/////////////////////////////////////////// // Running SimpleGAN 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 Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 2, 7 LR f1 score: 0.824 LR cohens kappa score: 0.813 LR average precision score: 0.917 -> 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: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 1/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 136, 2 LR fn, tp: 5, 4 LR f1 score: 0.533 LR cohens kappa score: 0.509 LR average precision score: 0.646 -> test with 'GB' GB tn, fp: 136, 2 GB fn, tp: 6, 3 GB f1 score: 0.429 GB cohens kappa score: 0.402 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 1/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 5, 4 LR f1 score: 0.571 LR cohens kappa score: 0.552 LR average precision score: 0.716 -> test with 'GB' GB tn, fp: 136, 2 GB fn, tp: 6, 3 GB f1 score: 0.429 GB cohens kappa score: 0.402 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 1/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 135, 3 LR fn, tp: 6, 3 LR f1 score: 0.400 LR cohens kappa score: 0.369 LR average precision score: 0.527 -> test with 'GB' GB tn, fp: 134, 4 GB fn, tp: 4, 5 GB f1 score: 0.556 GB cohens kappa score: 0.527 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 1/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 516 synthetic samples -> test with 'LR' LR tn, fp: 134, 3 LR fn, tp: 4, 2 LR f1 score: 0.364 LR cohens kappa score: 0.338 LR average precision score: 0.530 -> test with 'GB' GB tn, fp: 137, 0 GB fn, tp: 6, 0 GB f1 score: 0.000 GB cohens kappa score: 0.000 -> test with 'KNN' KNN tn, fp: 137, 0 KNN fn, tp: 6, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ====== Step 2/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 2/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 138, 0 LR fn, tp: 6, 3 LR f1 score: 0.500 LR cohens kappa score: 0.484 LR average precision score: 0.558 -> test with 'GB' GB tn, fp: 135, 3 GB fn, tp: 7, 2 GB f1 score: 0.286 GB cohens kappa score: 0.253 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 2/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 136, 2 LR fn, tp: 4, 5 LR f1 score: 0.625 LR cohens kappa score: 0.604 LR average precision score: 0.720 -> test with 'GB' GB tn, fp: 137, 1 GB fn, tp: 5, 4 GB f1 score: 0.571 GB cohens kappa score: 0.552 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 2/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 5, 4 LR f1 score: 0.571 LR cohens kappa score: 0.552 LR average precision score: 0.674 -> test with 'GB' GB tn, fp: 135, 3 GB fn, tp: 6, 3 GB f1 score: 0.400 GB cohens kappa score: 0.369 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 2/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 5, 4 LR f1 score: 0.571 LR cohens kappa score: 0.552 LR average precision score: 0.717 -> 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: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 2/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 516 synthetic samples -> test with 'LR' LR tn, fp: 135, 2 LR fn, tp: 2, 4 LR f1 score: 0.667 LR cohens kappa score: 0.652 LR average precision score: 0.719 -> test with 'GB' GB tn, fp: 136, 1 GB fn, tp: 4, 2 GB f1 score: 0.444 GB cohens kappa score: 0.428 -> test with 'KNN' KNN tn, fp: 137, 0 KNN fn, tp: 6, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ====== Step 3/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 3/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 134, 4 LR fn, tp: 6, 3 LR f1 score: 0.375 LR cohens kappa score: 0.340 LR average precision score: 0.521 -> test with 'GB' GB tn, fp: 135, 3 GB fn, tp: 8, 1 GB f1 score: 0.154 GB cohens kappa score: 0.121 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 3/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 4, 5 LR f1 score: 0.667 LR cohens kappa score: 0.649 LR average precision score: 0.825 -> test with 'GB' GB tn, fp: 137, 1 GB fn, tp: 6, 3 GB f1 score: 0.462 GB cohens kappa score: 0.440 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 3/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 138, 0 LR fn, tp: 5, 4 LR f1 score: 0.615 LR cohens kappa score: 0.600 LR average precision score: 0.675 -> test with 'GB' GB tn, fp: 136, 2 GB fn, tp: 7, 2 GB f1 score: 0.308 GB cohens kappa score: 0.281 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 3/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 136, 2 LR fn, tp: 4, 5 LR f1 score: 0.625 LR cohens kappa score: 0.604 LR average precision score: 0.790 -> test with 'GB' GB tn, fp: 137, 1 GB fn, tp: 6, 3 GB f1 score: 0.462 GB cohens kappa score: 0.440 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 3/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 516 synthetic samples -> test with 'LR' LR tn, fp: 135, 2 LR fn, tp: 3, 3 LR f1 score: 0.545 LR cohens kappa score: 0.527 LR average precision score: 0.550 -> test with 'GB' GB tn, fp: 135, 2 GB fn, tp: 3, 3 GB f1 score: 0.545 GB cohens kappa score: 0.527 -> test with 'KNN' KNN tn, fp: 137, 0 KNN fn, tp: 6, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ====== Step 4/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 4/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 134, 4 LR fn, tp: 5, 4 LR f1 score: 0.471 LR cohens kappa score: 0.438 LR average precision score: 0.498 -> test with 'GB' GB tn, fp: 137, 1 GB fn, tp: 6, 3 GB f1 score: 0.462 GB cohens kappa score: 0.440 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 4/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 135, 3 LR fn, tp: 5, 4 LR f1 score: 0.500 LR cohens kappa score: 0.472 LR average precision score: 0.656 -> 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: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 4/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 4, 5 LR f1 score: 0.667 LR cohens kappa score: 0.649 LR average precision score: 0.719 -> test with 'GB' GB tn, fp: 135, 3 GB fn, tp: 6, 3 GB f1 score: 0.400 GB cohens kappa score: 0.369 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 4/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 5, 4 LR f1 score: 0.571 LR cohens kappa score: 0.552 LR average precision score: 0.879 -> test with 'GB' GB tn, fp: 137, 1 GB fn, tp: 6, 3 GB f1 score: 0.462 GB cohens kappa score: 0.440 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 4/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 516 synthetic samples -> test with 'LR' LR tn, fp: 135, 2 LR fn, tp: 4, 2 LR f1 score: 0.400 LR cohens kappa score: 0.379 LR average precision score: 0.605 -> test with 'GB' GB tn, fp: 135, 2 GB fn, tp: 5, 1 GB f1 score: 0.222 GB cohens kappa score: 0.200 -> test with 'KNN' KNN tn, fp: 137, 0 KNN fn, tp: 6, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ====== Step 5/5 ======= -> Shuffling data -> Spliting data to slices ------ Step 5/5: Slice 1/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 133, 5 LR fn, tp: 5, 4 LR f1 score: 0.444 LR cohens kappa score: 0.408 LR average precision score: 0.610 -> test with 'GB' GB tn, fp: 133, 5 GB fn, tp: 7, 2 GB f1 score: 0.250 GB cohens kappa score: 0.208 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 5/5: Slice 2/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 136, 2 LR fn, tp: 3, 6 LR f1 score: 0.706 LR cohens kappa score: 0.688 LR average precision score: 0.686 -> test with 'GB' GB tn, fp: 136, 2 GB fn, tp: 7, 2 GB f1 score: 0.308 GB cohens kappa score: 0.281 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 5/5: Slice 3/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 135, 3 LR fn, tp: 5, 4 LR f1 score: 0.500 LR cohens kappa score: 0.472 LR average precision score: 0.535 -> test with 'GB' GB tn, fp: 136, 2 GB fn, tp: 6, 3 GB f1 score: 0.429 GB cohens kappa score: 0.402 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 5/5: Slice 4/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 518 synthetic samples -> test with 'LR' LR tn, fp: 137, 1 LR fn, tp: 4, 5 LR f1 score: 0.667 LR cohens kappa score: 0.649 LR average precision score: 0.842 -> test with 'GB' GB tn, fp: 137, 1 GB fn, tp: 7, 2 GB f1 score: 0.333 GB cohens kappa score: 0.312 -> test with 'KNN' KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ------ Step 5/5: Slice 5/5 ------- -> Reset the GAN -> Train generator for synthetic samples Epoch 1/3 Epoch 2/3 Epoch 3/3 -> create 516 synthetic samples -> test with 'LR' LR tn, fp: 137, 0 LR fn, tp: 3, 3 LR f1 score: 0.667 LR cohens kappa score: 0.657 LR average precision score: 0.760 -> test with 'GB' GB tn, fp: 136, 1 GB fn, tp: 3, 3 GB f1 score: 0.600 GB cohens kappa score: 0.586 -> test with 'KNN' KNN tn, fp: 137, 0 KNN fn, tp: 6, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 138, 5 LR fn, tp: 6, 7 LR f1 score: 0.824 LR cohens kappa score: 0.813 LR average precision score: 0.917 average: LR tn, fp: 135.92, 1.88 LR fn, tp: 4.36, 4.04 LR f1 score: 0.562 LR cohens kappa score: 0.540 LR average precision score: 0.675 minimum: LR tn, fp: 133, 0 LR fn, tp: 2, 2 LR f1 score: 0.364 LR cohens kappa score: 0.338 LR average precision score: 0.498 -----[ GB ]----- maximum: GB tn, fp: 137, 5 GB fn, tp: 8, 5 GB f1 score: 0.600 GB cohens kappa score: 0.586 average: GB tn, fp: 135.64, 2.16 GB fn, tp: 5.72, 2.68 GB f1 score: 0.395 GB cohens kappa score: 0.370 minimum: GB tn, fp: 133, 0 GB fn, tp: 3, 0 GB f1 score: 0.000 GB cohens kappa score: 0.000 -----[ KNN ]----- maximum: KNN tn, fp: 138, 0 KNN fn, tp: 9, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 average: KNN tn, fp: 137.8, 0.0 KNN fn, tp: 8.4, 0.0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 minimum: KNN tn, fp: 137, 0 KNN fn, tp: 6, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000