Review of Decision Tree Data mining Algorithms: CART and C4.5

Abstract

Data mining is a process of identification of useful information from large amount of random data. It is used to discover meaningful pattern and rules from data. Classification, clustering, association rules are data mining techniques. Classification is a process of assigning entities to an already defined class by examining the features. Decision tree is a classification technique in which a model is created that anticipates the value of target variable depends on input values. CART and C4.5 are commonly used decision tree algorithms. These algorithms are based on Hunt’s algorithm. Goal of this study is to provide review of these decision tree algorithms At first we present concept of Data Mining, Classification and Decision Tree. Then we present CART and C4.5 algorithms and we will make comparison of these two algorithms.