计算机工程与应用 ›› 2008, Vol. 44 ›› Issue (34): 139-141.DOI: 10.3778/j.issn.1002-8331.2008.34.043

• 数据库、信号与信息处理 • 上一篇    下一篇

朴素贝叶斯分类器的独立性假设研究

范金金1,刘 鹏2   

  1. 1.上海财经大学 信息管理与工程学院,上海 200433
    2.上海财经大学 人事处,上海 200433
  • 收稿日期:2008-05-07 修回日期:2008-08-11 出版日期:2008-12-01 发布日期:2008-12-01
  • 通讯作者: 范金金

Research on Naïve Bayesian Classifier’s independence assumption

FAN Jin-jin1,LIU Peng2   

  1. 1.School of Information Management and Engineering,Shanghai University of Finance and Economics,Shanghai 200433,China
    2.Department of Human Resources,Shanghai University of Finance and Economics,Shanghai 200433,China
  • Received:2008-05-07 Revised:2008-08-11 Online:2008-12-01 Published:2008-12-01
  • Contact: FAN Jin-jin

摘要: 朴素贝叶斯分类器(NBC)是一种简洁而有效的分类模型。介绍了NBC模型的基本原理,并着重分析了该模型的独立性假设条件。在总结现有独立性假设研究的基础上,通过例子和实验分析得出结论:NBC模型的表现和独立性假设是否满足没有必然联系。

关键词: 数据挖掘, 朴素贝叶斯分类器, 独立性假设

Abstract: Naïve Bayesian Classifier(NBC) is a simple and effective classification model.In this paper,after the introduction of the basic principle of the NBC model,the independence assumption of the model is analyzed.Based on the summary of the current research of the independence assumption,It is concluded that the satisfaction of the independence assumption is not a necessary condition for the NBC model’s efficiency,through the demonstration from an example and some experimental analysis.

Key words: data mining, Naï, ve Bayesian Classifier(NBC) model, independence assumption