Comparison of Data Mining Classification Algorithms, C5.0 and CART for Car Evaluation and Credit Card Information Datasets

Abstract

Data mining is the use of algorithm to discover enormous amount of data automatically by searching hidden information from large data sets using multiple algorithms and techniques. Different methods and algorithms are available in data mining system. Classification and prediction are the most common method used to make out models and predict probable data patterns and can be solving several problems in different domains like education, medicine, business, and science. In the present scenario, as almost everything is becoming computerized, various classifications algorithms have been developed to make the automatic decision process. The Decision Tree is an imperative classification method in data mining classification. This paper provides a comparison between two data mining classification algorithms: C5.0 and CART (classification and regression tree) applied on two different UCI datasets: car evaluation dataset and credit card dataset.