diff --git a/docs/examples/simple-mag/confusion-matrix.png b/docs/examples/simple-mag/confusion-matrix.png deleted file mode 100644 index b152adf..0000000 Binary files a/docs/examples/simple-mag/confusion-matrix.png and /dev/null differ diff --git a/docs/examples/simple-mag/mag-confusion.png b/docs/examples/simple-mag/mag-confusion.png new file mode 100644 index 0000000..e1d3718 Binary files /dev/null and b/docs/examples/simple-mag/mag-confusion.png differ diff --git a/docs/examples/simple-mag/train.ipynb b/docs/examples/simple-mag/train.ipynb index 75ed417..09faf2c 100644 --- a/docs/examples/simple-mag/train.ipynb +++ b/docs/examples/simple-mag/train.ipynb @@ -19,8 +19,8 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████| 84000/84000 [00:08<00:00, 9514.74it/s] \n", - "100%|██████████| 22399/22399 [00:02<00:00, 7728.92it/s] \n" + "100%|██████████| 84000/84000 [00:16<00:00, 4964.08it/s]\n", + "100%|██████████| 22399/22399 [00:05<00:00, 3847.04it/s]\n" ] } ], @@ -162,10 +162,10 @@ "
\n", "| \n", + " | mean_fit_time | \n", + "std_fit_time | \n", + "mean_score_time | \n", + "std_score_time | \n", + "param_classifier__alpha | \n", + "param_classifier__fit_prior | \n", + "param_vectorizer__max_df | \n", + "param_vectorizer__min_df | \n", + "params | \n", + "split0_test_score | \n", + "split1_test_score | \n", + "split2_test_score | \n", + "mean_test_score | \n", + "std_test_score | \n", + "rank_test_score | \n", + "
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 7 | \n", + "14.549476 | \n", + "0.361685 | \n", + "8.476837 | \n", + "0.222398 | \n", + "0.5 | \n", + "False | \n", + "0.05 | \n", + "20 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.518061 | \n", + "0.514842 | \n", + "0.511599 | \n", + "0.514834 | \n", + "0.002638 | \n", + "1 | \n", + "
| 10 | \n", + "11.235289 | \n", + "0.130426 | \n", + "4.092868 | \n", + "0.082518 | \n", + "0.5 | \n", + "False | \n", + "0.1 | \n", + "20 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.513897 | \n", + "0.515661 | \n", + "0.507867 | \n", + "0.512475 | \n", + "0.003337 | \n", + "2 | \n", + "
| 19 | \n", + "7.383645 | \n", + "0.138110 | \n", + "4.130709 | \n", + "0.250048 | \n", + "1 | \n", + "False | \n", + "0.05 | \n", + "20 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.496825 | \n", + "0.501045 | \n", + "0.496854 | \n", + "0.498241 | \n", + "0.001983 | \n", + "3 | \n", + "
| 11 | \n", + "10.435154 | \n", + "0.305144 | \n", + "3.882101 | \n", + "0.128886 | \n", + "0.5 | \n", + "False | \n", + "0.1 | \n", + "100 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.493247 | \n", + "0.497814 | \n", + "0.502245 | \n", + "0.497769 | \n", + "0.003674 | \n", + "4 | \n", + "
| 8 | \n", + "13.643193 | \n", + "0.310696 | \n", + "4.173707 | \n", + "0.142980 | \n", + "0.5 | \n", + "False | \n", + "0.05 | \n", + "100 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.489609 | \n", + "0.495207 | \n", + "0.498154 | \n", + "0.494323 | \n", + "0.003544 | \n", + "5 | \n", + "
| 22 | \n", + "7.048340 | \n", + "0.050070 | \n", + "3.172948 | \n", + "0.152418 | \n", + "1 | \n", + "False | \n", + "0.1 | \n", + "20 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.487456 | \n", + "0.493865 | \n", + "0.491157 | \n", + "0.490826 | \n", + "0.002627 | \n", + "6 | \n", + "
| 23 | \n", + "7.564685 | \n", + "0.146092 | \n", + "2.374111 | \n", + "0.285026 | \n", + "1 | \n", + "False | \n", + "0.1 | \n", + "100 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.485160 | \n", + "0.494039 | \n", + "0.490127 | \n", + "0.489776 | \n", + "0.003633 | \n", + "7 | \n", + "
| 20 | \n", + "7.172353 | \n", + "0.212599 | \n", + "3.747219 | \n", + "0.130217 | \n", + "1 | \n", + "False | \n", + "0.05 | \n", + "100 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.481303 | \n", + "0.490002 | \n", + "0.488269 | \n", + "0.486524 | \n", + "0.003759 | \n", + "8 | \n", + "
| 6 | \n", + "14.276345 | \n", + "0.456576 | \n", + "8.318859 | \n", + "0.268701 | \n", + "0.5 | \n", + "False | \n", + "0.05 | \n", + "5 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.482429 | \n", + "0.487735 | \n", + "0.484888 | \n", + "0.485017 | \n", + "0.002168 | \n", + "9 | \n", + "
| 2 | \n", + "14.902358 | \n", + "0.737693 | \n", + "5.975091 | \n", + "0.171150 | \n", + "0.5 | \n", + "True | \n", + "0.05 | \n", + "100 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.469598 | \n", + "0.474490 | \n", + "0.473637 | \n", + "0.472575 | \n", + "0.002134 | \n", + "10 | \n", + "
| 9 | \n", + "12.677349 | \n", + "0.145143 | \n", + "4.374204 | \n", + "0.175674 | \n", + "0.5 | \n", + "False | \n", + "0.1 | \n", + "5 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.468872 | \n", + "0.476451 | \n", + "0.470921 | \n", + "0.472082 | \n", + "0.003201 | \n", + "11 | \n", + "
| 5 | \n", + "13.423686 | \n", + "0.482872 | \n", + "8.008324 | \n", + "0.442975 | \n", + "0.5 | \n", + "True | \n", + "0.1 | \n", + "100 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.465726 | \n", + "0.474548 | \n", + "0.471879 | \n", + "0.470718 | \n", + "0.003694 | \n", + "12 | \n", + "
| 1 | \n", + "13.819117 | \n", + "0.838347 | \n", + "6.161175 | \n", + "0.336590 | \n", + "0.5 | \n", + "True | \n", + "0.05 | \n", + "20 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.463395 | \n", + "0.473982 | \n", + "0.471262 | \n", + "0.469546 | \n", + "0.004489 | \n", + "13 | \n", + "
| 4 | \n", + "13.281476 | \n", + "0.588822 | \n", + "8.335852 | \n", + "0.254627 | \n", + "0.5 | \n", + "True | \n", + "0.1 | \n", + "20 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.458734 | \n", + "0.468053 | \n", + "0.464418 | \n", + "0.463735 | \n", + "0.003835 | \n", + "14 | \n", + "
| 14 | \n", + "7.282247 | \n", + "0.444940 | \n", + "3.567094 | \n", + "0.044519 | \n", + "1 | \n", + "True | \n", + "0.05 | \n", + "100 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.438189 | \n", + "0.450160 | \n", + "0.446180 | \n", + "0.444843 | \n", + "0.004978 | \n", + "15 | \n", + "
| 17 | \n", + "7.098797 | \n", + "0.196241 | \n", + "3.838628 | \n", + "0.091128 | \n", + "1 | \n", + "True | \n", + "0.1 | \n", + "100 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.436488 | \n", + "0.444503 | \n", + "0.445900 | \n", + "0.442297 | \n", + "0.004147 | \n", + "16 | \n", + "
| 18 | \n", + "7.492791 | \n", + "0.288889 | \n", + "3.843224 | \n", + "0.073438 | \n", + "1 | \n", + "False | \n", + "0.05 | \n", + "5 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.428196 | \n", + "0.431945 | \n", + "0.430160 | \n", + "0.430100 | \n", + "0.001531 | \n", + "17 | \n", + "
| 21 | \n", + "7.229826 | \n", + "0.099823 | \n", + "3.656332 | \n", + "0.073780 | \n", + "1 | \n", + "False | \n", + "0.1 | \n", + "5 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.403130 | \n", + "0.410170 | \n", + "0.409801 | \n", + "0.407700 | \n", + "0.003235 | \n", + "18 | \n", + "
| 13 | \n", + "7.158370 | \n", + "0.169818 | \n", + "3.765632 | \n", + "0.082924 | \n", + "1 | \n", + "True | \n", + "0.05 | \n", + "20 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.399237 | \n", + "0.412872 | \n", + "0.407982 | \n", + "0.406697 | \n", + "0.005640 | \n", + "19 | \n", + "
| 16 | \n", + "7.064643 | \n", + "0.119529 | \n", + "3.810983 | \n", + "0.125897 | \n", + "1 | \n", + "True | \n", + "0.1 | \n", + "20 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.388060 | \n", + "0.399247 | \n", + "0.396325 | \n", + "0.394544 | \n", + "0.004737 | \n", + "20 | \n", + "
| 0 | \n", + "13.749660 | \n", + "0.465174 | \n", + "6.407841 | \n", + "0.549166 | \n", + "0.5 | \n", + "True | \n", + "0.05 | \n", + "5 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.384852 | \n", + "0.386487 | \n", + "0.386796 | \n", + "0.386045 | \n", + "0.000853 | \n", + "21 | \n", + "
| 3 | \n", + "15.954147 | \n", + "0.318013 | \n", + "6.337361 | \n", + "0.261697 | \n", + "0.5 | \n", + "True | \n", + "0.1 | \n", + "5 | \n", + "{'classifier__alpha': 0.5, 'classifier__fit_pr... | \n", + "0.369785 | \n", + "0.375645 | \n", + "0.375858 | \n", + "0.373763 | \n", + "0.002814 | \n", + "22 | \n", + "
| 12 | \n", + "7.120198 | \n", + "0.050452 | \n", + "3.833905 | \n", + "0.069540 | \n", + "1 | \n", + "True | \n", + "0.05 | \n", + "5 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.277741 | \n", + "0.280564 | \n", + "0.285337 | \n", + "0.281214 | \n", + "0.003135 | \n", + "23 | \n", + "
| 15 | \n", + "7.497707 | \n", + "0.183054 | \n", + "3.870714 | \n", + "0.062888 | \n", + "1 | \n", + "True | \n", + "0.1 | \n", + "5 | \n", + "{'classifier__alpha': 1, 'classifier__fit_prio... | \n", + "0.255578 | \n", + "0.263381 | \n", + "0.266184 | \n", + "0.261714 | \n", + "0.004487 | \n", + "24 | \n", + "