/////////////////////////////////////////// // Running convGAN-proximary-5 on folding_abalone9-18 /////////////////////////////////////////// Load 'data_input/folding_abalone9-18' 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 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.3139 48/56 [========================>.....] - ETA: 0s - loss: 0.3170 56/56 [==============================] - 0s 1ms/step - loss: 0.3105 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.2118 49/56 [=========================>....] - ETA: 0s - loss: 0.2738 56/56 [==============================] - 0s 1ms/step - loss: 0.2798 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.3107 49/56 [=========================>....] - ETA: 0s - loss: 0.2656 56/56 [==============================] - 0s 1ms/step - loss: 0.2692 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2456 50/56 [=========================>....] - ETA: 0s - loss: 0.2558 56/56 [==============================] - 0s 1ms/step - loss: 0.2661 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.2137 49/56 [=========================>....] - ETA: 0s - loss: 0.2639 56/56 [==============================] - 0s 1ms/step - loss: 0.2594 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.3034 48/56 [========================>.....] - ETA: 0s - loss: 0.2571 56/56 [==============================] - 0s 1ms/step - loss: 0.2606 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.2322 49/56 [=========================>....] - ETA: 0s - loss: 0.2535 56/56 [==============================] - 0s 1ms/step - loss: 0.2596 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1629 49/56 [=========================>....] - ETA: 0s - loss: 0.2469 56/56 [==============================] - 0s 1ms/step - loss: 0.2525 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2681 49/56 [=========================>....] - ETA: 0s - loss: 0.2412 56/56 [==============================] - 0s 1ms/step - loss: 0.2452 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1973 46/56 [=======================>......] - ETA: 0s - loss: 0.2521 56/56 [==============================] - 0s 1ms/step - loss: 0.2437 -> test with GAN.predict GAN tn, fp: 123, 15 GAN fn, tp: 0, 9 GAN f1 score: 0.545 GAN cohens kappa score: 0.501 -> test with 'LR' LR tn, fp: 121, 17 LR fn, tp: 0, 9 LR f1 score: 0.514 LR cohens kappa score: 0.466 LR average precision score: 0.900 -> test with 'RF' RF tn, fp: 135, 3 RF fn, tp: 8, 1 RF f1 score: 0.154 RF cohens kappa score: 0.121 -> test with 'GB' GB tn, fp: 131, 7 GB fn, tp: 6, 3 GB f1 score: 0.316 GB cohens kappa score: 0.269 -> test with 'KNN' KNN tn, fp: 127, 11 KNN fn, tp: 5, 4 KNN f1 score: 0.333 KNN cohens kappa score: 0.278 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.2407 48/56 [========================>.....] - ETA: 0s - loss: 0.2346 56/56 [==============================] - 0s 1ms/step - loss: 0.2280 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.3300 50/56 [=========================>....] - ETA: 0s - loss: 0.2117 56/56 [==============================] - 0s 1ms/step - loss: 0.2228 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1163 49/56 [=========================>....] - ETA: 0s - loss: 0.1994 56/56 [==============================] - 0s 1ms/step - loss: 0.2135 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.0709 50/56 [=========================>....] - ETA: 0s - loss: 0.2164 56/56 [==============================] - 0s 1ms/step - loss: 0.2159 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1597 49/56 [=========================>....] - ETA: 0s - loss: 0.2100 56/56 [==============================] - 0s 1ms/step - loss: 0.2090 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1629 49/56 [=========================>....] - ETA: 0s - loss: 0.2090 56/56 [==============================] - 0s 1ms/step - loss: 0.2055 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.3150 49/56 [=========================>....] - ETA: 0s - loss: 0.1964 56/56 [==============================] - 0s 1ms/step - loss: 0.2037 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1107 49/56 [=========================>....] - ETA: 0s - loss: 0.2042 56/56 [==============================] - 0s 1ms/step - loss: 0.2030 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2163 50/56 [=========================>....] - ETA: 0s - loss: 0.1992 56/56 [==============================] - 0s 1ms/step - loss: 0.2018 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1248 49/56 [=========================>....] - ETA: 0s - loss: 0.2044 56/56 [==============================] - 0s 1ms/step - loss: 0.2029 -> test with GAN.predict GAN tn, fp: 122, 16 GAN fn, tp: 2, 7 GAN f1 score: 0.438 GAN cohens kappa score: 0.383 -> test with 'LR' LR tn, fp: 128, 10 LR fn, tp: 3, 6 LR f1 score: 0.480 LR cohens kappa score: 0.436 LR average precision score: 0.573 -> test with 'RF' RF tn, fp: 136, 2 RF fn, tp: 7, 2 RF f1 score: 0.308 RF cohens kappa score: 0.281 -> test with 'GB' GB tn, fp: 132, 6 GB fn, tp: 5, 4 GB f1 score: 0.421 GB cohens kappa score: 0.381 -> test with 'KNN' KNN tn, fp: 118, 20 KNN fn, tp: 3, 6 KNN f1 score: 0.343 KNN cohens kappa score: 0.277 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.2635 48/56 [========================>.....] - ETA: 0s - loss: 0.2359 56/56 [==============================] - 0s 1ms/step - loss: 0.2345 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.2846 49/56 [=========================>....] - ETA: 0s - loss: 0.2214 56/56 [==============================] - 0s 1ms/step - loss: 0.2227 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1574 49/56 [=========================>....] - ETA: 0s - loss: 0.2240 56/56 [==============================] - 0s 1ms/step - loss: 0.2171 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2210 48/56 [========================>.....] - ETA: 0s - loss: 0.2208 56/56 [==============================] - 0s 1ms/step - loss: 0.2166 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.2292 49/56 [=========================>....] - ETA: 0s - loss: 0.2114 56/56 [==============================] - 0s 1ms/step - loss: 0.2076 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1754 49/56 [=========================>....] - ETA: 0s - loss: 0.2012 56/56 [==============================] - 0s 1ms/step - loss: 0.2072 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1733 50/56 [=========================>....] - ETA: 0s - loss: 0.2011 56/56 [==============================] - 0s 1ms/step - loss: 0.2066 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1175 50/56 [=========================>....] - ETA: 0s - loss: 0.2050 56/56 [==============================] - 0s 1ms/step - loss: 0.2051 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2323 50/56 [=========================>....] - ETA: 0s - loss: 0.2060 56/56 [==============================] - 0s 1ms/step - loss: 0.2056 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1022 49/56 [=========================>....] - ETA: 0s - loss: 0.2028 56/56 [==============================] - 0s 1ms/step - loss: 0.1999 -> test with GAN.predict GAN tn, fp: 129, 9 GAN fn, tp: 2, 7 GAN f1 score: 0.560 GAN cohens kappa score: 0.523 -> test with 'LR' LR tn, fp: 127, 11 LR fn, tp: 0, 9 LR f1 score: 0.621 LR cohens kappa score: 0.586 LR average precision score: 0.805 -> test with 'RF' RF tn, fp: 133, 5 RF fn, tp: 6, 3 RF f1 score: 0.353 RF cohens kappa score: 0.313 -> test with 'GB' GB tn, fp: 131, 7 GB fn, tp: 6, 3 GB f1 score: 0.316 GB cohens kappa score: 0.269 -> test with 'KNN' KNN tn, fp: 124, 14 KNN fn, tp: 2, 7 KNN f1 score: 0.467 KNN cohens kappa score: 0.417 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.1883 48/56 [========================>.....] - ETA: 0s - loss: 0.2052 56/56 [==============================] - 0s 1ms/step - loss: 0.2019 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1815 45/56 [=======================>......] - ETA: 0s - loss: 0.1912 56/56 [==============================] - 0s 1ms/step - loss: 0.1940 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1067 49/56 [=========================>....] - ETA: 0s - loss: 0.1914 56/56 [==============================] - 0s 1ms/step - loss: 0.1935 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1867 50/56 [=========================>....] - ETA: 0s - loss: 0.1895 56/56 [==============================] - 0s 1ms/step - loss: 0.1848 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1981 50/56 [=========================>....] - ETA: 0s - loss: 0.1763 56/56 [==============================] - 0s 1ms/step - loss: 0.1816 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.0840 49/56 [=========================>....] - ETA: 0s - loss: 0.1715 56/56 [==============================] - 0s 1ms/step - loss: 0.1821 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1028 43/56 [======================>.......] - ETA: 0s - loss: 0.1836 56/56 [==============================] - 0s 1ms/step - loss: 0.1797 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1717 41/56 [====================>.........] - ETA: 0s - loss: 0.2001 56/56 [==============================] - 0s 1ms/step - loss: 0.1828 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.3013 49/56 [=========================>....] - ETA: 0s - loss: 0.1804 56/56 [==============================] - 0s 1ms/step - loss: 0.1774 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1836 48/56 [========================>.....] - ETA: 0s - loss: 0.1884 56/56 [==============================] - 0s 1ms/step - loss: 0.1765 -> test with GAN.predict GAN tn, fp: 127, 11 GAN fn, tp: 2, 7 GAN f1 score: 0.519 GAN cohens kappa score: 0.476 -> test with 'LR' LR tn, fp: 131, 7 LR fn, tp: 1, 8 LR f1 score: 0.667 LR cohens kappa score: 0.639 LR average precision score: 0.669 -> test with 'RF' RF tn, fp: 137, 1 RF fn, tp: 5, 4 RF f1 score: 0.571 RF cohens kappa score: 0.552 -> test with 'GB' GB tn, fp: 136, 2 GB fn, tp: 5, 4 GB f1 score: 0.533 GB cohens kappa score: 0.509 -> test with 'KNN' KNN tn, fp: 124, 14 KNN fn, tp: 2, 7 KNN f1 score: 0.467 KNN cohens kappa score: 0.417 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 516 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.3542 47/56 [========================>.....] - ETA: 0s - loss: 0.2176 56/56 [==============================] - 0s 1ms/step - loss: 0.2063 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1315 48/56 [========================>.....] - ETA: 0s - loss: 0.1924 56/56 [==============================] - 0s 1ms/step - loss: 0.1923 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1444 47/56 [========================>.....] - ETA: 0s - loss: 0.1957 56/56 [==============================] - 0s 1ms/step - loss: 0.1920 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.3794 48/56 [========================>.....] - ETA: 0s - loss: 0.1849 56/56 [==============================] - 0s 1ms/step - loss: 0.1904 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1571 48/56 [========================>.....] - ETA: 0s - loss: 0.1909 56/56 [==============================] - 0s 1ms/step - loss: 0.1883 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1487 49/56 [=========================>....] - ETA: 0s - loss: 0.1864 56/56 [==============================] - 0s 1ms/step - loss: 0.1890 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1989 49/56 [=========================>....] - ETA: 0s - loss: 0.1829 56/56 [==============================] - 0s 1ms/step - loss: 0.1871 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1690 49/56 [=========================>....] - ETA: 0s - loss: 0.1946 56/56 [==============================] - 0s 1ms/step - loss: 0.1880 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2217 47/56 [========================>.....] - ETA: 0s - loss: 0.1890 56/56 [==============================] - 0s 1ms/step - loss: 0.1835 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1385 49/56 [=========================>....] - ETA: 0s - loss: 0.1833 56/56 [==============================] - 0s 1ms/step - loss: 0.1823 -> test with GAN.predict GAN tn, fp: 128, 9 GAN fn, tp: 2, 4 GAN f1 score: 0.421 GAN cohens kappa score: 0.386 -> test with 'LR' LR tn, fp: 128, 9 LR fn, tp: 1, 5 LR f1 score: 0.500 LR cohens kappa score: 0.469 LR average precision score: 0.488 -> test with 'RF' RF tn, fp: 134, 3 RF fn, tp: 4, 2 RF f1 score: 0.364 RF cohens kappa score: 0.338 -> test with 'GB' GB tn, fp: 135, 2 GB fn, tp: 4, 2 GB f1 score: 0.400 GB cohens kappa score: 0.379 -> test with 'KNN' KNN tn, fp: 127, 10 KNN fn, tp: 4, 2 KNN f1 score: 0.222 KNN cohens kappa score: 0.176 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 9s - loss: 0.5198 46/56 [=======================>......] - ETA: 0s - loss: 0.3123 56/56 [==============================] - 0s 1ms/step - loss: 0.3063 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1574 49/56 [=========================>....] - ETA: 0s - loss: 0.2654 56/56 [==============================] - 0s 1ms/step - loss: 0.2622 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.2367 48/56 [========================>.....] - ETA: 0s - loss: 0.2370 56/56 [==============================] - 0s 1ms/step - loss: 0.2432 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1719 49/56 [=========================>....] - ETA: 0s - loss: 0.2384 56/56 [==============================] - 0s 1ms/step - loss: 0.2345 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1483 44/56 [======================>.......] - ETA: 0s - loss: 0.2310 56/56 [==============================] - 0s 1ms/step - loss: 0.2326 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1500 44/56 [======================>.......] - ETA: 0s - loss: 0.2235 56/56 [==============================] - 0s 1ms/step - loss: 0.2216 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1761 49/56 [=========================>....] - ETA: 0s - loss: 0.2160 56/56 [==============================] - 0s 1ms/step - loss: 0.2173 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.2005 45/56 [=======================>......] - ETA: 0s - loss: 0.2181 56/56 [==============================] - 0s 1ms/step - loss: 0.2157 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.0900 49/56 [=========================>....] - ETA: 0s - loss: 0.2123 56/56 [==============================] - 0s 1ms/step - loss: 0.2136 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1490 49/56 [=========================>....] - ETA: 0s - loss: 0.2099 56/56 [==============================] - 0s 1ms/step - loss: 0.2083 -> test with GAN.predict GAN tn, fp: 130, 8 GAN fn, tp: 3, 6 GAN f1 score: 0.522 GAN cohens kappa score: 0.483 -> test with 'LR' LR tn, fp: 121, 17 LR fn, tp: 1, 8 LR f1 score: 0.471 LR cohens kappa score: 0.418 LR average precision score: 0.615 -> test with 'RF' RF tn, fp: 136, 2 RF fn, tp: 5, 4 RF f1 score: 0.533 RF cohens kappa score: 0.509 -> test with 'GB' GB tn, fp: 136, 2 GB fn, tp: 5, 4 GB f1 score: 0.533 GB cohens kappa score: 0.509 -> test with 'KNN' KNN tn, fp: 124, 14 KNN fn, tp: 3, 6 KNN f1 score: 0.414 KNN cohens kappa score: 0.360 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.2087 45/56 [=======================>......] - ETA: 0s - loss: 0.2563 56/56 [==============================] - 0s 1ms/step - loss: 0.2467 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.3892 49/56 [=========================>....] - ETA: 0s - loss: 0.2263 56/56 [==============================] - 0s 1ms/step - loss: 0.2234 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.2216 50/56 [=========================>....] - ETA: 0s - loss: 0.2153 56/56 [==============================] - 0s 1ms/step - loss: 0.2153 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.4768 49/56 [=========================>....] - ETA: 0s - loss: 0.2135 56/56 [==============================] - 0s 1ms/step - loss: 0.2094 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.0968 50/56 [=========================>....] - ETA: 0s - loss: 0.2049 56/56 [==============================] - 0s 1ms/step - loss: 0.2061 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1665 48/56 [========================>.....] - ETA: 0s - loss: 0.2112 56/56 [==============================] - 0s 1ms/step - loss: 0.2057 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1630 48/56 [========================>.....] - ETA: 0s - loss: 0.2047 56/56 [==============================] - 0s 1ms/step - loss: 0.2038 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.3013 50/56 [=========================>....] - ETA: 0s - loss: 0.1948 56/56 [==============================] - 0s 1ms/step - loss: 0.1963 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.3779 49/56 [=========================>....] - ETA: 0s - loss: 0.1951 56/56 [==============================] - 0s 1ms/step - loss: 0.1955 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.2761 50/56 [=========================>....] - ETA: 0s - loss: 0.1847 56/56 [==============================] - 0s 1ms/step - loss: 0.1937 -> test with GAN.predict GAN tn, fp: 131, 7 GAN fn, tp: 2, 7 GAN f1 score: 0.609 GAN cohens kappa score: 0.577 -> test with 'LR' LR tn, fp: 131, 7 LR fn, tp: 1, 8 LR f1 score: 0.667 LR cohens kappa score: 0.639 LR average precision score: 0.779 -> test with 'RF' RF tn, fp: 137, 1 RF fn, tp: 5, 4 RF f1 score: 0.571 RF cohens kappa score: 0.552 -> test with 'GB' GB tn, fp: 132, 6 GB fn, tp: 5, 4 GB f1 score: 0.421 GB cohens kappa score: 0.381 -> test with 'KNN' KNN tn, fp: 128, 10 KNN fn, tp: 3, 6 KNN f1 score: 0.480 KNN cohens kappa score: 0.436 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.3832 49/56 [=========================>....] - ETA: 0s - loss: 0.2224 56/56 [==============================] - 0s 1ms/step - loss: 0.2263 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1226 50/56 [=========================>....] - ETA: 0s - loss: 0.2063 56/56 [==============================] - 0s 1ms/step - loss: 0.2012 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1903 49/56 [=========================>....] - ETA: 0s - loss: 0.1957 56/56 [==============================] - 0s 1ms/step - loss: 0.1927 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1583 47/56 [========================>.....] - ETA: 0s - loss: 0.1902 56/56 [==============================] - 0s 1ms/step - loss: 0.1873 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1104 48/56 [========================>.....] - ETA: 0s - loss: 0.1877 56/56 [==============================] - 0s 1ms/step - loss: 0.1853 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.3978 49/56 [=========================>....] - ETA: 0s - loss: 0.1900 56/56 [==============================] - 0s 1ms/step - loss: 0.1890 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1967 49/56 [=========================>....] - ETA: 0s - loss: 0.1893 56/56 [==============================] - 0s 1ms/step - loss: 0.1847 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.0754 49/56 [=========================>....] - ETA: 0s - loss: 0.1870 56/56 [==============================] - 0s 1ms/step - loss: 0.1811 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.1500 46/56 [=======================>......] - ETA: 0s - loss: 0.1763 56/56 [==============================] - 0s 1ms/step - loss: 0.1799 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1444 46/56 [=======================>......] - ETA: 0s - loss: 0.1732 56/56 [==============================] - 0s 1ms/step - loss: 0.1772 -> test with GAN.predict GAN tn, fp: 131, 7 GAN fn, tp: 2, 7 GAN f1 score: 0.609 GAN cohens kappa score: 0.577 -> test with 'LR' LR tn, fp: 133, 5 LR fn, tp: 2, 7 LR f1 score: 0.667 LR cohens kappa score: 0.642 LR average precision score: 0.692 -> test with 'RF' RF tn, fp: 134, 4 RF fn, tp: 7, 2 RF f1 score: 0.267 RF cohens kappa score: 0.229 -> test with 'GB' GB tn, fp: 130, 8 GB fn, tp: 6, 3 GB f1 score: 0.300 GB cohens kappa score: 0.249 -> test with 'KNN' KNN tn, fp: 122, 16 KNN fn, tp: 1, 8 KNN f1 score: 0.485 KNN cohens kappa score: 0.434 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.1423 48/56 [========================>.....] - ETA: 0s - loss: 0.2661 56/56 [==============================] - 0s 1ms/step - loss: 0.2678 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1593 50/56 [=========================>....] - ETA: 0s - loss: 0.2483 56/56 [==============================] - 0s 1ms/step - loss: 0.2468 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1922 49/56 [=========================>....] - ETA: 0s - loss: 0.2419 56/56 [==============================] - 0s 1ms/step - loss: 0.2438 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1893 50/56 [=========================>....] - ETA: 0s - loss: 0.2372 56/56 [==============================] - 0s 1ms/step - loss: 0.2374 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.3468 49/56 [=========================>....] - ETA: 0s - loss: 0.2322 56/56 [==============================] - 0s 1ms/step - loss: 0.2358 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.3377 50/56 [=========================>....] - ETA: 0s - loss: 0.2306 56/56 [==============================] - 0s 1ms/step - loss: 0.2333 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1090 50/56 [=========================>....] - ETA: 0s - loss: 0.2296 56/56 [==============================] - 0s 1ms/step - loss: 0.2234 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.2045 50/56 [=========================>....] - ETA: 0s - loss: 0.2256 56/56 [==============================] - 0s 1ms/step - loss: 0.2252 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.3298 50/56 [=========================>....] - ETA: 0s - loss: 0.2233 56/56 [==============================] - 0s 1ms/step - loss: 0.2236 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.2426 50/56 [=========================>....] - ETA: 0s - loss: 0.2205 56/56 [==============================] - 0s 1ms/step - loss: 0.2218 -> test with GAN.predict GAN tn, fp: 126, 12 GAN fn, tp: 2, 7 GAN f1 score: 0.500 GAN cohens kappa score: 0.455 -> test with 'LR' LR tn, fp: 126, 12 LR fn, tp: 1, 8 LR f1 score: 0.552 LR cohens kappa score: 0.510 LR average precision score: 0.722 -> test with 'RF' RF tn, fp: 132, 6 RF fn, tp: 6, 3 RF f1 score: 0.333 RF cohens kappa score: 0.290 -> test with 'GB' GB tn, fp: 133, 5 GB fn, tp: 6, 3 GB f1 score: 0.353 GB cohens kappa score: 0.313 -> test with 'KNN' KNN tn, fp: 117, 21 KNN fn, tp: 3, 6 KNN f1 score: 0.333 KNN cohens kappa score: 0.266 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 516 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.3023 46/56 [=======================>......] - ETA: 0s - loss: 0.3004 56/56 [==============================] - 0s 1ms/step - loss: 0.2928 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.2360 46/56 [=======================>......] - ETA: 0s - loss: 0.2585 56/56 [==============================] - 0s 1ms/step - loss: 0.2608 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1936 45/56 [=======================>......] - ETA: 0s - loss: 0.2493 56/56 [==============================] - 0s 1ms/step - loss: 0.2479 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.3681 40/56 [====================>.........] - ETA: 0s - loss: 0.2417 56/56 [==============================] - 0s 1ms/step - loss: 0.2411 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1630 46/56 [=======================>......] - ETA: 0s - loss: 0.2347 56/56 [==============================] - 0s 1ms/step - loss: 0.2363 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.3446 45/56 [=======================>......] - ETA: 0s - loss: 0.2383 56/56 [==============================] - 0s 1ms/step - loss: 0.2308 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1040 43/56 [======================>.......] - ETA: 0s - loss: 0.2255 56/56 [==============================] - 0s 1ms/step - loss: 0.2330 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.3649 39/56 [===================>..........] - ETA: 0s - loss: 0.2345 56/56 [==============================] - 0s 1ms/step - loss: 0.2300 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.1428 38/56 [===================>..........] - ETA: 0s - loss: 0.2273 56/56 [==============================] - 0s 1ms/step - loss: 0.2277 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.3110 43/56 [======================>.......] - ETA: 0s - loss: 0.2220 56/56 [==============================] - 0s 1ms/step - loss: 0.2238 -> test with GAN.predict GAN tn, fp: 125, 12 GAN fn, tp: 1, 5 GAN f1 score: 0.435 GAN cohens kappa score: 0.397 -> test with 'LR' LR tn, fp: 128, 9 LR fn, tp: 1, 5 LR f1 score: 0.500 LR cohens kappa score: 0.469 LR average precision score: 0.660 -> test with 'RF' RF tn, fp: 133, 4 RF fn, tp: 3, 3 RF f1 score: 0.462 RF cohens kappa score: 0.436 -> test with 'GB' GB tn, fp: 128, 9 GB fn, tp: 3, 3 GB f1 score: 0.333 GB cohens kappa score: 0.294 -> test with 'KNN' KNN tn, fp: 121, 16 KNN fn, tp: 2, 4 KNN f1 score: 0.308 KNN cohens kappa score: 0.260 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.1362 50/56 [=========================>....] - ETA: 0s - loss: 0.2042 56/56 [==============================] - 0s 1ms/step - loss: 0.2049 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.2579 49/56 [=========================>....] - ETA: 0s - loss: 0.1885 56/56 [==============================] - 0s 1ms/step - loss: 0.1844 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.2180 49/56 [=========================>....] - ETA: 0s - loss: 0.1706 56/56 [==============================] - 0s 1ms/step - loss: 0.1780 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2120 49/56 [=========================>....] - ETA: 0s - loss: 0.1832 56/56 [==============================] - 0s 1ms/step - loss: 0.1756 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.0857 49/56 [=========================>....] - ETA: 0s - loss: 0.1624 56/56 [==============================] - 0s 1ms/step - loss: 0.1672 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.0752 50/56 [=========================>....] - ETA: 0s - loss: 0.1655 56/56 [==============================] - 0s 1ms/step - loss: 0.1613 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1524 49/56 [=========================>....] - ETA: 0s - loss: 0.1665 56/56 [==============================] - 0s 1ms/step - loss: 0.1627 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1300 50/56 [=========================>....] - ETA: 0s - loss: 0.1542 56/56 [==============================] - 0s 1ms/step - loss: 0.1599 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.0827 49/56 [=========================>....] - ETA: 0s - loss: 0.1559 56/56 [==============================] - 0s 1ms/step - loss: 0.1580 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.4976 44/56 [======================>.......] - ETA: 0s - loss: 0.1494 56/56 [==============================] - 0s 1ms/step - loss: 0.1564 -> test with GAN.predict GAN tn, fp: 129, 9 GAN fn, tp: 4, 5 GAN f1 score: 0.435 GAN cohens kappa score: 0.389 -> test with 'LR' LR tn, fp: 131, 7 LR fn, tp: 3, 6 LR f1 score: 0.545 LR cohens kappa score: 0.510 LR average precision score: 0.632 -> test with 'RF' RF tn, fp: 135, 3 RF fn, tp: 8, 1 RF f1 score: 0.154 RF cohens kappa score: 0.121 -> test with 'GB' GB tn, fp: 133, 5 GB fn, tp: 9, 0 GB f1 score: 0.000 GB cohens kappa score: -0.046 -> test with 'KNN' KNN tn, fp: 127, 11 KNN fn, tp: 4, 5 KNN f1 score: 0.400 KNN cohens kappa score: 0.349 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.3375 49/56 [=========================>....] - ETA: 0s - loss: 0.2766 56/56 [==============================] - 0s 1ms/step - loss: 0.2821 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.2954 49/56 [=========================>....] - ETA: 0s - loss: 0.2556 56/56 [==============================] - 0s 1ms/step - loss: 0.2607 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.3850 49/56 [=========================>....] - ETA: 0s - loss: 0.2504 56/56 [==============================] - 0s 1ms/step - loss: 0.2561 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.3233 45/56 [=======================>......] - ETA: 0s - loss: 0.2509 56/56 [==============================] - 0s 1ms/step - loss: 0.2566 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.2869 43/56 [======================>.......] - ETA: 0s - loss: 0.2541 56/56 [==============================] - 0s 1ms/step - loss: 0.2549 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.3954 47/56 [========================>.....] - ETA: 0s - loss: 0.2613 56/56 [==============================] - 0s 1ms/step - loss: 0.2516 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.3010 49/56 [=========================>....] - ETA: 0s - loss: 0.2620 56/56 [==============================] - 0s 1ms/step - loss: 0.2558 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1121 49/56 [=========================>....] - ETA: 0s - loss: 0.2553 56/56 [==============================] - 0s 1ms/step - loss: 0.2513 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.1591 48/56 [========================>.....] - ETA: 0s - loss: 0.2543 56/56 [==============================] - 0s 1ms/step - loss: 0.2544 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.5318 48/56 [========================>.....] - ETA: 0s - loss: 0.2418 56/56 [==============================] - 0s 1ms/step - loss: 0.2440 -> test with GAN.predict GAN tn, fp: 130, 8 GAN fn, tp: 0, 9 GAN f1 score: 0.692 GAN cohens kappa score: 0.666 -> test with 'LR' LR tn, fp: 130, 8 LR fn, tp: 0, 9 LR f1 score: 0.692 LR cohens kappa score: 0.666 LR average precision score: 0.897 -> test with 'RF' RF tn, fp: 137, 1 RF fn, tp: 3, 6 RF f1 score: 0.750 RF cohens kappa score: 0.736 -> test with 'GB' GB tn, fp: 133, 5 GB fn, tp: 3, 6 GB f1 score: 0.600 GB cohens kappa score: 0.571 -> test with 'KNN' KNN tn, fp: 114, 24 KNN fn, tp: 2, 7 KNN f1 score: 0.350 KNN cohens kappa score: 0.282 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.2047 49/56 [=========================>....] - ETA: 0s - loss: 0.2176 56/56 [==============================] - 0s 1ms/step - loss: 0.2141 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1747 49/56 [=========================>....] - ETA: 0s - loss: 0.1911 56/56 [==============================] - 0s 1ms/step - loss: 0.1851 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.2245 46/56 [=======================>......] - ETA: 0s - loss: 0.1803 56/56 [==============================] - 0s 1ms/step - loss: 0.1751 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1362 49/56 [=========================>....] - ETA: 0s - loss: 0.1652 56/56 [==============================] - 0s 1ms/step - loss: 0.1707 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1438 49/56 [=========================>....] - ETA: 0s - loss: 0.1729 56/56 [==============================] - 0s 1ms/step - loss: 0.1748 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1629 49/56 [=========================>....] - ETA: 0s - loss: 0.1751 56/56 [==============================] - 0s 1ms/step - loss: 0.1654 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1457 49/56 [=========================>....] - ETA: 0s - loss: 0.1679 56/56 [==============================] - 0s 1ms/step - loss: 0.1676 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1484 50/56 [=========================>....] - ETA: 0s - loss: 0.1651 56/56 [==============================] - 0s 1ms/step - loss: 0.1669 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.0550 49/56 [=========================>....] - ETA: 0s - loss: 0.1583 56/56 [==============================] - 0s 1ms/step - loss: 0.1643 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.3054 49/56 [=========================>....] - ETA: 0s - loss: 0.1762 56/56 [==============================] - 0s 1ms/step - loss: 0.1649 -> test with GAN.predict GAN tn, fp: 129, 9 GAN fn, tp: 4, 5 GAN f1 score: 0.435 GAN cohens kappa score: 0.389 -> test with 'LR' LR tn, fp: 134, 4 LR fn, tp: 4, 5 LR f1 score: 0.556 LR cohens kappa score: 0.527 LR average precision score: 0.658 -> test with 'RF' RF tn, fp: 133, 5 RF fn, tp: 8, 1 RF f1 score: 0.133 RF cohens kappa score: 0.089 -> test with 'GB' GB tn, fp: 133, 5 GB fn, tp: 8, 1 GB f1 score: 0.133 GB cohens kappa score: 0.089 -> test with 'KNN' KNN tn, fp: 127, 11 KNN fn, tp: 4, 5 KNN f1 score: 0.400 KNN cohens kappa score: 0.349 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.3215 47/56 [========================>.....] - ETA: 0s - loss: 0.2617 56/56 [==============================] - 0s 1ms/step - loss: 0.2603 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1743 49/56 [=========================>....] - ETA: 0s - loss: 0.2110 56/56 [==============================] - 0s 1ms/step - loss: 0.2151 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.0760 49/56 [=========================>....] - ETA: 0s - loss: 0.2045 56/56 [==============================] - 0s 1ms/step - loss: 0.2023 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2530 47/56 [========================>.....] - ETA: 0s - loss: 0.2080 56/56 [==============================] - 0s 1ms/step - loss: 0.2029 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.0733 44/56 [======================>.......] - ETA: 0s - loss: 0.1957 56/56 [==============================] - 0s 1ms/step - loss: 0.1923 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1731 43/56 [======================>.......] - ETA: 0s - loss: 0.1919 56/56 [==============================] - 0s 1ms/step - loss: 0.1922 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1584 48/56 [========================>.....] - ETA: 0s - loss: 0.1898 56/56 [==============================] - 0s 1ms/step - loss: 0.1963 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.3475 49/56 [=========================>....] - ETA: 0s - loss: 0.1952 56/56 [==============================] - 0s 1ms/step - loss: 0.1918 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.1989 49/56 [=========================>....] - ETA: 0s - loss: 0.1935 56/56 [==============================] - 0s 1ms/step - loss: 0.1929 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.0584 49/56 [=========================>....] - ETA: 0s - loss: 0.1887 56/56 [==============================] - 0s 1ms/step - loss: 0.1875 -> test with GAN.predict GAN tn, fp: 128, 10 GAN fn, tp: 2, 7 GAN f1 score: 0.538 GAN cohens kappa score: 0.498 -> test with 'LR' LR tn, fp: 117, 21 LR fn, tp: 1, 8 LR f1 score: 0.421 LR cohens kappa score: 0.361 LR average precision score: 0.669 -> test with 'RF' RF tn, fp: 132, 6 RF fn, tp: 6, 3 RF f1 score: 0.333 RF cohens kappa score: 0.290 -> test with 'GB' GB tn, fp: 131, 7 GB fn, tp: 7, 2 GB f1 score: 0.222 GB cohens kappa score: 0.171 -> test with 'KNN' KNN tn, fp: 117, 21 KNN fn, tp: 4, 5 KNN f1 score: 0.286 KNN cohens kappa score: 0.214 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 516 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.3721 48/56 [========================>.....] - ETA: 0s - loss: 0.3107 56/56 [==============================] - 0s 1ms/step - loss: 0.3054 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1666 48/56 [========================>.....] - ETA: 0s - loss: 0.2745 56/56 [==============================] - 0s 1ms/step - loss: 0.2676 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.3163 49/56 [=========================>....] - ETA: 0s - loss: 0.2637 56/56 [==============================] - 0s 1ms/step - loss: 0.2577 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.4875 49/56 [=========================>....] - ETA: 0s - loss: 0.2516 56/56 [==============================] - 0s 1ms/step - loss: 0.2516 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1483 49/56 [=========================>....] - ETA: 0s - loss: 0.2565 56/56 [==============================] - 0s 1ms/step - loss: 0.2520 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1717 47/56 [========================>.....] - ETA: 0s - loss: 0.2483 56/56 [==============================] - 0s 1ms/step - loss: 0.2476 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1302 46/56 [=======================>......] - ETA: 0s - loss: 0.2507 56/56 [==============================] - 0s 1ms/step - loss: 0.2428 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.3707 46/56 [=======================>......] - ETA: 0s - loss: 0.2335 56/56 [==============================] - 0s 1ms/step - loss: 0.2393 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2797 49/56 [=========================>....] - ETA: 0s - loss: 0.2346 56/56 [==============================] - 0s 1ms/step - loss: 0.2369 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1580 48/56 [========================>.....] - ETA: 0s - loss: 0.2359 56/56 [==============================] - 0s 1ms/step - loss: 0.2334 -> test with GAN.predict GAN tn, fp: 127, 10 GAN fn, tp: 1, 5 GAN f1 score: 0.476 GAN cohens kappa score: 0.443 -> test with 'LR' LR tn, fp: 124, 13 LR fn, tp: 1, 5 LR f1 score: 0.417 LR cohens kappa score: 0.377 LR average precision score: 0.524 -> test with 'RF' RF tn, fp: 134, 3 RF fn, tp: 5, 1 RF f1 score: 0.200 RF cohens kappa score: 0.172 -> test with 'GB' GB tn, fp: 131, 6 GB fn, tp: 4, 2 GB f1 score: 0.286 GB cohens kappa score: 0.250 -> test with 'KNN' KNN tn, fp: 123, 14 KNN fn, tp: 3, 3 KNN f1 score: 0.261 KNN cohens kappa score: 0.212 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.3891 48/56 [========================>.....] - ETA: 0s - loss: 0.2063 56/56 [==============================] - 0s 1ms/step - loss: 0.2079 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.5178 49/56 [=========================>....] - ETA: 0s - loss: 0.1920 56/56 [==============================] - 0s 1ms/step - loss: 0.1890 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1397 49/56 [=========================>....] - ETA: 0s - loss: 0.1740 56/56 [==============================] - 0s 1ms/step - loss: 0.1793 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1523 49/56 [=========================>....] - ETA: 0s - loss: 0.1816 56/56 [==============================] - 0s 1ms/step - loss: 0.1758 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1697 49/56 [=========================>....] - ETA: 0s - loss: 0.1759 56/56 [==============================] - 0s 1ms/step - loss: 0.1718 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.0981 49/56 [=========================>....] - ETA: 0s - loss: 0.1583 56/56 [==============================] - 0s 1ms/step - loss: 0.1707 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1355 49/56 [=========================>....] - ETA: 0s - loss: 0.1747 56/56 [==============================] - 0s 1ms/step - loss: 0.1722 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.0808 48/56 [========================>.....] - ETA: 0s - loss: 0.1573 56/56 [==============================] - 0s 1ms/step - loss: 0.1618 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.3679 49/56 [=========================>....] - ETA: 0s - loss: 0.1634 56/56 [==============================] - 0s 1ms/step - loss: 0.1622 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.0795 49/56 [=========================>....] - ETA: 0s - loss: 0.1594 56/56 [==============================] - 0s 1ms/step - loss: 0.1616 -> test with GAN.predict GAN tn, fp: 130, 8 GAN fn, tp: 4, 5 GAN f1 score: 0.455 GAN cohens kappa score: 0.412 -> test with 'LR' LR tn, fp: 129, 9 LR fn, tp: 4, 5 LR f1 score: 0.435 LR cohens kappa score: 0.389 LR average precision score: 0.528 -> test with 'RF' RF tn, fp: 135, 3 RF fn, tp: 8, 1 RF f1 score: 0.154 RF cohens kappa score: 0.121 -> test with 'GB' GB tn, fp: 134, 4 GB fn, tp: 6, 3 GB f1 score: 0.375 GB cohens kappa score: 0.340 -> test with 'KNN' KNN tn, fp: 119, 19 KNN fn, tp: 5, 4 KNN f1 score: 0.250 KNN cohens kappa score: 0.178 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.2591 49/56 [=========================>....] - ETA: 0s - loss: 0.2513 56/56 [==============================] - 0s 1ms/step - loss: 0.2539 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.2648 50/56 [=========================>....] - ETA: 0s - loss: 0.2341 56/56 [==============================] - 0s 1ms/step - loss: 0.2342 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1330 47/56 [========================>.....] - ETA: 0s - loss: 0.2301 56/56 [==============================] - 0s 1ms/step - loss: 0.2244 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2741 49/56 [=========================>....] - ETA: 0s - loss: 0.2271 56/56 [==============================] - 0s 1ms/step - loss: 0.2198 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.2502 44/56 [======================>.......] - ETA: 0s - loss: 0.2170 56/56 [==============================] - 0s 1ms/step - loss: 0.2168 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1363 42/56 [=====================>........] - ETA: 0s - loss: 0.2302 56/56 [==============================] - 0s 1ms/step - loss: 0.2196 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1227 49/56 [=========================>....] - ETA: 0s - loss: 0.2077 56/56 [==============================] - 0s 1ms/step - loss: 0.2142 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.3130 49/56 [=========================>....] - ETA: 0s - loss: 0.2149 56/56 [==============================] - 0s 1ms/step - loss: 0.2103 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.1320 48/56 [========================>.....] - ETA: 0s - loss: 0.2109 56/56 [==============================] - 0s 1ms/step - loss: 0.2086 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.2576 49/56 [=========================>....] - ETA: 0s - loss: 0.2060 56/56 [==============================] - 0s 1ms/step - loss: 0.2074 -> test with GAN.predict GAN tn, fp: 126, 12 GAN fn, tp: 2, 7 GAN f1 score: 0.500 GAN cohens kappa score: 0.455 -> test with 'LR' LR tn, fp: 122, 16 LR fn, tp: 2, 7 LR f1 score: 0.438 LR cohens kappa score: 0.383 LR average precision score: 0.731 -> test with 'RF' RF tn, fp: 133, 5 RF fn, tp: 6, 3 RF f1 score: 0.353 RF cohens kappa score: 0.313 -> test with 'GB' GB tn, fp: 126, 12 GB fn, tp: 4, 5 GB f1 score: 0.385 GB cohens kappa score: 0.331 -> test with 'KNN' KNN tn, fp: 119, 19 KNN fn, tp: 3, 6 KNN f1 score: 0.353 KNN cohens kappa score: 0.289 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.3396 49/56 [=========================>....] - ETA: 0s - loss: 0.3057 56/56 [==============================] - 0s 1ms/step - loss: 0.2962 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.2924 49/56 [=========================>....] - ETA: 0s - loss: 0.2696 56/56 [==============================] - 0s 1ms/step - loss: 0.2703 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.3754 49/56 [=========================>....] - ETA: 0s - loss: 0.2553 56/56 [==============================] - 0s 1ms/step - loss: 0.2541 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1269 49/56 [=========================>....] - ETA: 0s - loss: 0.2523 56/56 [==============================] - 0s 1ms/step - loss: 0.2525 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.2213 49/56 [=========================>....] - ETA: 0s - loss: 0.2399 56/56 [==============================] - 0s 1ms/step - loss: 0.2493 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.5061 49/56 [=========================>....] - ETA: 0s - loss: 0.2336 56/56 [==============================] - 0s 1ms/step - loss: 0.2458 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.2685 49/56 [=========================>....] - ETA: 0s - loss: 0.2384 56/56 [==============================] - 0s 1ms/step - loss: 0.2432 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1918 49/56 [=========================>....] - ETA: 0s - loss: 0.2403 56/56 [==============================] - 0s 1ms/step - loss: 0.2395 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.0840 49/56 [=========================>....] - ETA: 0s - loss: 0.2437 56/56 [==============================] - 0s 1ms/step - loss: 0.2374 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.3303 49/56 [=========================>....] - ETA: 0s - loss: 0.2342 56/56 [==============================] - 0s 1ms/step - loss: 0.2341 -> test with GAN.predict GAN tn, fp: 125, 13 GAN fn, tp: 2, 7 GAN f1 score: 0.483 GAN cohens kappa score: 0.435 -> test with 'LR' LR tn, fp: 125, 13 LR fn, tp: 1, 8 LR f1 score: 0.533 LR cohens kappa score: 0.490 LR average precision score: 0.727 -> test with 'RF' RF tn, fp: 134, 4 RF fn, tp: 6, 3 RF f1 score: 0.375 RF cohens kappa score: 0.340 -> test with 'GB' GB tn, fp: 134, 4 GB fn, tp: 7, 2 GB f1 score: 0.267 GB cohens kappa score: 0.229 -> test with 'KNN' KNN tn, fp: 123, 15 KNN fn, tp: 4, 5 KNN f1 score: 0.345 KNN cohens kappa score: 0.284 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.2849 45/56 [=======================>......] - ETA: 0s - loss: 0.3005 56/56 [==============================] - 0s 1ms/step - loss: 0.2916 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.3584 50/56 [=========================>....] - ETA: 0s - loss: 0.2545 56/56 [==============================] - 0s 1ms/step - loss: 0.2578 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.2532 49/56 [=========================>....] - ETA: 0s - loss: 0.2435 56/56 [==============================] - 0s 1ms/step - loss: 0.2464 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2418 50/56 [=========================>....] - ETA: 0s - loss: 0.2369 56/56 [==============================] - 0s 1ms/step - loss: 0.2395 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.4912 46/56 [=======================>......] - ETA: 0s - loss: 0.2460 56/56 [==============================] - 0s 1ms/step - loss: 0.2390 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.2449 49/56 [=========================>....] - ETA: 0s - loss: 0.2374 56/56 [==============================] - 0s 1ms/step - loss: 0.2394 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.2292 50/56 [=========================>....] - ETA: 0s - loss: 0.2512 56/56 [==============================] - 0s 1ms/step - loss: 0.2434 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.2250 49/56 [=========================>....] - ETA: 0s - loss: 0.2437 56/56 [==============================] - 0s 1ms/step - loss: 0.2381 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2693 50/56 [=========================>....] - ETA: 0s - loss: 0.2318 56/56 [==============================] - 0s 1ms/step - loss: 0.2341 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.3104 50/56 [=========================>....] - ETA: 0s - loss: 0.2250 56/56 [==============================] - 0s 1ms/step - loss: 0.2284 -> test with GAN.predict GAN tn, fp: 129, 9 GAN fn, tp: 1, 8 GAN f1 score: 0.615 GAN cohens kappa score: 0.582 -> test with 'LR' LR tn, fp: 124, 14 LR fn, tp: 0, 9 LR f1 score: 0.562 LR cohens kappa score: 0.520 LR average precision score: 0.958 -> test with 'RF' RF tn, fp: 133, 5 RF fn, tp: 7, 2 RF f1 score: 0.250 RF cohens kappa score: 0.208 -> test with 'GB' GB tn, fp: 131, 7 GB fn, tp: 5, 4 GB f1 score: 0.400 GB cohens kappa score: 0.357 -> test with 'KNN' KNN tn, fp: 120, 18 KNN fn, tp: 3, 6 KNN f1 score: 0.364 KNN cohens kappa score: 0.301 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 516 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.3238 50/56 [=========================>....] - ETA: 0s - loss: 0.2530 56/56 [==============================] - 0s 1ms/step - loss: 0.2508 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1750 50/56 [=========================>....] - ETA: 0s - loss: 0.2356 56/56 [==============================] - 0s 1ms/step - loss: 0.2382 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1995 50/56 [=========================>....] - ETA: 0s - loss: 0.2310 56/56 [==============================] - 0s 1ms/step - loss: 0.2334 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2328 50/56 [=========================>....] - ETA: 0s - loss: 0.2345 56/56 [==============================] - 0s 1ms/step - loss: 0.2325 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.4335 50/56 [=========================>....] - ETA: 0s - loss: 0.2316 56/56 [==============================] - 0s 1ms/step - loss: 0.2312 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1077 50/56 [=========================>....] - ETA: 0s - loss: 0.2239 56/56 [==============================] - 0s 1ms/step - loss: 0.2263 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.2216 50/56 [=========================>....] - ETA: 0s - loss: 0.2355 56/56 [==============================] - 0s 1ms/step - loss: 0.2265 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.2095 50/56 [=========================>....] - ETA: 0s - loss: 0.2196 56/56 [==============================] - 0s 1ms/step - loss: 0.2193 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2192 45/56 [=======================>......] - ETA: 0s - loss: 0.2331 56/56 [==============================] - 0s 1ms/step - loss: 0.2233 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1169 50/56 [=========================>....] - ETA: 0s - loss: 0.2106 56/56 [==============================] - 0s 1ms/step - loss: 0.2213 -> test with GAN.predict GAN tn, fp: 130, 7 GAN fn, tp: 2, 4 GAN f1 score: 0.471 GAN cohens kappa score: 0.440 -> test with 'LR' LR tn, fp: 129, 8 LR fn, tp: 1, 5 LR f1 score: 0.526 LR cohens kappa score: 0.497 LR average precision score: 0.518 -> test with 'RF' RF tn, fp: 132, 5 RF fn, tp: 4, 2 RF f1 score: 0.308 RF cohens kappa score: 0.275 -> test with 'GB' GB tn, fp: 132, 5 GB fn, tp: 4, 2 GB f1 score: 0.308 GB cohens kappa score: 0.275 -> test with 'KNN' KNN tn, fp: 124, 13 KNN fn, tp: 3, 3 KNN f1 score: 0.273 KNN cohens kappa score: 0.225 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.1795 46/56 [=======================>......] - ETA: 0s - loss: 0.2000 56/56 [==============================] - 0s 1ms/step - loss: 0.2077 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1479 42/56 [=====================>........] - ETA: 0s - loss: 0.2005 56/56 [==============================] - 0s 1ms/step - loss: 0.1997 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.3554 47/56 [========================>.....] - ETA: 0s - loss: 0.1998 56/56 [==============================] - 0s 1ms/step - loss: 0.1986 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2524 49/56 [=========================>....] - ETA: 0s - loss: 0.1997 56/56 [==============================] - 0s 1ms/step - loss: 0.1954 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1217 49/56 [=========================>....] - ETA: 0s - loss: 0.1945 56/56 [==============================] - 0s 1ms/step - loss: 0.1950 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.2385 50/56 [=========================>....] - ETA: 0s - loss: 0.1889 56/56 [==============================] - 0s 1ms/step - loss: 0.1909 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.0792 50/56 [=========================>....] - ETA: 0s - loss: 0.1936 56/56 [==============================] - 0s 1ms/step - loss: 0.1912 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.1513 49/56 [=========================>....] - ETA: 0s - loss: 0.1913 56/56 [==============================] - 0s 1ms/step - loss: 0.1924 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.0957 49/56 [=========================>....] - ETA: 0s - loss: 0.1816 56/56 [==============================] - 0s 1ms/step - loss: 0.1867 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1030 50/56 [=========================>....] - ETA: 0s - loss: 0.1920 56/56 [==============================] - 0s 1ms/step - loss: 0.1940 -> test with GAN.predict GAN tn, fp: 128, 10 GAN fn, tp: 4, 5 GAN f1 score: 0.417 GAN cohens kappa score: 0.368 -> test with 'LR' LR tn, fp: 125, 13 LR fn, tp: 1, 8 LR f1 score: 0.533 LR cohens kappa score: 0.490 LR average precision score: 0.755 -> test with 'RF' RF tn, fp: 132, 6 RF fn, tp: 8, 1 RF f1 score: 0.125 RF cohens kappa score: 0.075 -> test with 'GB' GB tn, fp: 129, 9 GB fn, tp: 8, 1 GB f1 score: 0.105 GB cohens kappa score: 0.044 -> test with 'KNN' KNN tn, fp: 117, 21 KNN fn, tp: 5, 4 KNN f1 score: 0.235 KNN cohens kappa score: 0.160 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.3113 48/56 [========================>.....] - ETA: 0s - loss: 0.3935 56/56 [==============================] - 0s 1ms/step - loss: 0.3818 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.3873 49/56 [=========================>....] - ETA: 0s - loss: 0.3027 56/56 [==============================] - 0s 1ms/step - loss: 0.3019 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.3392 49/56 [=========================>....] - ETA: 0s - loss: 0.2648 56/56 [==============================] - 0s 1ms/step - loss: 0.2744 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2312 49/56 [=========================>....] - ETA: 0s - loss: 0.2624 56/56 [==============================] - 0s 1ms/step - loss: 0.2587 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.2391 49/56 [=========================>....] - ETA: 0s - loss: 0.2533 56/56 [==============================] - 0s 1ms/step - loss: 0.2509 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.2340 49/56 [=========================>....] - ETA: 0s - loss: 0.2398 56/56 [==============================] - 0s 1ms/step - loss: 0.2428 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.3075 49/56 [=========================>....] - ETA: 0s - loss: 0.2324 56/56 [==============================] - 0s 1ms/step - loss: 0.2345 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.2320 48/56 [========================>.....] - ETA: 0s - loss: 0.2364 56/56 [==============================] - 0s 1ms/step - loss: 0.2324 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.1967 49/56 [=========================>....] - ETA: 0s - loss: 0.2241 56/56 [==============================] - 0s 1ms/step - loss: 0.2231 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.2048 48/56 [========================>.....] - ETA: 0s - loss: 0.2157 56/56 [==============================] - 0s 1ms/step - loss: 0.2178 -> test with GAN.predict GAN tn, fp: 128, 10 GAN fn, tp: 2, 7 GAN f1 score: 0.538 GAN cohens kappa score: 0.498 -> test with 'LR' LR tn, fp: 128, 10 LR fn, tp: 1, 8 LR f1 score: 0.593 LR cohens kappa score: 0.556 LR average precision score: 0.671 -> test with 'RF' RF tn, fp: 134, 4 RF fn, tp: 8, 1 RF f1 score: 0.143 RF cohens kappa score: 0.104 -> test with 'GB' GB tn, fp: 132, 6 GB fn, tp: 7, 2 GB f1 score: 0.235 GB cohens kappa score: 0.189 -> test with 'KNN' KNN tn, fp: 110, 28 KNN fn, tp: 4, 5 KNN f1 score: 0.238 KNN cohens kappa score: 0.157 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 7s - loss: 0.5053 46/56 [=======================>......] - ETA: 0s - loss: 0.2127 56/56 [==============================] - 0s 1ms/step - loss: 0.2073 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1119 49/56 [=========================>....] - ETA: 0s - loss: 0.1761 56/56 [==============================] - 0s 1ms/step - loss: 0.1802 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.2157 49/56 [=========================>....] - ETA: 0s - loss: 0.1799 56/56 [==============================] - 0s 1ms/step - loss: 0.1754 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.1917 49/56 [=========================>....] - ETA: 0s - loss: 0.1721 56/56 [==============================] - 0s 1ms/step - loss: 0.1762 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.0888 49/56 [=========================>....] - ETA: 0s - loss: 0.1752 56/56 [==============================] - 0s 1ms/step - loss: 0.1728 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.2025 49/56 [=========================>....] - ETA: 0s - loss: 0.1721 56/56 [==============================] - 0s 1ms/step - loss: 0.1735 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1283 49/56 [=========================>....] - ETA: 0s - loss: 0.1649 56/56 [==============================] - 0s 1ms/step - loss: 0.1686 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.0902 45/56 [=======================>......] - ETA: 0s - loss: 0.1684 56/56 [==============================] - 0s 1ms/step - loss: 0.1649 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.1399 49/56 [=========================>....] - ETA: 0s - loss: 0.1644 56/56 [==============================] - 0s 1ms/step - loss: 0.1644 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1484 49/56 [=========================>....] - ETA: 0s - loss: 0.1595 56/56 [==============================] - 0s 1ms/step - loss: 0.1648 -> test with GAN.predict GAN tn, fp: 126, 12 GAN fn, tp: 4, 5 GAN f1 score: 0.385 GAN cohens kappa score: 0.331 -> test with 'LR' LR tn, fp: 127, 11 LR fn, tp: 3, 6 LR f1 score: 0.462 LR cohens kappa score: 0.415 LR average precision score: 0.543 -> test with 'RF' RF tn, fp: 134, 4 RF fn, tp: 6, 3 RF f1 score: 0.375 RF cohens kappa score: 0.340 -> test with 'GB' GB tn, fp: 134, 4 GB fn, tp: 5, 4 GB f1 score: 0.471 GB cohens kappa score: 0.438 -> test with 'KNN' KNN tn, fp: 125, 13 KNN fn, tp: 4, 5 KNN f1 score: 0.370 KNN cohens kappa score: 0.314 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 518 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.4582 40/56 [====================>.........] - ETA: 0s - loss: 0.2239 56/56 [==============================] - 0s 1ms/step - loss: 0.2205 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1949 39/56 [===================>..........] - ETA: 0s - loss: 0.2035 56/56 [==============================] - 0s 1ms/step - loss: 0.1999 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.2725 42/56 [=====================>........] - ETA: 0s - loss: 0.2016 56/56 [==============================] - 0s 1ms/step - loss: 0.1910 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.0800 46/56 [=======================>......] - ETA: 0s - loss: 0.1895 56/56 [==============================] - 0s 1ms/step - loss: 0.1879 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1216 46/56 [=======================>......] - ETA: 0s - loss: 0.1827 56/56 [==============================] - 0s 1ms/step - loss: 0.1869 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.0749 40/56 [====================>.........] - ETA: 0s - loss: 0.1728 56/56 [==============================] - 0s 1ms/step - loss: 0.1826 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.1862 46/56 [=======================>......] - ETA: 0s - loss: 0.1931 56/56 [==============================] - 0s 1ms/step - loss: 0.1911 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.2612 41/56 [====================>.........] - ETA: 0s - loss: 0.1756 56/56 [==============================] - 0s 1ms/step - loss: 0.1789 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.2274 44/56 [======================>.......] - ETA: 0s - loss: 0.1847 56/56 [==============================] - 0s 1ms/step - loss: 0.1772 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1362 43/56 [======================>.......] - ETA: 0s - loss: 0.1771 56/56 [==============================] - 0s 1ms/step - loss: 0.1795 -> test with GAN.predict GAN tn, fp: 131, 7 GAN fn, tp: 2, 7 GAN f1 score: 0.609 GAN cohens kappa score: 0.577 -> test with 'LR' LR tn, fp: 130, 8 LR fn, tp: 1, 8 LR f1 score: 0.640 LR cohens kappa score: 0.609 LR average precision score: 0.894 -> test with 'RF' RF tn, fp: 133, 5 RF fn, tp: 6, 3 RF f1 score: 0.353 RF cohens kappa score: 0.313 -> test with 'GB' GB tn, fp: 133, 5 GB fn, tp: 4, 5 GB f1 score: 0.526 GB cohens kappa score: 0.494 -> test with 'KNN' KNN tn, fp: 123, 15 KNN fn, tp: 4, 5 KNN f1 score: 0.345 KNN cohens kappa score: 0.284 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples -> create 516 synthetic samples -> retrain GAN for predict Epoch 1/10 1/56 [..............................] - ETA: 8s - loss: 0.2666 48/56 [========================>.....] - ETA: 0s - loss: 0.2991 56/56 [==============================] - 0s 1ms/step - loss: 0.2940 Epoch 2/10 1/56 [..............................] - ETA: 0s - loss: 0.1052 50/56 [=========================>....] - ETA: 0s - loss: 0.2796 56/56 [==============================] - 0s 1ms/step - loss: 0.2734 Epoch 3/10 1/56 [..............................] - ETA: 0s - loss: 0.1489 49/56 [=========================>....] - ETA: 0s - loss: 0.2568 56/56 [==============================] - 0s 1ms/step - loss: 0.2640 Epoch 4/10 1/56 [..............................] - ETA: 0s - loss: 0.2715 50/56 [=========================>....] - ETA: 0s - loss: 0.2667 56/56 [==============================] - 0s 1ms/step - loss: 0.2649 Epoch 5/10 1/56 [..............................] - ETA: 0s - loss: 0.1735 49/56 [=========================>....] - ETA: 0s - loss: 0.2606 56/56 [==============================] - 0s 1ms/step - loss: 0.2586 Epoch 6/10 1/56 [..............................] - ETA: 0s - loss: 0.1865 49/56 [=========================>....] - ETA: 0s - loss: 0.2571 56/56 [==============================] - 0s 1ms/step - loss: 0.2552 Epoch 7/10 1/56 [..............................] - ETA: 0s - loss: 0.2250 50/56 [=========================>....] - ETA: 0s - loss: 0.2519 56/56 [==============================] - 0s 1ms/step - loss: 0.2505 Epoch 8/10 1/56 [..............................] - ETA: 0s - loss: 0.2226 46/56 [=======================>......] - ETA: 0s - loss: 0.2536 56/56 [==============================] - 0s 1ms/step - loss: 0.2494 Epoch 9/10 1/56 [..............................] - ETA: 0s - loss: 0.3662 49/56 [=========================>....] - ETA: 0s - loss: 0.2405 56/56 [==============================] - 0s 1ms/step - loss: 0.2501 Epoch 10/10 1/56 [..............................] - ETA: 0s - loss: 0.1495 50/56 [=========================>....] - ETA: 0s - loss: 0.2454 56/56 [==============================] - 0s 1ms/step - loss: 0.2503 -> test with GAN.predict GAN tn, fp: 129, 8 GAN fn, tp: 0, 6 GAN f1 score: 0.600 GAN cohens kappa score: 0.575 -> test with 'LR' LR tn, fp: 127, 10 LR fn, tp: 0, 6 LR f1 score: 0.545 LR cohens kappa score: 0.516 LR average precision score: 0.805 -> test with 'RF' RF tn, fp: 133, 4 RF fn, tp: 3, 3 RF f1 score: 0.462 RF cohens kappa score: 0.436 -> test with 'GB' GB tn, fp: 133, 4 GB fn, tp: 4, 2 GB f1 score: 0.333 GB cohens kappa score: 0.304 -> test with 'KNN' KNN tn, fp: 125, 12 KNN fn, tp: 2, 4 KNN f1 score: 0.364 KNN cohens kappa score: 0.322 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 134, 21 LR fn, tp: 4, 9 LR f1 score: 0.692 LR cohens kappa score: 0.666 LR average precision score: 0.958 average: LR tn, fp: 127.04, 10.76 LR fn, tp: 1.36, 7.04 LR f1 score: 0.541 LR cohens kappa score: 0.503 LR average precision score: 0.697 minimum: LR tn, fp: 117, 4 LR fn, tp: 0, 5 LR f1 score: 0.417 LR cohens kappa score: 0.361 LR average precision score: 0.488 -----[ RF ]----- maximum: RF tn, fp: 137, 6 RF fn, tp: 8, 6 RF f1 score: 0.750 RF cohens kappa score: 0.736 average: RF tn, fp: 134.04, 3.76 RF fn, tp: 5.92, 2.48 RF f1 score: 0.335 RF cohens kappa score: 0.302 minimum: RF tn, fp: 132, 1 RF fn, tp: 3, 1 RF f1 score: 0.125 RF cohens kappa score: 0.075 -----[ GB ]----- maximum: GB tn, fp: 136, 12 GB fn, tp: 9, 6 GB f1 score: 0.600 GB cohens kappa score: 0.571 average: GB tn, fp: 132.12, 5.68 GB fn, tp: 5.44, 2.96 GB f1 score: 0.343 GB cohens kappa score: 0.304 minimum: GB tn, fp: 126, 2 GB fn, tp: 3, 0 GB f1 score: 0.000 GB cohens kappa score: -0.046 -----[ KNN ]----- maximum: KNN tn, fp: 128, 28 KNN fn, tp: 5, 8 KNN f1 score: 0.485 KNN cohens kappa score: 0.436 average: KNN tn, fp: 121.8, 16.0 KNN fn, tp: 3.28, 5.12 KNN f1 score: 0.347 KNN cohens kappa score: 0.290 minimum: KNN tn, fp: 110, 10 KNN fn, tp: 1, 2 KNN f1 score: 0.222 KNN cohens kappa score: 0.157 -----[ GAN ]----- maximum: GAN tn, fp: 131, 16 GAN fn, tp: 4, 9 GAN f1 score: 0.692 GAN cohens kappa score: 0.666 average: GAN tn, fp: 127.88, 9.92 GAN fn, tp: 2.08, 6.32 GAN f1 score: 0.512 GAN cohens kappa score: 0.473 minimum: GAN tn, fp: 122, 7 GAN fn, tp: 0, 4 GAN f1 score: 0.385 GAN cohens kappa score: 0.331