A Weighted Naive Bayes Algorithm Based on the Attribute Order Reduction

摘要

Naive Bayes classifier was generally considered as a simple and efficient classification method. However, its classification performance was affected to some extent because of the assuming that the conditions properties were independent of each other. By analyzing the classification principle and improvement of Bayesian and the Attribute Reduction of Rough Set, this paper proposed a Naive Bayes algorithm that the attribute order reduction and weighting were improved simultaneously. Experiment results demonstrated that the proposed method performed well in classification accuracy.