Baseline Model trained on alidatelcyrtea0 to apply classification on auditStatus
Metrics of the best model:
accuracy 1.0
average_precision 1.0
roc_auc 1.0
recall_macro 1.0
f1_macro 1.0
Name: DecisionTreeClassifier(class_weight='balanced', max_depth=5), dtype: float64
See model plot below:
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string uselessIn a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.DrawMoney False False False ... False False False DrawCount False False False ... False False False LastDrawMin True False False ... False False False SignUpMin True False False ... False False False Balance True False False ... False False False TodayMoney False False False ... False False False[6 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced', max_depth=5))])
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
Pipeline(steps=[('easypreprocessor',EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless DrawMoney False False False ... False False False DrawCount False False False ... False False False LastDrawMin True False False ... False False False SignUpMin True False False ... False False False Balance True False False ... False False False TodayMoney False False False ... False False False[6 rows x 7 columns])),('decisiontreeclassifier',DecisionTreeClassifier(class_weight='balanced', max_depth=5))])
EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless DrawMoney False False False ... False False False DrawCount False False False ... False False False LastDrawMin True False False ... False False False SignUpMin True False False ... False False False Balance True False False ... False False False TodayMoney False False False ... False False False[6 rows x 7 columns])
DecisionTreeClassifier(class_weight='balanced', max_depth=5)
Disclaimer: This model is trained with dabl library as a baseline, for better results, use AutoTrain.
Logs of training including the models tried in the process can be found in logs.txt
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