.

app.py

@@ -10,7 +10,7 @@ healthcare_stroke_data['gender'] = encoder.fit_transform(healthcare_stroke_data[
 encoder= ce.OrdinalEncoder(cols=['work_type'],return_df=True, mapping=[{'col':'work_type', 'mapping':{0: 1, 1: 2, 'children': 3, '2': 4, 'Never_worked': 5}}])
 healthcare_stroke_data['work_type'] = encoder.fit_transform(healthcare_stroke_data['work_type'])
 
-s = setup(data = healthcare_stroke_data, target = 'stroke', normalize = True, normalize_method = 'zscore', transformation=True, fix_imbalance = True, session_id=123, fold = 60, remove_outliers= True, outliers_threshold = 0.05, remove_multicollinearity=True, multicollinearity_threshold = 0.9)
+s = setup(data = healthcare_stroke_data, target = 'stroke', fix_imbalance = True, session_id=123)
 
 best = compare_models()
 compare_model_results = pull()