--- license: apache-2.0 library_name: sklearn tags: - tabular-classification - baseline-trainer --- ## Baseline Model trained on trainii_ac94u to apply classification on label **Metrics of the best model:** accuracy 0.361046 recall_macro 0.353192 precision_macro 0.240667 f1_macro 0.278231 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 id True False False ... False False False text False False False ... False True False[2 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 id True False False ... False False False text False False False ... False True False[2 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 id True False False ... False False False text False False False ... False True False[2 rows x 7 columns])
LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)