--- license: apache-2.0 library_name: sklearn tags: - tabular-classification - baseline-trainer --- ## Baseline Model trained on Airlinesuiztcxpg to apply classification on Delay **Metrics of the best model:** accuracy 0.612210 average_precision 0.405509 roc_auc 0.635865 recall_macro 0.594188 f1_macro 0.569725 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 Airline False False False ... False False False Flight True False False ... False False False AirportFrom False False False ... False True False AirportTo False False False ... False True False Time True False False ... False False False Length True False False ... False False False[6 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 Airline False False False ... False False False Flight True False False ... False False False AirportFrom False False False ... False True False AirportTo False False False ... False True False Time True False False ... False False False Length True False False ... False False False[6 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 Airline False False False ... False False False Flight True False False ... False False False AirportFrom False False False ... False True False AirportTo False False False ... False True False Time True False False ... False False False Length True False False ... False False False[6 rows x 7 columns])
LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)