.

app.py

@@ -10,8 +10,8 @@ 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'])
 
-exp_clf101 = setup(data = healthcare_stroke_data, target = 'stroke', session_id=123)
-best = compare_models(sort = 'AUC', n_select = 15)
+setup(data = healthcare_stroke_data, target = 'stroke', session_id=123)
+best = compare_models()
 compare_model_results = pull()
             
 model = gr.inputs.Dropdown(list(compare_model_results['Model']),label="Model")