Performance Comparison of Naïve Bayes and J48 Classification Algorithms

Classification is an important data mining technique with broad applications. It classifies data of various kinds. Classification is used in every field of our life. Classification is used to classify each item in a set of data into one of predefined set of classes or groups. This paper has been carried out to make a performance evaluation of Naïve Bayes and j48 classification algorithm. Naive Bayes algorithm is based on probability and j48 algorithm is based on decision tree. The paper sets out to make comparative evaluation of classifiers NAÏVE BAYES AND J48 in the context of financial institute dataset to maximize true positive rate and minimize false positive rate of defaulters rather than achieving only higher classification accuracy using WEKA tool. The experiments results shown in this paper are about classification accuracy and cost analysis. The results in the paper on this dataset also show that the efficiency and accuracy of j48 and Naive bayes is good.