/////////////////////////////////////////// // Running convGAN-majority-5 on folding_car_good /////////////////////////////////////////// Load 'data_input/folding_car_good' from pickle file Data loaded. -> Shuffling data ### Start exercise for synthetic point generator ====== Step 1/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 1/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 21s - loss: 0.0111 36/133 [=======>......................] - ETA: 0s - loss: 0.0348  76/133 [================>.............] - ETA: 0s - loss: 0.0314 110/133 [=======================>......] - ETA: 0s - loss: 0.0381 133/133 [==============================] - 0s 1ms/step - loss: 0.0384 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0811 40/133 [========>.....................] - ETA: 0s - loss: 0.0478 79/133 [================>.............] - ETA: 0s - loss: 0.0362 120/133 [==========================>...] - ETA: 0s - loss: 0.0368 133/133 [==============================] - 0s 1ms/step - loss: 0.0374 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0107 47/133 [=========>....................] - ETA: 0s - loss: 0.0451 91/133 [===================>..........] - ETA: 0s - loss: 0.0383 133/133 [==============================] - 0s 1ms/step - loss: 0.0333 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0092 43/133 [========>.....................] - ETA: 0s - loss: 0.0364 88/133 [==================>...........] - ETA: 0s - loss: 0.0315 132/133 [============================>.] - ETA: 0s - loss: 0.0329 133/133 [==============================] - 0s 1ms/step - loss: 0.0332 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0152 46/133 [=========>....................] - ETA: 0s - loss: 0.0404 92/133 [===================>..........] - ETA: 0s - loss: 0.0296 133/133 [==============================] - 0s 1ms/step - loss: 0.0311 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0134 44/133 [========>.....................] - ETA: 0s - loss: 0.0216 90/133 [===================>..........] - ETA: 0s - loss: 0.0296 133/133 [==============================] - 0s 1ms/step - loss: 0.0304 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0073 48/133 [=========>....................] - ETA: 0s - loss: 0.0187 94/133 [====================>.........] - ETA: 0s - loss: 0.0280 133/133 [==============================] - 0s 1ms/step - loss: 0.0291 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0140 48/133 [=========>....................] - ETA: 0s - loss: 0.0215 93/133 [===================>..........] - ETA: 0s - loss: 0.0277 133/133 [==============================] - 0s 1ms/step - loss: 0.0277 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0770 38/133 [=======>......................] - ETA: 0s - loss: 0.0220 77/133 [================>.............] - ETA: 0s - loss: 0.0244 115/133 [========================>.....] - ETA: 0s - loss: 0.0267 133/133 [==============================] - 0s 1ms/step - loss: 0.0266 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0076 46/133 [=========>....................] - ETA: 0s - loss: 0.0182 90/133 [===================>..........] - ETA: 0s - loss: 0.0244 133/133 [==============================] - 0s 1ms/step - loss: 0.0254 -> test with GAN.predict GAN tn, fp: 328, 4 GAN fn, tp: 0, 14 GAN f1 score: 0.875 GAN cohens kappa score: 0.869 -> test with 'LR' LR tn, fp: 176, 156 LR fn, tp: 5, 9 LR f1 score: 0.101 LR cohens kappa score: 0.028 LR average precision score: 0.059 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 4, 10 RF f1 score: 0.833 RF cohens kappa score: 0.828 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 4, 10 GB f1 score: 0.769 GB cohens kappa score: 0.760 -> test with 'KNN' KNN tn, fp: 311, 21 KNN fn, tp: 1, 13 KNN f1 score: 0.542 KNN cohens kappa score: 0.514 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0552 47/133 [=========>....................] - ETA: 0s - loss: 0.0453  92/133 [===================>..........] - ETA: 0s - loss: 0.0459 133/133 [==============================] - 0s 1ms/step - loss: 0.0424 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.2267 47/133 [=========>....................] - ETA: 0s - loss: 0.0448 93/133 [===================>..........] - ETA: 0s - loss: 0.0414 133/133 [==============================] - 0s 1ms/step - loss: 0.0395 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0112 47/133 [=========>....................] - ETA: 0s - loss: 0.0431 92/133 [===================>..........] - ETA: 0s - loss: 0.0417 133/133 [==============================] - 0s 1ms/step - loss: 0.0399 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0260 47/133 [=========>....................] - ETA: 0s - loss: 0.0362 93/133 [===================>..........] - ETA: 0s - loss: 0.0386 133/133 [==============================] - 0s 1ms/step - loss: 0.0357 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0906 47/133 [=========>....................] - ETA: 0s - loss: 0.0276 93/133 [===================>..........] - ETA: 0s - loss: 0.0332 133/133 [==============================] - 0s 1ms/step - loss: 0.0349 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0427 48/133 [=========>....................] - ETA: 0s - loss: 0.0278 94/133 [====================>.........] - ETA: 0s - loss: 0.0314 133/133 [==============================] - 0s 1ms/step - loss: 0.0322 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0459 45/133 [=========>....................] - ETA: 0s - loss: 0.0203 87/133 [==================>...........] - ETA: 0s - loss: 0.0251 133/133 [==============================] - ETA: 0s - loss: 0.0305 133/133 [==============================] - 0s 1ms/step - loss: 0.0305 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0217 48/133 [=========>....................] - ETA: 0s - loss: 0.0263 93/133 [===================>..........] - ETA: 0s - loss: 0.0295 133/133 [==============================] - 0s 1ms/step - loss: 0.0304 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0150 42/133 [========>.....................] - ETA: 0s - loss: 0.0348 82/133 [=================>............] - ETA: 0s - loss: 0.0289 121/133 [==========================>...] - ETA: 0s - loss: 0.0288 133/133 [==============================] - 0s 1ms/step - loss: 0.0283 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0081 47/133 [=========>....................] - ETA: 0s - loss: 0.0312 94/133 [====================>.........] - ETA: 0s - loss: 0.0318 133/133 [==============================] - 0s 1ms/step - loss: 0.0270 -> test with GAN.predict GAN tn, fp: 326, 6 GAN fn, tp: 2, 12 GAN f1 score: 0.750 GAN cohens kappa score: 0.738 -> test with 'LR' LR tn, fp: 180, 152 LR fn, tp: 4, 10 LR f1 score: 0.114 LR cohens kappa score: 0.042 LR average precision score: 0.083 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 5, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 4, 10 GB f1 score: 0.769 GB cohens kappa score: 0.760 -> test with 'KNN' KNN tn, fp: 303, 29 KNN fn, tp: 1, 13 KNN f1 score: 0.464 KNN cohens kappa score: 0.430 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.1097 45/133 [=========>....................] - ETA: 0s - loss: 0.0386  89/133 [===================>..........] - ETA: 0s - loss: 0.0387 133/133 [==============================] - 0s 1ms/step - loss: 0.0388 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0175 11/133 [=>............................] - ETA: 1s - loss: 0.0619 57/133 [===========>..................] - ETA: 0s - loss: 0.0456 105/133 [======================>.......] - ETA: 0s - loss: 0.0384 133/133 [==============================] - 0s 2ms/step - loss: 0.0364 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0149 49/133 [==========>...................] - ETA: 0s - loss: 0.0359 97/133 [====================>.........] - ETA: 0s - loss: 0.0370 133/133 [==============================] - 0s 1ms/step - loss: 0.0351 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0099 49/133 [==========>...................] - ETA: 0s - loss: 0.0287 97/133 [====================>.........] - ETA: 0s - loss: 0.0299 133/133 [==============================] - 0s 1ms/step - loss: 0.0328 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0285 49/133 [==========>...................] - ETA: 0s - loss: 0.0362 96/133 [====================>.........] - ETA: 0s - loss: 0.0332 133/133 [==============================] - 0s 1ms/step - loss: 0.0335 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0514 49/133 [==========>...................] - ETA: 0s - loss: 0.0317 96/133 [====================>.........] - ETA: 0s - loss: 0.0332 133/133 [==============================] - 0s 1ms/step - loss: 0.0304 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0115 47/133 [=========>....................] - ETA: 0s - loss: 0.0196 93/133 [===================>..........] - ETA: 0s - loss: 0.0261 133/133 [==============================] - 0s 1ms/step - loss: 0.0293 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0257 49/133 [==========>...................] - ETA: 0s - loss: 0.0387 97/133 [====================>.........] - ETA: 0s - loss: 0.0324 133/133 [==============================] - 0s 1ms/step - loss: 0.0282 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 49/133 [==========>...................] - ETA: 0s - loss: 0.0226 97/133 [====================>.........] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 1ms/step - loss: 0.0271 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0092 48/133 [=========>....................] - ETA: 0s - loss: 0.0270 95/133 [====================>.........] - ETA: 0s - loss: 0.0297 133/133 [==============================] - 0s 1ms/step - loss: 0.0253 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 2, 12 GAN f1 score: 0.774 GAN cohens kappa score: 0.764 -> test with 'LR' LR tn, fp: 175, 157 LR fn, tp: 5, 9 LR f1 score: 0.100 LR cohens kappa score: 0.027 LR average precision score: 0.058 -> test with 'RF' RF tn, fp: 330, 2 RF fn, tp: 6, 8 RF f1 score: 0.667 RF cohens kappa score: 0.655 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 6, 8 GB f1 score: 0.696 GB cohens kappa score: 0.686 -> test with 'KNN' KNN tn, fp: 303, 29 KNN fn, tp: 2, 12 KNN f1 score: 0.436 KNN cohens kappa score: 0.400 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.1354 46/133 [=========>....................] - ETA: 0s - loss: 0.0404  91/133 [===================>..........] - ETA: 0s - loss: 0.0378 133/133 [==============================] - 0s 1ms/step - loss: 0.0349 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0033 47/133 [=========>....................] - ETA: 0s - loss: 0.0266 92/133 [===================>..........] - ETA: 0s - loss: 0.0300 133/133 [==============================] - 0s 1ms/step - loss: 0.0324 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0292 46/133 [=========>....................] - ETA: 0s - loss: 0.0297 91/133 [===================>..........] - ETA: 0s - loss: 0.0343 133/133 [==============================] - 0s 1ms/step - loss: 0.0312 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.2217 38/133 [=======>......................] - ETA: 0s - loss: 0.0384 81/133 [=================>............] - ETA: 0s - loss: 0.0331 124/133 [==========================>...] - ETA: 0s - loss: 0.0294 133/133 [==============================] - 0s 1ms/step - loss: 0.0291 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0134 43/133 [========>.....................] - ETA: 0s - loss: 0.0243 87/133 [==================>...........] - ETA: 0s - loss: 0.0267 130/133 [============================>.] - ETA: 0s - loss: 0.0285 133/133 [==============================] - 0s 1ms/step - loss: 0.0284 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0069 45/133 [=========>....................] - ETA: 0s - loss: 0.0304 88/133 [==================>...........] - ETA: 0s - loss: 0.0296 133/133 [==============================] - ETA: 0s - loss: 0.0272 133/133 [==============================] - 0s 1ms/step - loss: 0.0272 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 45/133 [=========>....................] - ETA: 0s - loss: 0.0268 89/133 [===================>..........] - ETA: 0s - loss: 0.0268 133/133 [==============================] - ETA: 0s - loss: 0.0256 133/133 [==============================] - 0s 1ms/step - loss: 0.0256 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0121 48/133 [=========>....................] - ETA: 0s - loss: 0.0171 95/133 [====================>.........] - ETA: 0s - loss: 0.0215 133/133 [==============================] - 0s 1ms/step - loss: 0.0250 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0335 48/133 [=========>....................] - ETA: 0s - loss: 0.0277 96/133 [====================>.........] - ETA: 0s - loss: 0.0245 133/133 [==============================] - 0s 1ms/step - loss: 0.0233 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0274 49/133 [==========>...................] - ETA: 0s - loss: 0.0295 97/133 [====================>.........] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 1ms/step - loss: 0.0237 -> test with GAN.predict GAN tn, fp: 323, 9 GAN fn, tp: 3, 11 GAN f1 score: 0.647 GAN cohens kappa score: 0.629 -> test with 'LR' LR tn, fp: 181, 151 LR fn, tp: 3, 11 LR f1 score: 0.125 LR cohens kappa score: 0.055 LR average precision score: 0.076 -> test with 'RF' RF tn, fp: 331, 1 RF fn, tp: 10, 4 RF f1 score: 0.421 RF cohens kappa score: 0.408 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 7, 7 GB f1 score: 0.609 GB cohens kappa score: 0.596 -> test with 'KNN' KNN tn, fp: 317, 15 KNN fn, tp: 0, 14 KNN f1 score: 0.651 KNN cohens kappa score: 0.631 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0226 46/133 [=========>....................] - ETA: 0s - loss: 0.0355  93/133 [===================>..........] - ETA: 0s - loss: 0.0379 133/133 [==============================] - 0s 1ms/step - loss: 0.0376 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0134 48/133 [=========>....................] - ETA: 0s - loss: 0.0341 95/133 [====================>.........] - ETA: 0s - loss: 0.0361 133/133 [==============================] - 0s 1ms/step - loss: 0.0345 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0801 48/133 [=========>....................] - ETA: 0s - loss: 0.0415 95/133 [====================>.........] - ETA: 0s - loss: 0.0338 133/133 [==============================] - 0s 1ms/step - loss: 0.0332 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0719 49/133 [==========>...................] - ETA: 0s - loss: 0.0351 96/133 [====================>.........] - ETA: 0s - loss: 0.0341 133/133 [==============================] - 0s 1ms/step - loss: 0.0313 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0332 48/133 [=========>....................] - ETA: 0s - loss: 0.0343 95/133 [====================>.........] - ETA: 0s - loss: 0.0314 133/133 [==============================] - 0s 1ms/step - loss: 0.0301 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0167 49/133 [==========>...................] - ETA: 0s - loss: 0.0292 97/133 [====================>.........] - ETA: 0s - loss: 0.0293 133/133 [==============================] - 0s 1ms/step - loss: 0.0287 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0051 41/133 [========>.....................] - ETA: 0s - loss: 0.0319 79/133 [================>.............] - ETA: 0s - loss: 0.0316 120/133 [==========================>...] - ETA: 0s - loss: 0.0270 133/133 [==============================] - 0s 1ms/step - loss: 0.0279 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0426 47/133 [=========>....................] - ETA: 0s - loss: 0.0263 94/133 [====================>.........] - ETA: 0s - loss: 0.0273 133/133 [==============================] - 0s 1ms/step - loss: 0.0254 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0043 48/133 [=========>....................] - ETA: 0s - loss: 0.0260 96/133 [====================>.........] - ETA: 0s - loss: 0.0250 133/133 [==============================] - 0s 1ms/step - loss: 0.0238 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0046 48/133 [=========>....................] - ETA: 0s - loss: 0.0230 93/133 [===================>..........] - ETA: 0s - loss: 0.0243 133/133 [==============================] - 0s 1ms/step - loss: 0.0235 -> test with GAN.predict GAN tn, fp: 324, 7 GAN fn, tp: 2, 11 GAN f1 score: 0.710 GAN cohens kappa score: 0.696 -> test with 'LR' LR tn, fp: 179, 152 LR fn, tp: 4, 9 LR f1 score: 0.103 LR cohens kappa score: 0.036 LR average precision score: 0.057 -> test with 'RF' RF tn, fp: 329, 2 RF fn, tp: 9, 4 RF f1 score: 0.421 RF cohens kappa score: 0.407 -> test with 'GB' GB tn, fp: 328, 3 GB fn, tp: 3, 10 GB f1 score: 0.769 GB cohens kappa score: 0.760 -> test with 'KNN' KNN tn, fp: 312, 19 KNN fn, tp: 2, 11 KNN f1 score: 0.512 KNN cohens kappa score: 0.484 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0146 45/133 [=========>....................] - ETA: 0s - loss: 0.0300  91/133 [===================>..........] - ETA: 0s - loss: 0.0327 131/133 [============================>.] - ETA: 0s - loss: 0.0319 133/133 [==============================] - 0s 1ms/step - loss: 0.0322 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0083 42/133 [========>.....................] - ETA: 0s - loss: 0.0297 84/133 [=================>............] - ETA: 0s - loss: 0.0298 130/133 [============================>.] - ETA: 0s - loss: 0.0278 133/133 [==============================] - 0s 1ms/step - loss: 0.0282 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0308 47/133 [=========>....................] - ETA: 0s - loss: 0.0271 93/133 [===================>..........] - ETA: 0s - loss: 0.0270 133/133 [==============================] - 0s 1ms/step - loss: 0.0271 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0067 48/133 [=========>....................] - ETA: 0s - loss: 0.0376 94/133 [====================>.........] - ETA: 0s - loss: 0.0294 133/133 [==============================] - 0s 1ms/step - loss: 0.0260 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.1871 47/133 [=========>....................] - ETA: 0s - loss: 0.0271 92/133 [===================>..........] - ETA: 0s - loss: 0.0243 133/133 [==============================] - 0s 1ms/step - loss: 0.0248 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0034 47/133 [=========>....................] - ETA: 0s - loss: 0.0261 92/133 [===================>..........] - ETA: 0s - loss: 0.0233 133/133 [==============================] - 0s 1ms/step - loss: 0.0238 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0067 49/133 [==========>...................] - ETA: 0s - loss: 0.0143 95/133 [====================>.........] - ETA: 0s - loss: 0.0194 133/133 [==============================] - 0s 1ms/step - loss: 0.0223 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0028 47/133 [=========>....................] - ETA: 0s - loss: 0.0203 93/133 [===================>..........] - ETA: 0s - loss: 0.0187 133/133 [==============================] - 0s 1ms/step - loss: 0.0215 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0173 46/133 [=========>....................] - ETA: 0s - loss: 0.0155 93/133 [===================>..........] - ETA: 0s - loss: 0.0213 133/133 [==============================] - 0s 1ms/step - loss: 0.0201 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 46/133 [=========>....................] - ETA: 0s - loss: 0.0171 87/133 [==================>...........] - ETA: 0s - loss: 0.0188 133/133 [==============================] - ETA: 0s - loss: 0.0204 133/133 [==============================] - 0s 1ms/step - loss: 0.0204 -> test with GAN.predict GAN tn, fp: 325, 7 GAN fn, tp: 2, 12 GAN f1 score: 0.727 GAN cohens kappa score: 0.714 -> test with 'LR' LR tn, fp: 163, 169 LR fn, tp: 4, 10 LR f1 score: 0.104 LR cohens kappa score: 0.031 LR average precision score: 0.065 -> test with 'RF' RF tn, fp: 331, 1 RF fn, tp: 5, 9 RF f1 score: 0.750 RF cohens kappa score: 0.741 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 4, 10 GB f1 score: 0.800 GB cohens kappa score: 0.793 -> test with 'KNN' KNN tn, fp: 320, 12 KNN fn, tp: 2, 12 KNN f1 score: 0.632 KNN cohens kappa score: 0.612 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 0.0215 42/133 [========>.....................] - ETA: 0s - loss: 0.0295  78/133 [================>.............] - ETA: 0s - loss: 0.0410 113/133 [========================>.....] - ETA: 0s - loss: 0.0375 133/133 [==============================] - 0s 1ms/step - loss: 0.0392 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0148 41/133 [========>.....................] - ETA: 0s - loss: 0.0291 82/133 [=================>............] - ETA: 0s - loss: 0.0351 125/133 [===========================>..] - ETA: 0s - loss: 0.0366 133/133 [==============================] - 0s 1ms/step - loss: 0.0370 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0078 47/133 [=========>....................] - ETA: 0s - loss: 0.0322 92/133 [===================>..........] - ETA: 0s - loss: 0.0334 133/133 [==============================] - 0s 1ms/step - loss: 0.0354 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0362 48/133 [=========>....................] - ETA: 0s - loss: 0.0318 95/133 [====================>.........] - ETA: 0s - loss: 0.0338 133/133 [==============================] - 0s 1ms/step - loss: 0.0341 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0074 47/133 [=========>....................] - ETA: 0s - loss: 0.0310 93/133 [===================>..........] - ETA: 0s - loss: 0.0321 133/133 [==============================] - 0s 1ms/step - loss: 0.0323 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0154 48/133 [=========>....................] - ETA: 0s - loss: 0.0254 94/133 [====================>.........] - ETA: 0s - loss: 0.0243 133/133 [==============================] - 0s 1ms/step - loss: 0.0296 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0066 47/133 [=========>....................] - ETA: 0s - loss: 0.0264 94/133 [====================>.........] - ETA: 0s - loss: 0.0294 133/133 [==============================] - 0s 1ms/step - loss: 0.0301 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0016 45/133 [=========>....................] - ETA: 0s - loss: 0.0273 88/133 [==================>...........] - ETA: 0s - loss: 0.0301 133/133 [==============================] - 0s 1ms/step - loss: 0.0283 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0279 47/133 [=========>....................] - ETA: 0s - loss: 0.0367 94/133 [====================>.........] - ETA: 0s - loss: 0.0287 133/133 [==============================] - 0s 1ms/step - loss: 0.0275 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0044 47/133 [=========>....................] - ETA: 0s - loss: 0.0317 94/133 [====================>.........] - ETA: 0s - loss: 0.0288 133/133 [==============================] - 0s 1ms/step - loss: 0.0262 -> test with GAN.predict GAN tn, fp: 328, 4 GAN fn, tp: 1, 13 GAN f1 score: 0.839 GAN cohens kappa score: 0.831 -> test with 'LR' LR tn, fp: 183, 149 LR fn, tp: 4, 10 LR f1 score: 0.116 LR cohens kappa score: 0.045 LR average precision score: 0.059 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 5, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 3, 11 GB f1 score: 0.815 GB cohens kappa score: 0.807 -> test with 'KNN' KNN tn, fp: 302, 30 KNN fn, tp: 1, 13 KNN f1 score: 0.456 KNN cohens kappa score: 0.421 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0360 48/133 [=========>....................] - ETA: 0s - loss: 0.0375  95/133 [====================>.........] - ETA: 0s - loss: 0.0361 133/133 [==============================] - 0s 1ms/step - loss: 0.0415 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0674 48/133 [=========>....................] - ETA: 0s - loss: 0.0315 95/133 [====================>.........] - ETA: 0s - loss: 0.0375 133/133 [==============================] - 0s 1ms/step - loss: 0.0384 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0159 48/133 [=========>....................] - ETA: 0s - loss: 0.0390 95/133 [====================>.........] - ETA: 0s - loss: 0.0405 133/133 [==============================] - 0s 1ms/step - loss: 0.0372 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0543 48/133 [=========>....................] - ETA: 0s - loss: 0.0337 95/133 [====================>.........] - ETA: 0s - loss: 0.0375 133/133 [==============================] - 0s 1ms/step - loss: 0.0354 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0859 47/133 [=========>....................] - ETA: 0s - loss: 0.0331 94/133 [====================>.........] - ETA: 0s - loss: 0.0374 133/133 [==============================] - 0s 1ms/step - loss: 0.0341 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0152 48/133 [=========>....................] - ETA: 0s - loss: 0.0238 93/133 [===================>..........] - ETA: 0s - loss: 0.0273 128/133 [===========================>..] - ETA: 0s - loss: 0.0325 133/133 [==============================] - 0s 1ms/step - loss: 0.0322 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0259 45/133 [=========>....................] - ETA: 0s - loss: 0.0296 92/133 [===================>..........] - ETA: 0s - loss: 0.0349 133/133 [==============================] - 0s 1ms/step - loss: 0.0315 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0379 47/133 [=========>....................] - ETA: 0s - loss: 0.0328 94/133 [====================>.........] - ETA: 0s - loss: 0.0266 133/133 [==============================] - 0s 1ms/step - loss: 0.0291 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0226 48/133 [=========>....................] - ETA: 0s - loss: 0.0310 95/133 [====================>.........] - ETA: 0s - loss: 0.0293 133/133 [==============================] - 0s 1ms/step - loss: 0.0280 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0198 47/133 [=========>....................] - ETA: 0s - loss: 0.0226 93/133 [===================>..........] - ETA: 0s - loss: 0.0307 133/133 [==============================] - 0s 1ms/step - loss: 0.0274 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 1, 13 GAN f1 score: 0.813 GAN cohens kappa score: 0.804 -> test with 'LR' LR tn, fp: 191, 141 LR fn, tp: 4, 10 LR f1 score: 0.121 LR cohens kappa score: 0.051 LR average precision score: 0.071 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 7, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 8, 6 GB f1 score: 0.600 GB cohens kappa score: 0.590 -> test with 'KNN' KNN tn, fp: 309, 23 KNN fn, tp: 3, 11 KNN f1 score: 0.458 KNN cohens kappa score: 0.425 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0015 45/133 [=========>....................] - ETA: 0s - loss: 0.0288  86/133 [==================>...........] - ETA: 0s - loss: 0.0307 127/133 [===========================>..] - ETA: 0s - loss: 0.0325 133/133 [==============================] - 0s 1ms/step - loss: 0.0316 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0520 41/133 [========>.....................] - ETA: 0s - loss: 0.0337 86/133 [==================>...........] - ETA: 0s - loss: 0.0283 129/133 [============================>.] - ETA: 0s - loss: 0.0297 133/133 [==============================] - 0s 1ms/step - loss: 0.0301 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 48/133 [=========>....................] - ETA: 0s - loss: 0.0267 93/133 [===================>..........] - ETA: 0s - loss: 0.0270 133/133 [==============================] - 0s 1ms/step - loss: 0.0289 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0121 47/133 [=========>....................] - ETA: 0s - loss: 0.0220 93/133 [===================>..........] - ETA: 0s - loss: 0.0249 133/133 [==============================] - 0s 1ms/step - loss: 0.0279 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0602 47/133 [=========>....................] - ETA: 0s - loss: 0.0297 94/133 [====================>.........] - ETA: 0s - loss: 0.0282 133/133 [==============================] - 0s 1ms/step - loss: 0.0271 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0151 47/133 [=========>....................] - ETA: 0s - loss: 0.0239 92/133 [===================>..........] - ETA: 0s - loss: 0.0273 133/133 [==============================] - 0s 1ms/step - loss: 0.0254 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0300 48/133 [=========>....................] - ETA: 0s - loss: 0.0216 95/133 [====================>.........] - ETA: 0s - loss: 0.0235 133/133 [==============================] - 0s 1ms/step - loss: 0.0251 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0038 48/133 [=========>....................] - ETA: 0s - loss: 0.0269 94/133 [====================>.........] - ETA: 0s - loss: 0.0264 133/133 [==============================] - 0s 1ms/step - loss: 0.0238 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0058 46/133 [=========>....................] - ETA: 0s - loss: 0.0234 92/133 [===================>..........] - ETA: 0s - loss: 0.0267 133/133 [==============================] - 0s 1ms/step - loss: 0.0235 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0056 46/133 [=========>....................] - ETA: 0s - loss: 0.0187 93/133 [===================>..........] - ETA: 0s - loss: 0.0223 133/133 [==============================] - 0s 1ms/step - loss: 0.0223 -> test with GAN.predict GAN tn, fp: 326, 6 GAN fn, tp: 5, 9 GAN f1 score: 0.621 GAN cohens kappa score: 0.604 -> test with 'LR' LR tn, fp: 192, 140 LR fn, tp: 8, 6 LR f1 score: 0.075 LR cohens kappa score: 0.001 LR average precision score: 0.051 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 10, 4 RF f1 score: 0.444 RF cohens kappa score: 0.434 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 4, 10 GB f1 score: 0.800 GB cohens kappa score: 0.793 -> test with 'KNN' KNN tn, fp: 315, 17 KNN fn, tp: 2, 12 KNN f1 score: 0.558 KNN cohens kappa score: 0.533 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0045 46/133 [=========>....................] - ETA: 0s - loss: 0.0303  93/133 [===================>..........] - ETA: 0s - loss: 0.0381 133/133 [==============================] - 0s 1ms/step - loss: 0.0363 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0041 48/133 [=========>....................] - ETA: 0s - loss: 0.0396 94/133 [====================>.........] - ETA: 0s - loss: 0.0362 133/133 [==============================] - 0s 1ms/step - loss: 0.0341 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 43/133 [========>.....................] - ETA: 0s - loss: 0.0316 83/133 [=================>............] - ETA: 0s - loss: 0.0287 124/133 [==========================>...] - ETA: 0s - loss: 0.0351 133/133 [==============================] - 0s 1ms/step - loss: 0.0336 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0287 47/133 [=========>....................] - ETA: 0s - loss: 0.0296 93/133 [===================>..........] - ETA: 0s - loss: 0.0289 133/133 [==============================] - 0s 1ms/step - loss: 0.0322 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0088 48/133 [=========>....................] - ETA: 0s - loss: 0.0319 94/133 [====================>.........] - ETA: 0s - loss: 0.0261 133/133 [==============================] - 0s 1ms/step - loss: 0.0306 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0046 48/133 [=========>....................] - ETA: 0s - loss: 0.0270 95/133 [====================>.........] - ETA: 0s - loss: 0.0261 133/133 [==============================] - 0s 1ms/step - loss: 0.0292 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0124 47/133 [=========>....................] - ETA: 0s - loss: 0.0305 92/133 [===================>..........] - ETA: 0s - loss: 0.0305 133/133 [==============================] - 0s 1ms/step - loss: 0.0282 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0061 48/133 [=========>....................] - ETA: 0s - loss: 0.0255 94/133 [====================>.........] - ETA: 0s - loss: 0.0260 133/133 [==============================] - 0s 1ms/step - loss: 0.0268 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0109 48/133 [=========>....................] - ETA: 0s - loss: 0.0194 94/133 [====================>.........] - ETA: 0s - loss: 0.0195 133/133 [==============================] - 0s 1ms/step - loss: 0.0269 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0087 48/133 [=========>....................] - ETA: 0s - loss: 0.0151 94/133 [====================>.........] - ETA: 0s - loss: 0.0276 133/133 [==============================] - 0s 1ms/step - loss: 0.0269 -> test with GAN.predict GAN tn, fp: 327, 4 GAN fn, tp: 5, 8 GAN f1 score: 0.640 GAN cohens kappa score: 0.626 -> test with 'LR' LR tn, fp: 187, 144 LR fn, tp: 5, 8 LR f1 score: 0.097 LR cohens kappa score: 0.029 LR average precision score: 0.074 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 7, 6 RF f1 score: 0.632 RF cohens kappa score: 0.623 -> test with 'GB' GB tn, fp: 328, 3 GB fn, tp: 3, 10 GB f1 score: 0.769 GB cohens kappa score: 0.760 -> test with 'KNN' KNN tn, fp: 304, 27 KNN fn, tp: 0, 13 KNN f1 score: 0.491 KNN cohens kappa score: 0.460 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 28s - loss: 0.0284 30/133 [=====>........................] - ETA: 0s - loss: 0.0480  60/133 [============>.................] - ETA: 0s - loss: 0.0391 90/133 [===================>..........] - ETA: 0s - loss: 0.0307 123/133 [==========================>...] - ETA: 0s - loss: 0.0320 133/133 [==============================] - 0s 2ms/step - loss: 0.0320 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0206 32/133 [======>.......................] - ETA: 0s - loss: 0.0206 56/133 [===========>..................] - ETA: 0s - loss: 0.0289 80/133 [=================>............] - ETA: 0s - loss: 0.0301 105/133 [======================>.......] - ETA: 0s - loss: 0.0301 130/133 [============================>.] - ETA: 0s - loss: 0.0303 133/133 [==============================] - 0s 2ms/step - loss: 0.0301 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0372 26/133 [====>.........................] - ETA: 0s - loss: 0.0210 53/133 [==========>...................] - ETA: 0s - loss: 0.0242 82/133 [=================>............] - ETA: 0s - loss: 0.0288 109/133 [=======================>......] - ETA: 0s - loss: 0.0279 133/133 [==============================] - 0s 2ms/step - loss: 0.0285 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0115 29/133 [=====>........................] - ETA: 0s - loss: 0.0274 52/133 [==========>...................] - ETA: 0s - loss: 0.0283 80/133 [=================>............] - ETA: 0s - loss: 0.0235 108/133 [=======================>......] - ETA: 0s - loss: 0.0245 133/133 [==============================] - 0s 2ms/step - loss: 0.0268 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0128 29/133 [=====>........................] - ETA: 0s - loss: 0.0194 56/133 [===========>..................] - ETA: 0s - loss: 0.0258 87/133 [==================>...........] - ETA: 0s - loss: 0.0263 116/133 [=========================>....] - ETA: 0s - loss: 0.0246 133/133 [==============================] - 0s 2ms/step - loss: 0.0255 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0290 28/133 [=====>........................] - ETA: 0s - loss: 0.0172 52/133 [==========>...................] - ETA: 0s - loss: 0.0215 72/133 [===============>..............] - ETA: 0s - loss: 0.0242 94/133 [====================>.........] - ETA: 0s - loss: 0.0233 113/133 [========================>.....] - ETA: 0s - loss: 0.0230 131/133 [============================>.] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 2ms/step - loss: 0.0246 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0129 17/133 [==>...........................] - ETA: 0s - loss: 0.0230 31/133 [=====>........................] - ETA: 0s - loss: 0.0191 49/133 [==========>...................] - ETA: 0s - loss: 0.0250 66/133 [=============>................] - ETA: 0s - loss: 0.0234 81/133 [=================>............] - ETA: 0s - loss: 0.0220 97/133 [====================>.........] - ETA: 0s - loss: 0.0252 114/133 [========================>.....] - ETA: 0s - loss: 0.0253 133/133 [==============================] - ETA: 0s - loss: 0.0240 133/133 [==============================] - 0s 3ms/step - loss: 0.0240 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0029 24/133 [====>.........................] - ETA: 0s - loss: 0.0237 47/133 [=========>....................] - ETA: 0s - loss: 0.0213 66/133 [=============>................] - ETA: 0s - loss: 0.0210 89/133 [===================>..........] - ETA: 0s - loss: 0.0196 112/133 [========================>.....] - ETA: 0s - loss: 0.0222 129/133 [============================>.] - ETA: 0s - loss: 0.0216 133/133 [==============================] - 0s 2ms/step - loss: 0.0214 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0023 17/133 [==>...........................] - ETA: 0s - loss: 0.0200 41/133 [========>.....................] - ETA: 0s - loss: 0.0218 71/133 [===============>..............] - ETA: 0s - loss: 0.0274 99/133 [=====================>........] - ETA: 0s - loss: 0.0259 130/133 [============================>.] - ETA: 0s - loss: 0.0218 133/133 [==============================] - 0s 2ms/step - loss: 0.0215 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0060 30/133 [=====>........................] - ETA: 0s - loss: 0.0095 59/133 [============>.................] - ETA: 0s - loss: 0.0183 82/133 [=================>............] - ETA: 0s - loss: 0.0200 105/133 [======================>.......] - ETA: 0s - loss: 0.0208 127/133 [===========================>..] - ETA: 0s - loss: 0.0216 133/133 [==============================] - 0s 2ms/step - loss: 0.0211 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 2, 12 GAN f1 score: 0.774 GAN cohens kappa score: 0.764 -> test with 'LR' LR tn, fp: 169, 163 LR fn, tp: 3, 11 LR f1 score: 0.117 LR cohens kappa score: 0.046 LR average precision score: 0.076 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 7, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 331, 1 GB fn, tp: 3, 11 GB f1 score: 0.846 GB cohens kappa score: 0.840 -> test with 'KNN' KNN tn, fp: 320, 12 KNN fn, tp: 1, 13 KNN f1 score: 0.667 KNN cohens kappa score: 0.648 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0256 43/133 [========>.....................] - ETA: 0s - loss: 0.0350  83/133 [=================>............] - ETA: 0s - loss: 0.0298 123/133 [==========================>...] - ETA: 0s - loss: 0.0341 133/133 [==============================] - 0s 1ms/step - loss: 0.0343 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0712 44/133 [========>.....................] - ETA: 0s - loss: 0.0278 89/133 [===================>..........] - ETA: 0s - loss: 0.0333 133/133 [==============================] - ETA: 0s - loss: 0.0323 133/133 [==============================] - 0s 1ms/step - loss: 0.0323 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0081 48/133 [=========>....................] - ETA: 0s - loss: 0.0240 93/133 [===================>..........] - ETA: 0s - loss: 0.0286 133/133 [==============================] - 0s 1ms/step - loss: 0.0319 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0203 46/133 [=========>....................] - ETA: 0s - loss: 0.0351 92/133 [===================>..........] - ETA: 0s - loss: 0.0291 133/133 [==============================] - 0s 1ms/step - loss: 0.0297 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0163 48/133 [=========>....................] - ETA: 0s - loss: 0.0260 95/133 [====================>.........] - ETA: 0s - loss: 0.0248 133/133 [==============================] - 0s 1ms/step - loss: 0.0281 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0198 46/133 [=========>....................] - ETA: 0s - loss: 0.0262 87/133 [==================>...........] - ETA: 0s - loss: 0.0249 129/133 [============================>.] - ETA: 0s - loss: 0.0274 133/133 [==============================] - 0s 1ms/step - loss: 0.0272 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0475 48/133 [=========>....................] - ETA: 0s - loss: 0.0229 96/133 [====================>.........] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 1ms/step - loss: 0.0261 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 49/133 [==========>...................] - ETA: 0s - loss: 0.0287 98/133 [=====================>........] - ETA: 0s - loss: 0.0259 133/133 [==============================] - 0s 1ms/step - loss: 0.0242 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0029 49/133 [==========>...................] - ETA: 0s - loss: 0.0258 97/133 [====================>.........] - ETA: 0s - loss: 0.0258 133/133 [==============================] - 0s 1ms/step - loss: 0.0241 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0093 49/133 [==========>...................] - ETA: 0s - loss: 0.0254 97/133 [====================>.........] - ETA: 0s - loss: 0.0254 133/133 [==============================] - 0s 1ms/step - loss: 0.0235 -> test with GAN.predict GAN tn, fp: 325, 7 GAN fn, tp: 3, 11 GAN f1 score: 0.688 GAN cohens kappa score: 0.673 -> test with 'LR' LR tn, fp: 188, 144 LR fn, tp: 3, 11 LR f1 score: 0.130 LR cohens kappa score: 0.060 LR average precision score: 0.066 -> test with 'RF' RF tn, fp: 330, 2 RF fn, tp: 8, 6 RF f1 score: 0.545 RF cohens kappa score: 0.532 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 0, 14 GB f1 score: 0.933 GB cohens kappa score: 0.930 -> test with 'KNN' KNN tn, fp: 319, 13 KNN fn, tp: 0, 14 KNN f1 score: 0.683 KNN cohens kappa score: 0.665 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0107 47/133 [=========>....................] - ETA: 0s - loss: 0.0388  94/133 [====================>.........] - ETA: 0s - loss: 0.0324 133/133 [==============================] - 0s 1ms/step - loss: 0.0330 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0080 49/133 [==========>...................] - ETA: 0s - loss: 0.0332 96/133 [====================>.........] - ETA: 0s - loss: 0.0306 133/133 [==============================] - 0s 1ms/step - loss: 0.0297 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0053 49/133 [==========>...................] - ETA: 0s - loss: 0.0260 95/133 [====================>.........] - ETA: 0s - loss: 0.0288 133/133 [==============================] - 0s 1ms/step - loss: 0.0295 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0081 49/133 [==========>...................] - ETA: 0s - loss: 0.0302 97/133 [====================>.........] - ETA: 0s - loss: 0.0256 133/133 [==============================] - 0s 1ms/step - loss: 0.0281 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0061 49/133 [==========>...................] - ETA: 0s - loss: 0.0248 96/133 [====================>.........] - ETA: 0s - loss: 0.0262 133/133 [==============================] - 0s 1ms/step - loss: 0.0263 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0150 48/133 [=========>....................] - ETA: 0s - loss: 0.0223 94/133 [====================>.........] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 1ms/step - loss: 0.0251 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0148 47/133 [=========>....................] - ETA: 0s - loss: 0.0264 94/133 [====================>.........] - ETA: 0s - loss: 0.0272 133/133 [==============================] - 0s 1ms/step - loss: 0.0249 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0062 49/133 [==========>...................] - ETA: 0s - loss: 0.0241 92/133 [===================>..........] - ETA: 0s - loss: 0.0195 133/133 [==============================] - 0s 1ms/step - loss: 0.0228 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0074 48/133 [=========>....................] - ETA: 0s - loss: 0.0183 96/133 [====================>.........] - ETA: 0s - loss: 0.0212 133/133 [==============================] - 0s 1ms/step - loss: 0.0218 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0118 48/133 [=========>....................] - ETA: 0s - loss: 0.0251 93/133 [===================>..........] - ETA: 0s - loss: 0.0231 133/133 [==============================] - 0s 1ms/step - loss: 0.0219 -> test with GAN.predict GAN tn, fp: 330, 2 GAN fn, tp: 6, 8 GAN f1 score: 0.667 GAN cohens kappa score: 0.655 -> test with 'LR' LR tn, fp: 181, 151 LR fn, tp: 6, 8 LR f1 score: 0.092 LR cohens kappa score: 0.020 LR average precision score: 0.056 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 7, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 9, 5 GB f1 score: 0.476 GB cohens kappa score: 0.462 -> test with 'KNN' KNN tn, fp: 320, 12 KNN fn, tp: 2, 12 KNN f1 score: 0.632 KNN cohens kappa score: 0.612 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 22s - loss: 0.0091 42/133 [========>.....................] - ETA: 0s - loss: 0.0370  88/133 [==================>...........] - ETA: 0s - loss: 0.0382 132/133 [============================>.] - ETA: 0s - loss: 0.0371 133/133 [==============================] - 0s 1ms/step - loss: 0.0371 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0229 46/133 [=========>....................] - ETA: 0s - loss: 0.0317 91/133 [===================>..........] - ETA: 0s - loss: 0.0326 133/133 [==============================] - 0s 1ms/step - loss: 0.0355 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0042 45/133 [=========>....................] - ETA: 0s - loss: 0.0392 90/133 [===================>..........] - ETA: 0s - loss: 0.0357 133/133 [==============================] - 0s 1ms/step - loss: 0.0349 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0099 44/133 [========>.....................] - ETA: 0s - loss: 0.0330 86/133 [==================>...........] - ETA: 0s - loss: 0.0361 130/133 [============================>.] - ETA: 0s - loss: 0.0325 133/133 [==============================] - 0s 1ms/step - loss: 0.0321 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0240 46/133 [=========>....................] - ETA: 0s - loss: 0.0251 86/133 [==================>...........] - ETA: 0s - loss: 0.0342 128/133 [===========================>..] - ETA: 0s - loss: 0.0306 133/133 [==============================] - 0s 1ms/step - loss: 0.0310 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0156 49/133 [==========>...................] - ETA: 0s - loss: 0.0281 96/133 [====================>.........] - ETA: 0s - loss: 0.0296 133/133 [==============================] - 0s 1ms/step - loss: 0.0288 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.1046 48/133 [=========>....................] - ETA: 0s - loss: 0.0259 95/133 [====================>.........] - ETA: 0s - loss: 0.0276 133/133 [==============================] - 0s 1ms/step - loss: 0.0283 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0432 47/133 [=========>....................] - ETA: 0s - loss: 0.0358 94/133 [====================>.........] - ETA: 0s - loss: 0.0284 133/133 [==============================] - 0s 1ms/step - loss: 0.0268 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.1162 47/133 [=========>....................] - ETA: 0s - loss: 0.0238 84/133 [=================>............] - ETA: 0s - loss: 0.0262 127/133 [===========================>..] - ETA: 0s - loss: 0.0257 133/133 [==============================] - 0s 1ms/step - loss: 0.0260 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0018 44/133 [========>.....................] - ETA: 0s - loss: 0.0266 87/133 [==================>...........] - ETA: 0s - loss: 0.0254 127/133 [===========================>..] - ETA: 0s - loss: 0.0265 133/133 [==============================] - 0s 1ms/step - loss: 0.0258 -> test with GAN.predict GAN tn, fp: 329, 3 GAN fn, tp: 3, 11 GAN f1 score: 0.786 GAN cohens kappa score: 0.777 -> test with 'LR' LR tn, fp: 184, 148 LR fn, tp: 2, 12 LR f1 score: 0.138 LR cohens kappa score: 0.069 LR average precision score: 0.081 -> test with 'RF' RF tn, fp: 331, 1 RF fn, tp: 6, 8 RF f1 score: 0.696 RF cohens kappa score: 0.686 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 7, 7 GB f1 score: 0.667 GB cohens kappa score: 0.657 -> test with 'KNN' KNN tn, fp: 316, 16 KNN fn, tp: 0, 14 KNN f1 score: 0.636 KNN cohens kappa score: 0.615 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 21s - loss: 0.0352 46/133 [=========>....................] - ETA: 0s - loss: 0.0330  94/133 [====================>.........] - ETA: 0s - loss: 0.0329 133/133 [==============================] - 0s 1ms/step - loss: 0.0339 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.1184 49/133 [==========>...................] - ETA: 0s - loss: 0.0308 97/133 [====================>.........] - ETA: 0s - loss: 0.0314 133/133 [==============================] - 0s 1ms/step - loss: 0.0309 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0211 48/133 [=========>....................] - ETA: 0s - loss: 0.0245 95/133 [====================>.........] - ETA: 0s - loss: 0.0285 133/133 [==============================] - 0s 1ms/step - loss: 0.0290 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0103 48/133 [=========>....................] - ETA: 0s - loss: 0.0325 96/133 [====================>.........] - ETA: 0s - loss: 0.0291 133/133 [==============================] - 0s 1ms/step - loss: 0.0277 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0568 48/133 [=========>....................] - ETA: 0s - loss: 0.0374 96/133 [====================>.........] - ETA: 0s - loss: 0.0283 133/133 [==============================] - 0s 1ms/step - loss: 0.0262 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0072 49/133 [==========>...................] - ETA: 0s - loss: 0.0263 95/133 [====================>.........] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 1ms/step - loss: 0.0253 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0024 48/133 [=========>....................] - ETA: 0s - loss: 0.0232 92/133 [===================>..........] - ETA: 0s - loss: 0.0236 131/133 [============================>.] - ETA: 0s - loss: 0.0246 133/133 [==============================] - 0s 1ms/step - loss: 0.0244 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0371 42/133 [========>.....................] - ETA: 0s - loss: 0.0327 81/133 [=================>............] - ETA: 0s - loss: 0.0272 125/133 [===========================>..] - ETA: 0s - loss: 0.0223 133/133 [==============================] - 0s 1ms/step - loss: 0.0225 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0094 48/133 [=========>....................] - ETA: 0s - loss: 0.0173 95/133 [====================>.........] - ETA: 0s - loss: 0.0205 133/133 [==============================] - 0s 1ms/step - loss: 0.0217 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0088 42/133 [========>.....................] - ETA: 0s - loss: 0.0240 84/133 [=================>............] - ETA: 0s - loss: 0.0228 121/133 [==========================>...] - ETA: 0s - loss: 0.0210 133/133 [==============================] - 0s 1ms/step - loss: 0.0206 -> 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: 176, 155 LR fn, tp: 5, 8 LR f1 score: 0.091 LR cohens kappa score: 0.022 LR average precision score: 0.049 -> test with 'RF' RF tn, fp: 331, 0 RF fn, tp: 5, 8 RF f1 score: 0.762 RF cohens kappa score: 0.755 -> test with 'GB' GB tn, fp: 328, 3 GB fn, tp: 4, 9 GB f1 score: 0.720 GB cohens kappa score: 0.709 -> test with 'KNN' KNN tn, fp: 277, 54 KNN fn, tp: 1, 12 KNN f1 score: 0.304 KNN cohens kappa score: 0.257 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0297 45/133 [=========>....................] - ETA: 0s - loss: 0.0415  90/133 [===================>..........] - ETA: 0s - loss: 0.0385 133/133 [==============================] - 0s 1ms/step - loss: 0.0360 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 48/133 [=========>....................] - ETA: 0s - loss: 0.0320 96/133 [====================>.........] - ETA: 0s - loss: 0.0333 133/133 [==============================] - 0s 1ms/step - loss: 0.0321 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0146 49/133 [==========>...................] - ETA: 0s - loss: 0.0323 97/133 [====================>.........] - ETA: 0s - loss: 0.0310 133/133 [==============================] - 0s 1ms/step - loss: 0.0312 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0092 49/133 [==========>...................] - ETA: 0s - loss: 0.0289 96/133 [====================>.........] - ETA: 0s - loss: 0.0255 133/133 [==============================] - 0s 1ms/step - loss: 0.0300 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0052 49/133 [==========>...................] - ETA: 0s - loss: 0.0212 95/133 [====================>.........] - ETA: 0s - loss: 0.0215 133/133 [==============================] - 0s 1ms/step - loss: 0.0285 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0938 49/133 [==========>...................] - ETA: 0s - loss: 0.0295 97/133 [====================>.........] - ETA: 0s - loss: 0.0318 133/133 [==============================] - 0s 1ms/step - loss: 0.0282 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0201 49/133 [==========>...................] - ETA: 0s - loss: 0.0290 98/133 [=====================>........] - ETA: 0s - loss: 0.0232 133/133 [==============================] - 0s 1ms/step - loss: 0.0259 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0128 50/133 [==========>...................] - ETA: 0s - loss: 0.0240 98/133 [=====================>........] - ETA: 0s - loss: 0.0266 133/133 [==============================] - 0s 1ms/step - loss: 0.0258 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0210 49/133 [==========>...................] - ETA: 0s - loss: 0.0124 98/133 [=====================>........] - ETA: 0s - loss: 0.0209 133/133 [==============================] - 0s 1ms/step - loss: 0.0231 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0105 49/133 [==========>...................] - ETA: 0s - loss: 0.0263 95/133 [====================>.........] - ETA: 0s - loss: 0.0244 133/133 [==============================] - 0s 1ms/step - loss: 0.0229 -> test with GAN.predict GAN tn, fp: 328, 4 GAN fn, tp: 2, 12 GAN f1 score: 0.800 GAN cohens kappa score: 0.791 -> test with 'LR' LR tn, fp: 182, 150 LR fn, tp: 3, 11 LR f1 score: 0.126 LR cohens kappa score: 0.055 LR average precision score: 0.067 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 5, 9 RF f1 score: 0.783 RF cohens kappa score: 0.775 -> test with 'GB' GB tn, fp: 332, 0 GB fn, tp: 5, 9 GB f1 score: 0.783 GB cohens kappa score: 0.775 -> test with 'KNN' KNN tn, fp: 328, 4 KNN fn, tp: 0, 14 KNN f1 score: 0.875 KNN cohens kappa score: 0.869 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 21s - loss: 0.0133 49/133 [==========>...................] - ETA: 0s - loss: 0.0277  98/133 [=====================>........] - ETA: 0s - loss: 0.0297 133/133 [==============================] - 0s 1ms/step - loss: 0.0300 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0172 49/133 [==========>...................] - ETA: 0s - loss: 0.0379 96/133 [====================>.........] - ETA: 0s - loss: 0.0312 133/133 [==============================] - 0s 1ms/step - loss: 0.0279 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0142 41/133 [========>.....................] - ETA: 0s - loss: 0.0227 88/133 [==================>...........] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 1ms/step - loss: 0.0260 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0412 48/133 [=========>....................] - ETA: 0s - loss: 0.0213 96/133 [====================>.........] - ETA: 0s - loss: 0.0241 133/133 [==============================] - 0s 1ms/step - loss: 0.0251 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0108 49/133 [==========>...................] - ETA: 0s - loss: 0.0199 97/133 [====================>.........] - ETA: 0s - loss: 0.0246 133/133 [==============================] - 0s 1ms/step - loss: 0.0240 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0056 50/133 [==========>...................] - ETA: 0s - loss: 0.0243 97/133 [====================>.........] - ETA: 0s - loss: 0.0225 133/133 [==============================] - 0s 1ms/step - loss: 0.0227 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0031 49/133 [==========>...................] - ETA: 0s - loss: 0.0158 97/133 [====================>.........] - ETA: 0s - loss: 0.0223 133/133 [==============================] - 0s 1ms/step - loss: 0.0214 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0054 49/133 [==========>...................] - ETA: 0s - loss: 0.0160 97/133 [====================>.........] - ETA: 0s - loss: 0.0183 133/133 [==============================] - 0s 1ms/step - loss: 0.0204 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 49/133 [==========>...................] - ETA: 0s - loss: 0.0235 94/133 [====================>.........] - ETA: 0s - loss: 0.0188 133/133 [==============================] - 0s 1ms/step - loss: 0.0192 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0190 49/133 [==========>...................] - ETA: 0s - loss: 0.0222 97/133 [====================>.........] - ETA: 0s - loss: 0.0188 133/133 [==============================] - 0s 1ms/step - loss: 0.0192 -> test with GAN.predict GAN tn, fp: 327, 5 GAN fn, tp: 6, 8 GAN f1 score: 0.593 GAN cohens kappa score: 0.576 -> test with 'LR' LR tn, fp: 180, 152 LR fn, tp: 6, 8 LR f1 score: 0.092 LR cohens kappa score: 0.019 LR average precision score: 0.062 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 11, 3 RF f1 score: 0.353 RF cohens kappa score: 0.344 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 7, 7 GB f1 score: 0.609 GB cohens kappa score: 0.596 -> test with 'KNN' KNN tn, fp: 312, 20 KNN fn, tp: 0, 14 KNN f1 score: 0.583 KNN cohens kappa score: 0.558 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0115 44/133 [========>.....................] - ETA: 0s - loss: 0.0420  88/133 [==================>...........] - ETA: 0s - loss: 0.0376 133/133 [==============================] - 0s 1ms/step - loss: 0.0367 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0138 49/133 [==========>...................] - ETA: 0s - loss: 0.0417 97/133 [====================>.........] - ETA: 0s - loss: 0.0365 133/133 [==============================] - 0s 1ms/step - loss: 0.0338 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0239 49/133 [==========>...................] - ETA: 0s - loss: 0.0286 96/133 [====================>.........] - ETA: 0s - loss: 0.0327 133/133 [==============================] - 0s 1ms/step - loss: 0.0320 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0054 49/133 [==========>...................] - ETA: 0s - loss: 0.0222 97/133 [====================>.........] - ETA: 0s - loss: 0.0301 133/133 [==============================] - 0s 1ms/step - loss: 0.0310 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0213 49/133 [==========>...................] - ETA: 0s - loss: 0.0362 97/133 [====================>.........] - ETA: 0s - loss: 0.0312 133/133 [==============================] - 0s 1ms/step - loss: 0.0291 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0170 46/133 [=========>....................] - ETA: 0s - loss: 0.0348 93/133 [===================>..........] - ETA: 0s - loss: 0.0277 133/133 [==============================] - 0s 1ms/step - loss: 0.0285 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0073 50/133 [==========>...................] - ETA: 0s - loss: 0.0262 98/133 [=====================>........] - ETA: 0s - loss: 0.0248 133/133 [==============================] - 0s 1ms/step - loss: 0.0269 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0049 46/133 [=========>....................] - ETA: 0s - loss: 0.0256 86/133 [==================>...........] - ETA: 0s - loss: 0.0260 132/133 [============================>.] - ETA: 0s - loss: 0.0263 133/133 [==============================] - 0s 1ms/step - loss: 0.0261 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0105 49/133 [==========>...................] - ETA: 0s - loss: 0.0229 97/133 [====================>.........] - ETA: 0s - loss: 0.0202 133/133 [==============================] - 0s 1ms/step - loss: 0.0252 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.1812 49/133 [==========>...................] - ETA: 0s - loss: 0.0257 97/133 [====================>.........] - ETA: 0s - loss: 0.0215 133/133 [==============================] - 0s 1ms/step - loss: 0.0237 -> test with GAN.predict GAN tn, fp: 324, 8 GAN fn, tp: 2, 12 GAN f1 score: 0.706 GAN cohens kappa score: 0.691 -> test with 'LR' LR tn, fp: 173, 159 LR fn, tp: 4, 10 LR f1 score: 0.109 LR cohens kappa score: 0.037 LR average precision score: 0.070 -> test with 'RF' RF tn, fp: 331, 1 RF fn, tp: 8, 6 RF f1 score: 0.571 RF cohens kappa score: 0.560 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 5, 9 GB f1 score: 0.720 GB cohens kappa score: 0.710 -> test with 'KNN' KNN tn, fp: 302, 30 KNN fn, tp: 0, 14 KNN f1 score: 0.483 KNN cohens kappa score: 0.449 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 23s - loss: 0.0706 49/133 [==========>...................] - ETA: 0s - loss: 0.0431  97/133 [====================>.........] - ETA: 0s - loss: 0.0384 133/133 [==============================] - 0s 1ms/step - loss: 0.0381 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0033 49/133 [==========>...................] - ETA: 0s - loss: 0.0388 90/133 [===================>..........] - ETA: 0s - loss: 0.0359 133/133 [==============================] - 0s 1ms/step - loss: 0.0354 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0849 49/133 [==========>...................] - ETA: 0s - loss: 0.0380 97/133 [====================>.........] - ETA: 0s - loss: 0.0356 133/133 [==============================] - 0s 1ms/step - loss: 0.0340 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0179 49/133 [==========>...................] - ETA: 0s - loss: 0.0272 97/133 [====================>.........] - ETA: 0s - loss: 0.0330 133/133 [==============================] - 0s 1ms/step - loss: 0.0323 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0186 49/133 [==========>...................] - ETA: 0s - loss: 0.0238 97/133 [====================>.........] - ETA: 0s - loss: 0.0276 133/133 [==============================] - 0s 1ms/step - loss: 0.0301 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0063 49/133 [==========>...................] - ETA: 0s - loss: 0.0300 97/133 [====================>.........] - ETA: 0s - loss: 0.0270 133/133 [==============================] - 0s 1ms/step - loss: 0.0283 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0083 49/133 [==========>...................] - ETA: 0s - loss: 0.0284 97/133 [====================>.........] - ETA: 0s - loss: 0.0273 133/133 [==============================] - 0s 1ms/step - loss: 0.0272 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0046 48/133 [=========>....................] - ETA: 0s - loss: 0.0231 96/133 [====================>.........] - ETA: 0s - loss: 0.0257 133/133 [==============================] - 0s 1ms/step - loss: 0.0260 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0031 49/133 [==========>...................] - ETA: 0s - loss: 0.0259 97/133 [====================>.........] - ETA: 0s - loss: 0.0255 133/133 [==============================] - 0s 1ms/step - loss: 0.0250 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0094 49/133 [==========>...................] - ETA: 0s - loss: 0.0235 97/133 [====================>.........] - ETA: 0s - loss: 0.0247 133/133 [==============================] - 0s 1ms/step - loss: 0.0236 -> test with GAN.predict GAN tn, fp: 330, 2 GAN fn, tp: 5, 9 GAN f1 score: 0.720 GAN cohens kappa score: 0.710 -> test with 'LR' LR tn, fp: 194, 138 LR fn, tp: 6, 8 LR f1 score: 0.100 LR cohens kappa score: 0.028 LR average precision score: 0.055 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 7, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 4, 10 GB f1 score: 0.769 GB cohens kappa score: 0.760 -> test with 'KNN' KNN tn, fp: 307, 25 KNN fn, tp: 0, 14 KNN f1 score: 0.528 KNN cohens kappa score: 0.498 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 20s - loss: 0.0049 48/133 [=========>....................] - ETA: 0s - loss: 0.0385  96/133 [====================>.........] - ETA: 0s - loss: 0.0315 133/133 [==============================] - 0s 1ms/step - loss: 0.0289 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0086 46/133 [=========>....................] - ETA: 0s - loss: 0.0265 87/133 [==================>...........] - ETA: 0s - loss: 0.0236 129/133 [============================>.] - ETA: 0s - loss: 0.0268 133/133 [==============================] - 0s 1ms/step - loss: 0.0267 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0541 45/133 [=========>....................] - ETA: 0s - loss: 0.0271 93/133 [===================>..........] - ETA: 0s - loss: 0.0243 133/133 [==============================] - 0s 1ms/step - loss: 0.0255 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.1640 49/133 [==========>...................] - ETA: 0s - loss: 0.0210 96/133 [====================>.........] - ETA: 0s - loss: 0.0228 133/133 [==============================] - 0s 1ms/step - loss: 0.0243 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0098 42/133 [========>.....................] - ETA: 0s - loss: 0.0274 84/133 [=================>............] - ETA: 0s - loss: 0.0213 126/133 [===========================>..] - ETA: 0s - loss: 0.0224 133/133 [==============================] - 0s 1ms/step - loss: 0.0231 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0249 49/133 [==========>...................] - ETA: 0s - loss: 0.0182 97/133 [====================>.........] - ETA: 0s - loss: 0.0209 133/133 [==============================] - 0s 1ms/step - loss: 0.0220 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0235 49/133 [==========>...................] - ETA: 0s - loss: 0.0179 97/133 [====================>.........] - ETA: 0s - loss: 0.0207 133/133 [==============================] - 0s 1ms/step - loss: 0.0215 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0079 49/133 [==========>...................] - ETA: 0s - loss: 0.0138 97/133 [====================>.........] - ETA: 0s - loss: 0.0153 133/133 [==============================] - 0s 1ms/step - loss: 0.0203 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0047 47/133 [=========>....................] - ETA: 0s - loss: 0.0190 95/133 [====================>.........] - ETA: 0s - loss: 0.0227 133/133 [==============================] - 0s 1ms/step - loss: 0.0193 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0264 49/133 [==========>...................] - ETA: 0s - loss: 0.0173 96/133 [====================>.........] - ETA: 0s - loss: 0.0173 133/133 [==============================] - 0s 1ms/step - loss: 0.0195 -> test with GAN.predict GAN tn, fp: 327, 4 GAN fn, tp: 3, 10 GAN f1 score: 0.741 GAN cohens kappa score: 0.730 -> test with 'LR' LR tn, fp: 180, 151 LR fn, tp: 2, 11 LR f1 score: 0.126 LR cohens kappa score: 0.060 LR average precision score: 0.080 -> test with 'RF' RF tn, fp: 330, 1 RF fn, tp: 8, 5 RF f1 score: 0.526 RF cohens kappa score: 0.515 -> test with 'GB' GB tn, fp: 329, 2 GB fn, tp: 8, 5 GB f1 score: 0.500 GB cohens kappa score: 0.486 -> test with 'KNN' KNN tn, fp: 304, 27 KNN fn, tp: 1, 12 KNN f1 score: 0.462 KNN cohens kappa score: 0.429 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0055 49/133 [==========>...................] - ETA: 0s - loss: 0.0356  98/133 [=====================>........] - ETA: 0s - loss: 0.0377 133/133 [==============================] - 0s 1ms/step - loss: 0.0374 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0258 49/133 [==========>...................] - ETA: 0s - loss: 0.0253 98/133 [=====================>........] - ETA: 0s - loss: 0.0345 133/133 [==============================] - 0s 1ms/step - loss: 0.0355 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0591 50/133 [==========>...................] - ETA: 0s - loss: 0.0265 99/133 [=====================>........] - ETA: 0s - loss: 0.0325 133/133 [==============================] - 0s 1ms/step - loss: 0.0346 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0127 49/133 [==========>...................] - ETA: 0s - loss: 0.0299 96/133 [====================>.........] - ETA: 0s - loss: 0.0298 133/133 [==============================] - 0s 1ms/step - loss: 0.0331 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0130 50/133 [==========>...................] - ETA: 0s - loss: 0.0299 99/133 [=====================>........] - ETA: 0s - loss: 0.0339 133/133 [==============================] - 0s 1ms/step - loss: 0.0315 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0135 50/133 [==========>...................] - ETA: 0s - loss: 0.0310 97/133 [====================>.........] - ETA: 0s - loss: 0.0301 133/133 [==============================] - 0s 1ms/step - loss: 0.0301 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0123 49/133 [==========>...................] - ETA: 0s - loss: 0.0259 97/133 [====================>.........] - ETA: 0s - loss: 0.0287 133/133 [==============================] - 0s 1ms/step - loss: 0.0284 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0133 49/133 [==========>...................] - ETA: 0s - loss: 0.0287 98/133 [=====================>........] - ETA: 0s - loss: 0.0266 133/133 [==============================] - 0s 1ms/step - loss: 0.0273 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0272 49/133 [==========>...................] - ETA: 0s - loss: 0.0191 97/133 [====================>.........] - ETA: 0s - loss: 0.0195 133/133 [==============================] - 0s 1ms/step - loss: 0.0247 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0228 49/133 [==========>...................] - ETA: 0s - loss: 0.0192 97/133 [====================>.........] - ETA: 0s - loss: 0.0263 133/133 [==============================] - 0s 1ms/step - loss: 0.0257 -> test with GAN.predict GAN tn, fp: 328, 4 GAN fn, tp: 2, 12 GAN f1 score: 0.800 GAN cohens kappa score: 0.791 -> test with 'LR' LR tn, fp: 183, 149 LR fn, tp: 8, 6 LR f1 score: 0.071 LR cohens kappa score: -0.003 LR average precision score: 0.050 -> test with 'RF' RF tn, fp: 329, 3 RF fn, tp: 9, 5 RF f1 score: 0.455 RF cohens kappa score: 0.438 -> test with 'GB' GB tn, fp: 328, 4 GB fn, tp: 6, 8 GB f1 score: 0.615 GB cohens kappa score: 0.600 -> test with 'KNN' KNN tn, fp: 307, 25 KNN fn, tp: 2, 12 KNN f1 score: 0.471 KNN cohens kappa score: 0.438 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 19s - loss: 0.0276 45/133 [=========>....................] - ETA: 0s - loss: 0.0300  89/133 [===================>..........] - ETA: 0s - loss: 0.0284 131/133 [============================>.] - ETA: 0s - loss: 0.0360 133/133 [==============================] - 0s 1ms/step - loss: 0.0359 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0161 45/133 [=========>....................] - ETA: 0s - loss: 0.0356 89/133 [===================>..........] - ETA: 0s - loss: 0.0321 133/133 [==============================] - ETA: 0s - loss: 0.0328 133/133 [==============================] - 0s 1ms/step - loss: 0.0328 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0134 45/133 [=========>....................] - ETA: 0s - loss: 0.0205 88/133 [==================>...........] - ETA: 0s - loss: 0.0309 130/133 [============================>.] - ETA: 0s - loss: 0.0305 133/133 [==============================] - 0s 1ms/step - loss: 0.0305 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0084 42/133 [========>.....................] - ETA: 0s - loss: 0.0351 84/133 [=================>............] - ETA: 0s - loss: 0.0294 122/133 [==========================>...] - ETA: 0s - loss: 0.0293 133/133 [==============================] - 0s 1ms/step - loss: 0.0301 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0198 39/133 [=======>......................] - ETA: 0s - loss: 0.0275 78/133 [================>.............] - ETA: 0s - loss: 0.0284 119/133 [=========================>....] - ETA: 0s - loss: 0.0273 133/133 [==============================] - 0s 1ms/step - loss: 0.0285 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0100 43/133 [========>.....................] - ETA: 0s - loss: 0.0303 85/133 [==================>...........] - ETA: 0s - loss: 0.0292 129/133 [============================>.] - ETA: 0s - loss: 0.0269 133/133 [==============================] - 0s 1ms/step - loss: 0.0273 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0036 43/133 [========>.....................] - ETA: 0s - loss: 0.0329 86/133 [==================>...........] - ETA: 0s - loss: 0.0295 128/133 [===========================>..] - ETA: 0s - loss: 0.0257 133/133 [==============================] - 0s 1ms/step - loss: 0.0264 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0215 43/133 [========>.....................] - ETA: 0s - loss: 0.0186 86/133 [==================>...........] - ETA: 0s - loss: 0.0212 130/133 [============================>.] - ETA: 0s - loss: 0.0264 133/133 [==============================] - 0s 1ms/step - loss: 0.0262 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0054 43/133 [========>.....................] - ETA: 0s - loss: 0.0251 87/133 [==================>...........] - ETA: 0s - loss: 0.0235 132/133 [============================>.] - ETA: 0s - loss: 0.0248 133/133 [==============================] - 0s 1ms/step - loss: 0.0247 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0153 44/133 [========>.....................] - ETA: 0s - loss: 0.0197 83/133 [=================>............] - ETA: 0s - loss: 0.0235 128/133 [===========================>..] - ETA: 0s - loss: 0.0232 133/133 [==============================] - 0s 1ms/step - loss: 0.0234 -> test with GAN.predict GAN tn, fp: 331, 1 GAN fn, tp: 3, 11 GAN f1 score: 0.846 GAN cohens kappa score: 0.840 -> test with 'LR' LR tn, fp: 189, 143 LR fn, tp: 4, 10 LR f1 score: 0.120 LR cohens kappa score: 0.049 LR average precision score: 0.069 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 6, 8 RF f1 score: 0.727 RF cohens kappa score: 0.719 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 8, 6 GB f1 score: 0.545 GB cohens kappa score: 0.532 -> test with 'KNN' KNN tn, fp: 322, 10 KNN fn, tp: 0, 14 KNN f1 score: 0.737 KNN cohens kappa score: 0.723 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0297 48/133 [=========>....................] - ETA: 0s - loss: 0.0512  96/133 [====================>.........] - ETA: 0s - loss: 0.0463 133/133 [==============================] - 0s 1ms/step - loss: 0.0396 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0275 43/133 [========>.....................] - ETA: 0s - loss: 0.0421 86/133 [==================>...........] - ETA: 0s - loss: 0.0377 131/133 [============================>.] - ETA: 0s - loss: 0.0365 133/133 [==============================] - 0s 1ms/step - loss: 0.0364 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0076 49/133 [==========>...................] - ETA: 0s - loss: 0.0273 97/133 [====================>.........] - ETA: 0s - loss: 0.0313 133/133 [==============================] - 0s 1ms/step - loss: 0.0343 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0331 49/133 [==========>...................] - ETA: 0s - loss: 0.0343 97/133 [====================>.........] - ETA: 0s - loss: 0.0344 133/133 [==============================] - 0s 1ms/step - loss: 0.0332 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0662 50/133 [==========>...................] - ETA: 0s - loss: 0.0374 93/133 [===================>..........] - ETA: 0s - loss: 0.0341 133/133 [==============================] - 0s 1ms/step - loss: 0.0314 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0052 50/133 [==========>...................] - ETA: 0s - loss: 0.0284 98/133 [=====================>........] - ETA: 0s - loss: 0.0325 133/133 [==============================] - 0s 1ms/step - loss: 0.0308 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0226 50/133 [==========>...................] - ETA: 0s - loss: 0.0324 98/133 [=====================>........] - ETA: 0s - loss: 0.0262 133/133 [==============================] - 0s 1ms/step - loss: 0.0289 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0206 49/133 [==========>...................] - ETA: 0s - loss: 0.0317 97/133 [====================>.........] - ETA: 0s - loss: 0.0296 133/133 [==============================] - 0s 1ms/step - loss: 0.0289 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0561 50/133 [==========>...................] - ETA: 0s - loss: 0.0221 99/133 [=====================>........] - ETA: 0s - loss: 0.0277 133/133 [==============================] - 0s 1ms/step - loss: 0.0272 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0114 49/133 [==========>...................] - ETA: 0s - loss: 0.0235 95/133 [====================>.........] - ETA: 0s - loss: 0.0250 133/133 [==============================] - 0s 1ms/step - loss: 0.0254 -> test with GAN.predict GAN tn, fp: 326, 6 GAN fn, tp: 3, 11 GAN f1 score: 0.710 GAN cohens kappa score: 0.696 -> test with 'LR' LR tn, fp: 164, 168 LR fn, tp: 3, 11 LR f1 score: 0.114 LR cohens kappa score: 0.042 LR average precision score: 0.073 -> test with 'RF' RF tn, fp: 330, 2 RF fn, tp: 4, 10 RF f1 score: 0.769 RF cohens kappa score: 0.760 -> test with 'GB' GB tn, fp: 329, 3 GB fn, tp: 5, 9 GB f1 score: 0.692 GB cohens kappa score: 0.680 -> test with 'KNN' KNN tn, fp: 302, 30 KNN fn, tp: 1, 13 KNN f1 score: 0.456 KNN cohens kappa score: 0.421 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0167 49/133 [==========>...................] - ETA: 0s - loss: 0.0449  98/133 [=====================>........] - ETA: 0s - loss: 0.0420 133/133 [==============================] - 0s 1ms/step - loss: 0.0402 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0096 50/133 [==========>...................] - ETA: 0s - loss: 0.0378 99/133 [=====================>........] - ETA: 0s - loss: 0.0327 133/133 [==============================] - 0s 1ms/step - loss: 0.0357 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0907 50/133 [==========>...................] - ETA: 0s - loss: 0.0437 99/133 [=====================>........] - ETA: 0s - loss: 0.0362 133/133 [==============================] - 0s 1ms/step - loss: 0.0354 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0508 49/133 [==========>...................] - ETA: 0s - loss: 0.0369 98/133 [=====================>........] - ETA: 0s - loss: 0.0329 133/133 [==============================] - 0s 1ms/step - loss: 0.0339 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0119 50/133 [==========>...................] - ETA: 0s - loss: 0.0361 96/133 [====================>.........] - ETA: 0s - loss: 0.0364 133/133 [==============================] - 0s 1ms/step - loss: 0.0324 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0269 50/133 [==========>...................] - ETA: 0s - loss: 0.0314 99/133 [=====================>........] - ETA: 0s - loss: 0.0293 133/133 [==============================] - 0s 1ms/step - loss: 0.0313 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0169 49/133 [==========>...................] - ETA: 0s - loss: 0.0273 97/133 [====================>.........] - ETA: 0s - loss: 0.0308 133/133 [==============================] - 0s 1ms/step - loss: 0.0301 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0230 49/133 [==========>...................] - ETA: 0s - loss: 0.0244 97/133 [====================>.........] - ETA: 0s - loss: 0.0269 133/133 [==============================] - 0s 1ms/step - loss: 0.0283 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0035 49/133 [==========>...................] - ETA: 0s - loss: 0.0242 98/133 [=====================>........] - ETA: 0s - loss: 0.0264 133/133 [==============================] - 0s 1ms/step - loss: 0.0274 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0401 49/133 [==========>...................] - ETA: 0s - loss: 0.0188 95/133 [====================>.........] - ETA: 0s - loss: 0.0283 133/133 [==============================] - 0s 1ms/step - loss: 0.0268 -> test with GAN.predict GAN tn, fp: 330, 2 GAN fn, tp: 5, 9 GAN f1 score: 0.720 GAN cohens kappa score: 0.710 -> test with 'LR' LR tn, fp: 178, 154 LR fn, tp: 3, 11 LR f1 score: 0.123 LR cohens kappa score: 0.052 LR average precision score: 0.059 -> test with 'RF' RF tn, fp: 332, 0 RF fn, tp: 8, 6 RF f1 score: 0.600 RF cohens kappa score: 0.590 -> test with 'GB' GB tn, fp: 330, 2 GB fn, tp: 5, 9 GB f1 score: 0.720 GB cohens kappa score: 0.710 -> test with 'KNN' KNN tn, fp: 308, 24 KNN fn, tp: 1, 13 KNN f1 score: 0.510 KNN cohens kappa score: 0.479 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1272 synthetic samples -> retrain GAN for predict Epoch 1/10 1/133 [..............................] - ETA: 18s - loss: 0.0088 44/133 [========>.....................] - ETA: 0s - loss: 0.0445  90/133 [===================>..........] - ETA: 0s - loss: 0.0396 133/133 [==============================] - 0s 1ms/step - loss: 0.0373 Epoch 2/10 1/133 [..............................] - ETA: 0s - loss: 0.0197 49/133 [==========>...................] - ETA: 0s - loss: 0.0382 98/133 [=====================>........] - ETA: 0s - loss: 0.0366 133/133 [==============================] - 0s 1ms/step - loss: 0.0351 Epoch 3/10 1/133 [..............................] - ETA: 0s - loss: 0.0228 49/133 [==========>...................] - ETA: 0s - loss: 0.0361 96/133 [====================>.........] - ETA: 0s - loss: 0.0358 133/133 [==============================] - 0s 1ms/step - loss: 0.0329 Epoch 4/10 1/133 [..............................] - ETA: 0s - loss: 0.0190 49/133 [==========>...................] - ETA: 0s - loss: 0.0358 97/133 [====================>.........] - ETA: 0s - loss: 0.0358 133/133 [==============================] - 0s 1ms/step - loss: 0.0323 Epoch 5/10 1/133 [..............................] - ETA: 0s - loss: 0.0993 50/133 [==========>...................] - ETA: 0s - loss: 0.0340 98/133 [=====================>........] - ETA: 0s - loss: 0.0344 133/133 [==============================] - 0s 1ms/step - loss: 0.0304 Epoch 6/10 1/133 [..............................] - ETA: 0s - loss: 0.0459 49/133 [==========>...................] - ETA: 0s - loss: 0.0268 98/133 [=====================>........] - ETA: 0s - loss: 0.0280 133/133 [==============================] - 0s 1ms/step - loss: 0.0288 Epoch 7/10 1/133 [..............................] - ETA: 0s - loss: 0.0157 50/133 [==========>...................] - ETA: 0s - loss: 0.0238 96/133 [====================>.........] - ETA: 0s - loss: 0.0276 133/133 [==============================] - 0s 1ms/step - loss: 0.0274 Epoch 8/10 1/133 [..............................] - ETA: 0s - loss: 0.0053 50/133 [==========>...................] - ETA: 0s - loss: 0.0309 99/133 [=====================>........] - ETA: 0s - loss: 0.0266 133/133 [==============================] - 0s 1ms/step - loss: 0.0259 Epoch 9/10 1/133 [..............................] - ETA: 0s - loss: 0.0596 50/133 [==========>...................] - ETA: 0s - loss: 0.0296 99/133 [=====================>........] - ETA: 0s - loss: 0.0278 133/133 [==============================] - 0s 1ms/step - loss: 0.0246 Epoch 10/10 1/133 [..............................] - ETA: 0s - loss: 0.0408 50/133 [==========>...................] - ETA: 0s - loss: 0.0212 99/133 [=====================>........] - ETA: 0s - loss: 0.0230 133/133 [==============================] - 0s 1ms/step - loss: 0.0243 -> test with GAN.predict GAN tn, fp: 325, 6 GAN fn, tp: 0, 13 GAN f1 score: 0.813 GAN cohens kappa score: 0.804 -> test with 'LR' LR tn, fp: 179, 152 LR fn, tp: 4, 9 LR f1 score: 0.103 LR cohens kappa score: 0.036 LR average precision score: 0.063 -> test with 'RF' RF tn, fp: 330, 1 RF fn, tp: 6, 7 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 331, 0 GB fn, tp: 3, 10 GB f1 score: 0.870 GB cohens kappa score: 0.865 -> test with 'KNN' KNN tn, fp: 321, 10 KNN fn, tp: 0, 13 KNN f1 score: 0.722 KNN cohens kappa score: 0.708 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 194, 169 LR fn, tp: 8, 12 LR f1 score: 0.138 LR cohens kappa score: 0.069 LR average precision score: 0.083 average: LR tn, fp: 180.28, 151.52 LR fn, tp: 4.32, 9.48 LR f1 score: 0.108 LR cohens kappa score: 0.038 LR average precision score: 0.065 minimum: LR tn, fp: 163, 138 LR fn, tp: 2, 6 LR f1 score: 0.071 LR cohens kappa score: -0.003 LR average precision score: 0.049 -----[ RF ]----- maximum: RF tn, fp: 332, 3 RF fn, tp: 11, 10 RF f1 score: 0.833 RF cohens kappa score: 0.828 average: RF tn, fp: 331.12, 0.68 RF fn, tp: 6.92, 6.88 RF f1 score: 0.634 RF cohens kappa score: 0.624 minimum: RF tn, fp: 329, 0 RF fn, tp: 4, 3 RF f1 score: 0.353 RF cohens kappa score: 0.344 -----[ GB ]----- maximum: GB tn, fp: 332, 4 GB fn, tp: 9, 14 GB f1 score: 0.933 GB cohens kappa score: 0.930 average: GB tn, fp: 330.04, 1.76 GB fn, tp: 5.0, 8.8 GB f1 score: 0.714 GB cohens kappa score: 0.705 minimum: GB tn, fp: 328, 0 GB fn, tp: 0, 5 GB f1 score: 0.476 GB cohens kappa score: 0.462 -----[ KNN ]----- maximum: KNN tn, fp: 328, 54 KNN fn, tp: 3, 14 KNN f1 score: 0.875 KNN cohens kappa score: 0.869 average: KNN tn, fp: 310.44, 21.36 KNN fn, tp: 0.92, 12.88 KNN f1 score: 0.558 KNN cohens kappa score: 0.531 minimum: KNN tn, fp: 277, 4 KNN fn, tp: 0, 11 KNN f1 score: 0.304 KNN cohens kappa score: 0.257 -----[ GAN ]----- maximum: GAN tn, fp: 331, 9 GAN fn, tp: 6, 14 GAN f1 score: 0.875 GAN cohens kappa score: 0.869 average: GAN tn, fp: 326.96, 4.84 GAN fn, tp: 2.8, 11.0 GAN f1 score: 0.741 GAN cohens kappa score: 0.729 minimum: GAN tn, fp: 323, 1 GAN fn, tp: 0, 8 GAN f1 score: 0.593 GAN cohens kappa score: 0.576