You can deploy this model and start earning money today!

cacauvicosa/
heart1ohr2x9e-target-classification

Name: heart1ohr2x9e-target-classification
Availability: InStock

sklearn

tabular-classification

baseline-trainer

apache-2.0

Views

No views yet

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

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

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

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

cacauvicosa/heart1ohr2x9e-target-classification

Baseline Model trained on heart1ohr2x9e to apply classification on target

cacauvicosa/
heart1ohr2x9e-target-classification