Baseline Model trained on heart1ohr2x9e to apply classification on target
Metrics of the best model:
accuracy 0.885854
average_precision 0.949471
roc_auc 0.050633
recall_macro 0.885324
f1_macro 0.885610
Name: LogisticRegression(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
age False False False ... False False False
sex False False False ... False False False
cp False False False ... False False False
trestbps True False False ... False False False
chol True False False ... False False False
fbs False False False ... False False False
restecg False Fa...... False False False
thalach True False False ... False False False
exang False False False ... False False False
oldpeak True False False ... False False False
slope False False False ... False False False
ca False False False ... False False False
thal False False False ... False False False[13 rows x 7 columns])),('logisticregression',LogisticRegression(C=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
age False False False ... False False False
sex False False False ... False False False
cp False False False ... False False False
trestbps True False False ... False False False
chol True False False ... False False False
fbs False False False ... False False False
restecg False Fa...... False False False
thalach True False False ... False False False
exang False False False ... False False False
oldpeak True False False ... False False False
slope False False False ... False False False
ca False False False ... False False False
thal False False False ... False False False[13 rows x 7 columns])),('logisticregression',LogisticRegression(C=1, class_weight='balanced',max_iter=1000))])EasyPreprocessor(types= continuous dirty_float low_card_int ... date free_string useless age False False False ... False False False sex False False False ... False False False cp False False False ... False False False trestbps True False False ... False False False chol True False False ... False False False fbs False False False ... False False False restecg False False False ... False False False thalach True False False ... False False False exang False False False ... False False False oldpeak True False False ... False False False slope False False False ... False False False ca False False False ... False False False thal False False False ... False False False[13 rows x 7 columns])
LogisticRegression(C=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