--- license: apache-2.0 library_name: sklearn --- ## Baseline Model trained on tips to predict sex Metrics of the best model: accuracy 0.647364 average_precision 0.481257 roc_auc 0.608805 recall_macro 0.588751 f1_macro 0.588435 Name: MultinomialNB(), dtype: float64 See model plot below:
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless total_bill True False False ... False False False tip True False False ... False False False smoker False False False ... False False False day False False False ... False False False time False False False ... False False False size False False True ... False False False[6 rows x 7 columns])),('pipeline',Pipeline(steps=[('minmaxscaler', MinMaxScaler()),('multinomialnb', MultinomialNB())]))])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 total_bill True False False ... False False False tip True False False ... False False False smoker False False False ... False False False day False False False ... False False False time False False False ... False False False size False False True ... False False False[6 rows x 7 columns])),('pipeline',Pipeline(steps=[('minmaxscaler', MinMaxScaler()),('multinomialnb', MultinomialNB())]))])
EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless total_bill True False False ... False False False tip True False False ... False False False smoker False False False ... False False False day False False False ... False False False time False False False ... False False False size False False True ... False False False[6 rows x 7 columns])
Pipeline(steps=[('minmaxscaler', MinMaxScaler()),('multinomialnb', MultinomialNB())])
MinMaxScaler()
MultinomialNB()