/////////////////////////////////////////// // Running convGAN-proximary-full on folding_yeast6 /////////////////////////////////////////// Load 'data_input/folding_yeast6' 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 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.2957 42/116 [=========>....................] - ETA: 0s - loss: 0.0826  82/116 [====================>.........] - ETA: 0s - loss: 0.0870 116/116 [==============================] - 0s 1ms/step - loss: 0.0975 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1553 42/116 [=========>....................] - ETA: 0s - loss: 0.0701 83/116 [====================>.........] - ETA: 0s - loss: 0.0771 116/116 [==============================] - 0s 1ms/step - loss: 0.0915 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0255 42/116 [=========>....................] - ETA: 0s - loss: 0.0933 82/116 [====================>.........] - ETA: 0s - loss: 0.0942 116/116 [==============================] - 0s 1ms/step - loss: 0.0895 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2713 40/116 [=========>....................] - ETA: 0s - loss: 0.1028 80/116 [===================>..........] - ETA: 0s - loss: 0.0946 116/116 [==============================] - 0s 1ms/step - loss: 0.0872 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0058 42/116 [=========>....................] - ETA: 0s - loss: 0.0809 83/116 [====================>.........] - ETA: 0s - loss: 0.0900 116/116 [==============================] - 0s 1ms/step - loss: 0.0862 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0254 34/116 [=======>......................] - ETA: 0s - loss: 0.1050 66/116 [================>.............] - ETA: 0s - loss: 0.0912 105/116 [==========================>...] - ETA: 0s - loss: 0.0835 116/116 [==============================] - 0s 1ms/step - loss: 0.0833 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0511 41/116 [=========>....................] - ETA: 0s - loss: 0.0950 83/116 [====================>.........] - ETA: 0s - loss: 0.0868 116/116 [==============================] - 0s 1ms/step - loss: 0.0819 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1233 40/116 [=========>....................] - ETA: 0s - loss: 0.0878 78/116 [===================>..........] - ETA: 0s - loss: 0.0906 116/116 [==============================] - 0s 1ms/step - loss: 0.0792 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0137 43/116 [==========>...................] - ETA: 0s - loss: 0.0710 79/116 [===================>..........] - ETA: 0s - loss: 0.0744 114/116 [============================>.] - ETA: 0s - loss: 0.0791 116/116 [==============================] - 0s 1ms/step - loss: 0.0797 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0213 34/116 [=======>......................] - ETA: 0s - loss: 0.0738 72/116 [=================>............] - ETA: 0s - loss: 0.0735 113/116 [============================>.] - ETA: 0s - loss: 0.0783 116/116 [==============================] - 0s 1ms/step - loss: 0.0771 -> test with GAN.predict GAN tn, fp: 279, 11 GAN fn, tp: 1, 6 GAN f1 score: 0.500 GAN cohens kappa score: 0.483 -> test with 'LR' LR tn, fp: 271, 19 LR fn, tp: 1, 6 LR f1 score: 0.375 LR cohens kappa score: 0.351 LR average precision score: 0.699 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 4, 3 RF f1 score: 0.500 RF cohens kappa score: 0.490 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 4, 3 GB f1 score: 0.462 GB cohens kappa score: 0.450 -> test with 'KNN' KNN tn, fp: 277, 13 KNN fn, tp: 1, 6 KNN f1 score: 0.462 KNN cohens kappa score: 0.442 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0451 40/116 [=========>....................] - ETA: 0s - loss: 0.1817  80/116 [===================>..........] - ETA: 0s - loss: 0.1935 116/116 [==============================] - 0s 1ms/step - loss: 0.1879 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2108 40/116 [=========>....................] - ETA: 0s - loss: 0.1967 80/116 [===================>..........] - ETA: 0s - loss: 0.1619 116/116 [==============================] - 0s 1ms/step - loss: 0.1664 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0913 41/116 [=========>....................] - ETA: 0s - loss: 0.1927 81/116 [===================>..........] - ETA: 0s - loss: 0.1677 116/116 [==============================] - 0s 1ms/step - loss: 0.1559 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2274 41/116 [=========>....................] - ETA: 0s - loss: 0.1641 81/116 [===================>..........] - ETA: 0s - loss: 0.1561 116/116 [==============================] - 0s 1ms/step - loss: 0.1478 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.5400 40/116 [=========>....................] - ETA: 0s - loss: 0.1668 80/116 [===================>..........] - ETA: 0s - loss: 0.1523 116/116 [==============================] - 0s 1ms/step - loss: 0.1429 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0459 41/116 [=========>....................] - ETA: 0s - loss: 0.1328 82/116 [====================>.........] - ETA: 0s - loss: 0.1383 116/116 [==============================] - 0s 1ms/step - loss: 0.1367 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0510 40/116 [=========>....................] - ETA: 0s - loss: 0.1131 79/116 [===================>..........] - ETA: 0s - loss: 0.1283 114/116 [============================>.] - ETA: 0s - loss: 0.1330 116/116 [==============================] - 0s 1ms/step - loss: 0.1356 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1984 38/116 [========>.....................] - ETA: 0s - loss: 0.1291 78/116 [===================>..........] - ETA: 0s - loss: 0.1377 116/116 [==============================] - 0s 1ms/step - loss: 0.1347 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0416 41/116 [=========>....................] - ETA: 0s - loss: 0.1405 82/116 [====================>.........] - ETA: 0s - loss: 0.1219 116/116 [==============================] - 0s 1ms/step - loss: 0.1296 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2945 41/116 [=========>....................] - ETA: 0s - loss: 0.1498 80/116 [===================>..........] - ETA: 0s - loss: 0.1245 116/116 [==============================] - 0s 1ms/step - loss: 0.1272 -> test with GAN.predict GAN tn, fp: 273, 17 GAN fn, tp: 3, 4 GAN f1 score: 0.286 GAN cohens kappa score: 0.260 -> test with 'LR' LR tn, fp: 265, 25 LR fn, tp: 2, 5 LR f1 score: 0.270 LR cohens kappa score: 0.241 LR average precision score: 0.427 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 5, 2 RF f1 score: 0.333 RF cohens kappa score: 0.320 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 3, 4 GB f1 score: 0.533 GB cohens kappa score: 0.521 -> test with 'KNN' KNN tn, fp: 273, 17 KNN fn, tp: 3, 4 KNN f1 score: 0.286 KNN cohens kappa score: 0.260 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.1592 42/116 [=========>....................] - ETA: 0s - loss: 0.1669  82/116 [====================>.........] - ETA: 0s - loss: 0.1676 116/116 [==============================] - 0s 1ms/step - loss: 0.1636 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1153 41/116 [=========>....................] - ETA: 0s - loss: 0.1407 79/116 [===================>..........] - ETA: 0s - loss: 0.1472 114/116 [============================>.] - ETA: 0s - loss: 0.1457 116/116 [==============================] - 0s 1ms/step - loss: 0.1470 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1232 36/116 [========>.....................] - ETA: 0s - loss: 0.1703 70/116 [=================>............] - ETA: 0s - loss: 0.1617 108/116 [==========================>...] - ETA: 0s - loss: 0.1473 116/116 [==============================] - 0s 1ms/step - loss: 0.1470 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0573 41/116 [=========>....................] - ETA: 0s - loss: 0.1350 82/116 [====================>.........] - ETA: 0s - loss: 0.1368 116/116 [==============================] - 0s 1ms/step - loss: 0.1389 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2281 43/116 [==========>...................] - ETA: 0s - loss: 0.1196 83/116 [====================>.........] - ETA: 0s - loss: 0.1306 116/116 [==============================] - 0s 1ms/step - loss: 0.1360 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.3991 41/116 [=========>....................] - ETA: 0s - loss: 0.1331 79/116 [===================>..........] - ETA: 0s - loss: 0.1344 116/116 [==============================] - 0s 1ms/step - loss: 0.1308 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1784 42/116 [=========>....................] - ETA: 0s - loss: 0.1321 82/116 [====================>.........] - ETA: 0s - loss: 0.1298 116/116 [==============================] - 0s 1ms/step - loss: 0.1307 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0736 40/116 [=========>....................] - ETA: 0s - loss: 0.1343 79/116 [===================>..........] - ETA: 0s - loss: 0.1337 116/116 [==============================] - 0s 1ms/step - loss: 0.1280 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2588 42/116 [=========>....................] - ETA: 0s - loss: 0.1201 81/116 [===================>..........] - ETA: 0s - loss: 0.1265 116/116 [==============================] - 0s 1ms/step - loss: 0.1249 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0385 42/116 [=========>....................] - ETA: 0s - loss: 0.1346 81/116 [===================>..........] - ETA: 0s - loss: 0.1290 116/116 [==============================] - 0s 1ms/step - loss: 0.1246 -> test with GAN.predict GAN tn, fp: 268, 22 GAN fn, tp: 1, 6 GAN f1 score: 0.343 GAN cohens kappa score: 0.317 -> test with 'LR' LR tn, fp: 261, 29 LR fn, tp: 1, 6 LR f1 score: 0.286 LR cohens kappa score: 0.257 LR average precision score: 0.297 -> test with 'RF' RF tn, fp: 290, 0 RF fn, tp: 3, 4 RF f1 score: 0.727 RF cohens kappa score: 0.723 -> test with 'GB' GB tn, fp: 290, 0 GB fn, tp: 3, 4 GB f1 score: 0.727 GB cohens kappa score: 0.723 -> test with 'KNN' KNN tn, fp: 274, 16 KNN fn, tp: 1, 6 KNN f1 score: 0.414 KNN cohens kappa score: 0.392 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.2895 38/116 [========>.....................] - ETA: 0s - loss: 0.2063  75/116 [==================>...........] - ETA: 0s - loss: 0.1902 116/116 [==============================] - ETA: 0s - loss: 0.1864 116/116 [==============================] - 0s 1ms/step - loss: 0.1864 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0656 38/116 [========>.....................] - ETA: 0s - loss: 0.1409 78/116 [===================>..........] - ETA: 0s - loss: 0.1496 116/116 [==============================] - 0s 1ms/step - loss: 0.1557 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1260 40/116 [=========>....................] - ETA: 0s - loss: 0.1268 80/116 [===================>..........] - ETA: 0s - loss: 0.1376 116/116 [==============================] - 0s 1ms/step - loss: 0.1406 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0746 43/116 [==========>...................] - ETA: 0s - loss: 0.1391 84/116 [====================>.........] - ETA: 0s - loss: 0.1397 116/116 [==============================] - 0s 1ms/step - loss: 0.1337 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0709 42/116 [=========>....................] - ETA: 0s - loss: 0.1151 81/116 [===================>..........] - ETA: 0s - loss: 0.1301 116/116 [==============================] - 0s 1ms/step - loss: 0.1291 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2247 39/116 [=========>....................] - ETA: 0s - loss: 0.1255 79/116 [===================>..........] - ETA: 0s - loss: 0.1282 116/116 [==============================] - 0s 1ms/step - loss: 0.1282 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1370 41/116 [=========>....................] - ETA: 0s - loss: 0.1300 82/116 [====================>.........] - ETA: 0s - loss: 0.1256 116/116 [==============================] - 0s 1ms/step - loss: 0.1240 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0395 42/116 [=========>....................] - ETA: 0s - loss: 0.1367 83/116 [====================>.........] - ETA: 0s - loss: 0.1262 116/116 [==============================] - 0s 1ms/step - loss: 0.1232 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1509 34/116 [=======>......................] - ETA: 0s - loss: 0.1254 69/116 [================>.............] - ETA: 0s - loss: 0.1164 106/116 [==========================>...] - ETA: 0s - loss: 0.1167 116/116 [==============================] - 0s 1ms/step - loss: 0.1199 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1721 41/116 [=========>....................] - ETA: 0s - loss: 0.1283 77/116 [==================>...........] - ETA: 0s - loss: 0.1278 116/116 [==============================] - 0s 1ms/step - loss: 0.1202 -> test with GAN.predict GAN tn, fp: 274, 16 GAN fn, tp: 1, 6 GAN f1 score: 0.414 GAN cohens kappa score: 0.392 -> test with 'LR' LR tn, fp: 270, 20 LR fn, tp: 1, 6 LR f1 score: 0.364 LR cohens kappa score: 0.339 LR average precision score: 0.600 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 5, 2 RF f1 score: 0.364 RF cohens kappa score: 0.353 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 4, 3 GB f1 score: 0.429 GB cohens kappa score: 0.415 -> test with 'KNN' KNN tn, fp: 276, 14 KNN fn, tp: 1, 6 KNN f1 score: 0.444 KNN cohens kappa score: 0.424 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 15s - loss: 0.1071 43/116 [==========>...................] - ETA: 0s - loss: 0.1561  84/116 [====================>.........] - ETA: 0s - loss: 0.1583 116/116 [==============================] - 0s 1ms/step - loss: 0.1644 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2072 43/116 [==========>...................] - ETA: 0s - loss: 0.1679 84/116 [====================>.........] - ETA: 0s - loss: 0.1444 116/116 [==============================] - 0s 1ms/step - loss: 0.1490 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0503 45/116 [==========>...................] - ETA: 0s - loss: 0.1444 88/116 [=====================>........] - ETA: 0s - loss: 0.1393 116/116 [==============================] - 0s 1ms/step - loss: 0.1410 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.3456 44/116 [==========>...................] - ETA: 0s - loss: 0.1398 87/116 [=====================>........] - ETA: 0s - loss: 0.1429 116/116 [==============================] - 0s 1ms/step - loss: 0.1360 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.3433 38/116 [========>.....................] - ETA: 0s - loss: 0.1395 80/116 [===================>..........] - ETA: 0s - loss: 0.1321 116/116 [==============================] - 0s 1ms/step - loss: 0.1369 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0456 42/116 [=========>....................] - ETA: 0s - loss: 0.1481 84/116 [====================>.........] - ETA: 0s - loss: 0.1426 116/116 [==============================] - 0s 1ms/step - loss: 0.1359 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1746 44/116 [==========>...................] - ETA: 0s - loss: 0.1302 87/116 [=====================>........] - ETA: 0s - loss: 0.1346 116/116 [==============================] - 0s 1ms/step - loss: 0.1329 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0592 43/116 [==========>...................] - ETA: 0s - loss: 0.1247 86/116 [=====================>........] - ETA: 0s - loss: 0.1268 116/116 [==============================] - 0s 1ms/step - loss: 0.1298 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0526 43/116 [==========>...................] - ETA: 0s - loss: 0.1471 87/116 [=====================>........] - ETA: 0s - loss: 0.1357 116/116 [==============================] - 0s 1ms/step - loss: 0.1318 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1364 43/116 [==========>...................] - ETA: 0s - loss: 0.1157 84/116 [====================>.........] - ETA: 0s - loss: 0.1179 116/116 [==============================] - 0s 1ms/step - loss: 0.1303 -> test with GAN.predict GAN tn, fp: 271, 18 GAN fn, tp: 1, 6 GAN f1 score: 0.387 GAN cohens kappa score: 0.364 -> test with 'LR' LR tn, fp: 253, 36 LR fn, tp: 0, 7 LR f1 score: 0.280 LR cohens kappa score: 0.249 LR average precision score: 0.585 -> test with 'RF' RF tn, fp: 287, 2 RF fn, tp: 2, 5 RF f1 score: 0.714 RF cohens kappa score: 0.707 -> test with 'GB' GB tn, fp: 285, 4 GB fn, tp: 1, 6 GB f1 score: 0.706 GB cohens kappa score: 0.697 -> test with 'KNN' KNN tn, fp: 267, 22 KNN fn, tp: 0, 7 KNN f1 score: 0.389 KNN cohens kappa score: 0.365 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.1792 40/116 [=========>....................] - ETA: 0s - loss: 0.1497  79/116 [===================>..........] - ETA: 0s - loss: 0.1440 116/116 [==============================] - 0s 1ms/step - loss: 0.1434 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2197 36/116 [========>.....................] - ETA: 0s - loss: 0.1358 69/116 [================>.............] - ETA: 0s - loss: 0.1339 108/116 [==========================>...] - ETA: 0s - loss: 0.1294 116/116 [==============================] - 0s 1ms/step - loss: 0.1278 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0809 42/116 [=========>....................] - ETA: 0s - loss: 0.1331 83/116 [====================>.........] - ETA: 0s - loss: 0.1239 116/116 [==============================] - 0s 1ms/step - loss: 0.1179 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0405 40/116 [=========>....................] - ETA: 0s - loss: 0.1179 78/116 [===================>..........] - ETA: 0s - loss: 0.1139 116/116 [==============================] - 0s 1ms/step - loss: 0.1146 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0493 41/116 [=========>....................] - ETA: 0s - loss: 0.1113 78/116 [===================>..........] - ETA: 0s - loss: 0.1235 116/116 [==============================] - ETA: 0s - loss: 0.1115 116/116 [==============================] - 0s 1ms/step - loss: 0.1115 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0678 42/116 [=========>....................] - ETA: 0s - loss: 0.0986 82/116 [====================>.........] - ETA: 0s - loss: 0.1064 116/116 [==============================] - 0s 1ms/step - loss: 0.1092 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1571 39/116 [=========>....................] - ETA: 0s - loss: 0.0971 79/116 [===================>..........] - ETA: 0s - loss: 0.1113 116/116 [==============================] - 0s 1ms/step - loss: 0.1085 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0236 41/116 [=========>....................] - ETA: 0s - loss: 0.1039 82/116 [====================>.........] - ETA: 0s - loss: 0.1035 116/116 [==============================] - 0s 1ms/step - loss: 0.1058 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0109 40/116 [=========>....................] - ETA: 0s - loss: 0.1113 79/116 [===================>..........] - ETA: 0s - loss: 0.1023 116/116 [==============================] - 0s 1ms/step - loss: 0.1069 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0096 41/116 [=========>....................] - ETA: 0s - loss: 0.0925 81/116 [===================>..........] - ETA: 0s - loss: 0.1099 116/116 [==============================] - 0s 1ms/step - loss: 0.1044 -> test with GAN.predict GAN tn, fp: 276, 14 GAN fn, tp: 1, 6 GAN f1 score: 0.444 GAN cohens kappa score: 0.424 -> test with 'LR' LR tn, fp: 272, 18 LR fn, tp: 1, 6 LR f1 score: 0.387 LR cohens kappa score: 0.364 LR average precision score: 0.668 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 3, 4 RF f1 score: 0.571 RF cohens kappa score: 0.561 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 3, 4 GB f1 score: 0.571 GB cohens kappa score: 0.561 -> test with 'KNN' KNN tn, fp: 274, 16 KNN fn, tp: 1, 6 KNN f1 score: 0.414 KNN cohens kappa score: 0.392 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0609 37/116 [========>.....................] - ETA: 0s - loss: 0.1247  67/116 [================>.............] - ETA: 0s - loss: 0.1340 96/116 [=======================>......] - ETA: 0s - loss: 0.1277 116/116 [==============================] - 0s 2ms/step - loss: 0.1309 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0089 40/116 [=========>....................] - ETA: 0s - loss: 0.1188 79/116 [===================>..........] - ETA: 0s - loss: 0.1177 116/116 [==============================] - 0s 1ms/step - loss: 0.1191 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2476 40/116 [=========>....................] - ETA: 0s - loss: 0.0959 79/116 [===================>..........] - ETA: 0s - loss: 0.1071 116/116 [==============================] - 0s 1ms/step - loss: 0.1115 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2014 39/116 [=========>....................] - ETA: 0s - loss: 0.0966 79/116 [===================>..........] - ETA: 0s - loss: 0.1020 116/116 [==============================] - 0s 1ms/step - loss: 0.1088 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1438 41/116 [=========>....................] - ETA: 0s - loss: 0.0807 80/116 [===================>..........] - ETA: 0s - loss: 0.1056 116/116 [==============================] - 0s 1ms/step - loss: 0.1071 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0268 40/116 [=========>....................] - ETA: 0s - loss: 0.1038 80/116 [===================>..........] - ETA: 0s - loss: 0.0990 116/116 [==============================] - 0s 1ms/step - loss: 0.1029 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0779 39/116 [=========>....................] - ETA: 0s - loss: 0.1078 79/116 [===================>..........] - ETA: 0s - loss: 0.0927 116/116 [==============================] - 0s 1ms/step - loss: 0.1007 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0448 41/116 [=========>....................] - ETA: 0s - loss: 0.0993 81/116 [===================>..........] - ETA: 0s - loss: 0.1007 116/116 [==============================] - 0s 1ms/step - loss: 0.0987 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0794 39/116 [=========>....................] - ETA: 0s - loss: 0.0998 80/116 [===================>..........] - ETA: 0s - loss: 0.0959 116/116 [==============================] - 0s 1ms/step - loss: 0.0978 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1047 42/116 [=========>....................] - ETA: 0s - loss: 0.1019 83/116 [====================>.........] - ETA: 0s - loss: 0.0955 116/116 [==============================] - 0s 1ms/step - loss: 0.0994 -> test with GAN.predict GAN tn, fp: 263, 27 GAN fn, tp: 1, 6 GAN f1 score: 0.300 GAN cohens kappa score: 0.272 -> test with 'LR' LR tn, fp: 263, 27 LR fn, tp: 0, 7 LR f1 score: 0.341 LR cohens kappa score: 0.315 LR average precision score: 0.291 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 3, 4 RF f1 score: 0.571 RF cohens kappa score: 0.561 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 0, 7 GB f1 score: 0.778 GB cohens kappa score: 0.771 -> test with 'KNN' KNN tn, fp: 276, 14 KNN fn, tp: 0, 7 KNN f1 score: 0.500 KNN cohens kappa score: 0.482 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.0070 41/116 [=========>....................] - ETA: 0s - loss: 0.1289  81/116 [===================>..........] - ETA: 0s - loss: 0.1437 116/116 [==============================] - 0s 1ms/step - loss: 0.1348 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0159 41/116 [=========>....................] - ETA: 0s - loss: 0.1472 79/116 [===================>..........] - ETA: 0s - loss: 0.1290 114/116 [============================>.] - ETA: 0s - loss: 0.1244 116/116 [==============================] - 0s 1ms/step - loss: 0.1230 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1720 40/116 [=========>....................] - ETA: 0s - loss: 0.0803 80/116 [===================>..........] - ETA: 0s - loss: 0.0925 116/116 [==============================] - 0s 1ms/step - loss: 0.1111 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1218 41/116 [=========>....................] - ETA: 0s - loss: 0.1070 82/116 [====================>.........] - ETA: 0s - loss: 0.1064 116/116 [==============================] - 0s 1ms/step - loss: 0.1043 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0270 39/116 [=========>....................] - ETA: 0s - loss: 0.1000 78/116 [===================>..........] - ETA: 0s - loss: 0.0970 116/116 [==============================] - 0s 1ms/step - loss: 0.1014 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0912 41/116 [=========>....................] - ETA: 0s - loss: 0.1124 81/116 [===================>..........] - ETA: 0s - loss: 0.1043 116/116 [==============================] - 0s 1ms/step - loss: 0.0994 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1788 41/116 [=========>....................] - ETA: 0s - loss: 0.1048 80/116 [===================>..........] - ETA: 0s - loss: 0.0959 116/116 [==============================] - 0s 1ms/step - loss: 0.0993 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0133 41/116 [=========>....................] - ETA: 0s - loss: 0.0917 79/116 [===================>..........] - ETA: 0s - loss: 0.0981 116/116 [==============================] - 0s 1ms/step - loss: 0.0954 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0861 41/116 [=========>....................] - ETA: 0s - loss: 0.0879 81/116 [===================>..........] - ETA: 0s - loss: 0.0949 116/116 [==============================] - 0s 1ms/step - loss: 0.0951 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1786 38/116 [========>.....................] - ETA: 0s - loss: 0.1069 77/116 [==================>...........] - ETA: 0s - loss: 0.0920 115/116 [============================>.] - ETA: 0s - loss: 0.0946 116/116 [==============================] - 0s 1ms/step - loss: 0.0947 -> test with GAN.predict GAN tn, fp: 277, 13 GAN fn, tp: 2, 5 GAN f1 score: 0.400 GAN cohens kappa score: 0.379 -> test with 'LR' LR tn, fp: 263, 27 LR fn, tp: 1, 6 LR f1 score: 0.300 LR cohens kappa score: 0.272 LR average precision score: 0.510 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 3, 4 RF f1 score: 0.615 RF cohens kappa score: 0.607 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 3, 4 GB f1 score: 0.571 GB cohens kappa score: 0.561 -> test with 'KNN' KNN tn, fp: 265, 25 KNN fn, tp: 1, 6 KNN f1 score: 0.316 KNN cohens kappa score: 0.288 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0782 42/116 [=========>....................] - ETA: 0s - loss: 0.1696  82/116 [====================>.........] - ETA: 0s - loss: 0.1557 116/116 [==============================] - 0s 1ms/step - loss: 0.1407 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0306 38/116 [========>.....................] - ETA: 0s - loss: 0.1247 78/116 [===================>..........] - ETA: 0s - loss: 0.1234 116/116 [==============================] - 0s 1ms/step - loss: 0.1203 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2236 41/116 [=========>....................] - ETA: 0s - loss: 0.1282 79/116 [===================>..........] - ETA: 0s - loss: 0.1191 116/116 [==============================] - 0s 1ms/step - loss: 0.1148 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0221 39/116 [=========>....................] - ETA: 0s - loss: 0.1153 79/116 [===================>..........] - ETA: 0s - loss: 0.1133 116/116 [==============================] - 0s 1ms/step - loss: 0.1098 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2293 39/116 [=========>....................] - ETA: 0s - loss: 0.1133 82/116 [====================>.........] - ETA: 0s - loss: 0.1001 116/116 [==============================] - 0s 1ms/step - loss: 0.1091 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0692 41/116 [=========>....................] - ETA: 0s - loss: 0.1049 81/116 [===================>..........] - ETA: 0s - loss: 0.1040 116/116 [==============================] - 0s 1ms/step - loss: 0.1062 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0720 40/116 [=========>....................] - ETA: 0s - loss: 0.1033 77/116 [==================>...........] - ETA: 0s - loss: 0.1115 115/116 [============================>.] - ETA: 0s - loss: 0.1047 116/116 [==============================] - 0s 1ms/step - loss: 0.1046 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0689 42/116 [=========>....................] - ETA: 0s - loss: 0.1190 82/116 [====================>.........] - ETA: 0s - loss: 0.1068 116/116 [==============================] - 0s 1ms/step - loss: 0.1012 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0463 41/116 [=========>....................] - ETA: 0s - loss: 0.0916 81/116 [===================>..........] - ETA: 0s - loss: 0.0957 116/116 [==============================] - 0s 1ms/step - loss: 0.0996 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0524 40/116 [=========>....................] - ETA: 0s - loss: 0.0924 80/116 [===================>..........] - ETA: 0s - loss: 0.0897 116/116 [==============================] - 0s 1ms/step - loss: 0.0986 -> test with GAN.predict GAN tn, fp: 279, 11 GAN fn, tp: 2, 5 GAN f1 score: 0.435 GAN cohens kappa score: 0.416 -> test with 'LR' LR tn, fp: 262, 28 LR fn, tp: 2, 5 LR f1 score: 0.250 LR cohens kappa score: 0.220 LR average precision score: 0.557 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 5, 2 RF f1 score: 0.333 RF cohens kappa score: 0.320 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 5, 2 GB f1 score: 0.333 GB cohens kappa score: 0.320 -> test with 'KNN' KNN tn, fp: 271, 19 KNN fn, tp: 2, 5 KNN f1 score: 0.323 KNN cohens kappa score: 0.297 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 20s - loss: 0.1684 42/116 [=========>....................] - ETA: 0s - loss: 0.1867  83/116 [====================>.........] - ETA: 0s - loss: 0.1660 116/116 [==============================] - 0s 1ms/step - loss: 0.1585 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0283 44/116 [==========>...................] - ETA: 0s - loss: 0.1532 87/116 [=====================>........] - ETA: 0s - loss: 0.1425 116/116 [==============================] - 0s 1ms/step - loss: 0.1393 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0584 41/116 [=========>....................] - ETA: 0s - loss: 0.1214 84/116 [====================>.........] - ETA: 0s - loss: 0.1261 116/116 [==============================] - 0s 1ms/step - loss: 0.1307 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0047 44/116 [==========>...................] - ETA: 0s - loss: 0.1246 87/116 [=====================>........] - ETA: 0s - loss: 0.1282 116/116 [==============================] - 0s 1ms/step - loss: 0.1282 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0164 34/116 [=======>......................] - ETA: 0s - loss: 0.1332 70/116 [=================>............] - ETA: 0s - loss: 0.1191 112/116 [===========================>..] - ETA: 0s - loss: 0.1244 116/116 [==============================] - 0s 1ms/step - loss: 0.1225 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1530 40/116 [=========>....................] - ETA: 0s - loss: 0.1164 82/116 [====================>.........] - ETA: 0s - loss: 0.1169 116/116 [==============================] - 0s 1ms/step - loss: 0.1176 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1344 43/116 [==========>...................] - ETA: 0s - loss: 0.1116 86/116 [=====================>........] - ETA: 0s - loss: 0.1193 116/116 [==============================] - 0s 1ms/step - loss: 0.1164 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0112 37/116 [========>.....................] - ETA: 0s - loss: 0.1209 79/116 [===================>..........] - ETA: 0s - loss: 0.1222 116/116 [==============================] - 0s 1ms/step - loss: 0.1138 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1132 43/116 [==========>...................] - ETA: 0s - loss: 0.1189 85/116 [====================>.........] - ETA: 0s - loss: 0.1124 116/116 [==============================] - 0s 1ms/step - loss: 0.1113 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1277 43/116 [==========>...................] - ETA: 0s - loss: 0.0986 82/116 [====================>.........] - ETA: 0s - loss: 0.1109 116/116 [==============================] - 0s 1ms/step - loss: 0.1110 -> test with GAN.predict GAN tn, fp: 279, 10 GAN fn, tp: 2, 5 GAN f1 score: 0.455 GAN cohens kappa score: 0.436 -> test with 'LR' LR tn, fp: 272, 17 LR fn, tp: 1, 6 LR f1 score: 0.400 LR cohens kappa score: 0.377 LR average precision score: 0.530 -> test with 'RF' RF tn, fp: 289, 0 RF fn, tp: 5, 2 RF f1 score: 0.444 RF cohens kappa score: 0.439 -> test with 'GB' GB tn, fp: 289, 0 GB fn, tp: 6, 1 GB f1 score: 0.250 GB cohens kappa score: 0.246 -> test with 'KNN' KNN tn, fp: 275, 14 KNN fn, tp: 2, 5 KNN f1 score: 0.385 KNN cohens kappa score: 0.363 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.3119 42/116 [=========>....................] - ETA: 0s - loss: 0.2817  83/116 [====================>.........] - ETA: 0s - loss: 0.2615 116/116 [==============================] - 0s 1ms/step - loss: 0.2507 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0014 41/116 [=========>....................] - ETA: 0s - loss: 0.2044 81/116 [===================>..........] - ETA: 0s - loss: 0.2124 116/116 [==============================] - 0s 1ms/step - loss: 0.2022 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0292 42/116 [=========>....................] - ETA: 0s - loss: 0.1617 82/116 [====================>.........] - ETA: 0s - loss: 0.1743 116/116 [==============================] - 0s 1ms/step - loss: 0.1772 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.4640 41/116 [=========>....................] - ETA: 0s - loss: 0.1685 81/116 [===================>..........] - ETA: 0s - loss: 0.1778 116/116 [==============================] - 0s 1ms/step - loss: 0.1655 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2000 42/116 [=========>....................] - ETA: 0s - loss: 0.1560 82/116 [====================>.........] - ETA: 0s - loss: 0.1722 116/116 [==============================] - 0s 1ms/step - loss: 0.1611 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1820 41/116 [=========>....................] - ETA: 0s - loss: 0.1574 81/116 [===================>..........] - ETA: 0s - loss: 0.1564 116/116 [==============================] - 0s 1ms/step - loss: 0.1527 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0354 41/116 [=========>....................] - ETA: 0s - loss: 0.1292 81/116 [===================>..........] - ETA: 0s - loss: 0.1342 116/116 [==============================] - 0s 1ms/step - loss: 0.1472 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2782 40/116 [=========>....................] - ETA: 0s - loss: 0.1627 78/116 [===================>..........] - ETA: 0s - loss: 0.1459 116/116 [==============================] - 0s 1ms/step - loss: 0.1438 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.4791 40/116 [=========>....................] - ETA: 0s - loss: 0.1515 76/116 [==================>...........] - ETA: 0s - loss: 0.1487 112/116 [===========================>..] - ETA: 0s - loss: 0.1434 116/116 [==============================] - 0s 1ms/step - loss: 0.1436 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0877 38/116 [========>.....................] - ETA: 0s - loss: 0.1542 70/116 [=================>............] - ETA: 0s - loss: 0.1468 100/116 [========================>.....] - ETA: 0s - loss: 0.1419 116/116 [==============================] - 0s 2ms/step - loss: 0.1417 -> test with GAN.predict GAN tn, fp: 269, 21 GAN fn, tp: 1, 6 GAN f1 score: 0.353 GAN cohens kappa score: 0.328 -> test with 'LR' LR tn, fp: 262, 28 LR fn, tp: 1, 6 LR f1 score: 0.293 LR cohens kappa score: 0.264 LR average precision score: 0.633 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 4, 3 RF f1 score: 0.545 RF cohens kappa score: 0.538 -> test with 'GB' GB tn, fp: 289, 1 GB fn, tp: 4, 3 GB f1 score: 0.545 GB cohens kappa score: 0.538 -> test with 'KNN' KNN tn, fp: 268, 22 KNN fn, tp: 1, 6 KNN f1 score: 0.343 KNN cohens kappa score: 0.317 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0013 42/116 [=========>....................] - ETA: 0s - loss: 0.2808  82/116 [====================>.........] - ETA: 0s - loss: 0.2459 116/116 [==============================] - 0s 1ms/step - loss: 0.2330 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1633 41/116 [=========>....................] - ETA: 0s - loss: 0.2272 82/116 [====================>.........] - ETA: 0s - loss: 0.2041 116/116 [==============================] - 0s 1ms/step - loss: 0.1931 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0183 42/116 [=========>....................] - ETA: 0s - loss: 0.2017 83/116 [====================>.........] - ETA: 0s - loss: 0.1877 116/116 [==============================] - 0s 1ms/step - loss: 0.1749 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2477 43/116 [==========>...................] - ETA: 0s - loss: 0.1687 83/116 [====================>.........] - ETA: 0s - loss: 0.1668 116/116 [==============================] - 0s 1ms/step - loss: 0.1737 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1015 39/116 [=========>....................] - ETA: 0s - loss: 0.1678 81/116 [===================>..........] - ETA: 0s - loss: 0.1624 116/116 [==============================] - 0s 1ms/step - loss: 0.1651 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2256 42/116 [=========>....................] - ETA: 0s - loss: 0.1406 83/116 [====================>.........] - ETA: 0s - loss: 0.1544 116/116 [==============================] - 0s 1ms/step - loss: 0.1565 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.3604 42/116 [=========>....................] - ETA: 0s - loss: 0.1706 82/116 [====================>.........] - ETA: 0s - loss: 0.1500 116/116 [==============================] - 0s 1ms/step - loss: 0.1579 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0749 41/116 [=========>....................] - ETA: 0s - loss: 0.1367 81/116 [===================>..........] - ETA: 0s - loss: 0.1498 116/116 [==============================] - 0s 1ms/step - loss: 0.1541 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0564 36/116 [========>.....................] - ETA: 0s - loss: 0.1357 69/116 [================>.............] - ETA: 0s - loss: 0.1368 102/116 [=========================>....] - ETA: 0s - loss: 0.1494 116/116 [==============================] - 0s 2ms/step - loss: 0.1523 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0808 35/116 [========>.....................] - ETA: 0s - loss: 0.1486 76/116 [==================>...........] - ETA: 0s - loss: 0.1469 114/116 [============================>.] - ETA: 0s - loss: 0.1451 116/116 [==============================] - 0s 1ms/step - loss: 0.1511 -> test with GAN.predict GAN tn, fp: 267, 23 GAN fn, tp: 0, 7 GAN f1 score: 0.378 GAN cohens kappa score: 0.354 -> test with 'LR' LR tn, fp: 255, 35 LR fn, tp: 0, 7 LR f1 score: 0.286 LR cohens kappa score: 0.256 LR average precision score: 0.746 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 3, 4 RF f1 score: 0.571 RF cohens kappa score: 0.561 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 2, 5 GB f1 score: 0.625 GB cohens kappa score: 0.615 -> test with 'KNN' KNN tn, fp: 259, 31 KNN fn, tp: 0, 7 KNN f1 score: 0.311 KNN cohens kappa score: 0.283 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.2032 41/116 [=========>....................] - ETA: 0s - loss: 0.1768  82/116 [====================>.........] - ETA: 0s - loss: 0.1658 116/116 [==============================] - 0s 1ms/step - loss: 0.1653 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1805 41/116 [=========>....................] - ETA: 0s - loss: 0.1595 81/116 [===================>..........] - ETA: 0s - loss: 0.1603 116/116 [==============================] - 0s 1ms/step - loss: 0.1522 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1415 41/116 [=========>....................] - ETA: 0s - loss: 0.1523 81/116 [===================>..........] - ETA: 0s - loss: 0.1535 116/116 [==============================] - 0s 1ms/step - loss: 0.1465 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0405 40/116 [=========>....................] - ETA: 0s - loss: 0.1355 81/116 [===================>..........] - ETA: 0s - loss: 0.1449 116/116 [==============================] - 0s 1ms/step - loss: 0.1415 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0360 41/116 [=========>....................] - ETA: 0s - loss: 0.1289 82/116 [====================>.........] - ETA: 0s - loss: 0.1410 116/116 [==============================] - 0s 1ms/step - loss: 0.1405 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1497 42/116 [=========>....................] - ETA: 0s - loss: 0.1312 82/116 [====================>.........] - ETA: 0s - loss: 0.1446 116/116 [==============================] - 0s 1ms/step - loss: 0.1406 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.2624 37/116 [========>.....................] - ETA: 0s - loss: 0.1369 72/116 [=================>............] - ETA: 0s - loss: 0.1391 106/116 [==========================>...] - ETA: 0s - loss: 0.1391 116/116 [==============================] - 0s 1ms/step - loss: 0.1370 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.3044 42/116 [=========>....................] - ETA: 0s - loss: 0.1506 84/116 [====================>.........] - ETA: 0s - loss: 0.1478 116/116 [==============================] - 0s 1ms/step - loss: 0.1392 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0619 36/116 [========>.....................] - ETA: 0s - loss: 0.1514 75/116 [==================>...........] - ETA: 0s - loss: 0.1411 115/116 [============================>.] - ETA: 0s - loss: 0.1353 116/116 [==============================] - 0s 1ms/step - loss: 0.1343 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0430 42/116 [=========>....................] - ETA: 0s - loss: 0.1255 82/116 [====================>.........] - ETA: 0s - loss: 0.1243 116/116 [==============================] - 0s 1ms/step - loss: 0.1325 -> test with GAN.predict GAN tn, fp: 268, 22 GAN fn, tp: 3, 4 GAN f1 score: 0.242 GAN cohens kappa score: 0.213 -> test with 'LR' LR tn, fp: 265, 25 LR fn, tp: 2, 5 LR f1 score: 0.270 LR cohens kappa score: 0.241 LR average precision score: 0.382 -> test with 'RF' RF tn, fp: 288, 2 RF fn, tp: 6, 1 RF f1 score: 0.200 RF cohens kappa score: 0.189 -> test with 'GB' GB tn, fp: 288, 2 GB fn, tp: 5, 2 GB f1 score: 0.364 GB cohens kappa score: 0.353 -> test with 'KNN' KNN tn, fp: 276, 14 KNN fn, tp: 2, 5 KNN f1 score: 0.385 KNN cohens kappa score: 0.363 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0490 36/116 [========>.....................] - ETA: 0s - loss: 0.1699  72/116 [=================>............] - ETA: 0s - loss: 0.1642 111/116 [===========================>..] - ETA: 0s - loss: 0.1509 116/116 [==============================] - 0s 1ms/step - loss: 0.1510 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1900 42/116 [=========>....................] - ETA: 0s - loss: 0.1183 83/116 [====================>.........] - ETA: 0s - loss: 0.1362 116/116 [==============================] - 0s 1ms/step - loss: 0.1309 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0516 40/116 [=========>....................] - ETA: 0s - loss: 0.1372 81/116 [===================>..........] - ETA: 0s - loss: 0.1317 116/116 [==============================] - 0s 1ms/step - loss: 0.1282 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0476 42/116 [=========>....................] - ETA: 0s - loss: 0.1128 83/116 [====================>.........] - ETA: 0s - loss: 0.1238 116/116 [==============================] - 0s 1ms/step - loss: 0.1251 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.2836 40/116 [=========>....................] - ETA: 0s - loss: 0.1189 80/116 [===================>..........] - ETA: 0s - loss: 0.1195 116/116 [==============================] - 0s 1ms/step - loss: 0.1235 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0225 42/116 [=========>....................] - ETA: 0s - loss: 0.1012 82/116 [====================>.........] - ETA: 0s - loss: 0.1282 116/116 [==============================] - 0s 1ms/step - loss: 0.1220 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0272 38/116 [========>.....................] - ETA: 0s - loss: 0.1079 77/116 [==================>...........] - ETA: 0s - loss: 0.1127 114/116 [============================>.] - ETA: 0s - loss: 0.1217 116/116 [==============================] - 0s 1ms/step - loss: 0.1221 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0082 41/116 [=========>....................] - ETA: 0s - loss: 0.1374 81/116 [===================>..........] - ETA: 0s - loss: 0.1266 114/116 [============================>.] - ETA: 0s - loss: 0.1244 116/116 [==============================] - 0s 1ms/step - loss: 0.1226 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0696 41/116 [=========>....................] - ETA: 0s - loss: 0.1297 82/116 [====================>.........] - ETA: 0s - loss: 0.1140 116/116 [==============================] - 0s 1ms/step - loss: 0.1205 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0128 41/116 [=========>....................] - ETA: 0s - loss: 0.0967 81/116 [===================>..........] - ETA: 0s - loss: 0.1143 116/116 [==============================] - 0s 1ms/step - loss: 0.1221 -> test with GAN.predict GAN tn, fp: 276, 14 GAN fn, tp: 2, 5 GAN f1 score: 0.385 GAN cohens kappa score: 0.363 -> test with 'LR' LR tn, fp: 263, 27 LR fn, tp: 1, 6 LR f1 score: 0.300 LR cohens kappa score: 0.272 LR average precision score: 0.410 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 3, 4 RF f1 score: 0.571 RF cohens kappa score: 0.561 -> test with 'GB' GB tn, fp: 281, 9 GB fn, tp: 3, 4 GB f1 score: 0.400 GB cohens kappa score: 0.381 -> test with 'KNN' KNN tn, fp: 268, 22 KNN fn, tp: 1, 6 KNN f1 score: 0.343 KNN cohens kappa score: 0.317 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 15s - loss: 0.0440 44/116 [==========>...................] - ETA: 0s - loss: 0.1650  87/116 [=====================>........] - ETA: 0s - loss: 0.1573 116/116 [==============================] - 0s 1ms/step - loss: 0.1748 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0625 41/116 [=========>....................] - ETA: 0s - loss: 0.1617 82/116 [====================>.........] - ETA: 0s - loss: 0.1641 116/116 [==============================] - 0s 1ms/step - loss: 0.1600 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0205 44/116 [==========>...................] - ETA: 0s - loss: 0.1550 87/116 [=====================>........] - ETA: 0s - loss: 0.1508 116/116 [==============================] - 0s 1ms/step - loss: 0.1487 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1963 42/116 [=========>....................] - ETA: 0s - loss: 0.1306 86/116 [=====================>........] - ETA: 0s - loss: 0.1524 116/116 [==============================] - 0s 1ms/step - loss: 0.1480 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0733 44/116 [==========>...................] - ETA: 0s - loss: 0.1360 87/116 [=====================>........] - ETA: 0s - loss: 0.1386 116/116 [==============================] - 0s 1ms/step - loss: 0.1396 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0346 43/116 [==========>...................] - ETA: 0s - loss: 0.1505 86/116 [=====================>........] - ETA: 0s - loss: 0.1360 116/116 [==============================] - 0s 1ms/step - loss: 0.1351 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0557 44/116 [==========>...................] - ETA: 0s - loss: 0.1425 87/116 [=====================>........] - ETA: 0s - loss: 0.1385 116/116 [==============================] - 0s 1ms/step - loss: 0.1337 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0258 43/116 [==========>...................] - ETA: 0s - loss: 0.1334 86/116 [=====================>........] - ETA: 0s - loss: 0.1306 116/116 [==============================] - 0s 1ms/step - loss: 0.1315 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2260 45/116 [==========>...................] - ETA: 0s - loss: 0.1416 88/116 [=====================>........] - ETA: 0s - loss: 0.1300 116/116 [==============================] - 0s 1ms/step - loss: 0.1330 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0290 45/116 [==========>...................] - ETA: 0s - loss: 0.1406 89/116 [======================>.......] - ETA: 0s - loss: 0.1335 116/116 [==============================] - 0s 1ms/step - loss: 0.1301 -> test with GAN.predict GAN tn, fp: 274, 15 GAN fn, tp: 2, 5 GAN f1 score: 0.370 GAN cohens kappa score: 0.348 -> test with 'LR' LR tn, fp: 269, 20 LR fn, tp: 1, 6 LR f1 score: 0.364 LR cohens kappa score: 0.339 LR average precision score: 0.409 -> test with 'RF' RF tn, fp: 289, 0 RF fn, tp: 7, 0 RF f1 score: 0.000 RF cohens kappa score: 0.000 -> test with 'GB' GB tn, fp: 288, 1 GB fn, tp: 7, 0 GB f1 score: 0.000 GB cohens kappa score: -0.006 -> test with 'KNN' KNN tn, fp: 278, 11 KNN fn, tp: 1, 6 KNN f1 score: 0.500 KNN cohens kappa score: 0.483 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 21s - loss: 0.3112 42/116 [=========>....................] - ETA: 0s - loss: 0.2133  81/116 [===================>..........] - ETA: 0s - loss: 0.1953 116/116 [==============================] - 0s 1ms/step - loss: 0.1916 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2523 42/116 [=========>....................] - ETA: 0s - loss: 0.1741 82/116 [====================>.........] - ETA: 0s - loss: 0.1812 116/116 [==============================] - 0s 1ms/step - loss: 0.1770 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1135 42/116 [=========>....................] - ETA: 0s - loss: 0.1841 82/116 [====================>.........] - ETA: 0s - loss: 0.1757 116/116 [==============================] - 0s 1ms/step - loss: 0.1714 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2480 42/116 [=========>....................] - ETA: 0s - loss: 0.1602 78/116 [===================>..........] - ETA: 0s - loss: 0.1654 116/116 [==============================] - 0s 1ms/step - loss: 0.1686 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1390 41/116 [=========>....................] - ETA: 0s - loss: 0.1851 81/116 [===================>..........] - ETA: 0s - loss: 0.1698 116/116 [==============================] - 0s 1ms/step - loss: 0.1673 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1251 41/116 [=========>....................] - ETA: 0s - loss: 0.1703 80/116 [===================>..........] - ETA: 0s - loss: 0.1572 116/116 [==============================] - 0s 1ms/step - loss: 0.1643 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0489 40/116 [=========>....................] - ETA: 0s - loss: 0.1739 81/116 [===================>..........] - ETA: 0s - loss: 0.1649 116/116 [==============================] - 0s 1ms/step - loss: 0.1636 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2643 41/116 [=========>....................] - ETA: 0s - loss: 0.1528 81/116 [===================>..........] - ETA: 0s - loss: 0.1614 116/116 [==============================] - 0s 1ms/step - loss: 0.1628 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2024 40/116 [=========>....................] - ETA: 0s - loss: 0.1596 78/116 [===================>..........] - ETA: 0s - loss: 0.1655 116/116 [==============================] - 0s 1ms/step - loss: 0.1621 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2515 41/116 [=========>....................] - ETA: 0s - loss: 0.1337 77/116 [==================>...........] - ETA: 0s - loss: 0.1537 112/116 [===========================>..] - ETA: 0s - loss: 0.1562 116/116 [==============================] - 0s 1ms/step - loss: 0.1587 -> test with GAN.predict GAN tn, fp: 281, 9 GAN fn, tp: 2, 5 GAN f1 score: 0.476 GAN cohens kappa score: 0.459 -> test with 'LR' LR tn, fp: 270, 20 LR fn, tp: 1, 6 LR f1 score: 0.364 LR cohens kappa score: 0.339 LR average precision score: 0.631 -> test with 'RF' RF tn, fp: 290, 0 RF fn, tp: 3, 4 RF f1 score: 0.727 RF cohens kappa score: 0.723 -> test with 'GB' GB tn, fp: 288, 2 GB fn, tp: 1, 6 GB f1 score: 0.800 GB cohens kappa score: 0.795 -> test with 'KNN' KNN tn, fp: 271, 19 KNN fn, tp: 1, 6 KNN f1 score: 0.375 KNN cohens kappa score: 0.351 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 30s - loss: 0.1600 26/116 [=====>........................] - ETA: 0s - loss: 0.1633  55/116 [=============>................] - ETA: 0s - loss: 0.1360 81/116 [===================>..........] - ETA: 0s - loss: 0.1194 103/116 [=========================>....] - ETA: 0s - loss: 0.1180 116/116 [==============================] - 0s 2ms/step - loss: 0.1200 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0616 23/116 [====>.........................] - ETA: 0s - loss: 0.1204 46/116 [==========>...................] - ETA: 0s - loss: 0.1104 68/116 [================>.............] - ETA: 0s - loss: 0.1128 100/116 [========================>.....] - ETA: 0s - loss: 0.1167 116/116 [==============================] - 0s 2ms/step - loss: 0.1101 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1012 28/116 [======>.......................] - ETA: 0s - loss: 0.0836 53/116 [============>.................] - ETA: 0s - loss: 0.1135 83/116 [====================>.........] - ETA: 0s - loss: 0.1057 107/116 [==========================>...] - ETA: 0s - loss: 0.1020 116/116 [==============================] - 0s 2ms/step - loss: 0.1060 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1102 26/116 [=====>........................] - ETA: 0s - loss: 0.1224 47/116 [===========>..................] - ETA: 0s - loss: 0.1098 72/116 [=================>............] - ETA: 0s - loss: 0.1086 97/116 [========================>.....] - ETA: 0s - loss: 0.0975 116/116 [==============================] - 0s 2ms/step - loss: 0.1036 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1823 24/116 [=====>........................] - ETA: 0s - loss: 0.1306 42/116 [=========>....................] - ETA: 0s - loss: 0.1153 51/116 [============>.................] - ETA: 0s - loss: 0.1100 61/116 [==============>...............] - ETA: 0s - loss: 0.1124 73/116 [=================>............] - ETA: 0s - loss: 0.1106 94/116 [=======================>......] - ETA: 0s - loss: 0.1041 108/116 [==========================>...] - ETA: 0s - loss: 0.1064 116/116 [==============================] - 0s 3ms/step - loss: 0.1014 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1082 16/116 [===>..........................] - ETA: 0s - loss: 0.0819 27/116 [=====>........................] - ETA: 0s - loss: 0.1024 44/116 [==========>...................] - ETA: 0s - loss: 0.0960 64/116 [===============>..............] - ETA: 0s - loss: 0.0984 86/116 [=====================>........] - ETA: 0s - loss: 0.0955 105/116 [==========================>...] - ETA: 0s - loss: 0.0999 116/116 [==============================] - 0s 3ms/step - loss: 0.1005 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.3103 20/116 [====>.........................] - ETA: 0s - loss: 0.1127 44/116 [==========>...................] - ETA: 0s - loss: 0.1130 58/116 [==============>...............] - ETA: 0s - loss: 0.1144 74/116 [==================>...........] - ETA: 0s - loss: 0.1066 95/116 [=======================>......] - ETA: 0s - loss: 0.0987 116/116 [==============================] - 0s 3ms/step - loss: 0.0992 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0071 24/116 [=====>........................] - ETA: 0s - loss: 0.0939 47/116 [===========>..................] - ETA: 0s - loss: 0.0883 65/116 [===============>..............] - ETA: 0s - loss: 0.0967 87/116 [=====================>........] - ETA: 0s - loss: 0.1000 111/116 [===========================>..] - ETA: 0s - loss: 0.0987 116/116 [==============================] - 0s 2ms/step - loss: 0.1011 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0482 23/116 [====>.........................] - ETA: 0s - loss: 0.0962 46/116 [==========>...................] - ETA: 0s - loss: 0.0921 65/116 [===============>..............] - ETA: 0s - loss: 0.0904 80/116 [===================>..........] - ETA: 0s - loss: 0.0936 100/116 [========================>.....] - ETA: 0s - loss: 0.0945 116/116 [==============================] - 0s 3ms/step - loss: 0.0972 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2095 17/116 [===>..........................] - ETA: 0s - loss: 0.0819 38/116 [========>.....................] - ETA: 0s - loss: 0.0824 62/116 [===============>..............] - ETA: 0s - loss: 0.0891 83/116 [====================>.........] - ETA: 0s - loss: 0.0975 99/116 [========================>.....] - ETA: 0s - loss: 0.0948 115/116 [============================>.] - ETA: 0s - loss: 0.0965 116/116 [==============================] - 0s 3ms/step - loss: 0.0979 -> test with GAN.predict GAN tn, fp: 279, 11 GAN fn, tp: 1, 6 GAN f1 score: 0.500 GAN cohens kappa score: 0.483 -> test with 'LR' LR tn, fp: 266, 24 LR fn, tp: 0, 7 LR f1 score: 0.368 LR cohens kappa score: 0.343 LR average precision score: 0.303 -> test with 'RF' RF tn, fp: 287, 3 RF fn, tp: 5, 2 RF f1 score: 0.333 RF cohens kappa score: 0.320 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 4, 3 GB f1 score: 0.429 GB cohens kappa score: 0.415 -> test with 'KNN' KNN tn, fp: 273, 17 KNN fn, tp: 1, 6 KNN f1 score: 0.400 KNN cohens kappa score: 0.378 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.1128 42/116 [=========>....................] - ETA: 0s - loss: 0.1272  83/116 [====================>.........] - ETA: 0s - loss: 0.1420 116/116 [==============================] - 0s 1ms/step - loss: 0.1367 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1040 41/116 [=========>....................] - ETA: 0s - loss: 0.1126 80/116 [===================>..........] - ETA: 0s - loss: 0.1235 116/116 [==============================] - 0s 1ms/step - loss: 0.1318 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1292 42/116 [=========>....................] - ETA: 0s - loss: 0.1291 83/116 [====================>.........] - ETA: 0s - loss: 0.1361 116/116 [==============================] - 0s 1ms/step - loss: 0.1304 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.2499 41/116 [=========>....................] - ETA: 0s - loss: 0.1406 81/116 [===================>..........] - ETA: 0s - loss: 0.1205 116/116 [==============================] - 0s 1ms/step - loss: 0.1255 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0328 40/116 [=========>....................] - ETA: 0s - loss: 0.1308 81/116 [===================>..........] - ETA: 0s - loss: 0.1212 116/116 [==============================] - 0s 1ms/step - loss: 0.1251 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0819 42/116 [=========>....................] - ETA: 0s - loss: 0.1313 83/116 [====================>.........] - ETA: 0s - loss: 0.1202 116/116 [==============================] - 0s 1ms/step - loss: 0.1227 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.1839 40/116 [=========>....................] - ETA: 0s - loss: 0.1215 79/116 [===================>..........] - ETA: 0s - loss: 0.1210 116/116 [==============================] - 0s 1ms/step - loss: 0.1228 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1975 41/116 [=========>....................] - ETA: 0s - loss: 0.1208 80/116 [===================>..........] - ETA: 0s - loss: 0.1198 116/116 [==============================] - 0s 1ms/step - loss: 0.1203 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0825 42/116 [=========>....................] - ETA: 0s - loss: 0.1478 82/116 [====================>.........] - ETA: 0s - loss: 0.1112 116/116 [==============================] - 0s 1ms/step - loss: 0.1178 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.2397 42/116 [=========>....................] - ETA: 0s - loss: 0.1081 82/116 [====================>.........] - ETA: 0s - loss: 0.1210 116/116 [==============================] - 0s 1ms/step - loss: 0.1171 -> test with GAN.predict GAN tn, fp: 270, 20 GAN fn, tp: 1, 6 GAN f1 score: 0.364 GAN cohens kappa score: 0.339 -> test with 'LR' LR tn, fp: 257, 33 LR fn, tp: 1, 6 LR f1 score: 0.261 LR cohens kappa score: 0.230 LR average precision score: 0.634 -> test with 'RF' RF tn, fp: 286, 4 RF fn, tp: 2, 5 RF f1 score: 0.625 RF cohens kappa score: 0.615 -> test with 'GB' GB tn, fp: 286, 4 GB fn, tp: 1, 6 GB f1 score: 0.706 GB cohens kappa score: 0.697 -> test with 'KNN' KNN tn, fp: 262, 28 KNN fn, tp: 0, 7 KNN f1 score: 0.333 KNN cohens kappa score: 0.306 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 23s - loss: 0.0428 35/116 [========>.....................] - ETA: 0s - loss: 0.1659  73/116 [=================>............] - ETA: 0s - loss: 0.1580 112/116 [===========================>..] - ETA: 0s - loss: 0.1560 116/116 [==============================] - 0s 1ms/step - loss: 0.1557 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.1764 43/116 [==========>...................] - ETA: 0s - loss: 0.1502 82/116 [====================>.........] - ETA: 0s - loss: 0.1534 116/116 [==============================] - 0s 1ms/step - loss: 0.1508 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1980 42/116 [=========>....................] - ETA: 0s - loss: 0.1355 81/116 [===================>..........] - ETA: 0s - loss: 0.1447 116/116 [==============================] - 0s 1ms/step - loss: 0.1449 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0284 39/116 [=========>....................] - ETA: 0s - loss: 0.1564 71/116 [=================>............] - ETA: 0s - loss: 0.1445 110/116 [===========================>..] - ETA: 0s - loss: 0.1469 116/116 [==============================] - 0s 1ms/step - loss: 0.1425 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0970 40/116 [=========>....................] - ETA: 0s - loss: 0.1555 80/116 [===================>..........] - ETA: 0s - loss: 0.1487 116/116 [==============================] - 0s 1ms/step - loss: 0.1401 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.1246 40/116 [=========>....................] - ETA: 0s - loss: 0.1550 80/116 [===================>..........] - ETA: 0s - loss: 0.1332 116/116 [==============================] - 0s 1ms/step - loss: 0.1368 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0770 39/116 [=========>....................] - ETA: 0s - loss: 0.1387 80/116 [===================>..........] - ETA: 0s - loss: 0.1301 116/116 [==============================] - 0s 1ms/step - loss: 0.1343 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1725 41/116 [=========>....................] - ETA: 0s - loss: 0.1336 79/116 [===================>..........] - ETA: 0s - loss: 0.1329 116/116 [==============================] - 0s 1ms/step - loss: 0.1339 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1424 41/116 [=========>....................] - ETA: 0s - loss: 0.1370 80/116 [===================>..........] - ETA: 0s - loss: 0.1392 116/116 [==============================] - 0s 1ms/step - loss: 0.1331 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1734 41/116 [=========>....................] - ETA: 0s - loss: 0.1387 81/116 [===================>..........] - ETA: 0s - loss: 0.1311 116/116 [==============================] - 0s 1ms/step - loss: 0.1292 -> test with GAN.predict GAN tn, fp: 273, 17 GAN fn, tp: 2, 5 GAN f1 score: 0.345 GAN cohens kappa score: 0.321 -> test with 'LR' LR tn, fp: 262, 28 LR fn, tp: 1, 6 LR f1 score: 0.293 LR cohens kappa score: 0.264 LR average precision score: 0.653 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 4, 3 RF f1 score: 0.545 RF cohens kappa score: 0.538 -> test with 'GB' GB tn, fp: 289, 1 GB fn, tp: 4, 3 GB f1 score: 0.545 GB cohens kappa score: 0.538 -> test with 'KNN' KNN tn, fp: 274, 16 KNN fn, tp: 1, 6 KNN f1 score: 0.414 KNN cohens kappa score: 0.392 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 16s - loss: 0.1605 44/116 [==========>...................] - ETA: 0s - loss: 0.1422  87/116 [=====================>........] - ETA: 0s - loss: 0.1406 116/116 [==============================] - 0s 1ms/step - loss: 0.1370 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0135 45/116 [==========>...................] - ETA: 0s - loss: 0.1366 89/116 [======================>.......] - ETA: 0s - loss: 0.1313 116/116 [==============================] - 0s 1ms/step - loss: 0.1233 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1735 44/116 [==========>...................] - ETA: 0s - loss: 0.1240 87/116 [=====================>........] - ETA: 0s - loss: 0.1230 116/116 [==============================] - 0s 1ms/step - loss: 0.1176 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1072 44/116 [==========>...................] - ETA: 0s - loss: 0.1018 87/116 [=====================>........] - ETA: 0s - loss: 0.1078 116/116 [==============================] - 0s 1ms/step - loss: 0.1115 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1275 45/116 [==========>...................] - ETA: 0s - loss: 0.1129 86/116 [=====================>........] - ETA: 0s - loss: 0.1166 116/116 [==============================] - 0s 1ms/step - loss: 0.1093 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0587 44/116 [==========>...................] - ETA: 0s - loss: 0.1153 87/116 [=====================>........] - ETA: 0s - loss: 0.1176 116/116 [==============================] - 0s 1ms/step - loss: 0.1083 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0499 42/116 [=========>....................] - ETA: 0s - loss: 0.1234 85/116 [====================>.........] - ETA: 0s - loss: 0.1075 116/116 [==============================] - 0s 1ms/step - loss: 0.1076 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0469 45/116 [==========>...................] - ETA: 0s - loss: 0.1100 86/116 [=====================>........] - ETA: 0s - loss: 0.0964 116/116 [==============================] - 0s 1ms/step - loss: 0.1037 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1585 44/116 [==========>...................] - ETA: 0s - loss: 0.0907 87/116 [=====================>........] - ETA: 0s - loss: 0.1047 116/116 [==============================] - 0s 1ms/step - loss: 0.1038 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1129 44/116 [==========>...................] - ETA: 0s - loss: 0.0998 87/116 [=====================>........] - ETA: 0s - loss: 0.0960 116/116 [==============================] - 0s 1ms/step - loss: 0.1005 -> test with GAN.predict GAN tn, fp: 276, 13 GAN fn, tp: 2, 5 GAN f1 score: 0.400 GAN cohens kappa score: 0.379 -> test with 'LR' LR tn, fp: 267, 22 LR fn, tp: 2, 5 LR f1 score: 0.294 LR cohens kappa score: 0.267 LR average precision score: 0.672 -> test with 'RF' RF tn, fp: 288, 1 RF fn, tp: 4, 3 RF f1 score: 0.545 RF cohens kappa score: 0.537 -> test with 'GB' GB tn, fp: 288, 1 GB fn, tp: 4, 3 GB f1 score: 0.545 GB cohens kappa score: 0.537 -> test with 'KNN' KNN tn, fp: 277, 12 KNN fn, tp: 2, 5 KNN f1 score: 0.417 KNN cohens kappa score: 0.396 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 19s - loss: 0.0042 41/116 [=========>....................] - ETA: 0s - loss: 0.1682  82/116 [====================>.........] - ETA: 0s - loss: 0.1598 116/116 [==============================] - 0s 1ms/step - loss: 0.1608 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2251 40/116 [=========>....................] - ETA: 0s - loss: 0.1772 79/116 [===================>..........] - ETA: 0s - loss: 0.1708 116/116 [==============================] - 0s 1ms/step - loss: 0.1588 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2664 40/116 [=========>....................] - ETA: 0s - loss: 0.1475 80/116 [===================>..........] - ETA: 0s - loss: 0.1483 115/116 [============================>.] - ETA: 0s - loss: 0.1465 116/116 [==============================] - 0s 1ms/step - loss: 0.1458 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1695 35/116 [========>.....................] - ETA: 0s - loss: 0.1174 70/116 [=================>............] - ETA: 0s - loss: 0.1282 111/116 [===========================>..] - ETA: 0s - loss: 0.1392 116/116 [==============================] - 0s 1ms/step - loss: 0.1425 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0563 41/116 [=========>....................] - ETA: 0s - loss: 0.1378 81/116 [===================>..........] - ETA: 0s - loss: 0.1418 116/116 [==============================] - 0s 1ms/step - loss: 0.1388 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0431 41/116 [=========>....................] - ETA: 0s - loss: 0.1235 81/116 [===================>..........] - ETA: 0s - loss: 0.1344 116/116 [==============================] - 0s 1ms/step - loss: 0.1404 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0790 40/116 [=========>....................] - ETA: 0s - loss: 0.1292 81/116 [===================>..........] - ETA: 0s - loss: 0.1312 116/116 [==============================] - 0s 1ms/step - loss: 0.1386 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.1650 40/116 [=========>....................] - ETA: 0s - loss: 0.1307 76/116 [==================>...........] - ETA: 0s - loss: 0.1248 116/116 [==============================] - ETA: 0s - loss: 0.1316 116/116 [==============================] - 0s 1ms/step - loss: 0.1316 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0423 41/116 [=========>....................] - ETA: 0s - loss: 0.1295 82/116 [====================>.........] - ETA: 0s - loss: 0.1305 116/116 [==============================] - 0s 1ms/step - loss: 0.1307 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.4222 41/116 [=========>....................] - ETA: 0s - loss: 0.1276 82/116 [====================>.........] - ETA: 0s - loss: 0.1331 116/116 [==============================] - 0s 1ms/step - loss: 0.1317 -> test with GAN.predict GAN tn, fp: 265, 25 GAN fn, tp: 1, 6 GAN f1 score: 0.316 GAN cohens kappa score: 0.288 -> test with 'LR' LR tn, fp: 259, 31 LR fn, tp: 0, 7 LR f1 score: 0.311 LR cohens kappa score: 0.283 LR average precision score: 0.503 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 3, 4 RF f1 score: 0.667 RF cohens kappa score: 0.660 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 3, 4 GB f1 score: 0.571 GB cohens kappa score: 0.561 -> test with 'KNN' KNN tn, fp: 268, 22 KNN fn, tp: 1, 6 KNN f1 score: 0.343 KNN cohens kappa score: 0.317 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 18s - loss: 0.0216 37/116 [========>.....................] - ETA: 0s - loss: 0.0721  71/116 [=================>............] - ETA: 0s - loss: 0.0743 108/116 [==========================>...] - ETA: 0s - loss: 0.0756 116/116 [==============================] - 0s 1ms/step - loss: 0.0805 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.0577 38/116 [========>.....................] - ETA: 0s - loss: 0.0601 72/116 [=================>............] - ETA: 0s - loss: 0.0663 108/116 [==========================>...] - ETA: 0s - loss: 0.0690 116/116 [==============================] - 0s 1ms/step - loss: 0.0689 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.2663 36/116 [========>.....................] - ETA: 0s - loss: 0.0681 69/116 [================>.............] - ETA: 0s - loss: 0.0721 104/116 [=========================>....] - ETA: 0s - loss: 0.0684 116/116 [==============================] - 0s 1ms/step - loss: 0.0638 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.1261 36/116 [========>.....................] - ETA: 0s - loss: 0.0466 71/116 [=================>............] - ETA: 0s - loss: 0.0425 106/116 [==========================>...] - ETA: 0s - loss: 0.0482 116/116 [==============================] - 0s 1ms/step - loss: 0.0585 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1395 32/116 [=======>......................] - ETA: 0s - loss: 0.0723 63/116 [===============>..............] - ETA: 0s - loss: 0.0589 97/116 [========================>.....] - ETA: 0s - loss: 0.0585 116/116 [==============================] - 0s 2ms/step - loss: 0.0590 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0030 40/116 [=========>....................] - ETA: 0s - loss: 0.0606 79/116 [===================>..........] - ETA: 0s - loss: 0.0641 110/116 [===========================>..] - ETA: 0s - loss: 0.0578 116/116 [==============================] - 0s 1ms/step - loss: 0.0580 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0757 35/116 [========>.....................] - ETA: 0s - loss: 0.0580 62/116 [===============>..............] - ETA: 0s - loss: 0.0653 93/116 [=======================>......] - ETA: 0s - loss: 0.0590 116/116 [==============================] - 0s 2ms/step - loss: 0.0560 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0528 36/116 [========>.....................] - ETA: 0s - loss: 0.0484 72/116 [=================>............] - ETA: 0s - loss: 0.0493 108/116 [==========================>...] - ETA: 0s - loss: 0.0575 116/116 [==============================] - 0s 1ms/step - loss: 0.0554 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.1425 33/116 [=======>......................] - ETA: 0s - loss: 0.0778 71/116 [=================>............] - ETA: 0s - loss: 0.0592 109/116 [===========================>..] - ETA: 0s - loss: 0.0528 116/116 [==============================] - 0s 1ms/step - loss: 0.0545 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0086 37/116 [========>.....................] - ETA: 0s - loss: 0.0367 68/116 [================>.............] - ETA: 0s - loss: 0.0517 102/116 [=========================>....] - ETA: 0s - loss: 0.0534 116/116 [==============================] - 0s 1ms/step - loss: 0.0549 -> test with GAN.predict GAN tn, fp: 284, 6 GAN fn, tp: 3, 4 GAN f1 score: 0.471 GAN cohens kappa score: 0.455 -> test with 'LR' LR tn, fp: 274, 16 LR fn, tp: 3, 4 LR f1 score: 0.296 LR cohens kappa score: 0.271 LR average precision score: 0.222 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 3, 4 RF f1 score: 0.667 RF cohens kappa score: 0.660 -> test with 'GB' GB tn, fp: 287, 3 GB fn, tp: 3, 4 GB f1 score: 0.571 GB cohens kappa score: 0.561 -> test with 'KNN' KNN tn, fp: 284, 6 KNN fn, tp: 3, 4 KNN f1 score: 0.471 KNN cohens kappa score: 0.455 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 17s - loss: 0.5072 41/116 [=========>....................] - ETA: 0s - loss: 0.1911  82/116 [====================>.........] - ETA: 0s - loss: 0.1917 116/116 [==============================] - 0s 1ms/step - loss: 0.2063 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2567 41/116 [=========>....................] - ETA: 0s - loss: 0.1957 81/116 [===================>..........] - ETA: 0s - loss: 0.2007 116/116 [==============================] - 0s 1ms/step - loss: 0.1866 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.1290 40/116 [=========>....................] - ETA: 0s - loss: 0.2091 80/116 [===================>..........] - ETA: 0s - loss: 0.1828 114/116 [============================>.] - ETA: 0s - loss: 0.1777 116/116 [==============================] - 0s 1ms/step - loss: 0.1781 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0311 38/116 [========>.....................] - ETA: 0s - loss: 0.1637 73/116 [=================>............] - ETA: 0s - loss: 0.1729 112/116 [===========================>..] - ETA: 0s - loss: 0.1720 116/116 [==============================] - 0s 1ms/step - loss: 0.1736 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0930 38/116 [========>.....................] - ETA: 0s - loss: 0.1898 79/116 [===================>..........] - ETA: 0s - loss: 0.1688 116/116 [==============================] - 0s 1ms/step - loss: 0.1674 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2449 40/116 [=========>....................] - ETA: 0s - loss: 0.1651 79/116 [===================>..........] - ETA: 0s - loss: 0.1648 116/116 [==============================] - 0s 1ms/step - loss: 0.1670 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0724 42/116 [=========>....................] - ETA: 0s - loss: 0.1734 78/116 [===================>..........] - ETA: 0s - loss: 0.1716 115/116 [============================>.] - ETA: 0s - loss: 0.1636 116/116 [==============================] - 0s 1ms/step - loss: 0.1633 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.2415 40/116 [=========>....................] - ETA: 0s - loss: 0.1590 81/116 [===================>..........] - ETA: 0s - loss: 0.1668 116/116 [==============================] - 0s 1ms/step - loss: 0.1653 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2866 41/116 [=========>....................] - ETA: 0s - loss: 0.1590 80/116 [===================>..........] - ETA: 0s - loss: 0.1732 116/116 [==============================] - 0s 1ms/step - loss: 0.1676 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.1148 40/116 [=========>....................] - ETA: 0s - loss: 0.1453 81/116 [===================>..........] - ETA: 0s - loss: 0.1499 116/116 [==============================] - 0s 1ms/step - loss: 0.1591 -> test with GAN.predict GAN tn, fp: 266, 24 GAN fn, tp: 0, 7 GAN f1 score: 0.368 GAN cohens kappa score: 0.343 -> test with 'LR' LR tn, fp: 259, 31 LR fn, tp: 0, 7 LR f1 score: 0.311 LR cohens kappa score: 0.283 LR average precision score: 0.720 -> test with 'RF' RF tn, fp: 285, 5 RF fn, tp: 1, 6 RF f1 score: 0.667 RF cohens kappa score: 0.657 -> test with 'GB' GB tn, fp: 285, 5 GB fn, tp: 0, 7 GB f1 score: 0.737 GB cohens kappa score: 0.729 -> test with 'KNN' KNN tn, fp: 273, 17 KNN fn, tp: 0, 7 KNN f1 score: 0.452 KNN cohens kappa score: 0.431 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1131 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 49s - loss: 0.1183 42/116 [=========>....................] - ETA: 0s - loss: 0.1624  83/116 [====================>.........] - ETA: 0s - loss: 0.1627 116/116 [==============================] - 1s 1ms/step - loss: 0.1681 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.2805 41/116 [=========>....................] - ETA: 0s - loss: 0.1486 82/116 [====================>.........] - ETA: 0s - loss: 0.1588 116/116 [==============================] - 0s 1ms/step - loss: 0.1548 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.0235 42/116 [=========>....................] - ETA: 0s - loss: 0.1062 82/116 [====================>.........] - ETA: 0s - loss: 0.1361 116/116 [==============================] - 0s 1ms/step - loss: 0.1455 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.3295 41/116 [=========>....................] - ETA: 0s - loss: 0.1444 82/116 [====================>.........] - ETA: 0s - loss: 0.1329 116/116 [==============================] - 0s 1ms/step - loss: 0.1454 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.0205 41/116 [=========>....................] - ETA: 0s - loss: 0.1218 82/116 [====================>.........] - ETA: 0s - loss: 0.1449 116/116 [==============================] - 0s 1ms/step - loss: 0.1398 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.2333 41/116 [=========>....................] - ETA: 0s - loss: 0.1468 80/116 [===================>..........] - ETA: 0s - loss: 0.1323 116/116 [==============================] - 0s 1ms/step - loss: 0.1378 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.0970 42/116 [=========>....................] - ETA: 0s - loss: 0.1211 81/116 [===================>..........] - ETA: 0s - loss: 0.1427 116/116 [==============================] - 0s 1ms/step - loss: 0.1355 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0464 41/116 [=========>....................] - ETA: 0s - loss: 0.1344 76/116 [==================>...........] - ETA: 0s - loss: 0.1297 110/116 [===========================>..] - ETA: 0s - loss: 0.1349 116/116 [==============================] - 0s 1ms/step - loss: 0.1360 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.0965 35/116 [========>.....................] - ETA: 0s - loss: 0.1337 74/116 [==================>...........] - ETA: 0s - loss: 0.1275 113/116 [============================>.] - ETA: 0s - loss: 0.1335 116/116 [==============================] - 0s 1ms/step - loss: 0.1330 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0340 40/116 [=========>....................] - ETA: 0s - loss: 0.1294 80/116 [===================>..........] - ETA: 0s - loss: 0.1300 116/116 [==============================] - 0s 1ms/step - loss: 0.1320 -> test with GAN.predict GAN tn, fp: 273, 17 GAN fn, tp: 3, 4 GAN f1 score: 0.286 GAN cohens kappa score: 0.260 -> test with 'LR' LR tn, fp: 259, 31 LR fn, tp: 0, 7 LR f1 score: 0.311 LR cohens kappa score: 0.283 LR average precision score: 0.439 -> test with 'RF' RF tn, fp: 289, 1 RF fn, tp: 5, 2 RF f1 score: 0.400 RF cohens kappa score: 0.391 -> test with 'GB' GB tn, fp: 289, 1 GB fn, tp: 5, 2 GB f1 score: 0.400 GB cohens kappa score: 0.391 -> test with 'KNN' KNN tn, fp: 275, 15 KNN fn, tp: 1, 6 KNN f1 score: 0.429 KNN cohens kappa score: 0.408 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 1132 synthetic samples -> retrain GAN for predict Epoch 1/10 1/116 [..............................] - ETA: 16s - loss: 0.1445 51/116 [============>.................] - ETA: 0s - loss: 0.1981  101/116 [=========================>....] - ETA: 0s - loss: 0.2016 116/116 [==============================] - 0s 1ms/step - loss: 0.1933 Epoch 2/10 1/116 [..............................] - ETA: 0s - loss: 0.3912 51/116 [============>.................] - ETA: 0s - loss: 0.1831 102/116 [=========================>....] - ETA: 0s - loss: 0.1798 116/116 [==============================] - 0s 1ms/step - loss: 0.1774 Epoch 3/10 1/116 [..............................] - ETA: 0s - loss: 0.4066 51/116 [============>.................] - ETA: 0s - loss: 0.1535 100/116 [========================>.....] - ETA: 0s - loss: 0.1676 116/116 [==============================] - 0s 1ms/step - loss: 0.1641 Epoch 4/10 1/116 [..............................] - ETA: 0s - loss: 0.0619 52/116 [============>.................] - ETA: 0s - loss: 0.1676 103/116 [=========================>....] - ETA: 0s - loss: 0.1642 116/116 [==============================] - 0s 995us/step - loss: 0.1591 Epoch 5/10 1/116 [..............................] - ETA: 0s - loss: 0.1903 51/116 [============>.................] - ETA: 0s - loss: 0.1571 100/116 [========================>.....] - ETA: 0s - loss: 0.1537 116/116 [==============================] - 0s 1ms/step - loss: 0.1543 Epoch 6/10 1/116 [..............................] - ETA: 0s - loss: 0.0047 49/116 [===========>..................] - ETA: 0s - loss: 0.1451 96/116 [=======================>......] - ETA: 0s - loss: 0.1543 116/116 [==============================] - 0s 1ms/step - loss: 0.1517 Epoch 7/10 1/116 [..............................] - ETA: 0s - loss: 0.4658 51/116 [============>.................] - ETA: 0s - loss: 0.1713 102/116 [=========================>....] - ETA: 0s - loss: 0.1463 116/116 [==============================] - 0s 1ms/step - loss: 0.1462 Epoch 8/10 1/116 [..............................] - ETA: 0s - loss: 0.0147 51/116 [============>.................] - ETA: 0s - loss: 0.1340 102/116 [=========================>....] - ETA: 0s - loss: 0.1440 116/116 [==============================] - 0s 1ms/step - loss: 0.1429 Epoch 9/10 1/116 [..............................] - ETA: 0s - loss: 0.2071 52/116 [============>.................] - ETA: 0s - loss: 0.1433 103/116 [=========================>....] - ETA: 0s - loss: 0.1443 116/116 [==============================] - 0s 998us/step - loss: 0.1418 Epoch 10/10 1/116 [..............................] - ETA: 0s - loss: 0.0283 52/116 [============>.................] - ETA: 0s - loss: 0.1293 103/116 [=========================>....] - ETA: 0s - loss: 0.1375 116/116 [==============================] - 0s 995us/step - loss: 0.1367 -> test with GAN.predict GAN tn, fp: 271, 18 GAN fn, tp: 2, 5 GAN f1 score: 0.333 GAN cohens kappa score: 0.308 -> test with 'LR' LR tn, fp: 270, 19 LR fn, tp: 2, 5 LR f1 score: 0.323 LR cohens kappa score: 0.297 LR average precision score: 0.432 -> test with 'RF' RF tn, fp: 287, 2 RF fn, tp: 4, 3 RF f1 score: 0.500 RF cohens kappa score: 0.490 -> test with 'GB' GB tn, fp: 284, 5 GB fn, tp: 4, 3 GB f1 score: 0.400 GB cohens kappa score: 0.384 -> test with 'KNN' KNN tn, fp: 268, 21 KNN fn, tp: 2, 5 KNN f1 score: 0.303 KNN cohens kappa score: 0.276 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 274, 36 LR fn, tp: 3, 7 LR f1 score: 0.400 LR cohens kappa score: 0.377 LR average precision score: 0.746 average: LR tn, fp: 264.36, 25.44 LR fn, tp: 1.0, 6.0 LR f1 score: 0.316 LR cohens kappa score: 0.289 LR average precision score: 0.518 minimum: LR tn, fp: 253, 16 LR fn, tp: 0, 4 LR f1 score: 0.250 LR cohens kappa score: 0.220 LR average precision score: 0.222 -----[ RF ]----- maximum: RF tn, fp: 290, 5 RF fn, tp: 7, 6 RF f1 score: 0.727 RF cohens kappa score: 0.723 average: RF tn, fp: 287.88, 1.92 RF fn, tp: 3.8, 3.2 RF f1 score: 0.510 RF cohens kappa score: 0.501 minimum: RF tn, fp: 285, 0 RF fn, tp: 1, 0 RF f1 score: 0.000 RF cohens kappa score: 0.000 -----[ GB ]----- maximum: GB tn, fp: 290, 9 GB fn, tp: 7, 7 GB f1 score: 0.800 GB cohens kappa score: 0.795 average: GB tn, fp: 286.84, 2.96 GB fn, tp: 3.28, 3.72 GB f1 score: 0.520 GB cohens kappa score: 0.510 minimum: GB tn, fp: 281, 0 GB fn, tp: 0, 0 GB f1 score: 0.000 GB cohens kappa score: -0.006 -----[ KNN ]----- maximum: KNN tn, fp: 284, 31 KNN fn, tp: 3, 7 KNN f1 score: 0.500 KNN cohens kappa score: 0.483 average: KNN tn, fp: 272.08, 17.72 KNN fn, tp: 1.16, 5.84 KNN f1 score: 0.390 KNN cohens kappa score: 0.367 minimum: KNN tn, fp: 259, 6 KNN fn, tp: 0, 4 KNN f1 score: 0.286 KNN cohens kappa score: 0.260 -----[ GAN ]----- maximum: GAN tn, fp: 284, 27 GAN fn, tp: 3, 7 GAN f1 score: 0.500 GAN cohens kappa score: 0.483 average: GAN tn, fp: 273.24, 16.56 GAN fn, tp: 1.6, 5.4 GAN f1 score: 0.382 GAN cohens kappa score: 0.359 minimum: GAN tn, fp: 263, 6 GAN fn, tp: 0, 4 GAN f1 score: 0.242 GAN cohens kappa score: 0.213