Evaluation of Different Classification Techniques for WEB Data
The growth of data-mining applications such as classification and clustering has shown the need for machine learning algorithms to be applied to large scale data. In this paper, the authors present the comparison of different classification techniques using Waikato Environment for Knowledge Analysis or in short, WEKA. WEKA is open source software which consists of a collection of machine learning algorithms for data mining tasks. The aim of this paper is to examine the performance of different classification methods for a set of large data. The algorithm which have been tested are J48, SMO, Part, OneR, ZeroR and Navies Bayes Algorithm.