In recent years, medical research has incorporated the use of data analytics to find new ways to detect heart disease in its early stage. Medical doctors are particularly interested in accurately identifying high-risk patients so that preventive care and intervention can be administered in a timely manner. A set of information is available regarding a patient’s age (Age), blood pressure (BP Systolic and BP Diastolic), and BMI, along with an indicator of whether or not the patient has heart disease (Disease = 1 if heart disease, 0 otherwise). A portion of the data set is provided in the accompanying table. 

a. Create a bagging ensemble classification tree model to determine whether a patient has heart disease. What are the overall accuracy rate, sensitivity, and specificity of the model on the validation data? 

b. Create a boosting ensemble classification tree model. What are the overall accuracy rate, sensitivity, and specificity of the model on the validation data? 

c. Compare the two ensemble models. Which model shows more robust performance according to the AUC value?

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Disease 0 1 # 0 Age BP Systolic BP Diastolic 44 111 55 90 29 112 128 ⠀ 144 *** 85 BMI 17 27 ⠀ 32