Comparative Study of Rule Mining Classifiers with Hapatitus Datasets

This paper deals with comparison of the rule classifiers based on the evaluation parameters. The classification is a step by step procedure for designating a given piece of input data into any one of the given categories. We have used five Rule classifiers algorithms, namely Decision Table, JRIP, PART, OneR and ZeroR for experimental setup. The hepatitis datasets are used for calculating the performance by using the split percentage parameter. Finally find out the comparative analysis based on the performance factors such as the classification accuracy, Kappa statistic and execution time is performed on all the algorithms. The goal of this paper is to find out which classier is best to other rule classifier in WEKA under hepatitis data.