| 一种属性相关性的加权贝叶斯分类算法研究 |
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| 引用本文： | 郑默,刘琼荪.一种属性相关性的加权贝叶斯分类算法研究[J].微型机与应用,2011,30(7):96-98. |
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| 作者姓名： | 郑默 刘琼荪 |
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| 作者单位： | 重庆大学数理学院,重庆,400030 |
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| 摘 要： | 根据RoughSet属性重要度理论,构建了基于互信息的属性子集重要度,提出属性相关性的加权朴素贝叶斯分类算法,该算法同时放宽了朴素贝叶斯算法属性独立性、属性重要性相同的假设。通过在UCI部分数据集上进行仿真实验,与基于属性相关性分析的贝叶斯(CB)和加权朴素贝叶斯(WNB)两种算法做比较,证明了该算法的有效性。
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| 关 键 词： | 朴素贝叶斯 属性重要度 属性相关 分类 |
Weighted naive Bayesian classification based on attribute correlation |
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| Zheng Mo,Liu Qiongsun.Weighted naive Bayesian classification based on attribute correlation[J].Microcomputer & its Applications,2011,30(7):96-98. |
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| Authors: | Zheng Mo Liu Qiongsun |
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| Affiliation: | Zheng Mo,Liu Qiongsun (College of Mathematics and Physics,Chongqing University,Chongqing 400030,China) |
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| Abstract: | Based on the theory of rough set, a new naive Bayes method named mutual information-based algorithm for weighted naive Bayes (WCB) was proposed, which synchronously loosen naive Bayes classifier’s independence and equal importance of the attribute assumptions. compared with correlated Bayes(CB) and weighted naive Bayes(WNB), simulation results on a variety of UCI data sets illustrate the efficiency of this method. |
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| Keywords: | naive Bayes weightiness of attribute attribute correlation classification |
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