Clasiffication of Heart Disease using Decision Tree Algorithm

Abstract

Data mining is the process of manipulating data by extracting information that was previously unknown from a large dataset. The Tree Model in relation to data structures is a data type that simulates a hierarchical tree structure with root values and sub-Trees with the parent node represented as a series of recursively defined node links as a means of presenting complex data analysis. Every year an estimated 17.3 million people die from cardiovascular disease. As many as 7.3 million of them occur due to heart disease and 6.2 million due to stroke. Risk factors for heart disease are age, gender, heredity or genetics, smoking habits, lack of physical activity, obesity, diabetes mellitus, stress and diet. The purpose of the dataset in this study is to classify data to determine categories of heart disease based on the presence or absence of narrowing of the arteries.