Analysis of Machine Learning Algorithms using WEKA

The purpose of this paper is to conduct an experimental study of real world problems using the WEKA implementations of Machine Learning algorithms. It will mainly perform classification and comparison of relative performance of different algorithms under certain criteria. General Terms TreesJ48, TreesJ48graft, RandomTree, OneR, ZeroR, Decision Table, Naive Bayes, Bayes Net, Naive Bayes Simple, Bayes Updatable, Multilayer Perceptron, Logistic, RBF Network, Simple Logistic