--- license: apache-2.0 library_name: sklearn tags: - tabular-classification - baseline-trainer --- ## Baseline Model trained on model_tuning_mindalle9_jsy6zj to apply classification on labels **Metrics of the best model:** accuracy 0.735922 recall_macro 0.631737 precision_macro 0.440117 f1_macro 0.457940 Name: LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000), dtype: float64 **See model plot below:**
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float ... free_string useless temperatures False False ... False False superconditions True False ... False False is_megas False False ... False False feature_0 True False ... False False feature_1 True False ... False False ... ... ... ... ... ... feature_763 True False ... False False feature_764 True False ... False False feature_765 True False ... False False feature_766 True False ... False False feature_767 True False ... False False[771 rows x 7 columns])),('logisticregression',LogisticRegression(C=0.1, class_weight='balanced',max_iter=1000))])In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float ... free_string useless temperatures False False ... False False superconditions True False ... False False is_megas False False ... False False feature_0 True False ... False False feature_1 True False ... False False ... ... ... ... ... ... feature_763 True False ... False False feature_764 True False ... False False feature_765 True False ... False False feature_766 True False ... False False feature_767 True False ... False False[771 rows x 7 columns])),('logisticregression',LogisticRegression(C=0.1, class_weight='balanced',max_iter=1000))])
EasyPreprocessor(types= continuous dirty_float ... free_string useless temperatures False False ... False False superconditions True False ... False False is_megas False False ... False False feature_0 True False ... False False feature_1 True False ... False False ... ... ... ... ... ... feature_763 True False ... False False feature_764 True False ... False False feature_765 True False ... False False feature_766 True False ... False False feature_767 True False ... False False[771 rows x 7 columns])
LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)