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())]))])
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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()