Naive Bayesian Classifier Based on Multiple Discriminant Analysis

On the basis of analyzing the classification principle of naive Bayesian classifier and integrating the advantages of multiple discriminant analysis,a naive Bayesian classifier based on multiple discriminant analysis,DANB(Discriminant Analysis Naive Bayes),is proposed.The DANB classifier is compared with Naive Bayes(NB) classifier and TAN(Tree Augmented Naive Bayes) classifier by an experiment.Experiment results show that this model has higher classification accuracy in most datasets.