/////////////////////////////////////////// // Running convGAN-proximary-5 on folding_car-vgood /////////////////////////////////////////// Load 'data_input/folding_car-vgood' 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 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 15s - loss: 0.1343 51/133 [==========>...................] - ETA: 0s - loss: 0.0347  101/133 [=====================>........] - ETA: 0s - loss: 0.0246 133/133 [==============================] - 0s 1ms/step - loss: 0.0278 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0110 52/133 [==========>...................] - ETA: 0s - loss: 0.0265 103/133 [======================>.......] - ETA: 0s - loss: 0.0236 133/133 [==============================] - 0s 989us/step - loss: 0.0236 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0070 52/133 [==========>...................] - ETA: 0s - loss: 0.0228 101/133 [=====================>........] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 1ms/step - loss: 0.0226 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0210 46/133 [=========>....................] - ETA: 0s - loss: 0.0219 95/133 [====================>.........] - ETA: 0s - loss: 0.0239 133/133 [==============================] - 0s 1ms/step - loss: 0.0194 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0278 53/133 [==========>...................] - ETA: 0s - loss: 0.0190 101/133 [=====================>........] - ETA: 0s - loss: 0.0203 133/133 [==============================] - 0s 1ms/step - loss: 0.0206 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0136 50/133 [==========>...................] - ETA: 0s - loss: 0.0148 100/133 [=====================>........] - ETA: 0s - loss: 0.0171 133/133 [==============================] - 0s 1ms/step - loss: 0.0176 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0025 52/133 [==========>...................] - ETA: 0s - loss: 0.0174 104/133 [======================>.......] - ETA: 0s - loss: 0.0156 133/133 [==============================] - 0s 980us/step - loss: 0.0161 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0032 50/133 [==========>...................] - ETA: 0s - loss: 0.0140 89/133 [===================>..........] - ETA: 0s - loss: 0.0144 133/133 [==============================] - 0s 1ms/step - loss: 0.0153 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0060 51/133 [==========>...................] - ETA: 0s - loss: 0.0173 103/133 [======================>.......] - ETA: 0s - loss: 0.0132 133/133 [==============================] - 0s 991us/step - loss: 0.0151 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0058 53/133 [==========>...................] - ETA: 0s - loss: 0.0117 104/133 [======================>.......] - ETA: 0s - loss: 0.0139 133/133 [==============================] - 0s 984us/step - loss: 0.0142 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 4, 9 GAN f1 score: 0.750 GAN cohens kappa score: 0.741 -> test with 'LR' LR tn, fp: 292, 41 LR fn, tp: 0, 13 LR f1 score: 0.388 LR cohens kappa score: 0.349 LR average precision score: 0.361 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 326, 7 KNN fn, tp: 0, 13 KNN f1 score: 0.788 KNN cohens kappa score: 0.778 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 16s - loss: 0.0027 51/133 [==========>...................] - ETA: 0s - loss: 0.0204  102/133 [======================>.......] - ETA: 0s - loss: 0.0243 133/133 [==============================] - 0s 1ms/step - loss: 0.0272 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0074 50/133 [==========>...................] - ETA: 0s - loss: 0.0215 93/133 [===================>..........] - ETA: 0s - loss: 0.0224 133/133 [==============================] - 0s 1ms/step - loss: 0.0225 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0429 45/133 [=========>....................] - ETA: 0s - loss: 0.0151 95/133 [====================>.........] - ETA: 0s - loss: 0.0178 133/133 [==============================] - 0s 1ms/step - loss: 0.0191 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0286 52/133 [==========>...................] - ETA: 0s - loss: 0.0141 103/133 [======================>.......] - ETA: 0s - loss: 0.0182 133/133 [==============================] - 0s 996us/step - loss: 0.0165 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0206 52/133 [==========>...................] - ETA: 0s - loss: 0.0206 103/133 [======================>.......] - ETA: 0s - loss: 0.0161 133/133 [==============================] - 0s 991us/step - loss: 0.0158 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0050 52/133 [==========>...................] - ETA: 0s - loss: 0.0159 103/133 [======================>.......] - ETA: 0s - loss: 0.0141 133/133 [==============================] - 0s 989us/step - loss: 0.0147 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0055 52/133 [==========>...................] - ETA: 0s - loss: 0.0138 102/133 [======================>.......] - ETA: 0s - loss: 0.0134 133/133 [==============================] - 0s 1ms/step - loss: 0.0133 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0013 49/133 [==========>...................] - ETA: 0s - loss: 0.0149 96/133 [====================>.........] - ETA: 0s - loss: 0.0144 133/133 [==============================] - 0s 1ms/step - loss: 0.0129 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0056 52/133 [==========>...................] - ETA: 0s - loss: 0.0093 103/133 [======================>.......] - ETA: 0s - loss: 0.0123 133/133 [==============================] - 0s 991us/step - loss: 0.0116 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 52/133 [==========>...................] - ETA: 0s - loss: 0.0128 103/133 [======================>.......] - ETA: 0s - loss: 0.0115 133/133 [==============================] - 0s 989us/step - loss: 0.0120 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 1, 12 GAN f1 score: 0.889 GAN cohens kappa score: 0.884 -> test with 'LR' LR tn, fp: 294, 39 LR fn, tp: 2, 11 LR f1 score: 0.349 LR cohens kappa score: 0.308 LR average precision score: 0.302 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 316, 17 KNN fn, tp: 0, 13 KNN f1 score: 0.605 KNN cohens kappa score: 0.583 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 15s - loss: 0.0250 51/133 [==========>...................] - ETA: 0s - loss: 0.0420  98/133 [=====================>........] - ETA: 0s - loss: 0.0370 133/133 [==============================] - 0s 1ms/step - loss: 0.0322 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0219 52/133 [==========>...................] - ETA: 0s - loss: 0.0267 103/133 [======================>.......] - ETA: 0s - loss: 0.0297 133/133 [==============================] - 0s 988us/step - loss: 0.0281 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0118 51/133 [==========>...................] - ETA: 0s - loss: 0.0279 102/133 [======================>.......] - ETA: 0s - loss: 0.0269 133/133 [==============================] - 0s 997us/step - loss: 0.0261 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0194 52/133 [==========>...................] - ETA: 0s - loss: 0.0333 103/133 [======================>.......] - ETA: 0s - loss: 0.0268 133/133 [==============================] - 0s 990us/step - loss: 0.0243 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 51/133 [==========>...................] - ETA: 0s - loss: 0.0174 102/133 [======================>.......] - ETA: 0s - loss: 0.0206 133/133 [==============================] - 0s 994us/step - loss: 0.0215 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0069 52/133 [==========>...................] - ETA: 0s - loss: 0.0214 103/133 [======================>.......] - ETA: 0s - loss: 0.0202 133/133 [==============================] - 0s 992us/step - loss: 0.0215 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0045 52/133 [==========>...................] - ETA: 0s - loss: 0.0188 103/133 [======================>.......] - ETA: 0s - loss: 0.0171 133/133 [==============================] - 0s 994us/step - loss: 0.0180 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0048 51/133 [==========>...................] - ETA: 0s - loss: 0.0104 101/133 [=====================>........] - ETA: 0s - loss: 0.0138 133/133 [==============================] - 0s 1ms/step - loss: 0.0160 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0270 49/133 [==========>...................] - ETA: 0s - loss: 0.0237 99/133 [=====================>........] - ETA: 0s - loss: 0.0172 133/133 [==============================] - 0s 1ms/step - loss: 0.0158 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0338 52/133 [==========>...................] - ETA: 0s - loss: 0.0143 103/133 [======================>.......] - ETA: 0s - loss: 0.0138 133/133 [==============================] - 0s 990us/step - loss: 0.0141 -> test with GAN.predict GAN tn, fp: 327, 6 GAN fn, tp: 0, 13 GAN f1 score: 0.813 GAN cohens kappa score: 0.804 -> test with 'LR' LR tn, fp: 282, 51 LR fn, tp: 0, 13 LR f1 score: 0.338 LR cohens kappa score: 0.294 LR average precision score: 0.378 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 1, 12 GB f1 score: 0.960 GB cohens kappa score: 0.959 -> test with 'KNN' KNN tn, fp: 317, 16 KNN fn, tp: 0, 13 KNN f1 score: 0.619 KNN cohens kappa score: 0.598 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 15s - loss: 0.0049 51/133 [==========>...................] - ETA: 0s - loss: 0.0365  102/133 [======================>.......] - ETA: 0s - loss: 0.0383 133/133 [==============================] - 0s 999us/step - loss: 0.0386 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0071 52/133 [==========>...................] - ETA: 0s - loss: 0.0282 103/133 [======================>.......] - ETA: 0s - loss: 0.0331 133/133 [==============================] - 0s 987us/step - loss: 0.0333 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 9.1451e-04 49/133 [==========>...................] - ETA: 0s - loss: 0.0278  100/133 [=====================>........] - ETA: 0s - loss: 0.0240 133/133 [==============================] - 0s 1ms/step - loss: 0.0287 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0303 48/133 [=========>....................] - ETA: 0s - loss: 0.0262 95/133 [====================>.........] - ETA: 0s - loss: 0.0268 133/133 [==============================] - 0s 1ms/step - loss: 0.0254 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0110 52/133 [==========>...................] - ETA: 0s - loss: 0.0215 103/133 [======================>.......] - ETA: 0s - loss: 0.0256 133/133 [==============================] - 0s 991us/step - loss: 0.0240 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0042 51/133 [==========>...................] - ETA: 0s - loss: 0.0264 102/133 [======================>.......] - ETA: 0s - loss: 0.0232 133/133 [==============================] - 0s 1ms/step - loss: 0.0228 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.1526 52/133 [==========>...................] - ETA: 0s - loss: 0.0142 103/133 [======================>.......] - ETA: 0s - loss: 0.0152 133/133 [==============================] - 0s 994us/step - loss: 0.0199 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0418 52/133 [==========>...................] - ETA: 0s - loss: 0.0114 103/133 [======================>.......] - ETA: 0s - loss: 0.0175 133/133 [==============================] - 0s 989us/step - loss: 0.0185 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0300 52/133 [==========>...................] - ETA: 0s - loss: 0.0195 103/133 [======================>.......] - ETA: 0s - loss: 0.0198 133/133 [==============================] - 0s 992us/step - loss: 0.0182 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 7.0630e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0158  103/133 [======================>.......] - ETA: 0s - loss: 0.0168 133/133 [==============================] - 0s 989us/step - loss: 0.0162 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 1, 12 GAN f1 score: 0.857 GAN cohens kappa score: 0.851 -> test with 'LR' LR tn, fp: 294, 39 LR fn, tp: 0, 13 LR f1 score: 0.400 LR cohens kappa score: 0.362 LR average precision score: 0.359 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 321, 12 KNN fn, tp: 0, 13 KNN f1 score: 0.684 KNN cohens kappa score: 0.668 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 19s - loss: 0.0127 49/134 [=========>....................] - ETA: 0s - loss: 0.0266  97/134 [====================>.........] - ETA: 0s - loss: 0.0272 134/134 [==============================] - 0s 1ms/step - loss: 0.0306 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.0161 49/134 [=========>....................] - ETA: 0s - loss: 0.0288 97/134 [====================>.........] - ETA: 0s - loss: 0.0296 134/134 [==============================] - 0s 1ms/step - loss: 0.0283 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.0156 45/134 [=========>....................] - ETA: 0s - loss: 0.0155 88/134 [==================>...........] - ETA: 0s - loss: 0.0240 131/134 [============================>.] - ETA: 0s - loss: 0.0262 134/134 [==============================] - 0s 1ms/step - loss: 0.0262 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0104 48/134 [=========>....................] - ETA: 0s - loss: 0.0266 96/134 [====================>.........] - ETA: 0s - loss: 0.0258 134/134 [==============================] - 0s 1ms/step - loss: 0.0251 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.0041 49/134 [=========>....................] - ETA: 0s - loss: 0.0269 96/134 [====================>.........] - ETA: 0s - loss: 0.0245 134/134 [==============================] - 0s 1ms/step - loss: 0.0231 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0141 49/134 [=========>....................] - ETA: 0s - loss: 0.0236 97/134 [====================>.........] - ETA: 0s - loss: 0.0212 134/134 [==============================] - 0s 1ms/step - loss: 0.0218 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0018 50/134 [==========>...................] - ETA: 0s - loss: 0.0192 99/134 [=====================>........] - ETA: 0s - loss: 0.0199 134/134 [==============================] - 0s 1ms/step - loss: 0.0204 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0065 49/134 [=========>....................] - ETA: 0s - loss: 0.0254 98/134 [====================>.........] - ETA: 0s - loss: 0.0210 134/134 [==============================] - 0s 1ms/step - loss: 0.0192 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0041 50/134 [==========>...................] - ETA: 0s - loss: 0.0155 98/134 [====================>.........] - ETA: 0s - loss: 0.0179 134/134 [==============================] - 0s 1ms/step - loss: 0.0183 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0094 50/134 [==========>...................] - ETA: 0s - loss: 0.0198 99/134 [=====================>........] - ETA: 0s - loss: 0.0174 134/134 [==============================] - 0s 1ms/step - loss: 0.0172 -> test with GAN.predict GAN tn, fp: 329, 2 GAN fn, tp: 2, 11 GAN f1 score: 0.846 GAN cohens kappa score: 0.840 -> test with 'LR' LR tn, fp: 299, 32 LR fn, tp: 2, 11 LR f1 score: 0.393 LR cohens kappa score: 0.355 LR average precision score: 0.448 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 329, 2 GB fn, tp: 0, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 322, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 16s - loss: 0.0176 47/133 [=========>....................] - ETA: 0s - loss: 0.0270  93/133 [===================>..........] - ETA: 0s - loss: 0.0370 133/133 [==============================] - 0s 1ms/step - loss: 0.0363 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0331 47/133 [=========>....................] - ETA: 0s - loss: 0.0343 92/133 [===================>..........] - ETA: 0s - loss: 0.0315 133/133 [==============================] - 0s 1ms/step - loss: 0.0277 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0111 47/133 [=========>....................] - ETA: 0s - loss: 0.0287 95/133 [====================>.........] - ETA: 0s - loss: 0.0275 133/133 [==============================] - 0s 1ms/step - loss: 0.0249 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0252 48/133 [=========>....................] - ETA: 0s - loss: 0.0190 96/133 [====================>.........] - ETA: 0s - loss: 0.0203 133/133 [==============================] - 0s 1ms/step - loss: 0.0219 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0053 47/133 [=========>....................] - ETA: 0s - loss: 0.0254 90/133 [===================>..........] - ETA: 0s - loss: 0.0214 133/133 [==============================] - 0s 1ms/step - loss: 0.0200 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0559 47/133 [=========>....................] - ETA: 0s - loss: 0.0203 95/133 [====================>.........] - ETA: 0s - loss: 0.0203 133/133 [==============================] - 0s 1ms/step - loss: 0.0190 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 49/133 [==========>...................] - ETA: 0s - loss: 0.0264 96/133 [====================>.........] - ETA: 0s - loss: 0.0211 133/133 [==============================] - 0s 1ms/step - loss: 0.0184 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0102 47/133 [=========>....................] - ETA: 0s - loss: 0.0218 94/133 [====================>.........] - ETA: 0s - loss: 0.0167 133/133 [==============================] - 0s 1ms/step - loss: 0.0170 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0122 52/133 [==========>...................] - ETA: 0s - loss: 0.0174 103/133 [======================>.......] - ETA: 0s - loss: 0.0166 133/133 [==============================] - 0s 987us/step - loss: 0.0159 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0027 52/133 [==========>...................] - ETA: 0s - loss: 0.0120 102/133 [======================>.......] - ETA: 0s - loss: 0.0146 133/133 [==============================] - 0s 996us/step - loss: 0.0152 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 5, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.627 -> test with 'LR' LR tn, fp: 290, 43 LR fn, tp: 0, 13 LR f1 score: 0.377 LR cohens kappa score: 0.336 LR average precision score: 0.281 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 3, 10 RF f1 score: 0.870 RF cohens kappa score: 0.865 -> test with 'GB' GB tn, fp: 332, 1 GB fn, tp: 2, 11 GB f1 score: 0.880 GB cohens kappa score: 0.876 -> test with 'KNN' KNN tn, fp: 321, 12 KNN fn, tp: 0, 13 KNN f1 score: 0.684 KNN cohens kappa score: 0.668 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 15s - loss: 0.0123 51/133 [==========>...................] - ETA: 0s - loss: 0.0366  102/133 [======================>.......] - ETA: 0s - loss: 0.0297 133/133 [==============================] - 0s 1ms/step - loss: 0.0277 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0168 49/133 [==========>...................] - ETA: 0s - loss: 0.0243 100/133 [=====================>........] - ETA: 0s - loss: 0.0218 133/133 [==============================] - 0s 1ms/step - loss: 0.0230 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0661 52/133 [==========>...................] - ETA: 0s - loss: 0.0180 103/133 [======================>.......] - ETA: 0s - loss: 0.0210 133/133 [==============================] - 0s 995us/step - loss: 0.0207 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0067 52/133 [==========>...................] - ETA: 0s - loss: 0.0236 103/133 [======================>.......] - ETA: 0s - loss: 0.0205 133/133 [==============================] - 0s 989us/step - loss: 0.0204 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0034 52/133 [==========>...................] - ETA: 0s - loss: 0.0194 103/133 [======================>.......] - ETA: 0s - loss: 0.0186 133/133 [==============================] - 0s 989us/step - loss: 0.0184 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0407 52/133 [==========>...................] - ETA: 0s - loss: 0.0218 101/133 [=====================>........] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 1ms/step - loss: 0.0178 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0255 52/133 [==========>...................] - ETA: 0s - loss: 0.0176 99/133 [=====================>........] - ETA: 0s - loss: 0.0179 133/133 [==============================] - 0s 1ms/step - loss: 0.0165 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 45/133 [=========>....................] - ETA: 0s - loss: 0.0163 90/133 [===================>..........] - ETA: 0s - loss: 0.0156 133/133 [==============================] - 0s 1ms/step - loss: 0.0158 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0212 50/133 [==========>...................] - ETA: 0s - loss: 0.0150 101/133 [=====================>........] - ETA: 0s - loss: 0.0145 133/133 [==============================] - 0s 1ms/step - loss: 0.0153 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0062 52/133 [==========>...................] - ETA: 0s - loss: 0.0101 103/133 [======================>.......] - ETA: 0s - loss: 0.0133 133/133 [==============================] - 0s 986us/step - loss: 0.0137 -> test with GAN.predict GAN tn, fp: 328, 5 GAN fn, tp: 2, 11 GAN f1 score: 0.759 GAN cohens kappa score: 0.748 -> test with 'LR' LR tn, fp: 276, 57 LR fn, tp: 0, 13 LR f1 score: 0.313 LR cohens kappa score: 0.267 LR average precision score: 0.359 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 328, 5 GB fn, tp: 0, 13 GB f1 score: 0.839 GB cohens kappa score: 0.831 -> test with 'KNN' KNN tn, fp: 310, 23 KNN fn, tp: 0, 13 KNN f1 score: 0.531 KNN cohens kappa score: 0.503 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0600 44/133 [========>.....................] - ETA: 0s - loss: 0.0327  88/133 [==================>...........] - ETA: 0s - loss: 0.0354 133/133 [==============================] - 0s 1ms/step - loss: 0.0360 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0198 48/133 [=========>....................] - ETA: 0s - loss: 0.0236 96/133 [====================>.........] - ETA: 0s - loss: 0.0300 133/133 [==============================] - 0s 1ms/step - loss: 0.0293 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0377 51/133 [==========>...................] - ETA: 0s - loss: 0.0177 99/133 [=====================>........] - ETA: 0s - loss: 0.0271 133/133 [==============================] - 0s 1ms/step - loss: 0.0259 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0032 51/133 [==========>...................] - ETA: 0s - loss: 0.0217 102/133 [======================>.......] - ETA: 0s - loss: 0.0246 133/133 [==============================] - 0s 1ms/step - loss: 0.0237 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0130 50/133 [==========>...................] - ETA: 0s - loss: 0.0224 100/133 [=====================>........] - ETA: 0s - loss: 0.0208 133/133 [==============================] - 0s 1ms/step - loss: 0.0222 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0136 51/133 [==========>...................] - ETA: 0s - loss: 0.0208 100/133 [=====================>........] - ETA: 0s - loss: 0.0195 133/133 [==============================] - 0s 1ms/step - loss: 0.0202 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0025 50/133 [==========>...................] - ETA: 0s - loss: 0.0220 100/133 [=====================>........] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 1ms/step - loss: 0.0188 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0085 52/133 [==========>...................] - ETA: 0s - loss: 0.0143 102/133 [======================>.......] - ETA: 0s - loss: 0.0150 133/133 [==============================] - 0s 998us/step - loss: 0.0174 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0179 52/133 [==========>...................] - ETA: 0s - loss: 0.0210 102/133 [======================>.......] - ETA: 0s - loss: 0.0165 133/133 [==============================] - 0s 999us/step - loss: 0.0162 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0105 44/133 [========>.....................] - ETA: 0s - loss: 0.0139 85/133 [==================>...........] - ETA: 0s - loss: 0.0157 127/133 [===========================>..] - ETA: 0s - loss: 0.0158 133/133 [==============================] - 0s 1ms/step - loss: 0.0157 -> test with GAN.predict GAN tn, fp: 331, 2 GAN fn, tp: 1, 12 GAN f1 score: 0.889 GAN cohens kappa score: 0.884 -> test with 'LR' LR tn, fp: 296, 37 LR fn, tp: 1, 12 LR f1 score: 0.387 LR cohens kappa score: 0.348 LR average precision score: 0.333 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 327, 6 KNN fn, tp: 0, 13 KNN f1 score: 0.813 KNN cohens kappa score: 0.804 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.1085 49/133 [==========>...................] - ETA: 0s - loss: 0.0370  95/133 [====================>.........] - ETA: 0s - loss: 0.0380 133/133 [==============================] - 0s 1ms/step - loss: 0.0352 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0078 44/133 [========>.....................] - ETA: 0s - loss: 0.0235 88/133 [==================>...........] - ETA: 0s - loss: 0.0285 133/133 [==============================] - 0s 1ms/step - loss: 0.0300 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0074 51/133 [==========>...................] - ETA: 0s - loss: 0.0340 101/133 [=====================>........] - ETA: 0s - loss: 0.0274 133/133 [==============================] - 0s 1ms/step - loss: 0.0278 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0123 35/133 [======>.......................] - ETA: 0s - loss: 0.0362 78/133 [================>.............] - ETA: 0s - loss: 0.0296 126/133 [===========================>..] - ETA: 0s - loss: 0.0249 133/133 [==============================] - 0s 1ms/step - loss: 0.0253 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0432 47/133 [=========>....................] - ETA: 0s - loss: 0.0249 97/133 [====================>.........] - ETA: 0s - loss: 0.0211 133/133 [==============================] - 0s 1ms/step - loss: 0.0245 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0032 40/133 [========>.....................] - ETA: 0s - loss: 0.0256 74/133 [===============>..............] - ETA: 0s - loss: 0.0216 107/133 [=======================>......] - ETA: 0s - loss: 0.0232 133/133 [==============================] - 0s 1ms/step - loss: 0.0225 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0061 40/133 [========>.....................] - ETA: 0s - loss: 0.0167 88/133 [==================>...........] - ETA: 0s - loss: 0.0226 133/133 [==============================] - 0s 1ms/step - loss: 0.0218 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.1212 48/133 [=========>....................] - ETA: 0s - loss: 0.0234 96/133 [====================>.........] - ETA: 0s - loss: 0.0185 133/133 [==============================] - 0s 1ms/step - loss: 0.0197 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0267 45/133 [=========>....................] - ETA: 0s - loss: 0.0230 80/133 [=================>............] - ETA: 0s - loss: 0.0210 115/133 [========================>.....] - ETA: 0s - loss: 0.0196 133/133 [==============================] - 0s 1ms/step - loss: 0.0189 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0051 46/133 [=========>....................] - ETA: 0s - loss: 0.0162 90/133 [===================>..........] - ETA: 0s - loss: 0.0192 133/133 [==============================] - 0s 1ms/step - loss: 0.0175 -> test with GAN.predict GAN tn, fp: 326, 7 GAN fn, tp: 4, 9 GAN f1 score: 0.621 GAN cohens kappa score: 0.604 -> test with 'LR' LR tn, fp: 295, 38 LR fn, tp: 0, 13 LR f1 score: 0.406 LR cohens kappa score: 0.368 LR average precision score: 0.323 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 2, 11 GB f1 score: 0.917 GB cohens kappa score: 0.914 -> test with 'KNN' KNN tn, fp: 324, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 19s - loss: 0.0024 44/134 [========>.....................] - ETA: 0s - loss: 0.0420  88/134 [==================>...........] - ETA: 0s - loss: 0.0521 129/134 [===========================>..] - ETA: 0s - loss: 0.0470 134/134 [==============================] - 0s 1ms/step - loss: 0.0459 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.2678 43/134 [========>.....................] - ETA: 0s - loss: 0.0425 83/134 [=================>............] - ETA: 0s - loss: 0.0322 120/134 [=========================>....] - ETA: 0s - loss: 0.0331 134/134 [==============================] - 0s 1ms/step - loss: 0.0326 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.2882 43/134 [========>.....................] - ETA: 0s - loss: 0.0416 86/134 [==================>...........] - ETA: 0s - loss: 0.0326 127/134 [===========================>..] - ETA: 0s - loss: 0.0292 134/134 [==============================] - 0s 1ms/step - loss: 0.0280 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0025 37/134 [=======>......................] - ETA: 0s - loss: 0.0319 73/134 [===============>..............] - ETA: 0s - loss: 0.0281 113/134 [========================>.....] - ETA: 0s - loss: 0.0275 134/134 [==============================] - 0s 1ms/step - loss: 0.0271 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.0121 44/134 [========>.....................] - ETA: 0s - loss: 0.0418 86/134 [==================>...........] - ETA: 0s - loss: 0.0294 128/134 [===========================>..] - ETA: 0s - loss: 0.0267 134/134 [==============================] - 0s 1ms/step - loss: 0.0260 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0013 38/134 [=======>......................] - ETA: 0s - loss: 0.0237 81/134 [=================>............] - ETA: 0s - loss: 0.0201 125/134 [==========================>...] - ETA: 0s - loss: 0.0215 134/134 [==============================] - 0s 1ms/step - loss: 0.0222 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0051 44/134 [========>.....................] - ETA: 0s - loss: 0.0119 87/134 [==================>...........] - ETA: 0s - loss: 0.0204 130/134 [============================>.] - ETA: 0s - loss: 0.0220 134/134 [==============================] - 0s 1ms/step - loss: 0.0216 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0057 41/134 [========>.....................] - ETA: 0s - loss: 0.0149 80/134 [================>.............] - ETA: 0s - loss: 0.0164 121/134 [==========================>...] - ETA: 0s - loss: 0.0206 134/134 [==============================] - 0s 1ms/step - loss: 0.0199 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0012 43/134 [========>.....................] - ETA: 0s - loss: 0.0147 86/134 [==================>...........] - ETA: 0s - loss: 0.0167 127/134 [===========================>..] - ETA: 0s - loss: 0.0188 134/134 [==============================] - 0s 1ms/step - loss: 0.0193 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0099 42/134 [========>.....................] - ETA: 0s - loss: 0.0201 80/134 [================>.............] - ETA: 0s - loss: 0.0177 121/134 [==========================>...] - ETA: 0s - loss: 0.0169 134/134 [==============================] - 0s 1ms/step - loss: 0.0173 -> test with GAN.predict GAN tn, fp: 326, 5 GAN fn, tp: 2, 11 GAN f1 score: 0.759 GAN cohens kappa score: 0.748 -> test with 'LR' LR tn, fp: 289, 42 LR fn, tp: 0, 13 LR f1 score: 0.382 LR cohens kappa score: 0.342 LR average precision score: 0.534 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 331, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 323, 8 KNN fn, tp: 0, 13 KNN f1 score: 0.765 KNN cohens kappa score: 0.753 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 16s - loss: 0.0354 49/133 [==========>...................] - ETA: 0s - loss: 0.0467  98/133 [=====================>........] - ETA: 0s - loss: 0.0316 133/133 [==============================] - 0s 1ms/step - loss: 0.0396 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0109 51/133 [==========>...................] - ETA: 0s - loss: 0.0464 101/133 [=====================>........] - ETA: 0s - loss: 0.0373 133/133 [==============================] - 0s 1ms/step - loss: 0.0318 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0089 50/133 [==========>...................] - ETA: 0s - loss: 0.0295 96/133 [====================>.........] - ETA: 0s - loss: 0.0289 133/133 [==============================] - 0s 1ms/step - loss: 0.0270 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0046 46/133 [=========>....................] - ETA: 0s - loss: 0.0209 94/133 [====================>.........] - ETA: 0s - loss: 0.0231 133/133 [==============================] - 0s 1ms/step - loss: 0.0262 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0312 52/133 [==========>...................] - ETA: 0s - loss: 0.0235 102/133 [======================>.......] - ETA: 0s - loss: 0.0212 133/133 [==============================] - 0s 1ms/step - loss: 0.0217 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0059 52/133 [==========>...................] - ETA: 0s - loss: 0.0195 103/133 [======================>.......] - ETA: 0s - loss: 0.0154 133/133 [==============================] - 0s 999us/step - loss: 0.0188 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0091 51/133 [==========>...................] - ETA: 0s - loss: 0.0102 95/133 [====================>.........] - ETA: 0s - loss: 0.0182 133/133 [==============================] - 0s 1ms/step - loss: 0.0178 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0031 49/133 [==========>...................] - ETA: 0s - loss: 0.0148 97/133 [====================>.........] - ETA: 0s - loss: 0.0162 133/133 [==============================] - 0s 1ms/step - loss: 0.0192 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0714 38/133 [=======>......................] - ETA: 0s - loss: 0.0104 84/133 [=================>............] - ETA: 0s - loss: 0.0156 133/133 [==============================] - 0s 1ms/step - loss: 0.0150 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 51/133 [==========>...................] - ETA: 0s - loss: 0.0168 92/133 [===================>..........] - ETA: 0s - loss: 0.0183 133/133 [==============================] - 0s 1ms/step - loss: 0.0153 -> test with GAN.predict GAN tn, fp: 328, 5 GAN fn, tp: 2, 11 GAN f1 score: 0.759 GAN cohens kappa score: 0.748 -> test with 'LR' LR tn, fp: 294, 39 LR fn, tp: 1, 12 LR f1 score: 0.375 LR cohens kappa score: 0.335 LR average precision score: 0.274 -> test with 'RF' RF tn, fp: 332, 1 RF fn, tp: 4, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 331, 2 GB fn, tp: 2, 11 GB f1 score: 0.846 GB cohens kappa score: 0.840 -> test with 'KNN' KNN tn, fp: 317, 16 KNN fn, tp: 1, 12 KNN f1 score: 0.585 KNN cohens kappa score: 0.563 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 15s - loss: 0.0012 50/133 [==========>...................] - ETA: 0s - loss: 0.0900  101/133 [=====================>........] - ETA: 0s - loss: 0.0623 133/133 [==============================] - 0s 1ms/step - loss: 0.0557 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0162 52/133 [==========>...................] - ETA: 0s - loss: 0.0474 100/133 [=====================>........] - ETA: 0s - loss: 0.0436 133/133 [==============================] - 0s 1ms/step - loss: 0.0448 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0066 52/133 [==========>...................] - ETA: 0s - loss: 0.0502 102/133 [======================>.......] - ETA: 0s - loss: 0.0457 133/133 [==============================] - 0s 996us/step - loss: 0.0407 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0039 52/133 [==========>...................] - ETA: 0s - loss: 0.0451 102/133 [======================>.......] - ETA: 0s - loss: 0.0409 133/133 [==============================] - 0s 1ms/step - loss: 0.0370 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0311 51/133 [==========>...................] - ETA: 0s - loss: 0.0343 102/133 [======================>.......] - ETA: 0s - loss: 0.0331 133/133 [==============================] - 0s 999us/step - loss: 0.0341 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0373 52/133 [==========>...................] - ETA: 0s - loss: 0.0310 102/133 [======================>.......] - ETA: 0s - loss: 0.0327 133/133 [==============================] - 0s 999us/step - loss: 0.0325 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0111 49/133 [==========>...................] - ETA: 0s - loss: 0.0176 100/133 [=====================>........] - ETA: 0s - loss: 0.0330 133/133 [==============================] - 0s 1ms/step - loss: 0.0292 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 7.9586e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0296  103/133 [======================>.......] - ETA: 0s - loss: 0.0264 133/133 [==============================] - 0s 993us/step - loss: 0.0285 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 9.7966e-04 52/133 [==========>...................] - ETA: 0s - loss: 0.0287  103/133 [======================>.......] - ETA: 0s - loss: 0.0256 133/133 [==============================] - 0s 993us/step - loss: 0.0270 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0038 51/133 [==========>...................] - ETA: 0s - loss: 0.0361 102/133 [======================>.......] - ETA: 0s - loss: 0.0279 133/133 [==============================] - 0s 998us/step - loss: 0.0253 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 2, 11 GAN f1 score: 0.786 GAN cohens kappa score: 0.777 -> test with 'LR' LR tn, fp: 301, 32 LR fn, tp: 0, 13 LR f1 score: 0.448 LR cohens kappa score: 0.414 LR average precision score: 0.399 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 324, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0040 44/133 [========>.....................] - ETA: 0s - loss: 0.0347  87/133 [==================>...........] - ETA: 0s - loss: 0.0348 131/133 [============================>.] - ETA: 0s - loss: 0.0327 133/133 [==============================] - 0s 1ms/step - loss: 0.0333 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0337 48/133 [=========>....................] - ETA: 0s - loss: 0.0213 99/133 [=====================>........] - ETA: 0s - loss: 0.0266 133/133 [==============================] - 0s 1ms/step - loss: 0.0273 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0248 51/133 [==========>...................] - ETA: 0s - loss: 0.0162 101/133 [=====================>........] - ETA: 0s - loss: 0.0221 133/133 [==============================] - 0s 1ms/step - loss: 0.0247 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.2080 48/133 [=========>....................] - ETA: 0s - loss: 0.0284 94/133 [====================>.........] - ETA: 0s - loss: 0.0217 133/133 [==============================] - 0s 1ms/step - loss: 0.0224 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.1223 50/133 [==========>...................] - ETA: 0s - loss: 0.0188 99/133 [=====================>........] - ETA: 0s - loss: 0.0188 133/133 [==============================] - 0s 1ms/step - loss: 0.0220 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0583 47/133 [=========>....................] - ETA: 0s - loss: 0.0218 90/133 [===================>..........] - ETA: 0s - loss: 0.0214 133/133 [==============================] - 0s 1ms/step - loss: 0.0207 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.2658 52/133 [==========>...................] - ETA: 0s - loss: 0.0193 104/133 [======================>.......] - ETA: 0s - loss: 0.0197 133/133 [==============================] - 0s 999us/step - loss: 0.0183 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0069 52/133 [==========>...................] - ETA: 0s - loss: 0.0202 102/133 [======================>.......] - ETA: 0s - loss: 0.0184 133/133 [==============================] - 0s 1ms/step - loss: 0.0177 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0532 52/133 [==========>...................] - ETA: 0s - loss: 0.0129 103/133 [======================>.......] - ETA: 0s - loss: 0.0178 133/133 [==============================] - 0s 1ms/step - loss: 0.0161 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0038 42/133 [========>.....................] - ETA: 0s - loss: 0.0146 80/133 [=================>............] - ETA: 0s - loss: 0.0126 118/133 [=========================>....] - ETA: 0s - loss: 0.0175 133/133 [==============================] - 0s 1ms/step - loss: 0.0164 -> test with GAN.predict GAN tn, fp: 325, 8 GAN fn, tp: 0, 13 GAN f1 score: 0.765 GAN cohens kappa score: 0.753 -> test with 'LR' LR tn, fp: 281, 52 LR fn, tp: 0, 13 LR f1 score: 0.333 LR cohens kappa score: 0.289 LR average precision score: 0.342 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 331, 2 GB fn, tp: 0, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 312, 21 KNN fn, tp: 0, 13 KNN f1 score: 0.553 KNN cohens kappa score: 0.528 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0346 44/133 [========>.....................] - ETA: 0s - loss: 0.0308  88/133 [==================>...........] - ETA: 0s - loss: 0.0454 131/133 [============================>.] - ETA: 0s - loss: 0.0406 133/133 [==============================] - 0s 1ms/step - loss: 0.0402 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0035 44/133 [========>.....................] - ETA: 0s - loss: 0.0284 81/133 [=================>............] - ETA: 0s - loss: 0.0381 119/133 [=========================>....] - ETA: 0s - loss: 0.0349 133/133 [==============================] - 0s 1ms/step - loss: 0.0354 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0094 43/133 [========>.....................] - ETA: 0s - loss: 0.0507 86/133 [==================>...........] - ETA: 0s - loss: 0.0365 129/133 [============================>.] - ETA: 0s - loss: 0.0330 133/133 [==============================] - 0s 1ms/step - loss: 0.0325 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0129 41/133 [========>.....................] - ETA: 0s - loss: 0.0208 84/133 [=================>............] - ETA: 0s - loss: 0.0277 128/133 [===========================>..] - ETA: 0s - loss: 0.0293 133/133 [==============================] - 0s 1ms/step - loss: 0.0297 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0135 44/133 [========>.....................] - ETA: 0s - loss: 0.0188 90/133 [===================>..........] - ETA: 0s - loss: 0.0188 133/133 [==============================] - 0s 1ms/step - loss: 0.0268 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0169 44/133 [========>.....................] - ETA: 0s - loss: 0.0211 88/133 [==================>...........] - ETA: 0s - loss: 0.0263 130/133 [============================>.] - ETA: 0s - loss: 0.0263 133/133 [==============================] - 0s 1ms/step - loss: 0.0258 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0109 44/133 [========>.....................] - ETA: 0s - loss: 0.0257 87/133 [==================>...........] - ETA: 0s - loss: 0.0287 130/133 [============================>.] - ETA: 0s - loss: 0.0232 133/133 [==============================] - 0s 1ms/step - loss: 0.0229 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0100 44/133 [========>.....................] - ETA: 0s - loss: 0.0244 86/133 [==================>...........] - ETA: 0s - loss: 0.0208 128/133 [===========================>..] - ETA: 0s - loss: 0.0215 133/133 [==============================] - 0s 1ms/step - loss: 0.0221 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0031 46/133 [=========>....................] - ETA: 0s - loss: 0.0112 96/133 [====================>.........] - ETA: 0s - loss: 0.0163 133/133 [==============================] - 0s 1ms/step - loss: 0.0198 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0056 52/133 [==========>...................] - ETA: 0s - loss: 0.0280 103/133 [======================>.......] - ETA: 0s - loss: 0.0187 133/133 [==============================] - 0s 994us/step - loss: 0.0184 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 1, 12 GAN f1 score: 0.828 GAN cohens kappa score: 0.820 -> test with 'LR' LR tn, fp: 293, 40 LR fn, tp: 0, 13 LR f1 score: 0.394 LR cohens kappa score: 0.355 LR average precision score: 0.384 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 0, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 328, 5 KNN fn, tp: 0, 13 KNN f1 score: 0.839 KNN cohens kappa score: 0.831 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 18s - loss: 0.0400 36/134 [=======>......................] - ETA: 0s - loss: 0.0474  77/134 [================>.............] - ETA: 0s - loss: 0.0522 117/134 [=========================>....] - ETA: 0s - loss: 0.0443 134/134 [==============================] - 0s 1ms/step - loss: 0.0421 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.0030 49/134 [=========>....................] - ETA: 0s - loss: 0.0473 97/134 [====================>.........] - ETA: 0s - loss: 0.0385 134/134 [==============================] - 0s 1ms/step - loss: 0.0362 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.0076 43/134 [========>.....................] - ETA: 0s - loss: 0.0222 88/134 [==================>...........] - ETA: 0s - loss: 0.0324 134/134 [==============================] - 0s 1ms/step - loss: 0.0327 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0057 49/134 [=========>....................] - ETA: 0s - loss: 0.0264 97/134 [====================>.........] - ETA: 0s - loss: 0.0255 134/134 [==============================] - 0s 1ms/step - loss: 0.0299 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.0077 49/134 [=========>....................] - ETA: 0s - loss: 0.0216 97/134 [====================>.........] - ETA: 0s - loss: 0.0235 134/134 [==============================] - 0s 1ms/step - loss: 0.0276 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0119 49/134 [=========>....................] - ETA: 0s - loss: 0.0173 97/134 [====================>.........] - ETA: 0s - loss: 0.0269 134/134 [==============================] - 0s 1ms/step - loss: 0.0250 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0187 49/134 [=========>....................] - ETA: 0s - loss: 0.0249 98/134 [====================>.........] - ETA: 0s - loss: 0.0206 134/134 [==============================] - 0s 1ms/step - loss: 0.0243 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0031 49/134 [=========>....................] - ETA: 0s - loss: 0.0245 96/134 [====================>.........] - ETA: 0s - loss: 0.0223 134/134 [==============================] - 0s 1ms/step - loss: 0.0229 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0096 47/134 [=========>....................] - ETA: 0s - loss: 0.0194 92/134 [===================>..........] - ETA: 0s - loss: 0.0182 134/134 [==============================] - 0s 1ms/step - loss: 0.0204 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0061 47/134 [=========>....................] - ETA: 0s - loss: 0.0157 93/134 [===================>..........] - ETA: 0s - loss: 0.0194 134/134 [==============================] - 0s 1ms/step - loss: 0.0196 -> test with GAN.predict GAN tn, fp: 326, 5 GAN fn, tp: 1, 12 GAN f1 score: 0.800 GAN cohens kappa score: 0.791 -> test with 'LR' LR tn, fp: 289, 42 LR fn, tp: 2, 11 LR f1 score: 0.333 LR cohens kappa score: 0.290 LR average precision score: 0.362 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 4, 9 RF f1 score: 0.818 RF cohens kappa score: 0.812 -> test with 'GB' GB tn, fp: 331, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 322, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 15s - loss: 0.0074 51/133 [==========>...................] - ETA: 0s - loss: 0.0366  102/133 [======================>.......] - ETA: 0s - loss: 0.0435 133/133 [==============================] - 0s 1ms/step - loss: 0.0401 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0072 52/133 [==========>...................] - ETA: 0s - loss: 0.0292 103/133 [======================>.......] - ETA: 0s - loss: 0.0312 133/133 [==============================] - 0s 991us/step - loss: 0.0340 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.1007 51/133 [==========>...................] - ETA: 0s - loss: 0.0277 101/133 [=====================>........] - ETA: 0s - loss: 0.0279 133/133 [==============================] - 0s 1ms/step - loss: 0.0295 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0067 48/133 [=========>....................] - ETA: 0s - loss: 0.0258 99/133 [=====================>........] - ETA: 0s - loss: 0.0286 133/133 [==============================] - 0s 1ms/step - loss: 0.0266 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0021 52/133 [==========>...................] - ETA: 0s - loss: 0.0280 103/133 [======================>.......] - ETA: 0s - loss: 0.0258 133/133 [==============================] - 0s 990us/step - loss: 0.0241 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 51/133 [==========>...................] - ETA: 0s - loss: 0.0257 100/133 [=====================>........] - ETA: 0s - loss: 0.0228 133/133 [==============================] - 0s 1ms/step - loss: 0.0217 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0034 51/133 [==========>...................] - ETA: 0s - loss: 0.0255 102/133 [======================>.......] - ETA: 0s - loss: 0.0221 133/133 [==============================] - 0s 1ms/step - loss: 0.0211 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0038 52/133 [==========>...................] - ETA: 0s - loss: 0.0182 102/133 [======================>.......] - ETA: 0s - loss: 0.0185 133/133 [==============================] - 0s 999us/step - loss: 0.0187 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0222 51/133 [==========>...................] - ETA: 0s - loss: 0.0189 101/133 [=====================>........] - ETA: 0s - loss: 0.0181 133/133 [==============================] - 0s 1ms/step - loss: 0.0165 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0517 52/133 [==========>...................] - ETA: 0s - loss: 0.0181 103/133 [======================>.......] - ETA: 0s - loss: 0.0155 133/133 [==============================] - 0s 988us/step - loss: 0.0163 -> test with GAN.predict GAN tn, fp: 333, 0 GAN fn, tp: 1, 12 GAN f1 score: 0.960 GAN cohens kappa score: 0.959 -> test with 'LR' LR tn, fp: 301, 32 LR fn, tp: 1, 12 LR f1 score: 0.421 LR cohens kappa score: 0.385 LR average precision score: 0.410 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 326, 7 KNN fn, tp: 1, 12 KNN f1 score: 0.750 KNN cohens kappa score: 0.738 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0067 46/133 [=========>....................] - ETA: 0s - loss: 0.0272  91/133 [===================>..........] - ETA: 0s - loss: 0.0270 133/133 [==============================] - 0s 1ms/step - loss: 0.0265 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 45/133 [=========>....................] - ETA: 0s - loss: 0.0275 91/133 [===================>..........] - ETA: 0s - loss: 0.0228 133/133 [==============================] - 0s 1ms/step - loss: 0.0246 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0144 47/133 [=========>....................] - ETA: 0s - loss: 0.0276 91/133 [===================>..........] - ETA: 0s - loss: 0.0212 130/133 [============================>.] - ETA: 0s - loss: 0.0219 133/133 [==============================] - 0s 1ms/step - loss: 0.0219 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0051 39/133 [=======>......................] - ETA: 0s - loss: 0.0278 79/133 [================>.............] - ETA: 0s - loss: 0.0231 125/133 [===========================>..] - ETA: 0s - loss: 0.0217 133/133 [==============================] - 0s 1ms/step - loss: 0.0213 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0048 46/133 [=========>....................] - ETA: 0s - loss: 0.0264 92/133 [===================>..........] - ETA: 0s - loss: 0.0213 133/133 [==============================] - 0s 1ms/step - loss: 0.0189 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0060 47/133 [=========>....................] - ETA: 0s - loss: 0.0111 92/133 [===================>..........] - ETA: 0s - loss: 0.0162 133/133 [==============================] - 0s 1ms/step - loss: 0.0181 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0162 48/133 [=========>....................] - ETA: 0s - loss: 0.0157 94/133 [====================>.........] - ETA: 0s - loss: 0.0169 133/133 [==============================] - 0s 1ms/step - loss: 0.0177 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0164 48/133 [=========>....................] - ETA: 0s - loss: 0.0166 91/133 [===================>..........] - ETA: 0s - loss: 0.0162 133/133 [==============================] - 0s 1ms/step - loss: 0.0170 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0070 47/133 [=========>....................] - ETA: 0s - loss: 0.0154 93/133 [===================>..........] - ETA: 0s - loss: 0.0145 133/133 [==============================] - 0s 1ms/step - loss: 0.0152 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0064 47/133 [=========>....................] - ETA: 0s - loss: 0.0139 93/133 [===================>..........] - ETA: 0s - loss: 0.0163 133/133 [==============================] - 0s 1ms/step - loss: 0.0138 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 3, 10 GAN f1 score: 0.769 GAN cohens kappa score: 0.760 -> test with 'LR' LR tn, fp: 292, 41 LR fn, tp: 1, 12 LR f1 score: 0.364 LR cohens kappa score: 0.323 LR average precision score: 0.522 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 1, 12 GB f1 score: 0.960 GB cohens kappa score: 0.959 -> test with 'KNN' KNN tn, fp: 328, 5 KNN fn, tp: 0, 13 KNN f1 score: 0.839 KNN cohens kappa score: 0.831 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0222 50/133 [==========>...................] - ETA: 0s - loss: 0.0467  100/133 [=====================>........] - ETA: 0s - loss: 0.0505 133/133 [==============================] - 0s 1ms/step - loss: 0.0473 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0132 51/133 [==========>...................] - ETA: 0s - loss: 0.0579 101/133 [=====================>........] - ETA: 0s - loss: 0.0431 133/133 [==============================] - 0s 1ms/step - loss: 0.0441 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0065 51/133 [==========>...................] - ETA: 0s - loss: 0.0370 99/133 [=====================>........] - ETA: 0s - loss: 0.0443 133/133 [==============================] - 0s 1ms/step - loss: 0.0413 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.2036 48/133 [=========>....................] - ETA: 0s - loss: 0.0281 96/133 [====================>.........] - ETA: 0s - loss: 0.0373 133/133 [==============================] - 0s 1ms/step - loss: 0.0386 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0072 50/133 [==========>...................] - ETA: 0s - loss: 0.0421 99/133 [=====================>........] - ETA: 0s - loss: 0.0396 133/133 [==============================] - 0s 1ms/step - loss: 0.0366 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 49/133 [==========>...................] - ETA: 0s - loss: 0.0427 98/133 [=====================>........] - ETA: 0s - loss: 0.0403 133/133 [==============================] - 0s 1ms/step - loss: 0.0353 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0130 50/133 [==========>...................] - ETA: 0s - loss: 0.0431 98/133 [=====================>........] - ETA: 0s - loss: 0.0360 133/133 [==============================] - 0s 1ms/step - loss: 0.0327 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.1440 49/133 [==========>...................] - ETA: 0s - loss: 0.0432 95/133 [====================>.........] - ETA: 0s - loss: 0.0363 133/133 [==============================] - 0s 1ms/step - loss: 0.0316 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0017 48/133 [=========>....................] - ETA: 0s - loss: 0.0259 95/133 [====================>.........] - ETA: 0s - loss: 0.0285 133/133 [==============================] - 0s 1ms/step - loss: 0.0298 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0338 48/133 [=========>....................] - ETA: 0s - loss: 0.0379 93/133 [===================>..........] - ETA: 0s - loss: 0.0284 133/133 [==============================] - 0s 1ms/step - loss: 0.0269 -> test with GAN.predict GAN tn, fp: 325, 8 GAN fn, tp: 1, 12 GAN f1 score: 0.727 GAN cohens kappa score: 0.714 -> test with 'LR' LR tn, fp: 286, 47 LR fn, tp: 0, 13 LR f1 score: 0.356 LR cohens kappa score: 0.314 LR average precision score: 0.312 -> test with 'RF' RF tn, fp: 332, 1 RF fn, tp: 0, 13 RF f1 score: 0.963 RF cohens kappa score: 0.961 -> test with 'GB' GB tn, fp: 330, 3 GB fn, tp: 0, 13 GB f1 score: 0.897 GB cohens kappa score: 0.892 -> test with 'KNN' KNN tn, fp: 322, 11 KNN fn, tp: 0, 13 KNN f1 score: 0.703 KNN cohens kappa score: 0.687 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 16s - loss: 0.0015 48/133 [=========>....................] - ETA: 0s - loss: 0.0400  96/133 [====================>.........] - ETA: 0s - loss: 0.0303 133/133 [==============================] - 0s 1ms/step - loss: 0.0284 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0068 45/133 [=========>....................] - ETA: 0s - loss: 0.0315 94/133 [====================>.........] - ETA: 0s - loss: 0.0311 133/133 [==============================] - 0s 1ms/step - loss: 0.0292 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0098 42/133 [========>.....................] - ETA: 0s - loss: 0.0183 81/133 [=================>............] - ETA: 0s - loss: 0.0189 126/133 [===========================>..] - ETA: 0s - loss: 0.0212 133/133 [==============================] - 0s 1ms/step - loss: 0.0226 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0173 45/133 [=========>....................] - ETA: 0s - loss: 0.0261 95/133 [====================>.........] - ETA: 0s - loss: 0.0250 133/133 [==============================] - 0s 1ms/step - loss: 0.0229 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0419 52/133 [==========>...................] - ETA: 0s - loss: 0.0176 102/133 [======================>.......] - ETA: 0s - loss: 0.0217 133/133 [==============================] - 0s 995us/step - loss: 0.0202 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0080 52/133 [==========>...................] - ETA: 0s - loss: 0.0159 103/133 [======================>.......] - ETA: 0s - loss: 0.0171 133/133 [==============================] - 0s 1ms/step - loss: 0.0183 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0058 46/133 [=========>....................] - ETA: 0s - loss: 0.0138 94/133 [====================>.........] - ETA: 0s - loss: 0.0163 124/133 [==========================>...] - ETA: 0s - loss: 0.0177 133/133 [==============================] - 0s 1ms/step - loss: 0.0174 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0049 49/133 [==========>...................] - ETA: 0s - loss: 0.0182 97/133 [====================>.........] - ETA: 0s - loss: 0.0163 133/133 [==============================] - 0s 1ms/step - loss: 0.0163 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0026 43/133 [========>.....................] - ETA: 0s - loss: 0.0117 91/133 [===================>..........] - ETA: 0s - loss: 0.0116 133/133 [==============================] - 0s 1ms/step - loss: 0.0147 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0097 50/133 [==========>...................] - ETA: 0s - loss: 0.0115 100/133 [=====================>........] - ETA: 0s - loss: 0.0141 133/133 [==============================] - 0s 1ms/step - loss: 0.0138 -> test with GAN.predict GAN tn, fp: 327, 6 GAN fn, tp: 6, 7 GAN f1 score: 0.538 GAN cohens kappa score: 0.520 -> test with 'LR' LR tn, fp: 295, 38 LR fn, tp: 1, 12 LR f1 score: 0.381 LR cohens kappa score: 0.342 LR average precision score: 0.287 -> test with 'RF' RF tn, fp: 332, 1 RF fn, tp: 7, 6 RF f1 score: 0.600 RF cohens kappa score: 0.589 -> test with 'GB' GB tn, fp: 331, 2 GB fn, tp: 0, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 317, 16 KNN fn, tp: 0, 13 KNN f1 score: 0.619 KNN cohens kappa score: 0.598 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 20s - loss: 0.3805 48/134 [=========>....................] - ETA: 0s - loss: 0.0498  91/134 [===================>..........] - ETA: 0s - loss: 0.0524 131/134 [============================>.] - ETA: 0s - loss: 0.0493 134/134 [==============================] - 0s 1ms/step - loss: 0.0487 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.0032 43/134 [========>.....................] - ETA: 0s - loss: 0.0345 83/134 [=================>............] - ETA: 0s - loss: 0.0448 129/134 [===========================>..] - ETA: 0s - loss: 0.0444 134/134 [==============================] - 0s 1ms/step - loss: 0.0433 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.0176 48/134 [=========>....................] - ETA: 0s - loss: 0.0217 95/134 [====================>.........] - ETA: 0s - loss: 0.0359 134/134 [==============================] - 0s 1ms/step - loss: 0.0398 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0139 46/134 [=========>....................] - ETA: 0s - loss: 0.0365 91/134 [===================>..........] - ETA: 0s - loss: 0.0389 134/134 [==============================] - 0s 1ms/step - loss: 0.0373 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.0087 47/134 [=========>....................] - ETA: 0s - loss: 0.0433 92/134 [===================>..........] - ETA: 0s - loss: 0.0372 134/134 [==============================] - ETA: 0s - loss: 0.0364 134/134 [==============================] - 0s 1ms/step - loss: 0.0364 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0030 47/134 [=========>....................] - ETA: 0s - loss: 0.0486 93/134 [===================>..........] - ETA: 0s - loss: 0.0369 134/134 [==============================] - 0s 1ms/step - loss: 0.0338 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0063 49/134 [=========>....................] - ETA: 0s - loss: 0.0256 97/134 [====================>.........] - ETA: 0s - loss: 0.0294 134/134 [==============================] - 0s 1ms/step - loss: 0.0318 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0105 49/134 [=========>....................] - ETA: 0s - loss: 0.0331 94/134 [====================>.........] - ETA: 0s - loss: 0.0328 134/134 [==============================] - 0s 1ms/step - loss: 0.0300 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0192 49/134 [=========>....................] - ETA: 0s - loss: 0.0410 96/134 [====================>.........] - ETA: 0s - loss: 0.0309 134/134 [==============================] - 0s 1ms/step - loss: 0.0284 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0878 42/134 [========>.....................] - ETA: 0s - loss: 0.0351 83/134 [=================>............] - ETA: 0s - loss: 0.0280 128/134 [===========================>..] - ETA: 0s - loss: 0.0270 134/134 [==============================] - 0s 1ms/step - loss: 0.0265 -> test with GAN.predict GAN tn, fp: 327, 4 GAN fn, tp: 1, 12 GAN f1 score: 0.828 GAN cohens kappa score: 0.820 -> test with 'LR' LR tn, fp: 299, 32 LR fn, tp: 0, 13 LR f1 score: 0.448 LR cohens kappa score: 0.414 LR average precision score: 0.324 -> test with 'RF' RF tn, fp: 328, 3 RF fn, tp: 2, 11 RF f1 score: 0.815 RF cohens kappa score: 0.807 -> 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: 316, 15 KNN fn, tp: 0, 13 KNN f1 score: 0.634 KNN cohens kappa score: 0.614 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0037 49/133 [==========>...................] - ETA: 0s - loss: 0.0225  97/133 [====================>.........] - ETA: 0s - loss: 0.0314 128/133 [===========================>..] - ETA: 0s - loss: 0.0281 133/133 [==============================] - 0s 1ms/step - loss: 0.0272 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 9.5077e-04 28/133 [=====>........................] - ETA: 0s - loss: 0.0220  59/133 [============>.................] - ETA: 0s - loss: 0.0203 88/133 [==================>...........] - ETA: 0s - loss: 0.0191 114/133 [========================>.....] - ETA: 0s - loss: 0.0231 133/133 [==============================] - 0s 2ms/step - loss: 0.0231 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0392 27/133 [=====>........................] - ETA: 0s - loss: 0.0194 65/133 [=============>................] - ETA: 0s - loss: 0.0260 105/133 [======================>.......] - ETA: 0s - loss: 0.0234 133/133 [==============================] - 0s 2ms/step - loss: 0.0228 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0179 31/133 [=====>........................] - ETA: 0s - loss: 0.0184 59/133 [============>.................] - ETA: 0s - loss: 0.0223 90/133 [===================>..........] - ETA: 0s - loss: 0.0222 131/133 [============================>.] - ETA: 0s - loss: 0.0192 133/133 [==============================] - 0s 2ms/step - loss: 0.0190 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0079 32/133 [======>.......................] - ETA: 0s - loss: 0.0170 61/133 [============>.................] - ETA: 0s - loss: 0.0171 94/133 [====================>.........] - ETA: 0s - loss: 0.0167 133/133 [==============================] - 0s 2ms/step - loss: 0.0180 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0108 49/133 [==========>...................] - ETA: 0s - loss: 0.0212 96/133 [====================>.........] - ETA: 0s - loss: 0.0167 132/133 [============================>.] - ETA: 0s - loss: 0.0170 133/133 [==============================] - 0s 1ms/step - loss: 0.0173 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0056 31/133 [=====>........................] - ETA: 0s - loss: 0.0137 63/133 [=============>................] - ETA: 0s - loss: 0.0140 93/133 [===================>..........] - ETA: 0s - loss: 0.0152 124/133 [==========================>...] - ETA: 0s - loss: 0.0160 133/133 [==============================] - 0s 2ms/step - loss: 0.0158 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0238 32/133 [======>.......................] - ETA: 0s - loss: 0.0142 63/133 [=============>................] - ETA: 0s - loss: 0.0140 102/133 [======================>.......] - ETA: 0s - loss: 0.0125 133/133 [==============================] - ETA: 0s - loss: 0.0147 133/133 [==============================] - 0s 2ms/step - loss: 0.0147 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0047 32/133 [======>.......................] - ETA: 0s - loss: 0.0133 59/133 [============>.................] - ETA: 0s - loss: 0.0162 86/133 [==================>...........] - ETA: 0s - loss: 0.0133 111/133 [========================>.....] - ETA: 0s - loss: 0.0131 133/133 [==============================] - 0s 2ms/step - loss: 0.0148 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0049 32/133 [======>.......................] - ETA: 0s - loss: 0.0163 62/133 [============>.................] - ETA: 0s - loss: 0.0115 92/133 [===================>..........] - ETA: 0s - loss: 0.0131 123/133 [==========================>...] - ETA: 0s - loss: 0.0135 133/133 [==============================] - 0s 2ms/step - loss: 0.0136 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 4, 9 GAN f1 score: 0.692 GAN cohens kappa score: 0.680 -> test with 'LR' LR tn, fp: 273, 60 LR fn, tp: 0, 13 LR f1 score: 0.302 LR cohens kappa score: 0.255 LR average precision score: 0.316 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 2, 11 RF f1 score: 0.917 RF cohens kappa score: 0.914 -> test with 'GB' GB tn, fp: 332, 1 GB fn, tp: 2, 11 GB f1 score: 0.880 GB cohens kappa score: 0.876 -> test with 'KNN' KNN tn, fp: 318, 15 KNN fn, tp: 0, 13 KNN f1 score: 0.634 KNN cohens kappa score: 0.614 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 24s - loss: 0.0101 22/133 [===>..........................] - ETA: 0s - loss: 0.0186  41/133 [========>.....................] - ETA: 0s - loss: 0.0208 54/133 [===========>..................] - ETA: 0s - loss: 0.0182 81/133 [=================>............] - ETA: 0s - loss: 0.0406 106/133 [======================>.......] - ETA: 0s - loss: 0.0416 133/133 [==============================] - 0s 2ms/step - loss: 0.0375 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 30/133 [=====>........................] - ETA: 0s - loss: 0.0221 61/133 [============>.................] - ETA: 0s - loss: 0.0260 86/133 [==================>...........] - ETA: 0s - loss: 0.0293 107/133 [=======================>......] - ETA: 0s - loss: 0.0291 133/133 [==============================] - 0s 2ms/step - loss: 0.0304 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0014 31/133 [=====>........................] - ETA: 0s - loss: 0.0234 53/133 [==========>...................] - ETA: 0s - loss: 0.0242 80/133 [=================>............] - ETA: 0s - loss: 0.0208 115/133 [========================>.....] - ETA: 0s - loss: 0.0237 133/133 [==============================] - 0s 2ms/step - loss: 0.0252 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0330 37/133 [=======>......................] - ETA: 0s - loss: 0.0266 75/133 [===============>..............] - ETA: 0s - loss: 0.0199 109/133 [=======================>......] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 1ms/step - loss: 0.0219 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0085 33/133 [======>.......................] - ETA: 0s - loss: 0.0178 72/133 [===============>..............] - ETA: 0s - loss: 0.0182 113/133 [========================>.....] - ETA: 0s - loss: 0.0214 133/133 [==============================] - 0s 1ms/step - loss: 0.0223 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0062 42/133 [========>.....................] - ETA: 0s - loss: 0.0188 84/133 [=================>............] - ETA: 0s - loss: 0.0215 126/133 [===========================>..] - ETA: 0s - loss: 0.0209 133/133 [==============================] - 0s 1ms/step - loss: 0.0203 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0157 41/133 [========>.....................] - ETA: 0s - loss: 0.0142 82/133 [=================>............] - ETA: 0s - loss: 0.0225 119/133 [=========================>....] - ETA: 0s - loss: 0.0192 133/133 [==============================] - 0s 1ms/step - loss: 0.0188 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0019 41/133 [========>.....................] - ETA: 0s - loss: 0.0129 81/133 [=================>............] - ETA: 0s - loss: 0.0186 122/133 [==========================>...] - ETA: 0s - loss: 0.0179 133/133 [==============================] - 0s 1ms/step - loss: 0.0176 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0117 40/133 [========>.....................] - ETA: 0s - loss: 0.0112 82/133 [=================>............] - ETA: 0s - loss: 0.0119 118/133 [=========================>....] - ETA: 0s - loss: 0.0174 133/133 [==============================] - 0s 1ms/step - loss: 0.0180 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 7.1091e-04 51/133 [==========>...................] - ETA: 0s - loss: 0.0244  101/133 [=====================>........] - ETA: 0s - loss: 0.0184 133/133 [==============================] - 0s 1ms/step - loss: 0.0169 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 3, 10 GAN f1 score: 0.741 GAN cohens kappa score: 0.730 -> test with 'LR' LR tn, fp: 297, 36 LR fn, tp: 2, 11 LR f1 score: 0.367 LR cohens kappa score: 0.327 LR average precision score: 0.359 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 3, 10 RF f1 score: 0.870 RF cohens kappa score: 0.865 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 320, 13 KNN fn, tp: 0, 13 KNN f1 score: 0.667 KNN cohens kappa score: 0.649 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 27s - loss: 0.0319 28/133 [=====>........................] - ETA: 0s - loss: 0.0262  57/133 [===========>..................] - ETA: 0s - loss: 0.0213 89/133 [===================>..........] - ETA: 0s - loss: 0.0288 123/133 [==========================>...] - ETA: 0s - loss: 0.0298 133/133 [==============================] - 0s 2ms/step - loss: 0.0314 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0020 36/133 [=======>......................] - ETA: 0s - loss: 0.0332 71/133 [===============>..............] - ETA: 0s - loss: 0.0331 106/133 [======================>.......] - ETA: 0s - loss: 0.0287 133/133 [==============================] - 0s 1ms/step - loss: 0.0256 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0048 36/133 [=======>......................] - ETA: 0s - loss: 0.0337 72/133 [===============>..............] - ETA: 0s - loss: 0.0326 109/133 [=======================>......] - ETA: 0s - loss: 0.0248 133/133 [==============================] - 0s 1ms/step - loss: 0.0257 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0049 28/133 [=====>........................] - ETA: 0s - loss: 0.0306 58/133 [============>.................] - ETA: 0s - loss: 0.0298 94/133 [====================>.........] - ETA: 0s - loss: 0.0225 128/133 [===========================>..] - ETA: 0s - loss: 0.0224 133/133 [==============================] - 0s 2ms/step - loss: 0.0236 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0868 34/133 [======>.......................] - ETA: 0s - loss: 0.0284 71/133 [===============>..............] - ETA: 0s - loss: 0.0249 105/133 [======================>.......] - ETA: 0s - loss: 0.0215 133/133 [==============================] - 0s 1ms/step - loss: 0.0202 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 5.8253e-04 34/133 [======>.......................] - ETA: 0s - loss: 0.0123  69/133 [==============>...............] - ETA: 0s - loss: 0.0176 105/133 [======================>.......] - ETA: 0s - loss: 0.0189 133/133 [==============================] - ETA: 0s - loss: 0.0199 133/133 [==============================] - 0s 2ms/step - loss: 0.0199 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.1152 28/133 [=====>........................] - ETA: 0s - loss: 0.0247 60/133 [============>.................] - ETA: 0s - loss: 0.0257 96/133 [====================>.........] - ETA: 0s - loss: 0.0188 131/133 [============================>.] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 2ms/step - loss: 0.0192 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0039 36/133 [=======>......................] - ETA: 0s - loss: 0.0224 72/133 [===============>..............] - ETA: 0s - loss: 0.0225 102/133 [======================>.......] - ETA: 0s - loss: 0.0204 133/133 [==============================] - 0s 2ms/step - loss: 0.0194 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0053 35/133 [======>.......................] - ETA: 0s - loss: 0.0152 71/133 [===============>..............] - ETA: 0s - loss: 0.0160 106/133 [======================>.......] - ETA: 0s - loss: 0.0186 133/133 [==============================] - 0s 1ms/step - loss: 0.0181 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0030 31/133 [=====>........................] - ETA: 0s - loss: 0.0234 65/133 [=============>................] - ETA: 0s - loss: 0.0205 98/133 [=====================>........] - ETA: 0s - loss: 0.0173 127/133 [===========================>..] - ETA: 0s - loss: 0.0160 133/133 [==============================] - 0s 2ms/step - loss: 0.0169 -> test with GAN.predict GAN tn, fp: 330, 3 GAN fn, tp: 3, 10 GAN f1 score: 0.769 GAN cohens kappa score: 0.760 -> test with 'LR' LR tn, fp: 303, 30 LR fn, tp: 1, 12 LR f1 score: 0.436 LR cohens kappa score: 0.402 LR average precision score: 0.351 -> test with 'RF' RF tn, fp: 333, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.959 -> test with 'GB' GB tn, fp: 333, 0 GB fn, tp: 0, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 -> test with 'KNN' KNN tn, fp: 326, 7 KNN fn, tp: 0, 13 KNN f1 score: 0.788 KNN cohens kappa score: 0.778 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1278 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 30s - loss: 0.3633 23/133 [====>.........................] - ETA: 0s - loss: 0.0388  46/133 [=========>....................] - ETA: 0s - loss: 0.0343 74/133 [===============>..............] - ETA: 0s - loss: 0.0386 95/133 [====================>.........] - ETA: 0s - loss: 0.0366 117/133 [=========================>....] - ETA: 0s - loss: 0.0347 133/133 [==============================] - 1s 2ms/step - loss: 0.0354 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.2635 29/133 [=====>........................] - ETA: 0s - loss: 0.0433 55/133 [===========>..................] - ETA: 0s - loss: 0.0352 81/133 [=================>............] - ETA: 0s - loss: 0.0350 106/133 [======================>.......] - ETA: 0s - loss: 0.0334 133/133 [==============================] - 0s 2ms/step - loss: 0.0316 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0027 34/133 [======>.......................] - ETA: 0s - loss: 0.0203 65/133 [=============>................] - ETA: 0s - loss: 0.0305 91/133 [===================>..........] - ETA: 0s - loss: 0.0309 116/133 [=========================>....] - ETA: 0s - loss: 0.0296 133/133 [==============================] - 0s 2ms/step - loss: 0.0287 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0027 32/133 [======>.......................] - ETA: 0s - loss: 0.0261 65/133 [=============>................] - ETA: 0s - loss: 0.0228 97/133 [====================>.........] - ETA: 0s - loss: 0.0231 128/133 [===========================>..] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 2ms/step - loss: 0.0259 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0101 32/133 [======>.......................] - ETA: 0s - loss: 0.0285 58/133 [============>.................] - ETA: 0s - loss: 0.0228 84/133 [=================>............] - ETA: 0s - loss: 0.0235 115/133 [========================>.....] - ETA: 0s - loss: 0.0229 133/133 [==============================] - 0s 2ms/step - loss: 0.0236 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0080 30/133 [=====>........................] - ETA: 0s - loss: 0.0221 60/133 [============>.................] - ETA: 0s - loss: 0.0269 91/133 [===================>..........] - ETA: 0s - loss: 0.0212 122/133 [==========================>...] - ETA: 0s - loss: 0.0233 133/133 [==============================] - 0s 2ms/step - loss: 0.0239 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 33/133 [======>.......................] - ETA: 0s - loss: 0.0164 64/133 [=============>................] - ETA: 0s - loss: 0.0183 94/133 [====================>.........] - ETA: 0s - loss: 0.0148 124/133 [==========================>...] - ETA: 0s - loss: 0.0203 133/133 [==============================] - 0s 2ms/step - loss: 0.0213 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0039 29/133 [=====>........................] - ETA: 0s - loss: 0.0153 58/133 [============>.................] - ETA: 0s - loss: 0.0170 89/133 [===================>..........] - ETA: 0s - loss: 0.0159 122/133 [==========================>...] - ETA: 0s - loss: 0.0155 133/133 [==============================] - 0s 2ms/step - loss: 0.0188 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0035 33/133 [======>.......................] - ETA: 0s - loss: 0.0214 65/133 [=============>................] - ETA: 0s - loss: 0.0211 97/133 [====================>.........] - ETA: 0s - loss: 0.0197 128/133 [===========================>..] - ETA: 0s - loss: 0.0181 133/133 [==============================] - 0s 2ms/step - loss: 0.0183 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0054 33/133 [======>.......................] - ETA: 0s - loss: 0.0189 65/133 [=============>................] - ETA: 0s - loss: 0.0158 93/133 [===================>..........] - ETA: 0s - loss: 0.0172 122/133 [==========================>...] - ETA: 0s - loss: 0.0162 133/133 [==============================] - 0s 2ms/step - loss: 0.0163 -> test with GAN.predict GAN tn, fp: 329, 4 GAN fn, tp: 1, 12 GAN f1 score: 0.828 GAN cohens kappa score: 0.820 -> test with 'LR' LR tn, fp: 283, 50 LR fn, tp: 0, 13 LR f1 score: 0.342 LR cohens kappa score: 0.298 LR average precision score: 0.277 -> test with 'RF' RF tn, fp: 332, 1 RF fn, tp: 2, 11 RF f1 score: 0.880 RF cohens kappa score: 0.876 -> test with 'GB' GB tn, fp: 331, 2 GB fn, tp: 0, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 321, 12 KNN fn, tp: 0, 13 KNN f1 score: 0.684 KNN cohens kappa score: 0.668 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1280 synthetic samples -> retrain GAN for predict Epoch 1/10 1/134 [..............................] - ETA: 48s - loss: 0.0643 24/134 [====>.........................] - ETA: 0s - loss: 0.0397  47/134 [=========>....................] - ETA: 0s - loss: 0.0430 72/134 [===============>..............] - ETA: 0s - loss: 0.0357 94/134 [====================>.........] - ETA: 0s - loss: 0.0360 112/134 [========================>.....] - ETA: 0s - loss: 0.0403 131/134 [============================>.] - ETA: 0s - loss: 0.0376 134/134 [==============================] - 1s 2ms/step - loss: 0.0372 Epoch 2/10 1/134 [..............................] - ETA: 0s - loss: 0.1076 29/134 [=====>........................] - ETA: 0s - loss: 0.0304 58/134 [===========>..................] - ETA: 0s - loss: 0.0341 88/134 [==================>...........] - ETA: 0s - loss: 0.0356 116/134 [========================>.....] - ETA: 0s - loss: 0.0335 134/134 [==============================] - 0s 2ms/step - loss: 0.0316 Epoch 3/10 1/134 [..............................] - ETA: 0s - loss: 0.0157 27/134 [=====>........................] - ETA: 0s - loss: 0.0342 57/134 [===========>..................] - ETA: 0s - loss: 0.0310 86/134 [==================>...........] - ETA: 0s - loss: 0.0314 115/134 [========================>.....] - ETA: 0s - loss: 0.0301 134/134 [==============================] - 0s 2ms/step - loss: 0.0285 Epoch 4/10 1/134 [..............................] - ETA: 0s - loss: 0.0046 26/134 [====>.........................] - ETA: 0s - loss: 0.0147 52/134 [==========>...................] - ETA: 0s - loss: 0.0156 82/134 [=================>............] - ETA: 0s - loss: 0.0239 112/134 [========================>.....] - ETA: 0s - loss: 0.0241 134/134 [==============================] - 0s 2ms/step - loss: 0.0250 Epoch 5/10 1/134 [..............................] - ETA: 0s - loss: 0.0439 31/134 [=====>........................] - ETA: 0s - loss: 0.0215 61/134 [============>.................] - ETA: 0s - loss: 0.0267 91/134 [===================>..........] - ETA: 0s - loss: 0.0224 121/134 [==========================>...] - ETA: 0s - loss: 0.0236 134/134 [==============================] - 0s 2ms/step - loss: 0.0229 Epoch 6/10 1/134 [..............................] - ETA: 0s - loss: 0.0139 31/134 [=====>........................] - ETA: 0s - loss: 0.0200 61/134 [============>.................] - ETA: 0s - loss: 0.0214 88/134 [==================>...........] - ETA: 0s - loss: 0.0233 112/134 [========================>.....] - ETA: 0s - loss: 0.0217 134/134 [==============================] - 0s 2ms/step - loss: 0.0201 Epoch 7/10 1/134 [..............................] - ETA: 0s - loss: 0.0026 32/134 [======>.......................] - ETA: 0s - loss: 0.0142 61/134 [============>.................] - ETA: 0s - loss: 0.0150 90/134 [===================>..........] - ETA: 0s - loss: 0.0179 118/134 [=========================>....] - ETA: 0s - loss: 0.0183 134/134 [==============================] - 0s 2ms/step - loss: 0.0186 Epoch 8/10 1/134 [..............................] - ETA: 0s - loss: 0.0012 31/134 [=====>........................] - ETA: 0s - loss: 0.0182 60/134 [============>.................] - ETA: 0s - loss: 0.0180 90/134 [===================>..........] - ETA: 0s - loss: 0.0185 120/134 [=========================>....] - ETA: 0s - loss: 0.0173 134/134 [==============================] - 0s 2ms/step - loss: 0.0167 Epoch 9/10 1/134 [..............................] - ETA: 0s - loss: 0.0118 27/134 [=====>........................] - ETA: 0s - loss: 0.0196 52/134 [==========>...................] - ETA: 0s - loss: 0.0191 78/134 [================>.............] - ETA: 0s - loss: 0.0179 107/134 [======================>.......] - ETA: 0s - loss: 0.0162 130/134 [============================>.] - ETA: 0s - loss: 0.0149 134/134 [==============================] - 0s 2ms/step - loss: 0.0147 Epoch 10/10 1/134 [..............................] - ETA: 0s - loss: 0.0025 30/134 [=====>........................] - ETA: 0s - loss: 0.0119 59/134 [============>.................] - ETA: 0s - loss: 0.0138 86/134 [==================>...........] - ETA: 0s - loss: 0.0133 113/134 [========================>.....] - ETA: 0s - loss: 0.0145 134/134 [==============================] - 0s 2ms/step - loss: 0.0137 -> test with GAN.predict GAN tn, fp: 327, 4 GAN fn, tp: 2, 11 GAN f1 score: 0.786 GAN cohens kappa score: 0.777 -> test with 'LR' LR tn, fp: 289, 42 LR fn, tp: 0, 13 LR f1 score: 0.382 LR cohens kappa score: 0.342 LR average precision score: 0.532 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 1, 12 RF f1 score: 0.960 RF cohens kappa score: 0.958 -> test with 'GB' GB tn, fp: 329, 2 GB fn, tp: 0, 13 GB f1 score: 0.929 GB cohens kappa score: 0.926 -> test with 'KNN' KNN tn, fp: 322, 9 KNN fn, tp: 0, 13 KNN f1 score: 0.743 KNN cohens kappa score: 0.730 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 303, 60 LR fn, tp: 2, 13 LR f1 score: 0.448 LR cohens kappa score: 0.414 LR average precision score: 0.534 average: LR tn, fp: 291.32, 41.28 LR fn, tp: 0.56, 12.44 LR f1 score: 0.377 LR cohens kappa score: 0.337 LR average precision score: 0.365 minimum: LR tn, fp: 273, 30 LR fn, tp: 0, 11 LR f1 score: 0.302 LR cohens kappa score: 0.255 LR average precision score: 0.274 -----[ RF ]----- maximum: RF tn, fp: 333, 3 RF fn, tp: 7, 13 RF f1 score: 1.000 RF cohens kappa score: 1.000 average: RF tn, fp: 332.32, 0.28 RF fn, tp: 1.96, 11.04 RF f1 score: 0.904 RF cohens kappa score: 0.901 minimum: RF tn, fp: 328, 0 RF fn, tp: 0, 6 RF f1 score: 0.600 RF cohens kappa score: 0.589 -----[ GB ]----- maximum: GB tn, fp: 333, 5 GB fn, tp: 2, 13 GB f1 score: 1.000 GB cohens kappa score: 1.000 average: GB tn, fp: 331.68, 0.92 GB fn, tp: 0.4, 12.6 GB f1 score: 0.951 GB cohens kappa score: 0.949 minimum: GB tn, fp: 328, 0 GB fn, tp: 0, 11 GB f1 score: 0.839 GB cohens kappa score: 0.831 -----[ KNN ]----- maximum: KNN tn, fp: 328, 23 KNN fn, tp: 1, 13 KNN f1 score: 0.839 KNN cohens kappa score: 0.831 average: KNN tn, fp: 321.04, 11.56 KNN fn, tp: 0.08, 12.92 KNN f1 score: 0.700 KNN cohens kappa score: 0.684 minimum: KNN tn, fp: 310, 5 KNN fn, tp: 0, 12 KNN f1 score: 0.531 KNN cohens kappa score: 0.503 -----[ GAN ]----- maximum: GAN tn, fp: 333, 8 GAN fn, tp: 6, 13 GAN f1 score: 0.960 GAN cohens kappa score: 0.959 average: GAN tn, fp: 328.44, 4.16 GAN fn, tp: 2.12, 10.88 GAN f1 score: 0.776 GAN cohens kappa score: 0.766 minimum: GAN tn, fp: 325, 0 GAN fn, tp: 0, 7 GAN f1 score: 0.538 GAN cohens kappa score: 0.520