - loss: 1.5997e-10 46/128 [=========>....................] - ETA: 0s - loss: 1.7687e-10 73/128 [================>.............] - ETA: 0s - loss: 2.2715e-08 104/128 [=======================>......] - ETA: 0s - loss: 1.6166e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.3411e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 6.7461e-10 32/128 [======>.......................] - ETA: 0s - loss: 7.0629e-10 67/128 [==============>...............] - ETA: 0s - loss: 7.1316e-10 73/128 [================>.............] - ETA: 0s - loss: 6.6680e-10 111/128 [=========================>....] - ETA: 0s - loss: 1.4648e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.2813e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 2.0812e-10 41/128 [========>.....................] - ETA: 0s - loss: 1.7930e-10 75/128 [================>.............] - ETA: 0s - loss: 1.7289e-10 104/128 [=======================>......] - ETA: 0s - loss: 1.4782e-08 125/128 [============================>.] - ETA: 0s - loss: 1.2462e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.2265e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 1.5689e-10 39/128 [========>.....................] - ETA: 0s - loss: 6.1048e-10 79/128 [=================>............] - ETA: 0s - loss: 6.0160e-10 116/128 [==========================>...] - ETA: 0s - loss: 1.2792e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.1711e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 1.5624e-10 14/128 [==>...........................] - ETA: 0s - loss: 1.6856e-10 49/128 [==========>...................] - ETA: 0s - loss: 5.1283e-10 90/128 [====================>.........] - ETA: 0s - loss: 1.5518e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.1180e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.4218e-10 36/128 [=======>......................] - ETA: 0s - loss: 3.7138e-08 57/128 [============>.................] - ETA: 0s - loss: 2.3568e-08 87/128 [===================>..........] - ETA: 0s - loss: 1.5499e-08 120/128 [===========================>..] - ETA: 0s - loss: 1.1284e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.0668e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 1.3837e-10 40/128 [========>.....................] - ETA: 0s - loss: 5.4931e-10 70/128 [===============>..............] - ETA: 0s - loss: 1.8094e-08 85/128 [==================>...........] - ETA: 0s - loss: 1.4928e-08 118/128 [==========================>...] - ETA: 0s - loss: 1.0965e-08 128/128 [==============================] - 0s 2ms/step - loss: 1.0196e-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 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: 22s - loss: 8.7472e-10 38/128 [=======>......................] - ETA: 0s - loss: 1.5085e-09  78/128 [=================>............] - ETA: 0s - loss: 5.2083e-08 117/128 [==========================>...] - ETA: 0s - loss: 3.5248e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.2517e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 6.6027e-10 32/128 [======>.......................] - ETA: 0s - loss: 1.1286e-08 65/128 [==============>...............] - ETA: 0s - loss: 5.9416e-09 99/128 [======================>.......] - ETA: 0s - loss: 3.8419e-08 128/128 [==============================] - 0s 2ms/step - loss: 3.0354e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 7.1971e-10 36/128 [=======>......................] - ETA: 0s - loss: 1.6341e-09 71/128 [===============>..............] - ETA: 0s - loss: 5.0009e-08 105/128 [=======================>......] - ETA: 0s - loss: 3.4038e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.8410e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 6.7620e-10 33/128 [======>.......................] - ETA: 0s - loss: 1.4306e-09 65/128 [==============>...............] - ETA: 0s - loss: 4.6319e-08 100/128 [======================>.......] - ETA: 0s - loss: 3.3557e-08 128/128 [==============================] - 0s 2ms/step - loss: 2.6547e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 5.7567e-10 34/128 [======>.......................] - ETA: 0s - loss: 6.3176e-10 64/128 [==============>...............] - ETA: 0s - loss: 9.6434e-10 96/128 [=====================>........] - ETA: 0s - loss: 8.8325e-10 128/128 [==============================] - 0s 2ms/step - loss: 2.4863e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 8.6670e-10 40/128 [========>.....................] - ETA: 0s - loss: 7.2566e-09 76/128 [================>.............] - ETA: 0s - loss: 4.5781e-09 113/128 [=========================>....] - ETA: 0s - loss: 2.5910e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.3240e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 4.6509e-10 40/128 [========>.....................] - ETA: 0s - loss: 6.6740e-08 80/128 [=================>............] - ETA: 0s - loss: 3.3680e-08 119/128 [==========================>...] - ETA: 0s - loss: 2.3155e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.1848e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 8.5699e-10 38/128 [=======>......................] - ETA: 0s - loss: 1.4690e-09 77/128 [=================>............] - ETA: 0s - loss: 1.0383e-09 115/128 [=========================>....] - ETA: 0s - loss: 2.2533e-08 128/128 [==============================] - 0s 1ms/step - loss: 2.0439e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 5.0744e-10 37/128 [=======>......................] - ETA: 0s - loss: 5.8206e-08 74/128 [================>.............] - ETA: 0s - loss: 2.9576e-08 112/128 [=========================>....] - ETA: 0s - loss: 1.9734e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.9132e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 6.6511e-10 38/128 [=======>......................] - ETA: 0s - loss: 1.4476e-09 76/128 [================>.............] - ETA: 0s - loss: 1.1715e-09 113/128 [=========================>....] - ETA: 0s - loss: 2.0167e-08 128/128 [==============================] - 0s 1ms/step - loss: 1.7982e-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 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: 24s - loss: 1.6811e-08 9/128 [=>............................] - ETA: 0s - loss: 1.2239e-08  46/128 [=========>....................] - ETA: 0s - loss: 2.2484e-08 85/128 [==================>...........] - ETA: 0s - loss: 1.8608e-08 125/128 [============================>.] - ETA: 0s - loss: 7.5492e-08 128/128 [==============================] - 0s 2ms/step - loss: 7.4412e-08 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 1.2749e-08 34/128 [======>.......................] - ETA: 0s - loss: 1.1994e-08 50/128 [==========>...................] - ETA: 0s - loss: 1.3740e-08 72/128 [===============>..............] - ETA: 0s - loss: 1.0273e-07 111/128 [=========================>....] - ETA: 0s - loss: 7.1833e-08 128/128 [==============================] - 0s 2ms/step - loss: 6.4281e-08 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 8.6542e-09 39/128 [========>.....................] - ETA: 0s - loss: 1.6442e-07 74/128 [================>.............] - ETA: 0s - loss: 9.1221e-08 88/128 [===================>..........] - ETA: 0s - loss: 7.8976e-08 118/128 [==========================>...] - ETA: 0s - loss: 6.1474e-08 128/128 [==============================] - 0s 2ms/step - loss: 5.7722e-08 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 6.9185e-09 34/128 [======>.......................] - ETA: 0s - loss: 9.0737e-09 65/128 [==============>...............] - ETA: 0s - loss: 1.1234e-08 98/128 [=====================>........] - ETA: 0s - loss: 1.0090e-08 120/128 [===========================>..] - ETA: 0s - loss: 5.4462e-08 128/128 [==============================] - 0s 2ms/step - loss: 5.1741e-08 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 5.3381e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.3016e-07 80/128 [=================>............] - ETA: 0s - loss: 6.9872e-08 118/128 [==========================>...] - ETA: 0s - loss: 4.9730e-08 128/128 [==============================] - 0s 1ms/step - loss: 4.7042e-08 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 4.3778e-09 37/128 [=======>......................] - ETA: 0s - loss: 6.9474e-09 44/128 [=========>....................] - ETA: 0s - loss: 6.9909e-09 81/128 [=================>............] - ETA: 0s - loss: 8.4364e-09 120/128 [===========================>..] - ETA: 0s - loss: 7.9979e-09 128/128 [==============================] - 0s 2ms/step - loss: 4.2992e-08 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 4.3685e-06 39/128 [========>.....................] - ETA: 0s - loss: 1.2019e-07 76/128 [================>.............] - ETA: 0s - loss: 6.4916e-08 83/128 [==================>...........] - ETA: 0s - loss: 5.9902e-08 121/128 [===========================>..] - ETA: 0s - loss: 4.3362e-08 128/128 [==============================] - 0s 2ms/step - loss: 4.1583e-08 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 7.7135e-09 41/128 [========>.....................] - ETA: 0s - loss: 5.8424e-09 78/128 [=================>............] - ETA: 0s - loss: 7.6357e-09 115/128 [=========================>....] - ETA: 0s - loss: 3.9410e-08 128/128 [==============================] - 0s 2ms/step - loss: 3.6109e-08 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 4.8076e-09 41/128 [========>.....................] - ETA: 0s - loss: 9.1001e-08 81/128 [=================>............] - ETA: 0s - loss: 4.8701e-08 120/128 [===========================>..] - ETA: 0s - loss: 3.4990e-08 128/128 [==============================] - 0s 1ms/step - loss: 3.3244e-08 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 4.5266e-09 36/128 [=======>......................] - ETA: 0s - loss: 6.7322e-09 46/128 [=========>....................] - ETA: 0s - loss: 6.2347e-09 83/128 [==================>...........] - ETA: 0s - loss: 6.2177e-09 122/128 [===========================>..] - ETA: 0s - loss: 3.1798e-08 128/128 [==============================] - 0s 2ms/step - loss: 3.0743e-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 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: 21s - loss: 2.1151e-09 39/128 [========>.....................] - ETA: 0s - loss: 4.1698e-09  79/128 [=================>............] - ETA: 0s - loss: 4.7180e-09 114/128 [=========================>....] - ETA: 0s - loss: 9.9158e-09 128/128 [==============================] - 0s 1ms/step - loss: 9.1266e-09 Epoch 2/10 1/128 [..............................] - ETA: 0s - loss: 3.3923e-09 34/128 [======>.......................] - ETA: 0s - loss: 2.1035e-09 73/128 [================>.............] - ETA: 0s - loss: 6.6983e-09 112/128 [=========================>....] - ETA: 0s - loss: 6.0900e-09 128/128 [==============================] - 0s 1ms/step - loss: 8.2835e-09 Epoch 3/10 1/128 [..............................] - ETA: 0s - loss: 4.6258e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.9439e-09 79/128 [=================>............] - ETA: 0s - loss: 3.2851e-09 118/128 [==========================>...] - ETA: 0s - loss: 5.6437e-09 128/128 [==============================] - 0s 1ms/step - loss: 7.6838e-09 Epoch 4/10 1/128 [..............................] - ETA: 0s - loss: 1.5273e-09 40/128 [========>.....................] - ETA: 0s - loss: 1.1110e-08 81/128 [=================>............] - ETA: 0s - loss: 6.3336e-09 119/128 [==========================>...] - ETA: 0s - loss: 5.2021e-09 128/128 [==============================] - 0s 1ms/step - loss: 7.1429e-09 Epoch 5/10 1/128 [..............................] - ETA: 0s - loss: 3.3108e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.7906e-09 82/128 [==================>...........] - ETA: 0s - loss: 8.4982e-09 122/128 [===========================>..] - ETA: 0s - loss: 6.9264e-09 128/128 [==============================] - 0s 1ms/step - loss: 6.6991e-09 Epoch 6/10 1/128 [..............................] - ETA: 0s - loss: 1.8611e-09 42/128 [========>.....................] - ETA: 0s - loss: 1.5751e-09 82/128 [==================>...........] - ETA: 0s - loss: 8.3545e-09 122/128 [===========================>..] - ETA: 0s - loss: 6.5148e-09 128/128 [==============================] - 0s 1ms/step - loss: 6.3116e-09 Epoch 7/10 1/128 [..............................] - ETA: 0s - loss: 6.5404e-10 40/128 [========>.....................] - ETA: 0s - loss: 7.4848e-09 79/128 [=================>............] - ETA: 0s - loss: 5.2597e-09 118/128 [==========================>...] - ETA: 0s - loss: 6.2070e-09 128/128 [==============================] - 0s 1ms/step - loss: 5.8951e-09 Epoch 8/10 1/128 [..............................] - ETA: 0s - loss: 9.2511e-10 40/128 [========>.....................] - ETA: 0s - loss: 3.2079e-09 79/128 [=================>............] - ETA: 0s - loss: 2.3072e-09 118/128 [==========================>...] - ETA: 0s - loss: 5.9298e-09 128/128 [==============================] - 0s 1ms/step - loss: 5.5815e-09 Epoch 9/10 1/128 [..............................] - ETA: 0s - loss: 1.8196e-09 41/128 [========>.....................] - ETA: 0s - loss: 1.1539e-08 81/128 [=================>............] - ETA: 0s - loss: 7.2419e-09 121/128 [===========================>..] - ETA: 0s - loss: 5.3482e-09 128/128 [==============================] - 0s 1ms/step - loss: 5.2690e-09 Epoch 10/10 1/128 [..............................] - ETA: 0s - loss: 7.9201e-10 36/128 [=======>......................] - ETA: 0s - loss: 8.0221e-09 74/128 [================>.............] - ETA: 0s - loss: 7.5332e-09 112/128 [=========================>....] - ETA: 0s - loss: 5.4632e-09 128/128 [==============================] - 0s 1ms/step - loss: 4.9519e-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 ### 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: 317.68, 0.12 LR fn, tp: 0.0, 10.6 LR f1 score: 0.995 LR cohens kappa score: 0.995 LR average precision score: 1.000 minimum: LR tn, fp: 317, 0 LR fn, tp: 0, 9 LR f1 score: 0.957 LR cohens kappa score: 0.955 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