cacauvicosa/heart1ohr2x9e-target-classification

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))])

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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