Application of native Bayes classifier to text classification
Jing Li · Harbin Gongcheng Daxue Xuebao/Journal of Harbin Engineering University · 2003
The operating principle,training and application of native Bayes classifier were discussed on the basis of the feature independence,and training the classifier,and application of the classifier.The training text is automatically increased using the EM algorithm(expectation maximum) to get more general training text database thereby expanding its application,and getting higher precision.Experimental results show that a native Bayes classifier has a higher precision,and there is no difference in implementation between a single classifier and a multiclassifier,and it is a highly practicable identifier.