计算机工程与应用 ›› 2010, Vol. 46 ›› Issue (4): 132-133.DOI: 10.3778/j.issn.1002-8331.2010.04.042

• 数据库、信号与信息处理 • 上一篇    下一篇

基于改进属性加权的朴素贝叶斯分类模型

李 方,刘琼荪   

  1. 重庆大学 数理学院,重庆 400030
  • 收稿日期:2008-08-12 修回日期:2008-11-04 出版日期:2010-02-01 发布日期:2010-02-01
  • 通讯作者: 李 方

Naive Bayesian classifier model based on improved weighted attributes

LI Fang,LIU Qiong-sun   

  1. College of Mathematics and Physics,Chongqing University,Chongqing 400030,China
  • Received:2008-08-12 Revised:2008-11-04 Online:2010-02-01 Published:2010-02-01
  • Contact: LI Fang

摘要: 构造了一种新的属性间相关性度量方法,提出了改进属性加权的朴素贝叶斯分类模型。经实验证明,提出的朴素贝叶斯分类模型明显优于张舜仲等人提出的分类模型。

Abstract: To improve attribute weighted the naive Bayesian classifier model,a new measurement method of the inter-related weighted attributes is structured.The experiment proves that the naive Bayesian classifier model is superior to the classification model proposed by Zhang Shun-zhong et al.

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