/////////////////////////////////////////// // Running SimpleGAN on imblearn_ozone_level /////////////////////////////////////////// Load 'data_input/imblearn_ozone_level' from imblearn 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 487, 6 LR fn, tp: 10, 5 LR f1 score: 0.385 LR cohens kappa score: 0.369 LR average precision score: 0.463 -> test with 'GB' GB tn, fp: 492, 1 GB fn, tp: 11, 4 GB f1 score: 0.400 GB cohens kappa score: 0.391 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 486, 7 LR fn, tp: 11, 4 LR f1 score: 0.308 LR cohens kappa score: 0.290 LR average precision score: 0.251 -> test with 'GB' GB tn, fp: 492, 1 GB fn, tp: 14, 1 GB f1 score: 0.118 GB cohens kappa score: 0.111 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 482, 11 LR fn, tp: 11, 4 LR f1 score: 0.267 LR cohens kappa score: 0.244 LR average precision score: 0.209 -> test with 'GB' GB tn, fp: 490, 3 GB fn, tp: 13, 2 GB f1 score: 0.200 GB cohens kappa score: 0.188 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 486, 7 LR fn, tp: 14, 1 LR f1 score: 0.087 LR cohens kappa score: 0.068 LR average precision score: 0.212 -> test with 'GB' GB tn, fp: 488, 5 GB fn, tp: 14, 1 GB f1 score: 0.095 GB cohens kappa score: 0.080 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 484, 7 LR fn, tp: 13, 0 LR f1 score: 0.000 LR cohens kappa score: -0.018 LR average precision score: 0.169 -> test with 'GB' GB tn, fp: 488, 3 GB fn, tp: 13, 0 GB f1 score: 0.000 GB cohens kappa score: -0.010 -> test with 'KNN' KNN tn, fp: 491, 0 KNN fn, tp: 13, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 484, 9 LR fn, tp: 13, 2 LR f1 score: 0.154 LR cohens kappa score: 0.132 LR average precision score: 0.222 -> test with 'GB' GB tn, fp: 489, 4 GB fn, tp: 13, 2 GB f1 score: 0.190 GB cohens kappa score: 0.177 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 488, 5 LR fn, tp: 12, 3 LR f1 score: 0.261 LR cohens kappa score: 0.245 LR average precision score: 0.205 -> test with 'GB' GB tn, fp: 492, 1 GB fn, tp: 15, 0 GB f1 score: 0.000 GB cohens kappa score: -0.004 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 489, 4 LR fn, tp: 9, 6 LR f1 score: 0.480 LR cohens kappa score: 0.467 LR average precision score: 0.517 -> test with 'GB' GB tn, fp: 490, 3 GB fn, tp: 14, 1 GB f1 score: 0.105 GB cohens kappa score: 0.094 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 488, 5 LR fn, tp: 14, 1 LR f1 score: 0.095 LR cohens kappa score: 0.080 LR average precision score: 0.207 -> test with 'GB' GB tn, fp: 490, 3 GB fn, tp: 13, 2 GB f1 score: 0.200 GB cohens kappa score: 0.188 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 480, 11 LR fn, tp: 10, 3 LR f1 score: 0.222 LR cohens kappa score: 0.201 LR average precision score: 0.209 -> test with 'GB' GB tn, fp: 489, 2 GB fn, tp: 10, 3 GB f1 score: 0.333 GB cohens kappa score: 0.324 -> test with 'KNN' KNN tn, fp: 491, 0 KNN fn, tp: 13, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 484, 9 LR fn, tp: 11, 4 LR f1 score: 0.286 LR cohens kappa score: 0.266 LR average precision score: 0.281 -> test with 'GB' GB tn, fp: 490, 3 GB fn, tp: 14, 1 GB f1 score: 0.105 GB cohens kappa score: 0.094 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 478, 15 LR fn, tp: 14, 1 LR f1 score: 0.065 LR cohens kappa score: 0.035 LR average precision score: 0.162 -> test with 'GB' GB tn, fp: 491, 2 GB fn, tp: 15, 0 GB f1 score: 0.000 GB cohens kappa score: -0.007 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 483, 10 LR fn, tp: 12, 3 LR f1 score: 0.214 LR cohens kappa score: 0.192 LR average precision score: 0.219 -> test with 'GB' GB tn, fp: 490, 3 GB fn, tp: 13, 2 GB f1 score: 0.200 GB cohens kappa score: 0.188 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 489, 4 LR fn, tp: 12, 3 LR f1 score: 0.273 LR cohens kappa score: 0.259 LR average precision score: 0.271 -> test with 'GB' GB tn, fp: 492, 1 GB fn, tp: 13, 2 GB f1 score: 0.222 GB cohens kappa score: 0.214 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 482, 9 LR fn, tp: 9, 4 LR f1 score: 0.308 LR cohens kappa score: 0.289 LR average precision score: 0.363 -> test with 'GB' GB tn, fp: 488, 3 GB fn, tp: 12, 1 GB f1 score: 0.118 GB cohens kappa score: 0.107 -> test with 'KNN' KNN tn, fp: 491, 0 KNN fn, tp: 13, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 485, 8 LR fn, tp: 12, 3 LR f1 score: 0.231 LR cohens kappa score: 0.211 LR average precision score: 0.282 -> test with 'GB' GB tn, fp: 490, 3 GB fn, tp: 13, 2 GB f1 score: 0.200 GB cohens kappa score: 0.188 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 484, 9 LR fn, tp: 13, 2 LR f1 score: 0.154 LR cohens kappa score: 0.132 LR average precision score: 0.209 -> test with 'GB' GB tn, fp: 492, 1 GB fn, tp: 15, 0 GB f1 score: 0.000 GB cohens kappa score: -0.004 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 486, 7 LR fn, tp: 12, 3 LR f1 score: 0.240 LR cohens kappa score: 0.222 LR average precision score: 0.246 -> test with 'GB' GB tn, fp: 491, 2 GB fn, tp: 12, 3 GB f1 score: 0.300 GB cohens kappa score: 0.290 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 486, 7 LR fn, tp: 8, 7 LR f1 score: 0.483 LR cohens kappa score: 0.468 LR average precision score: 0.377 -> test with 'GB' GB tn, fp: 489, 4 GB fn, tp: 14, 1 GB f1 score: 0.100 GB cohens kappa score: 0.087 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 481, 10 LR fn, tp: 9, 4 LR f1 score: 0.296 LR cohens kappa score: 0.277 LR average precision score: 0.221 -> test with 'GB' GB tn, fp: 488, 3 GB fn, tp: 12, 1 GB f1 score: 0.118 GB cohens kappa score: 0.107 -> test with 'KNN' KNN tn, fp: 491, 0 KNN fn, tp: 13, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 484, 9 LR fn, tp: 12, 3 LR f1 score: 0.222 LR cohens kappa score: 0.201 LR average precision score: 0.307 -> test with 'GB' GB tn, fp: 491, 2 GB fn, tp: 13, 2 GB f1 score: 0.211 GB cohens kappa score: 0.201 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 487, 6 LR fn, tp: 13, 2 LR f1 score: 0.174 LR cohens kappa score: 0.157 LR average precision score: 0.270 -> test with 'GB' GB tn, fp: 489, 4 GB fn, tp: 13, 2 GB f1 score: 0.190 GB cohens kappa score: 0.177 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 484, 9 LR fn, tp: 13, 2 LR f1 score: 0.154 LR cohens kappa score: 0.132 LR average precision score: 0.182 -> test with 'GB' GB tn, fp: 492, 1 GB fn, tp: 15, 0 GB f1 score: 0.000 GB cohens kappa score: -0.004 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 482, 11 LR fn, tp: 13, 2 LR f1 score: 0.143 LR cohens kappa score: 0.119 LR average precision score: 0.240 -> test with 'GB' GB tn, fp: 488, 5 GB fn, tp: 13, 2 GB f1 score: 0.182 GB cohens kappa score: 0.166 -> test with 'KNN' KNN tn, fp: 493, 0 KNN fn, tp: 15, 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 1912 synthetic samples -> test with 'LR' LR tn, fp: 483, 8 LR fn, tp: 10, 3 LR f1 score: 0.250 LR cohens kappa score: 0.232 LR average precision score: 0.249 -> test with 'GB' GB tn, fp: 489, 2 GB fn, tp: 11, 2 GB f1 score: 0.235 GB cohens kappa score: 0.226 -> test with 'KNN' KNN tn, fp: 491, 0 KNN fn, tp: 13, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 ### Exercise is done. -----[ LR ]----- maximum: LR tn, fp: 489, 15 LR fn, tp: 14, 7 LR f1 score: 0.483 LR cohens kappa score: 0.468 LR average precision score: 0.517 average: LR tn, fp: 484.48, 8.12 LR fn, tp: 11.6, 3.0 LR f1 score: 0.230 LR cohens kappa score: 0.211 LR average precision score: 0.262 minimum: LR tn, fp: 478, 4 LR fn, tp: 8, 0 LR f1 score: 0.000 LR cohens kappa score: -0.018 LR average precision score: 0.162 -----[ GB ]----- maximum: GB tn, fp: 492, 5 GB fn, tp: 15, 4 GB f1 score: 0.400 GB cohens kappa score: 0.391 average: GB tn, fp: 490.0, 2.6 GB fn, tp: 13.12, 1.48 GB f1 score: 0.153 GB cohens kappa score: 0.143 minimum: GB tn, fp: 488, 1 GB fn, tp: 10, 0 GB f1 score: 0.000 GB cohens kappa score: -0.010 -----[ KNN ]----- maximum: KNN tn, fp: 493, 0 KNN fn, tp: 15, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 average: KNN tn, fp: 492.6, 0.0 KNN fn, tp: 14.6, 0.0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000 minimum: KNN tn, fp: 491, 0 KNN fn, tp: 13, 0 KNN f1 score: 0.000 KNN cohens kappa score: 0.000