--- license: apache-2.0 library_name: sklearn tags: - tabular-classification - baseline-trainer --- ## Baseline Model trained on train5a1e8w7 to apply classification on label **Metrics of the best model:** accuracy 0.693101 recall_macro 0.665973 precision_macro 0.657625 f1_macro 0.656998 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 low_card_int ... date free_string useless v_21 False False False ... False False False v_32 True False False ... False False False v_15 False False False ... False False False v_4 True False False ... False False False v_1 False False False ... False False False v_8 False False False ... False False False v_12 False False Fa... v_34 False False False ... False False False v_35 True False False ... False False False v_36 True False False ... False False False v_37 True False False ... False False False v_38 True False False ... False False False v_39 True False False ... False False False v_40 False False False ... False False False[40 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 low_card_int ... date free_string useless v_21 False False False ... False False False v_32 True False False ... False False False v_15 False False False ... False False False v_4 True False False ... False False False v_1 False False False ... False False False v_8 False False False ... False False False v_12 False False Fa... v_34 False False False ... False False False v_35 True False False ... False False False v_36 True False False ... False False False v_37 True False False ... False False False v_38 True False False ... False False False v_39 True False False ... False False False v_40 False False False ... False False False[40 rows x 7 columns])),('logisticregression',LogisticRegression(C=0.1, class_weight='balanced',max_iter=1000))])
EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless v_21 False False False ... False False False v_32 True False False ... False False False v_15 False False False ... False False False v_4 True False False ... False False False v_1 False False False ... False False False v_8 False False False ... False False False v_12 False False False ... False False False v_25 True False Fa... v_7 True False False ... False False False v_2 True False False ... False False False v_16 True False False ... False False False v_34 False False False ... False False False v_35 True False False ... False False False v_36 True False False ... False False False v_37 True False False ... False False False v_38 True False False ... False False False v_39 True False False ... False False False v_40 False False False ... False False False[40 rows x 7 columns])
LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)