A Naive Bayesian Classification Model Based on the Probabilistic Weights
Tao Zhu · Journal of Nanchang University · 2009
Nave Bayes Classifier is a simple and effective classification method,but its attribute independence assumption makes it unable to express the dependence among attributes in the real world,and affects its classification performance.In this paper a method for setting attribute weights based on probabilistic inference for using with Nave Bayes is presented.It improve the classification performance of Nave Bayes through set attributes different weights by their related-probability and unrelated-probability with classes.Experimental results illustrate the efficiency of this method.