/////////////////////////////////////////// // Running convGAN-majority-full on folding_car_good /////////////////////////////////////////// Load 'data_input/folding_car_good' 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 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0010 46/133 [=========>....................] - ETA: 0s - loss: 0.0121  91/133 [===================>..........] - ETA: 0s - loss: 0.0141 133/133 [==============================] - 0s 1ms/step - loss: 0.0119 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 47/133 [=========>....................] - ETA: 0s - loss: 0.0035 92/133 [===================>..........] - ETA: 0s - loss: 0.0096 133/133 [==============================] - 0s 1ms/step - loss: 0.0114 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0057 47/133 [=========>....................] - ETA: 0s - loss: 0.0167 93/133 [===================>..........] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0116 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0013 47/133 [=========>....................] - ETA: 0s - loss: 0.0136 92/133 [===================>..........] - ETA: 0s - loss: 0.0122 129/133 [============================>.] - ETA: 0s - loss: 0.0113 133/133 [==============================] - 0s 1ms/step - loss: 0.0112 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0022 42/133 [========>.....................] - ETA: 0s - loss: 0.0045 82/133 [=================>............] - ETA: 0s - loss: 0.0108 118/133 [=========================>....] - ETA: 0s - loss: 0.0104 133/133 [==============================] - 0s 1ms/step - loss: 0.0115 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0041 45/133 [=========>....................] - ETA: 0s - loss: 0.0028 87/133 [==================>...........] - ETA: 0s - loss: 0.0084 128/133 [===========================>..] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0104 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0017 43/133 [========>.....................] - ETA: 0s - loss: 0.0090 86/133 [==================>...........] - ETA: 0s - loss: 0.0079 128/133 [===========================>..] - ETA: 0s - loss: 0.0104 133/133 [==============================] - 0s 1ms/step - loss: 0.0103 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0050 43/133 [========>.....................] - ETA: 0s - loss: 0.0066 84/133 [=================>............] - ETA: 0s - loss: 0.0082 126/133 [===========================>..] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0103 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 43/133 [========>.....................] - ETA: 0s - loss: 0.0067 85/133 [==================>...........] - ETA: 0s - loss: 0.0050 127/133 [===========================>..] - ETA: 0s - loss: 0.0086 133/133 [==============================] - 0s 1ms/step - loss: 0.0101 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.2264 42/133 [========>.....................] - ETA: 0s - loss: 0.0084 84/133 [=================>............] - ETA: 0s - loss: 0.0103 126/133 [===========================>..] - ETA: 0s - loss: 0.0105 133/133 [==============================] - 0s 1ms/step - loss: 0.0101 -> test with GAN.predict GAN tn, fp: 330, 2 GAN fn, tp: 2, 12 GAN f1 score: 0.857 GAN cohens kappa score: 0.851 -> test with 'LR' LR tn, fp: 176, 156 LR fn, tp: 5, 9 LR f1 score: 0.101 LR cohens kappa score: 0.028 LR average precision score: 0.065 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 3, 11 RF f1 score: 0.880 RF cohens kappa score: 0.876 -> test with 'GB' GB tn, fp: 327, 5 GB fn, tp: 0, 14 GB f1 score: 0.848 GB cohens kappa score: 0.841 -> test with 'KNN' KNN tn, fp: 299, 33 KNN fn, tp: 0, 14 KNN f1 score: 0.459 KNN cohens kappa score: 0.423 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0162 49/133 [==========>...................] - ETA: 0s - loss: 0.0138  97/133 [====================>.........] - ETA: 0s - loss: 0.0096 133/133 [==============================] - 0s 1ms/step - loss: 0.0120 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 9.0780e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0151  97/133 [====================>.........] - ETA: 0s - loss: 0.0131 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0013 49/133 [==========>...................] - ETA: 0s - loss: 0.0135 97/133 [====================>.........] - ETA: 0s - loss: 0.0119 133/133 [==============================] - 0s 1ms/step - loss: 0.0115 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0037 49/133 [==========>...................] - ETA: 0s - loss: 0.0097 98/133 [=====================>........] - ETA: 0s - loss: 0.0112 133/133 [==============================] - 0s 1ms/step - loss: 0.0117 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0044 50/133 [==========>...................] - ETA: 0s - loss: 0.0038 99/133 [=====================>........] - ETA: 0s - loss: 0.0100 133/133 [==============================] - 0s 1ms/step - loss: 0.0109 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0068 49/133 [==========>...................] - ETA: 0s - loss: 0.0079 95/133 [====================>.........] - ETA: 0s - loss: 0.0128 133/133 [==============================] - 0s 1ms/step - loss: 0.0106 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 49/133 [==========>...................] - ETA: 0s - loss: 0.0118 98/133 [=====================>........] - ETA: 0s - loss: 0.0121 133/133 [==============================] - 0s 1ms/step - loss: 0.0102 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0037 50/133 [==========>...................] - ETA: 0s - loss: 0.0056 97/133 [====================>.........] - ETA: 0s - loss: 0.0117 133/133 [==============================] - 0s 1ms/step - loss: 0.0119 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 45/133 [=========>....................] - ETA: 0s - loss: 0.0068 89/133 [===================>..........] - ETA: 0s - loss: 0.0102 133/133 [==============================] - 0s 1ms/step - loss: 0.0108 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 9.2080e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0125  97/133 [====================>.........] - ETA: 0s - loss: 0.0120 133/133 [==============================] - 0s 1ms/step - loss: 0.0115 -> test with GAN.predict GAN tn, fp: 330, 2 GAN fn, tp: 8, 6 GAN f1 score: 0.545 GAN cohens kappa score: 0.532 -> test with 'LR' LR tn, fp: 191, 141 LR fn, tp: 1, 13 LR f1 score: 0.155 LR cohens kappa score: 0.087 LR average precision score: 0.088 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 6, 8 RF f1 score: 0.727 RF cohens kappa score: 0.719 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 4, 10 GB f1 score: 0.800 GB cohens kappa score: 0.793 -> test with 'KNN' KNN tn, fp: 305, 27 KNN fn, tp: 0, 14 KNN f1 score: 0.509 KNN cohens kappa score: 0.478 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0096 49/133 [==========>...................] - ETA: 0s - loss: 0.0124  98/133 [=====================>........] - ETA: 0s - loss: 0.0128 133/133 [==============================] - 0s 1ms/step - loss: 0.0131 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0056 50/133 [==========>...................] - ETA: 0s - loss: 0.0143 98/133 [=====================>........] - ETA: 0s - loss: 0.0123 133/133 [==============================] - 0s 1ms/step - loss: 0.0120 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.1042 49/133 [==========>...................] - ETA: 0s - loss: 0.0121 97/133 [====================>.........] - ETA: 0s - loss: 0.0110 133/133 [==============================] - 0s 1ms/step - loss: 0.0111 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 8.1660e-04 47/133 [=========>....................] - ETA: 0s - loss: 0.0120  90/133 [===================>..........] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 1ms/step - loss: 0.0113 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0172 49/133 [==========>...................] - ETA: 0s - loss: 0.0173 98/133 [=====================>........] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0110 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0017 49/133 [==========>...................] - ETA: 0s - loss: 0.0082 93/133 [===================>..........] - ETA: 0s - loss: 0.0114 133/133 [==============================] - 0s 1ms/step - loss: 0.0118 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0087 46/133 [=========>....................] - ETA: 0s - loss: 0.0075 95/133 [====================>.........] - ETA: 0s - loss: 0.0102 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 49/133 [==========>...................] - ETA: 0s - loss: 0.0113 98/133 [=====================>........] - ETA: 0s - loss: 0.0095 133/133 [==============================] - 0s 1ms/step - loss: 0.0102 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 49/133 [==========>...................] - ETA: 0s - loss: 0.0040 98/133 [=====================>........] - ETA: 0s - loss: 0.0096 133/133 [==============================] - 0s 1ms/step - loss: 0.0102 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 45/133 [=========>....................] - ETA: 0s - loss: 0.0102 89/133 [===================>..........] - ETA: 0s - loss: 0.0102 133/133 [==============================] - ETA: 0s - loss: 0.0103 133/133 [==============================] - 0s 1ms/step - loss: 0.0103 -> test with GAN.predict GAN tn, fp: 331, 1 GAN fn, tp: 4, 10 GAN f1 score: 0.800 GAN cohens kappa score: 0.793 -> test with 'LR' LR tn, fp: 179, 153 LR fn, tp: 5, 9 LR f1 score: 0.102 LR cohens kappa score: 0.030 LR average precision score: 0.058 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 6, 8 RF f1 score: 0.727 RF cohens kappa score: 0.719 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 4, 10 GB f1 score: 0.800 GB cohens kappa score: 0.793 -> test with 'KNN' KNN tn, fp: 300, 32 KNN fn, tp: 0, 14 KNN f1 score: 0.467 KNN cohens kappa score: 0.431 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0029 49/133 [==========>...................] - ETA: 0s - loss: 0.0023  98/133 [=====================>........] - ETA: 0s - loss: 0.0024 133/133 [==============================] - 0s 1ms/step - loss: 0.0032 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 48/133 [=========>....................] - ETA: 0s - loss: 0.0034 96/133 [====================>.........] - ETA: 0s - loss: 0.0030 133/133 [==============================] - 0s 1ms/step - loss: 0.0027 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 44/133 [========>.....................] - ETA: 0s - loss: 0.0036 86/133 [==================>...........] - ETA: 0s - loss: 0.0033 129/133 [============================>.] - ETA: 0s - loss: 0.0029 133/133 [==============================] - 0s 1ms/step - loss: 0.0028 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 7.9240e-04 47/133 [=========>....................] - ETA: 0s - loss: 0.0016  94/133 [====================>.........] - ETA: 0s - loss: 0.0028 133/133 [==============================] - 0s 1ms/step - loss: 0.0026 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 47/133 [=========>....................] - ETA: 0s - loss: 0.0019 94/133 [====================>.........] - ETA: 0s - loss: 0.0027 133/133 [==============================] - 0s 1ms/step - loss: 0.0023 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 3.4918e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0027  97/133 [====================>.........] - ETA: 0s - loss: 0.0032 133/133 [==============================] - 0s 1ms/step - loss: 0.0028 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 4.8723e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0020  98/133 [=====================>........] - ETA: 0s - loss: 0.0026 133/133 [==============================] - 0s 1ms/step - loss: 0.0023 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 5.1073e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0014  98/133 [=====================>........] - ETA: 0s - loss: 0.0018 133/133 [==============================] - 0s 1ms/step - loss: 0.0019 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 6.5050e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0012  98/133 [=====================>........] - ETA: 0s - loss: 0.0018 133/133 [==============================] - 0s 1ms/step - loss: 0.0019 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 5.5851e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0016  97/133 [====================>.........] - ETA: 0s - loss: 0.0022 133/133 [==============================] - 0s 1ms/step - loss: 0.0021 -> test with GAN.predict GAN tn, fp: 324, 8 GAN fn, tp: 4, 10 GAN f1 score: 0.625 GAN cohens kappa score: 0.607 -> test with 'LR' LR tn, fp: 193, 139 LR fn, tp: 5, 9 LR f1 score: 0.111 LR cohens kappa score: 0.040 LR average precision score: 0.078 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 10, 4 RF f1 score: 0.444 RF cohens kappa score: 0.434 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 3, 11 GB f1 score: 0.880 GB cohens kappa score: 0.876 -> test with 'KNN' KNN tn, fp: 305, 27 KNN fn, tp: 0, 14 KNN f1 score: 0.509 KNN cohens kappa score: 0.478 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0067 49/133 [==========>...................] - ETA: 0s - loss: 0.0107  98/133 [=====================>........] - ETA: 0s - loss: 0.0102 133/133 [==============================] - 0s 1ms/step - loss: 0.0110 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0033 49/133 [==========>...................] - ETA: 0s - loss: 0.0092 98/133 [=====================>........] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0109 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.2185 50/133 [==========>...................] - ETA: 0s - loss: 0.0090 98/133 [=====================>........] - ETA: 0s - loss: 0.0105 133/133 [==============================] - 0s 1ms/step - loss: 0.0109 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0023 50/133 [==========>...................] - ETA: 0s - loss: 0.0078 99/133 [=====================>........] - ETA: 0s - loss: 0.0117 133/133 [==============================] - 0s 1ms/step - loss: 0.0123 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 7.1262e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0166  99/133 [=====================>........] - ETA: 0s - loss: 0.0114 133/133 [==============================] - 0s 1ms/step - loss: 0.0098 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 7.7760e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0107  98/133 [=====================>........] - ETA: 0s - loss: 0.0100 133/133 [==============================] - 0s 1ms/step - loss: 0.0107 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 8.2575e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0141  95/133 [====================>.........] - ETA: 0s - loss: 0.0117 133/133 [==============================] - 0s 1ms/step - loss: 0.0109 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 8.8755e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0119  99/133 [=====================>........] - ETA: 0s - loss: 0.0126 133/133 [==============================] - 0s 1ms/step - loss: 0.0107 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 8.2866e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0089  99/133 [=====================>........] - ETA: 0s - loss: 0.0107 133/133 [==============================] - 0s 1ms/step - loss: 0.0094 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0026 50/133 [==========>...................] - ETA: 0s - loss: 0.0126 98/133 [=====================>........] - ETA: 0s - loss: 0.0104 133/133 [==============================] - 0s 1ms/step - loss: 0.0101 -> test with GAN.predict GAN tn, fp: 328, 3 GAN fn, tp: 5, 8 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 182, 149 LR fn, tp: 4, 9 LR f1 score: 0.105 LR cohens kappa score: 0.038 LR average precision score: 0.055 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 11, 2 RF f1 score: 0.267 RF cohens kappa score: 0.259 -> test with 'GB' GB tn, fp: 328, 3 GB fn, tp: 2, 11 GB f1 score: 0.815 GB cohens kappa score: 0.807 -> test with 'KNN' KNN tn, fp: 309, 22 KNN fn, tp: 0, 13 KNN f1 score: 0.542 KNN cohens kappa score: 0.515 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 22s - loss: 0.0053 49/133 [==========>...................] - ETA: 0s - loss: 0.0160  97/133 [====================>.........] - ETA: 0s - loss: 0.0113 133/133 [==============================] - 0s 1ms/step - loss: 0.0155 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 49/133 [==========>...................] - ETA: 0s - loss: 0.0144 97/133 [====================>.........] - ETA: 0s - loss: 0.0152 133/133 [==============================] - 0s 1ms/step - loss: 0.0150 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0299 46/133 [=========>....................] - ETA: 0s - loss: 0.0107 89/133 [===================>..........] - ETA: 0s - loss: 0.0157 133/133 [==============================] - 0s 1ms/step - loss: 0.0145 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0134 49/133 [==========>...................] - ETA: 0s - loss: 0.0064 97/133 [====================>.........] - ETA: 0s - loss: 0.0137 133/133 [==============================] - 0s 1ms/step - loss: 0.0142 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0042 49/133 [==========>...................] - ETA: 0s - loss: 0.0099 97/133 [====================>.........] - ETA: 0s - loss: 0.0110 133/133 [==============================] - 0s 1ms/step - loss: 0.0139 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0081 49/133 [==========>...................] - ETA: 0s - loss: 0.0058 97/133 [====================>.........] - ETA: 0s - loss: 0.0109 133/133 [==============================] - 0s 1ms/step - loss: 0.0139 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 49/133 [==========>...................] - ETA: 0s - loss: 0.0163 97/133 [====================>.........] - ETA: 0s - loss: 0.0162 133/133 [==============================] - 0s 1ms/step - loss: 0.0138 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 49/133 [==========>...................] - ETA: 0s - loss: 0.0054 97/133 [====================>.........] - ETA: 0s - loss: 0.0078 133/133 [==============================] - 0s 1ms/step - loss: 0.0131 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0044 50/133 [==========>...................] - ETA: 0s - loss: 0.0157 97/133 [====================>.........] - ETA: 0s - loss: 0.0101 133/133 [==============================] - 0s 1ms/step - loss: 0.0127 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0026 49/133 [==========>...................] - ETA: 0s - loss: 0.0143 97/133 [====================>.........] - ETA: 0s - loss: 0.0150 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 -> test with GAN.predict GAN tn, fp: 329, 3 GAN fn, tp: 5, 9 GAN f1 score: 0.692 GAN cohens kappa score: 0.680 -> test with 'LR' LR tn, fp: 167, 165 LR fn, tp: 4, 10 LR f1 score: 0.106 LR cohens kappa score: 0.033 LR average precision score: 0.072 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 5, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 2, 12 GB f1 score: 0.889 GB cohens kappa score: 0.884 -> test with 'KNN' KNN tn, fp: 319, 13 KNN fn, tp: 2, 12 KNN f1 score: 0.615 KNN cohens kappa score: 0.594 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 5.9296e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0136  98/133 [=====================>........] - ETA: 0s - loss: 0.0090 133/133 [==============================] - 0s 1ms/step - loss: 0.0081 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 2.7914e-04 48/133 [=========>....................] - ETA: 0s - loss: 0.0106  96/133 [====================>.........] - ETA: 0s - loss: 0.0079 133/133 [==============================] - 0s 1ms/step - loss: 0.0085 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 49/133 [==========>...................] - ETA: 0s - loss: 0.0122 97/133 [====================>.........] - ETA: 0s - loss: 0.0084 133/133 [==============================] - 0s 1ms/step - loss: 0.0077 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.1681 48/133 [=========>....................] - ETA: 0s - loss: 0.0088 96/133 [====================>.........] - ETA: 0s - loss: 0.0089 133/133 [==============================] - 0s 1ms/step - loss: 0.0079 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0026 49/133 [==========>...................] - ETA: 0s - loss: 0.0140 97/133 [====================>.........] - ETA: 0s - loss: 0.0111 133/133 [==============================] - 0s 1ms/step - loss: 0.0098 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 2.2858e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0052  99/133 [=====================>........] - ETA: 0s - loss: 0.0070 133/133 [==============================] - 0s 1ms/step - loss: 0.0074 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 49/133 [==========>...................] - ETA: 0s - loss: 0.0070 98/133 [=====================>........] - ETA: 0s - loss: 0.0077 133/133 [==============================] - 0s 1ms/step - loss: 0.0067 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0108 50/133 [==========>...................] - ETA: 0s - loss: 0.0065 98/133 [=====================>........] - ETA: 0s - loss: 0.0070 133/133 [==============================] - 0s 1ms/step - loss: 0.0063 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 5.8000e-04 47/133 [=========>....................] - ETA: 0s - loss: 0.0036  93/133 [===================>..........] - ETA: 0s - loss: 0.0057 133/133 [==============================] - 0s 1ms/step - loss: 0.0068 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 3.9625e-04 44/133 [========>.....................] - ETA: 0s - loss: 0.0084  86/133 [==================>...........] - ETA: 0s - loss: 0.0080 128/133 [===========================>..] - ETA: 0s - loss: 0.0063 133/133 [==============================] - 0s 1ms/step - loss: 0.0066 -> test with GAN.predict GAN tn, fp: 324, 8 GAN fn, tp: 2, 12 GAN f1 score: 0.706 GAN cohens kappa score: 0.691 -> test with 'LR' LR tn, fp: 177, 155 LR fn, tp: 4, 10 LR f1 score: 0.112 LR cohens kappa score: 0.040 LR average precision score: 0.074 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 7, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 1, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 309, 23 KNN fn, tp: 0, 14 KNN f1 score: 0.549 KNN cohens kappa score: 0.521 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 22s - loss: 0.0263 46/133 [=========>....................] - ETA: 0s - loss: 0.0165  93/133 [===================>..........] - ETA: 0s - loss: 0.0143 133/133 [==============================] - 0s 1ms/step - loss: 0.0149 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 47/133 [=========>....................] - ETA: 0s - loss: 0.0170 95/133 [====================>.........] - ETA: 0s - loss: 0.0143 133/133 [==============================] - 0s 1ms/step - loss: 0.0125 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0025 49/133 [==========>...................] - ETA: 0s - loss: 0.0084 97/133 [====================>.........] - ETA: 0s - loss: 0.0093 133/133 [==============================] - 0s 1ms/step - loss: 0.0125 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0071 49/133 [==========>...................] - ETA: 0s - loss: 0.0078 97/133 [====================>.........] - ETA: 0s - loss: 0.0097 133/133 [==============================] - 0s 1ms/step - loss: 0.0119 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 50/133 [==========>...................] - ETA: 0s - loss: 0.0056 99/133 [=====================>........] - ETA: 0s - loss: 0.0133 133/133 [==============================] - 0s 1ms/step - loss: 0.0133 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0094 49/133 [==========>...................] - ETA: 0s - loss: 0.0120 97/133 [====================>.........] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 1ms/step - loss: 0.0127 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 50/133 [==========>...................] - ETA: 0s - loss: 0.0055 98/133 [=====================>........] - ETA: 0s - loss: 0.0071 133/133 [==============================] - 0s 1ms/step - loss: 0.0106 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0105 49/133 [==========>...................] - ETA: 0s - loss: 0.0099 97/133 [====================>.........] - ETA: 0s - loss: 0.0096 133/133 [==============================] - 0s 1ms/step - loss: 0.0108 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 48/133 [=========>....................] - ETA: 0s - loss: 0.0132 96/133 [====================>.........] - ETA: 0s - loss: 0.0084 133/133 [==============================] - 0s 1ms/step - loss: 0.0100 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0060 49/133 [==========>...................] - ETA: 0s - loss: 0.0158 97/133 [====================>.........] - ETA: 0s - loss: 0.0118 133/133 [==============================] - 0s 1ms/step - loss: 0.0099 -> test with GAN.predict GAN tn, fp: 328, 4 GAN fn, tp: 3, 11 GAN f1 score: 0.759 GAN cohens kappa score: 0.748 -> test with 'LR' LR tn, fp: 193, 139 LR fn, tp: 5, 9 LR f1 score: 0.111 LR cohens kappa score: 0.040 LR average precision score: 0.072 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 8, 6 RF f1 score: 0.600 RF cohens kappa score: 0.590 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 4, 10 GB f1 score: 0.833 GB cohens kappa score: 0.828 -> test with 'KNN' KNN tn, fp: 312, 20 KNN fn, tp: 1, 13 KNN f1 score: 0.553 KNN cohens kappa score: 0.526 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 22s - loss: 0.0012 47/133 [=========>....................] - ETA: 0s - loss: 0.0033  96/133 [====================>.........] - ETA: 0s - loss: 0.0101 133/133 [==============================] - 0s 1ms/step - loss: 0.0088 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0022 50/133 [==========>...................] - ETA: 0s - loss: 0.0059 98/133 [=====================>........] - ETA: 0s - loss: 0.0073 133/133 [==============================] - 0s 1ms/step - loss: 0.0092 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 8.6886e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0107  98/133 [=====================>........] - ETA: 0s - loss: 0.0069 133/133 [==============================] - 0s 1ms/step - loss: 0.0091 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0086 49/133 [==========>...................] - ETA: 0s - loss: 0.0071 97/133 [====================>.........] - ETA: 0s - loss: 0.0084 133/133 [==============================] - 0s 1ms/step - loss: 0.0085 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0023 49/133 [==========>...................] - ETA: 0s - loss: 0.0080 97/133 [====================>.........] - ETA: 0s - loss: 0.0065 133/133 [==============================] - 0s 1ms/step - loss: 0.0079 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0012 49/133 [==========>...................] - ETA: 0s - loss: 0.0069 97/133 [====================>.........] - ETA: 0s - loss: 0.0058 133/133 [==============================] - 0s 1ms/step - loss: 0.0077 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0060 48/133 [=========>....................] - ETA: 0s - loss: 0.0087 96/133 [====================>.........] - ETA: 0s - loss: 0.0079 133/133 [==============================] - 0s 1ms/step - loss: 0.0073 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0011 49/133 [==========>...................] - ETA: 0s - loss: 0.0041 97/133 [====================>.........] - ETA: 0s - loss: 0.0078 133/133 [==============================] - 0s 1ms/step - loss: 0.0071 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 9.7304e-04 48/133 [=========>....................] - ETA: 0s - loss: 0.0051  96/133 [====================>.........] - ETA: 0s - loss: 0.0098 133/133 [==============================] - 0s 1ms/step - loss: 0.0082 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 49/133 [==========>...................] - ETA: 0s - loss: 0.0062 98/133 [=====================>........] - ETA: 0s - loss: 0.0089 133/133 [==============================] - 0s 1ms/step - loss: 0.0080 -> test with GAN.predict GAN tn, fp: 329, 3 GAN fn, tp: 6, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.627 -> test with 'LR' LR tn, fp: 190, 142 LR fn, tp: 8, 6 LR f1 score: 0.074 LR cohens kappa score: 0.000 LR average precision score: 0.049 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 10, 4 RF f1 score: 0.444 RF cohens kappa score: 0.434 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 2, 12 GB f1 score: 0.857 GB cohens kappa score: 0.851 -> test with 'KNN' KNN tn, fp: 284, 48 KNN fn, tp: 0, 14 KNN f1 score: 0.368 KNN cohens kappa score: 0.324 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 0.0030 48/133 [=========>....................] - ETA: 0s - loss: 0.0246  96/133 [====================>.........] - ETA: 0s - loss: 0.0242 133/133 [==============================] - 0s 1ms/step - loss: 0.0264 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0092 44/133 [========>.....................] - ETA: 0s - loss: 0.0303 89/133 [===================>..........] - ETA: 0s - loss: 0.0240 133/133 [==============================] - 0s 1ms/step - loss: 0.0242 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0210 48/133 [=========>....................] - ETA: 0s - loss: 0.0225 96/133 [====================>.........] - ETA: 0s - loss: 0.0294 133/133 [==============================] - 0s 1ms/step - loss: 0.0247 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0030 49/133 [==========>...................] - ETA: 0s - loss: 0.0170 97/133 [====================>.........] - ETA: 0s - loss: 0.0229 133/133 [==============================] - 0s 1ms/step - loss: 0.0243 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0106 49/133 [==========>...................] - ETA: 0s - loss: 0.0321 97/133 [====================>.........] - ETA: 0s - loss: 0.0256 133/133 [==============================] - 0s 1ms/step - loss: 0.0242 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 8.9354e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0211  97/133 [====================>.........] - ETA: 0s - loss: 0.0237 133/133 [==============================] - 0s 1ms/step - loss: 0.0226 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0033 45/133 [=========>....................] - ETA: 0s - loss: 0.0151 88/133 [==================>...........] - ETA: 0s - loss: 0.0188 132/133 [============================>.] - ETA: 0s - loss: 0.0226 133/133 [==============================] - 0s 1ms/step - loss: 0.0226 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0383 49/133 [==========>...................] - ETA: 0s - loss: 0.0242 97/133 [====================>.........] - ETA: 0s - loss: 0.0181 133/133 [==============================] - 0s 1ms/step - loss: 0.0214 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 48/133 [=========>....................] - ETA: 0s - loss: 0.0105 94/133 [====================>.........] - ETA: 0s - loss: 0.0177 133/133 [==============================] - 0s 1ms/step - loss: 0.0207 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 8.2997e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0189  98/133 [=====================>........] - ETA: 0s - loss: 0.0209 133/133 [==============================] - 0s 1ms/step - loss: 0.0213 -> test with GAN.predict GAN tn, fp: 327, 4 GAN fn, tp: 8, 5 GAN f1 score: 0.455 GAN cohens kappa score: 0.437 -> test with 'LR' LR tn, fp: 191, 140 LR fn, tp: 5, 8 LR f1 score: 0.099 LR cohens kappa score: 0.032 LR average precision score: 0.081 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 6, 7 RF f1 score: 0.700 RF cohens kappa score: 0.692 -> test with 'GB' GB tn, fp: 329, 2 GB fn, tp: 3, 10 GB f1 score: 0.800 GB cohens kappa score: 0.792 -> test with 'KNN' KNN tn, fp: 310, 21 KNN fn, tp: 0, 13 KNN f1 score: 0.553 KNN cohens kappa score: 0.527 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0027 44/133 [========>.....................] - ETA: 0s - loss: 0.0069  86/133 [==================>...........] - ETA: 0s - loss: 0.0116 131/133 [============================>.] - ETA: 0s - loss: 0.0114 133/133 [==============================] - 0s 1ms/step - loss: 0.0113 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0023 49/133 [==========>...................] - ETA: 0s - loss: 0.0041 96/133 [====================>.........] - ETA: 0s - loss: 0.0076 133/133 [==============================] - 0s 1ms/step - loss: 0.0106 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0025 49/133 [==========>...................] - ETA: 0s - loss: 0.0106 97/133 [====================>.........] - ETA: 0s - loss: 0.0087 133/133 [==============================] - 0s 1ms/step - loss: 0.0109 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 49/133 [==========>...................] - ETA: 0s - loss: 0.0100 97/133 [====================>.........] - ETA: 0s - loss: 0.0114 133/133 [==============================] - 0s 1ms/step - loss: 0.0108 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0123 50/133 [==========>...................] - ETA: 0s - loss: 0.0088 98/133 [=====================>........] - ETA: 0s - loss: 0.0123 133/133 [==============================] - 0s 1ms/step - loss: 0.0121 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 50/133 [==========>...................] - ETA: 0s - loss: 0.0096 98/133 [=====================>........] - ETA: 0s - loss: 0.0090 133/133 [==============================] - 0s 1ms/step - loss: 0.0098 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0012 49/133 [==========>...................] - ETA: 0s - loss: 0.0067 97/133 [====================>.........] - ETA: 0s - loss: 0.0098 133/133 [==============================] - 0s 1ms/step - loss: 0.0105 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 49/133 [==========>...................] - ETA: 0s - loss: 0.0045 97/133 [====================>.........] - ETA: 0s - loss: 0.0073 133/133 [==============================] - 0s 1ms/step - loss: 0.0093 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 49/133 [==========>...................] - ETA: 0s - loss: 0.0075 97/133 [====================>.........] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 1ms/step - loss: 0.0097 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 7.8261e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0089  96/133 [====================>.........] - ETA: 0s - loss: 0.0112 133/133 [==============================] - 0s 1ms/step - loss: 0.0089 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 2, 12 GAN f1 score: 0.774 GAN cohens kappa score: 0.764 -> test with 'LR' LR tn, fp: 177, 155 LR fn, tp: 3, 11 LR f1 score: 0.122 LR cohens kappa score: 0.051 LR average precision score: 0.079 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 5, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 3, 11 GB f1 score: 0.880 GB cohens kappa score: 0.876 -> test with 'KNN' KNN tn, fp: 302, 30 KNN fn, tp: 0, 14 KNN f1 score: 0.483 KNN cohens kappa score: 0.449 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0955 48/133 [=========>....................] - ETA: 0s - loss: 0.0369  96/133 [====================>.........] - ETA: 0s - loss: 0.0317 133/133 [==============================] - 0s 1ms/step - loss: 0.0325 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0376 48/133 [=========>....................] - ETA: 0s - loss: 0.0327 96/133 [====================>.........] - ETA: 0s - loss: 0.0293 133/133 [==============================] - 0s 1ms/step - loss: 0.0290 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0111 49/133 [==========>...................] - ETA: 0s - loss: 0.0227 96/133 [====================>.........] - ETA: 0s - loss: 0.0264 133/133 [==============================] - 0s 1ms/step - loss: 0.0294 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0353 49/133 [==========>...................] - ETA: 0s - loss: 0.0322 94/133 [====================>.........] - ETA: 0s - loss: 0.0332 133/133 [==============================] - 0s 1ms/step - loss: 0.0275 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0922 49/133 [==========>...................] - ETA: 0s - loss: 0.0362 95/133 [====================>.........] - ETA: 0s - loss: 0.0272 133/133 [==============================] - 0s 1ms/step - loss: 0.0273 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0083 48/133 [=========>....................] - ETA: 0s - loss: 0.0275 97/133 [====================>.........] - ETA: 0s - loss: 0.0274 133/133 [==============================] - 0s 1ms/step - loss: 0.0248 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0110 49/133 [==========>...................] - ETA: 0s - loss: 0.0266 97/133 [====================>.........] - ETA: 0s - loss: 0.0229 133/133 [==============================] - 0s 1ms/step - loss: 0.0239 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.2153 49/133 [==========>...................] - ETA: 0s - loss: 0.0330 95/133 [====================>.........] - ETA: 0s - loss: 0.0276 133/133 [==============================] - 0s 1ms/step - loss: 0.0238 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0312 49/133 [==========>...................] - ETA: 0s - loss: 0.0237 98/133 [=====================>........] - ETA: 0s - loss: 0.0225 133/133 [==============================] - 0s 1ms/step - loss: 0.0233 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0283 45/133 [=========>....................] - ETA: 0s - loss: 0.0232 88/133 [==================>...........] - ETA: 0s - loss: 0.0230 129/133 [============================>.] - ETA: 0s - loss: 0.0207 133/133 [==============================] - 0s 1ms/step - loss: 0.0212 -> test with GAN.predict GAN tn, fp: 325, 7 GAN fn, tp: 4, 10 GAN f1 score: 0.645 GAN cohens kappa score: 0.629 -> test with 'LR' LR tn, fp: 204, 128 LR fn, tp: 5, 9 LR f1 score: 0.119 LR cohens kappa score: 0.049 LR average precision score: 0.072 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 7, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 1, 13 GB f1 score: 0.897 GB cohens kappa score: 0.892 -> test with 'KNN' KNN tn, fp: 306, 26 KNN fn, tp: 0, 14 KNN f1 score: 0.519 KNN cohens kappa score: 0.488 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 24s - loss: 0.0118 48/133 [=========>....................] - ETA: 0s - loss: 0.0034  97/133 [====================>.........] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0080 47/133 [=========>....................] - ETA: 0s - loss: 0.0082 96/133 [====================>.........] - ETA: 0s - loss: 0.0090 133/133 [==============================] - 0s 1ms/step - loss: 0.0121 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0039 49/133 [==========>...................] - ETA: 0s - loss: 0.0030 96/133 [====================>.........] - ETA: 0s - loss: 0.0096 133/133 [==============================] - 0s 1ms/step - loss: 0.0118 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0020 48/133 [=========>....................] - ETA: 0s - loss: 0.0095 94/133 [====================>.........] - ETA: 0s - loss: 0.0118 133/133 [==============================] - 0s 1ms/step - loss: 0.0116 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 7.8163e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0034  97/133 [====================>.........] - ETA: 0s - loss: 0.0033 133/133 [==============================] - 0s 1ms/step - loss: 0.0114 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0073 47/133 [=========>....................] - ETA: 0s - loss: 0.0089 95/133 [====================>.........] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 1ms/step - loss: 0.0112 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 6.8889e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0088  97/133 [====================>.........] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 1ms/step - loss: 0.0113 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 49/133 [==========>...................] - ETA: 0s - loss: 0.0081 98/133 [=====================>........] - ETA: 0s - loss: 0.0103 133/133 [==============================] - 0s 1ms/step - loss: 0.0108 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0012 49/133 [==========>...................] - ETA: 0s - loss: 0.0122 97/133 [====================>.........] - ETA: 0s - loss: 0.0082 133/133 [==============================] - 0s 1ms/step - loss: 0.0108 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0020 49/133 [==========>...................] - ETA: 0s - loss: 0.0047 98/133 [=====================>........] - ETA: 0s - loss: 0.0086 133/133 [==============================] - 0s 1ms/step - loss: 0.0111 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 7, 7 GAN f1 score: 0.538 GAN cohens kappa score: 0.521 -> test with 'LR' LR tn, fp: 186, 146 LR fn, tp: 6, 8 LR f1 score: 0.095 LR cohens kappa score: 0.023 LR average precision score: 0.058 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 4, 10 RF f1 score: 0.833 RF cohens kappa score: 0.828 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 3, 11 GB f1 score: 0.815 GB cohens kappa score: 0.807 -> test with 'KNN' KNN tn, fp: 313, 19 KNN fn, tp: 2, 12 KNN f1 score: 0.533 KNN cohens kappa score: 0.506 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0085 44/133 [========>.....................] - ETA: 0s - loss: 0.0114  87/133 [==================>...........] - ETA: 0s - loss: 0.0139 127/133 [===========================>..] - ETA: 0s - loss: 0.0127 133/133 [==============================] - 0s 1ms/step - loss: 0.0124 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.2101 49/133 [==========>...................] - ETA: 0s - loss: 0.0095 97/133 [====================>.........] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 1ms/step - loss: 0.0125 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0033 49/133 [==========>...................] - ETA: 0s - loss: 0.0169 97/133 [====================>.........] - ETA: 0s - loss: 0.0135 133/133 [==============================] - 0s 1ms/step - loss: 0.0112 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0029 49/133 [==========>...................] - ETA: 0s - loss: 0.0164 94/133 [====================>.........] - ETA: 0s - loss: 0.0148 133/133 [==============================] - 0s 1ms/step - loss: 0.0116 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 41/133 [========>.....................] - ETA: 0s - loss: 0.0102 89/133 [===================>..........] - ETA: 0s - loss: 0.0091 133/133 [==============================] - 0s 1ms/step - loss: 0.0110 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 50/133 [==========>...................] - ETA: 0s - loss: 0.0123 98/133 [=====================>........] - ETA: 0s - loss: 0.0109 133/133 [==============================] - 0s 1ms/step - loss: 0.0121 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 48/133 [=========>....................] - ETA: 0s - loss: 0.0084 94/133 [====================>.........] - ETA: 0s - loss: 0.0111 133/133 [==============================] - 0s 1ms/step - loss: 0.0099 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 7.0736e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0082  97/133 [====================>.........] - ETA: 0s - loss: 0.0105 133/133 [==============================] - 0s 1ms/step - loss: 0.0099 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 49/133 [==========>...................] - ETA: 0s - loss: 0.0060 97/133 [====================>.........] - ETA: 0s - loss: 0.0047 133/133 [==============================] - 0s 1ms/step - loss: 0.0108 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 5.6829e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0145  97/133 [====================>.........] - ETA: 0s - loss: 0.0178 133/133 [==============================] - 0s 1ms/step - loss: 0.0138 -> test with GAN.predict GAN tn, fp: 326, 6 GAN fn, tp: 1, 13 GAN f1 score: 0.788 GAN cohens kappa score: 0.778 -> test with 'LR' LR tn, fp: 180, 152 LR fn, tp: 2, 12 LR f1 score: 0.135 LR cohens kappa score: 0.065 LR average precision score: 0.084 -> test with 'RF' RF tn, fp: 331, 1 RF fn, tp: 8, 6 RF f1 score: 0.571 RF cohens kappa score: 0.560 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 2, 12 GB f1 score: 0.923 GB cohens kappa score: 0.920 -> test with 'KNN' KNN tn, fp: 304, 28 KNN fn, tp: 0, 14 KNN f1 score: 0.500 KNN cohens kappa score: 0.468 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 24s - loss: 0.0050 46/133 [=========>....................] - ETA: 0s - loss: 0.0233  93/133 [===================>..........] - ETA: 0s - loss: 0.0201 133/133 [==============================] - 0s 1ms/step - loss: 0.0166 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0531 48/133 [=========>....................] - ETA: 0s - loss: 0.0109 96/133 [====================>.........] - ETA: 0s - loss: 0.0156 133/133 [==============================] - 0s 1ms/step - loss: 0.0164 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0017 49/133 [==========>...................] - ETA: 0s - loss: 0.0170 97/133 [====================>.........] - ETA: 0s - loss: 0.0153 133/133 [==============================] - 0s 1ms/step - loss: 0.0160 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0048 50/133 [==========>...................] - ETA: 0s - loss: 0.0125 98/133 [=====================>........] - ETA: 0s - loss: 0.0111 133/133 [==============================] - 0s 1ms/step - loss: 0.0149 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0039 49/133 [==========>...................] - ETA: 0s - loss: 0.0159 98/133 [=====================>........] - ETA: 0s - loss: 0.0138 133/133 [==============================] - 0s 1ms/step - loss: 0.0144 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0013 50/133 [==========>...................] - ETA: 0s - loss: 0.0141 98/133 [=====================>........] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 1ms/step - loss: 0.0142 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0025 50/133 [==========>...................] - ETA: 0s - loss: 0.0089 98/133 [=====================>........] - ETA: 0s - loss: 0.0087 133/133 [==============================] - 0s 1ms/step - loss: 0.0132 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0055 43/133 [========>.....................] - ETA: 0s - loss: 0.0098 86/133 [==================>...........] - ETA: 0s - loss: 0.0146 132/133 [============================>.] - ETA: 0s - loss: 0.0143 133/133 [==============================] - 0s 1ms/step - loss: 0.0142 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0032 44/133 [========>.....................] - ETA: 0s - loss: 0.0115 92/133 [===================>..........] - ETA: 0s - loss: 0.0097 133/133 [==============================] - 0s 1ms/step - loss: 0.0125 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 49/133 [==========>...................] - ETA: 0s - loss: 0.0088 97/133 [====================>.........] - ETA: 0s - loss: 0.0127 133/133 [==============================] - 0s 1ms/step - loss: 0.0141 -> test with GAN.predict GAN tn, fp: 322, 9 GAN fn, tp: 4, 9 GAN f1 score: 0.581 GAN cohens kappa score: 0.561 -> test with 'LR' LR tn, fp: 179, 152 LR fn, tp: 5, 8 LR f1 score: 0.092 LR cohens kappa score: 0.024 LR average precision score: 0.059 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 5, 8 RF f1 score: 0.762 RF cohens kappa score: 0.755 -> test with 'GB' GB tn, fp: 329, 2 GB fn, tp: 1, 12 GB f1 score: 0.889 GB cohens kappa score: 0.884 -> test with 'KNN' KNN tn, fp: 299, 32 KNN fn, tp: 0, 13 KNN f1 score: 0.448 KNN cohens kappa score: 0.414 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0028 48/133 [=========>....................] - ETA: 0s - loss: 0.0194  96/133 [====================>.........] - ETA: 0s - loss: 0.0324 133/133 [==============================] - 0s 1ms/step - loss: 0.0291 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.3525 49/133 [==========>...................] - ETA: 0s - loss: 0.0324 95/133 [====================>.........] - ETA: 0s - loss: 0.0282 133/133 [==============================] - 0s 1ms/step - loss: 0.0293 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0067 49/133 [==========>...................] - ETA: 0s - loss: 0.0373 90/133 [===================>..........] - ETA: 0s - loss: 0.0303 133/133 [==============================] - 0s 1ms/step - loss: 0.0279 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0178 48/133 [=========>....................] - ETA: 0s - loss: 0.0232 96/133 [====================>.........] - ETA: 0s - loss: 0.0263 133/133 [==============================] - 0s 1ms/step - loss: 0.0257 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0166 49/133 [==========>...................] - ETA: 0s - loss: 0.0217 97/133 [====================>.........] - ETA: 0s - loss: 0.0228 133/133 [==============================] - 0s 1ms/step - loss: 0.0249 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0272 44/133 [========>.....................] - ETA: 0s - loss: 0.0256 86/133 [==================>...........] - ETA: 0s - loss: 0.0243 133/133 [==============================] - ETA: 0s - loss: 0.0236 133/133 [==============================] - 0s 1ms/step - loss: 0.0236 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0271 48/133 [=========>....................] - ETA: 0s - loss: 0.0304 95/133 [====================>.........] - ETA: 0s - loss: 0.0201 133/133 [==============================] - 0s 1ms/step - loss: 0.0222 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0027 49/133 [==========>...................] - ETA: 0s - loss: 0.0223 97/133 [====================>.........] - ETA: 0s - loss: 0.0203 133/133 [==============================] - 0s 1ms/step - loss: 0.0217 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0025 50/133 [==========>...................] - ETA: 0s - loss: 0.0240 98/133 [=====================>........] - ETA: 0s - loss: 0.0234 133/133 [==============================] - 0s 1ms/step - loss: 0.0214 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0155 50/133 [==========>...................] - ETA: 0s - loss: 0.0183 98/133 [=====================>........] - ETA: 0s - loss: 0.0197 133/133 [==============================] - 0s 1ms/step - loss: 0.0222 -> test with GAN.predict GAN tn, fp: 329, 3 GAN fn, tp: 5, 9 GAN f1 score: 0.692 GAN cohens kappa score: 0.680 -> test with 'LR' LR tn, fp: 182, 150 LR fn, tp: 4, 10 LR f1 score: 0.115 LR cohens kappa score: 0.044 LR average precision score: 0.070 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 5, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 0, 14 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 316, 16 KNN fn, tp: 0, 14 KNN f1 score: 0.636 KNN cohens kappa score: 0.615 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 21s - loss: 0.0183 46/133 [=========>....................] - ETA: 0s - loss: 0.1486  92/133 [===================>..........] - ETA: 0s - loss: 0.1471 133/133 [==============================] - 0s 1ms/step - loss: 0.1520 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 5.7718e-05 45/133 [=========>....................] - ETA: 0s - loss: 0.1225  89/133 [===================>..........] - ETA: 0s - loss: 0.1135 133/133 [==============================] - ETA: 0s - loss: 0.0929 133/133 [==============================] - 0s 1ms/step - loss: 0.0929 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 9.7626e-04 45/133 [=========>....................] - ETA: 0s - loss: 0.0552  90/133 [===================>..........] - ETA: 0s - loss: 0.0605 133/133 [==============================] - 0s 1ms/step - loss: 0.0705 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.3058 46/133 [=========>....................] - ETA: 0s - loss: 0.0727 87/133 [==================>...........] - ETA: 0s - loss: 0.0642 128/133 [===========================>..] - ETA: 0s - loss: 0.0594 133/133 [==============================] - 0s 1ms/step - loss: 0.0596 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0363 39/133 [=======>......................] - ETA: 0s - loss: 0.0538 77/133 [================>.............] - ETA: 0s - loss: 0.0548 117/133 [=========================>....] - ETA: 0s - loss: 0.0524 133/133 [==============================] - 0s 1ms/step - loss: 0.0515 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0073 43/133 [========>.....................] - ETA: 0s - loss: 0.0569 89/133 [===================>..........] - ETA: 0s - loss: 0.0464 133/133 [==============================] - 0s 1ms/step - loss: 0.0484 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.2694 46/133 [=========>....................] - ETA: 0s - loss: 0.0415 91/133 [===================>..........] - ETA: 0s - loss: 0.0371 133/133 [==============================] - 0s 1ms/step - loss: 0.0447 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0200 45/133 [=========>....................] - ETA: 0s - loss: 0.0362 89/133 [===================>..........] - ETA: 0s - loss: 0.0398 133/133 [==============================] - ETA: 0s - loss: 0.0409 133/133 [==============================] - 0s 1ms/step - loss: 0.0409 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0305 49/133 [==========>...................] - ETA: 0s - loss: 0.0411 98/133 [=====================>........] - ETA: 0s - loss: 0.0383 133/133 [==============================] - 0s 1ms/step - loss: 0.0398 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0425 49/133 [==========>...................] - ETA: 0s - loss: 0.0329 98/133 [=====================>........] - ETA: 0s - loss: 0.0391 133/133 [==============================] - 0s 1ms/step - loss: 0.0372 -> test with GAN.predict GAN tn, fp: 326, 6 GAN fn, tp: 9, 5 GAN f1 score: 0.400 GAN cohens kappa score: 0.378 -> test with 'LR' LR tn, fp: 186, 146 LR fn, tp: 5, 9 LR f1 score: 0.107 LR cohens kappa score: 0.035 LR average precision score: 0.070 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 10, 4 RF f1 score: 0.444 RF cohens kappa score: 0.434 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 2, 12 GB f1 score: 0.923 GB cohens kappa score: 0.920 -> test with 'KNN' KNN tn, fp: 324, 8 KNN fn, tp: 8, 6 KNN f1 score: 0.429 KNN cohens kappa score: 0.404 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 6.6477e-05 44/133 [========>.....................] - ETA: 0s - loss: 0.0657  89/133 [===================>..........] - ETA: 0s - loss: 0.0609 133/133 [==============================] - 0s 1ms/step - loss: 0.0497 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 5.4101e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0290  98/133 [=====================>........] - ETA: 0s - loss: 0.0365 133/133 [==============================] - 0s 1ms/step - loss: 0.0353 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0219 48/133 [=========>....................] - ETA: 0s - loss: 0.0337 97/133 [====================>.........] - ETA: 0s - loss: 0.0378 133/133 [==============================] - 0s 1ms/step - loss: 0.0371 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 5.1801e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0263  99/133 [=====================>........] - ETA: 0s - loss: 0.0308 133/133 [==============================] - 0s 1ms/step - loss: 0.0305 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0348 42/133 [========>.....................] - ETA: 0s - loss: 0.0193 91/133 [===================>..........] - ETA: 0s - loss: 0.0302 133/133 [==============================] - 0s 1ms/step - loss: 0.0275 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 4.6215e-04 50/133 [==========>...................] - ETA: 0s - loss: 0.0259  98/133 [=====================>........] - ETA: 0s - loss: 0.0252 133/133 [==============================] - 0s 1ms/step - loss: 0.0265 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0796 49/133 [==========>...................] - ETA: 0s - loss: 0.0261 97/133 [====================>.........] - ETA: 0s - loss: 0.0268 133/133 [==============================] - 0s 1ms/step - loss: 0.0250 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0056 50/133 [==========>...................] - ETA: 0s - loss: 0.0258 98/133 [=====================>........] - ETA: 0s - loss: 0.0221 133/133 [==============================] - 0s 1ms/step - loss: 0.0244 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0034 50/133 [==========>...................] - ETA: 0s - loss: 0.0183 99/133 [=====================>........] - ETA: 0s - loss: 0.0185 133/133 [==============================] - 0s 1ms/step - loss: 0.0221 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0123 48/133 [=========>....................] - ETA: 0s - loss: 0.0159 89/133 [===================>..........] - ETA: 0s - loss: 0.0210 132/133 [============================>.] - ETA: 0s - loss: 0.0228 133/133 [==============================] - 0s 1ms/step - loss: 0.0227 -> test with GAN.predict GAN tn, fp: 321, 11 GAN fn, tp: 9, 5 GAN f1 score: 0.333 GAN cohens kappa score: 0.303 -> test with 'LR' LR tn, fp: 186, 146 LR fn, tp: 5, 9 LR f1 score: 0.107 LR cohens kappa score: 0.035 LR average precision score: 0.071 -> test with 'RF' RF tn, fp: 331, 1 RF fn, tp: 6, 8 RF f1 score: 0.696 RF cohens kappa score: 0.686 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 2, 12 GB f1 score: 0.857 GB cohens kappa score: 0.851 -> test with 'KNN' KNN tn, fp: 310, 22 KNN fn, tp: 1, 13 KNN f1 score: 0.531 KNN cohens kappa score: 0.502 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 24s - loss: 0.0042 49/133 [==========>...................] - ETA: 0s - loss: 0.0106  98/133 [=====================>........] - ETA: 0s - loss: 0.0177 133/133 [==============================] - 0s 1ms/step - loss: 0.0160 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0038 49/133 [==========>...................] - ETA: 0s - loss: 0.0212 97/133 [====================>.........] - ETA: 0s - loss: 0.0171 133/133 [==============================] - 0s 1ms/step - loss: 0.0168 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0020 49/133 [==========>...................] - ETA: 0s - loss: 0.0087 98/133 [=====================>........] - ETA: 0s - loss: 0.0163 133/133 [==============================] - 0s 1ms/step - loss: 0.0157 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0044 49/133 [==========>...................] - ETA: 0s - loss: 0.0113 97/133 [====================>.........] - ETA: 0s - loss: 0.0144 133/133 [==============================] - 0s 1ms/step - loss: 0.0151 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0099 49/133 [==========>...................] - ETA: 0s - loss: 0.0172 97/133 [====================>.........] - ETA: 0s - loss: 0.0168 133/133 [==============================] - 0s 1ms/step - loss: 0.0156 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 49/133 [==========>...................] - ETA: 0s - loss: 0.0133 97/133 [====================>.........] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 1ms/step - loss: 0.0147 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 50/133 [==========>...................] - ETA: 0s - loss: 0.0100 98/133 [=====================>........] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 1ms/step - loss: 0.0140 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0021 49/133 [==========>...................] - ETA: 0s - loss: 0.0128 96/133 [====================>.........] - ETA: 0s - loss: 0.0125 133/133 [==============================] - 0s 1ms/step - loss: 0.0148 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0029 49/133 [==========>...................] - ETA: 0s - loss: 0.0188 97/133 [====================>.........] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 1ms/step - loss: 0.0141 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 45/133 [=========>....................] - ETA: 0s - loss: 0.0199 88/133 [==================>...........] - ETA: 0s - loss: 0.0147 133/133 [==============================] - ETA: 0s - loss: 0.0135 133/133 [==============================] - 0s 1ms/step - loss: 0.0135 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 3, 11 GAN f1 score: 0.733 GAN cohens kappa score: 0.721 -> test with 'LR' LR tn, fp: 197, 135 LR fn, tp: 6, 8 LR f1 score: 0.102 LR cohens kappa score: 0.030 LR average precision score: 0.057 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 5, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 1, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 314, 18 KNN fn, tp: 1, 13 KNN f1 score: 0.578 KNN cohens kappa score: 0.553 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 0.0093 48/133 [=========>....................] - ETA: 0s - loss: 0.0099  96/133 [====================>.........] - ETA: 0s - loss: 0.0174 133/133 [==============================] - 0s 1ms/step - loss: 0.0154 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0037 49/133 [==========>...................] - ETA: 0s - loss: 0.0150 97/133 [====================>.........] - ETA: 0s - loss: 0.0140 133/133 [==============================] - 0s 1ms/step - loss: 0.0148 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0071 47/133 [=========>....................] - ETA: 0s - loss: 0.0131 95/133 [====================>.........] - ETA: 0s - loss: 0.0106 133/133 [==============================] - 0s 1ms/step - loss: 0.0133 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0010 43/133 [========>.....................] - ETA: 0s - loss: 0.0061 85/133 [==================>...........] - ETA: 0s - loss: 0.0108 127/133 [===========================>..] - ETA: 0s - loss: 0.0144 133/133 [==============================] - 0s 1ms/step - loss: 0.0141 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0042 49/133 [==========>...................] - ETA: 0s - loss: 0.0140 97/133 [====================>.........] - ETA: 0s - loss: 0.0152 133/133 [==============================] - 0s 1ms/step - loss: 0.0153 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0034 49/133 [==========>...................] - ETA: 0s - loss: 0.0062 96/133 [====================>.........] - ETA: 0s - loss: 0.0143 133/133 [==============================] - 0s 1ms/step - loss: 0.0127 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 9.6259e-04 48/133 [=========>....................] - ETA: 0s - loss: 0.0150  96/133 [====================>.........] - ETA: 0s - loss: 0.0157 133/133 [==============================] - 0s 1ms/step - loss: 0.0133 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 49/133 [==========>...................] - ETA: 0s - loss: 0.0155 97/133 [====================>.........] - ETA: 0s - loss: 0.0126 133/133 [==============================] - 0s 1ms/step - loss: 0.0132 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0041 43/133 [========>.....................] - ETA: 0s - loss: 0.0130 86/133 [==================>...........] - ETA: 0s - loss: 0.0118 127/133 [===========================>..] - ETA: 0s - loss: 0.0123 133/133 [==============================] - 0s 1ms/step - loss: 0.0123 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 3.6501e-04 48/133 [=========>....................] - ETA: 0s - loss: 0.0116  96/133 [====================>.........] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 1ms/step - loss: 0.0109 -> test with GAN.predict GAN tn, fp: 328, 3 GAN fn, tp: 5, 8 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 181, 150 LR fn, tp: 1, 12 LR f1 score: 0.137 LR cohens kappa score: 0.072 LR average precision score: 0.076 -> test with 'RF' RF tn, fp: 330, 1 RF fn, tp: 6, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 327, 4 GB fn, tp: 5, 8 GB f1 score: 0.640 GB cohens kappa score: 0.626 -> test with 'KNN' KNN tn, fp: 302, 29 KNN fn, tp: 0, 13 KNN f1 score: 0.473 KNN cohens kappa score: 0.440 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 0.0031 49/133 [==========>...................] - ETA: 0s - loss: 0.0090  97/133 [====================>.........] - ETA: 0s - loss: 0.0093 133/133 [==============================] - 0s 1ms/step - loss: 0.0098 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 49/133 [==========>...................] - ETA: 0s - loss: 0.0092 97/133 [====================>.........] - ETA: 0s - loss: 0.0112 133/133 [==============================] - 0s 1ms/step - loss: 0.0096 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0029 49/133 [==========>...................] - ETA: 0s - loss: 0.0091 97/133 [====================>.........] - ETA: 0s - loss: 0.0083 133/133 [==============================] - 0s 1ms/step - loss: 0.0088 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0080 48/133 [=========>....................] - ETA: 0s - loss: 0.0030 96/133 [====================>.........] - ETA: 0s - loss: 0.0090 133/133 [==============================] - 0s 1ms/step - loss: 0.0093 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 7.8210e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0040  98/133 [=====================>........] - ETA: 0s - loss: 0.0059 133/133 [==============================] - 0s 1ms/step - loss: 0.0089 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0033 49/133 [==========>...................] - ETA: 0s - loss: 0.0114 97/133 [====================>.........] - ETA: 0s - loss: 0.0102 133/133 [==============================] - 0s 1ms/step - loss: 0.0092 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0059 48/133 [=========>....................] - ETA: 0s - loss: 0.0115 95/133 [====================>.........] - ETA: 0s - loss: 0.0098 133/133 [==============================] - 0s 1ms/step - loss: 0.0082 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0053 46/133 [=========>....................] - ETA: 0s - loss: 0.0115 92/133 [===================>..........] - ETA: 0s - loss: 0.0076 133/133 [==============================] - 0s 1ms/step - loss: 0.0081 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0026 48/133 [=========>....................] - ETA: 0s - loss: 0.0072 96/133 [====================>.........] - ETA: 0s - loss: 0.0094 133/133 [==============================] - 0s 1ms/step - loss: 0.0084 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 9.4942e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0117  97/133 [====================>.........] - ETA: 0s - loss: 0.0095 133/133 [==============================] - 0s 1ms/step - loss: 0.0080 -> test with GAN.predict GAN tn, fp: 326, 6 GAN fn, tp: 3, 11 GAN f1 score: 0.710 GAN cohens kappa score: 0.696 -> test with 'LR' LR tn, fp: 181, 151 LR fn, tp: 8, 6 LR f1 score: 0.070 LR cohens kappa score: -0.004 LR average precision score: 0.055 -> test with 'RF' RF tn, fp: 331, 1 RF fn, tp: 8, 6 RF f1 score: 0.571 RF cohens kappa score: 0.560 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 1, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 304, 28 KNN fn, tp: 1, 13 KNN f1 score: 0.473 KNN cohens kappa score: 0.439 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 0.0014 37/133 [=======>......................] - ETA: 0s - loss: 0.0179  76/133 [================>.............] - ETA: 0s - loss: 0.0204 115/133 [========================>.....] - ETA: 0s - loss: 0.0156 133/133 [==============================] - 0s 1ms/step - loss: 0.0140 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0022 46/133 [=========>....................] - ETA: 0s - loss: 0.0158 90/133 [===================>..........] - ETA: 0s - loss: 0.0110 131/133 [============================>.] - ETA: 0s - loss: 0.0128 133/133 [==============================] - 0s 1ms/step - loss: 0.0127 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 45/133 [=========>....................] - ETA: 0s - loss: 0.0060 89/133 [===================>..........] - ETA: 0s - loss: 0.0149 131/133 [============================>.] - ETA: 0s - loss: 0.0152 133/133 [==============================] - 0s 1ms/step - loss: 0.0150 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.1522 38/133 [=======>......................] - ETA: 0s - loss: 0.0205 80/133 [=================>............] - ETA: 0s - loss: 0.0121 120/133 [==========================>...] - ETA: 0s - loss: 0.0122 133/133 [==============================] - 0s 1ms/step - loss: 0.0139 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 42/133 [========>.....................] - ETA: 0s - loss: 0.0108 83/133 [=================>............] - ETA: 0s - loss: 0.0134 121/133 [==========================>...] - ETA: 0s - loss: 0.0131 133/133 [==============================] - 0s 1ms/step - loss: 0.0123 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 5.3791e-04 41/133 [========>.....................] - ETA: 0s - loss: 0.0078  82/133 [=================>............] - ETA: 0s - loss: 0.0126 123/133 [==========================>...] - ETA: 0s - loss: 0.0123 133/133 [==============================] - 0s 1ms/step - loss: 0.0116 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0052 42/133 [========>.....................] - ETA: 0s - loss: 0.0115 83/133 [=================>............] - ETA: 0s - loss: 0.0129 123/133 [==========================>...] - ETA: 0s - loss: 0.0124 133/133 [==============================] - 0s 1ms/step - loss: 0.0120 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0393 41/133 [========>.....................] - ETA: 0s - loss: 0.0146 82/133 [=================>............] - ETA: 0s - loss: 0.0111 124/133 [==========================>...] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 1ms/step - loss: 0.0111 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 9.5381e-04 45/133 [=========>....................] - ETA: 0s - loss: 0.0178  88/133 [==================>...........] - ETA: 0s - loss: 0.0124 131/133 [============================>.] - ETA: 0s - loss: 0.0113 133/133 [==============================] - 0s 1ms/step - loss: 0.0112 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 7.7483e-04 45/133 [=========>....................] - ETA: 0s - loss: 0.0033  86/133 [==================>...........] - ETA: 0s - loss: 0.0060 131/133 [============================>.] - ETA: 0s - loss: 0.0118 133/133 [==============================] - 0s 1ms/step - loss: 0.0117 -> test with GAN.predict GAN tn, fp: 331, 1 GAN fn, tp: 4, 10 GAN f1 score: 0.800 GAN cohens kappa score: 0.793 -> test with 'LR' LR tn, fp: 195, 137 LR fn, tp: 6, 8 LR f1 score: 0.101 LR cohens kappa score: 0.029 LR average precision score: 0.081 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 6, 8 RF f1 score: 0.727 RF cohens kappa score: 0.719 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 2, 12 GB f1 score: 0.889 GB cohens kappa score: 0.884 -> test with 'KNN' KNN tn, fp: 307, 25 KNN fn, tp: 0, 14 KNN f1 score: 0.528 KNN cohens kappa score: 0.498 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0083 49/133 [==========>...................] - ETA: 0s - loss: 0.0154  98/133 [=====================>........] - ETA: 0s - loss: 0.0104 133/133 [==============================] - 0s 1ms/step - loss: 0.0101 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 6.8624e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0042  97/133 [====================>.........] - ETA: 0s - loss: 0.0076 133/133 [==============================] - 0s 1ms/step - loss: 0.0079 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0059 49/133 [==========>...................] - ETA: 0s - loss: 0.0114 97/133 [====================>.........] - ETA: 0s - loss: 0.0077 133/133 [==============================] - 0s 1ms/step - loss: 0.0074 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 49/133 [==========>...................] - ETA: 0s - loss: 0.0110 98/133 [=====================>........] - ETA: 0s - loss: 0.0071 133/133 [==============================] - 0s 1ms/step - loss: 0.0067 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 5.7823e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0045  97/133 [====================>.........] - ETA: 0s - loss: 0.0053 133/133 [==============================] - 0s 1ms/step - loss: 0.0064 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0068 47/133 [=========>....................] - ETA: 0s - loss: 0.0045 95/133 [====================>.........] - ETA: 0s - loss: 0.0029 133/133 [==============================] - 0s 1ms/step - loss: 0.0066 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 9.8956e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0084  97/133 [====================>.........] - ETA: 0s - loss: 0.0073 133/133 [==============================] - 0s 1ms/step - loss: 0.0062 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 7.7861e-04 47/133 [=========>....................] - ETA: 0s - loss: 0.0083  95/133 [====================>.........] - ETA: 0s - loss: 0.0072 133/133 [==============================] - 0s 1ms/step - loss: 0.0059 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 7.5626e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0059  97/133 [====================>.........] - ETA: 0s - loss: 0.0069 133/133 [==============================] - 0s 1ms/step - loss: 0.0066 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0047 43/133 [========>.....................] - ETA: 0s - loss: 0.0065 89/133 [===================>..........] - ETA: 0s - loss: 0.0070 133/133 [==============================] - 0s 1ms/step - loss: 0.0056 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 4, 10 GAN f1 score: 0.690 GAN cohens kappa score: 0.676 -> test with 'LR' LR tn, fp: 167, 165 LR fn, tp: 4, 10 LR f1 score: 0.106 LR cohens kappa score: 0.033 LR average precision score: 0.088 -> test with 'RF' RF tn, fp: 330, 2 RF fn, tp: 5, 9 RF f1 score: 0.720 RF cohens kappa score: 0.710 -> test with 'GB' GB tn, fp: 327, 5 GB fn, tp: 1, 13 GB f1 score: 0.813 GB cohens kappa score: 0.804 -> test with 'KNN' KNN tn, fp: 295, 37 KNN fn, tp: 0, 14 KNN f1 score: 0.431 KNN cohens kappa score: 0.392 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 21s - loss: 0.0016 49/133 [==========>...................] - ETA: 0s - loss: 0.0145  98/133 [=====================>........] - ETA: 0s - loss: 0.0131 133/133 [==============================] - 0s 1ms/step - loss: 0.0105 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0053 49/133 [==========>...................] - ETA: 0s - loss: 0.0106 97/133 [====================>.........] - ETA: 0s - loss: 0.0101 133/133 [==============================] - 0s 1ms/step - loss: 0.0112 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 48/133 [=========>....................] - ETA: 0s - loss: 0.0185 95/133 [====================>.........] - ETA: 0s - loss: 0.0121 133/133 [==============================] - 0s 1ms/step - loss: 0.0101 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0027 49/133 [==========>...................] - ETA: 0s - loss: 0.0050 97/133 [====================>.........] - ETA: 0s - loss: 0.0074 133/133 [==============================] - 0s 1ms/step - loss: 0.0092 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 8.1600e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0089  97/133 [====================>.........] - ETA: 0s - loss: 0.0063 133/133 [==============================] - 0s 1ms/step - loss: 0.0089 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0043 50/133 [==========>...................] - ETA: 0s - loss: 0.0055 98/133 [=====================>........] - ETA: 0s - loss: 0.0104 133/133 [==============================] - 0s 1ms/step - loss: 0.0088 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0296 49/133 [==========>...................] - ETA: 0s - loss: 0.0048 97/133 [====================>.........] - ETA: 0s - loss: 0.0108 133/133 [==============================] - 0s 1ms/step - loss: 0.0086 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0085 50/133 [==========>...................] - ETA: 0s - loss: 0.0042 98/133 [=====================>........] - ETA: 0s - loss: 0.0080 133/133 [==============================] - 0s 1ms/step - loss: 0.0096 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0013 48/133 [=========>....................] - ETA: 0s - loss: 0.0049 91/133 [===================>..........] - ETA: 0s - loss: 0.0045 133/133 [==============================] - 0s 1ms/step - loss: 0.0088 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.2356 44/133 [========>.....................] - ETA: 0s - loss: 0.0082 86/133 [==================>...........] - ETA: 0s - loss: 0.0106 132/133 [============================>.] - ETA: 0s - loss: 0.0088 133/133 [==============================] - 0s 1ms/step - loss: 0.0087 -> test with GAN.predict GAN tn, fp: 330, 2 GAN fn, tp: 6, 8 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 180, 152 LR fn, tp: 4, 10 LR f1 score: 0.114 LR cohens kappa score: 0.042 LR average precision score: 0.081 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 9, 5 RF f1 score: 0.526 RF cohens kappa score: 0.516 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 4, 10 GB f1 score: 0.800 GB cohens kappa score: 0.793 -> test with 'KNN' KNN tn, fp: 309, 23 KNN fn, tp: 0, 14 KNN f1 score: 0.549 KNN cohens kappa score: 0.521 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 22s - loss: 0.0024 49/133 [==========>...................] - ETA: 0s - loss: 0.0044  97/133 [====================>.........] - ETA: 0s - loss: 0.0079 133/133 [==============================] - 0s 1ms/step - loss: 0.0080 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0192 49/133 [==========>...................] - ETA: 0s - loss: 0.0054 97/133 [====================>.........] - ETA: 0s - loss: 0.0077 133/133 [==============================] - 0s 1ms/step - loss: 0.0072 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0061 48/133 [=========>....................] - ETA: 0s - loss: 0.0105 96/133 [====================>.........] - ETA: 0s - loss: 0.0072 133/133 [==============================] - 0s 1ms/step - loss: 0.0072 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 42/133 [========>.....................] - ETA: 0s - loss: 0.0059 85/133 [==================>...........] - ETA: 0s - loss: 0.0086 133/133 [==============================] - ETA: 0s - loss: 0.0073 133/133 [==============================] - 0s 1ms/step - loss: 0.0073 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0072 48/133 [=========>....................] - ETA: 0s - loss: 0.0060 96/133 [====================>.........] - ETA: 0s - loss: 0.0049 133/133 [==============================] - 0s 1ms/step - loss: 0.0069 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0012 50/133 [==========>...................] - ETA: 0s - loss: 0.0095 98/133 [=====================>........] - ETA: 0s - loss: 0.0066 133/133 [==============================] - 0s 1ms/step - loss: 0.0066 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0044 49/133 [==========>...................] - ETA: 0s - loss: 0.0096 97/133 [====================>.........] - ETA: 0s - loss: 0.0068 133/133 [==============================] - 0s 1ms/step - loss: 0.0065 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0011 48/133 [=========>....................] - ETA: 0s - loss: 0.0028 92/133 [===================>..........] - ETA: 0s - loss: 0.0077 133/133 [==============================] - 0s 1ms/step - loss: 0.0068 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 48/133 [=========>....................] - ETA: 0s - loss: 0.0091 96/133 [====================>.........] - ETA: 0s - loss: 0.0063 133/133 [==============================] - 0s 1ms/step - loss: 0.0057 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0015 50/133 [==========>...................] - ETA: 0s - loss: 0.0030 98/133 [=====================>........] - ETA: 0s - loss: 0.0065 133/133 [==============================] - 0s 1ms/step - loss: 0.0066 -> test with GAN.predict GAN tn, fp: 321, 10 GAN fn, tp: 0, 13 GAN f1 score: 0.722 GAN cohens kappa score: 0.708 -> test with 'LR' LR tn, fp: 188, 143 LR fn, tp: 3, 10 LR f1 score: 0.120 LR cohens kappa score: 0.055 LR average precision score: 0.067 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 6, 7 RF f1 score: 0.700 RF cohens kappa score: 0.692 -> test with 'GB' GB tn, fp: 330, 1 GB fn, tp: 0, 13 GB f1 score: 0.963 GB cohens kappa score: 0.961 -> test with 'KNN' KNN tn, fp: 305, 26 KNN fn, tp: 0, 13 KNN f1 score: 0.500 KNN cohens kappa score: 0.470 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 204, 165 LR fn, tp: 8, 13 LR f1 score: 0.155 LR cohens kappa score: 0.087 LR average precision score: 0.088 average: LR tn, fp: 184.32, 147.48 LR fn, tp: 4.52, 9.28 LR f1 score: 0.109 LR cohens kappa score: 0.038 LR average precision score: 0.070 minimum: LR tn, fp: 167, 128 LR fn, tp: 1, 6 LR f1 score: 0.070 LR cohens kappa score: -0.004 LR average precision score: 0.049 -----[ RF ]----- maximum: RF tn, fp: 332, 2 RF fn, tp: 11, 11 RF f1 score: 0.880 RF cohens kappa score: 0.876 average: RF tn, fp: 331.56, 0.24 RF fn, tp: 6.68, 7.12 RF f1 score: 0.659 RF cohens kappa score: 0.650 minimum: RF tn, fp: 330, 0 RF fn, tp: 3, 2 RF f1 score: 0.267 RF cohens kappa score: 0.259 -----[ GB ]----- maximum: GB tn, fp: 332, 5 GB fn, tp: 5, 14 GB f1 score: 1.000 GB cohens kappa score: 1.000 average: GB tn, fp: 330.28, 1.52 GB fn, tp: 2.12, 11.68 GB f1 score: 0.864 GB cohens kappa score: 0.858 minimum: GB tn, fp: 327, 0 GB fn, tp: 0, 8 GB f1 score: 0.640 GB cohens kappa score: 0.626 -----[ KNN ]----- maximum: KNN tn, fp: 324, 48 KNN fn, tp: 8, 14 KNN f1 score: 0.636 KNN cohens kappa score: 0.615 average: KNN tn, fp: 306.48, 25.32 KNN fn, tp: 0.64, 13.16 KNN f1 score: 0.509 KNN cohens kappa score: 0.479 minimum: KNN tn, fp: 284, 8 KNN fn, tp: 0, 6 KNN f1 score: 0.368 KNN cohens kappa score: 0.324 -----[ GAN ]----- maximum: GAN tn, fp: 331, 11 GAN fn, tp: 9, 13 GAN f1 score: 0.857 GAN cohens kappa score: 0.851 average: GAN tn, fp: 326.92, 4.88 GAN fn, tp: 4.52, 9.28 GAN f1 score: 0.659 GAN cohens kappa score: 0.646 minimum: GAN tn, fp: 321, 1 GAN fn, tp: 0, 5 GAN f1 score: 0.333 GAN cohens kappa score: 0.303