Bayes classification model based on ICA
Hui Luo · Jisuanji gongcheng yu sheji · 2007
Naive 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.The method of independent component is applied to naive Bayes classifier,which improve the cluster capacity by projecting the sample to the character space defined by independent component analysis.The experiment shows that the classifier based on independent component analysis model has good capacity.