计算机工程与应用2016，Vol.52Issue(18)：84-87,4.DOI:10.3778/j.issn.1002-8331.1412-0318
互信息匹配的半朴素贝叶斯分类器
Semi-naive Bayesian classifier matched by mutual information
摘要
Abstract
Because the class-conditional independence assumption which is the mainly feature of Naive Bayesian classifier is a so strong assumption and difference appears between datasets, the class-conditional independence assumption becomes the entry point of improvement methods. But some researches indicate that the violations of independence assumption do not make so much influence to the classifier as expected. This paper proposes a conditional entropy matching half-naive Bayesian classifier for the purpose of lower posterior probability estimation error. Experiments show that this method can effectively improve the performance of naive Bayesian classifier.关键词
半朴素贝叶斯分类器/互信息/匹配Key words
semi-naive Bayesian classifier/mutual information/matching分类
信息技术与安全科学引用本文复制引用
赵亮,刘建辉,崔彩峰..互信息匹配的半朴素贝叶斯分类器[J].计算机工程与应用,2016,52(18):84-87,4.基金项目
国家自然科学基金（No.F020512）。 （）
