Baseline Model trained on train5a1e8w7 to apply classification on label
Metrics of the best model:
accuracy 0.693101
recall_macro 0.665973
precision_macro 0.657625
f1_macro 0.656998
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
v_21 False False False ... False False False
v_32 True False False ... False False False
v_15 False False False ... False False False
v_4 True False False ... False False False
v_1 False False False ... False False False
v_8 False False False ... False False False
v_12 False False Fa...
v_34 False False False ... False False False
v_35 True False False ... False False False
v_36 True False False ... False False False
v_37 True False False ... False False False
v_38 True False False ... False False False
v_39 True False False ... False False False
v_40 False False False ... False False False[40 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. 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
v_21 False False False ... False False False
v_32 True False False ... False False False
v_15 False False False ... False False False
v_4 True False False ... False False False
v_1 False False False ... False False False
v_8 False False False ... False False False
v_12 False False Fa...
v_34 False False False ... False False False
v_35 True False False ... False False False
v_36 True False False ... False False False
v_37 True False False ... False False False
v_38 True False False ... False False False
v_39 True False False ... False False False
v_40 False False False ... False False False[40 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 v_21 False False False ... False False False v_32 True False False ... False False False v_15 False False False ... False False False v_4 True False False ... False False False v_1 False False False ... False False False v_8 False False False ... False False False v_12 False False False ... False False False v_25 True False Fa... v_7 True False False ... False False False v_2 True False False ... False False False v_16 True False False ... False False False v_34 False False False ... False False False v_35 True False False ... False False False v_36 True False False ... False False False v_37 True False False ... False False False v_38 True False False ... False False False v_39 True False False ... False False False v_40 False False False ... False False False[40 rows x 7 columns])
LogisticRegression(C=0.1, class_weight='balanced', max_iter=1000)
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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