Abstract: Naive Bayes Classifier is effective and useful model. Bayesian network is also a kind of probabilistic classifier. The elegant simplicity and apparent accuracy of naive Bayes (NB) even when the independence assumption is violated, fosters the on-going interest in the model. In this paper we have implemented several classification algorithms like Hidden
naive Bayesian , Lazy Instance-based leaner(IB1) , Naive Bayesian, Bayesnet , Naive Bayes Updateable . We have discovered that Naive Bayesian Classifier gives maximum information gain .This paper discusses issues on Naive Bayesian along with its advantages and disadvantages. The objective of this paper is to perform analysis on data set using different Naive Bayesian variants and other classifiers and select the features for Maximizing the Performance.