Classification Algorithm for Naive Bayes Based on Validity and Correlation

被引：0

作者：

Dong, Huailin ^{[1
]}

Zhu, Xiaodan ^{[1
]}

Wu, Qingfeng ^{[1
]}

Huang, Juanjuan ^{[1
]}

机构：

[1] Xiamen Univ, Software Sch, Xiamen, Peoples R China

来源：

SENSORS, MEASUREMENT AND INTELLIGENT MATERIALS, PTS 1-4 | 2013年 / 303-306卷

关键词：

Correlation; Validity; Naive Bayes;

D O I：

10.4028/www.scientific.net/AMM.303-306.1609

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Naive Bayes classification algorithm based on validity (NBCABV) optimizes the training data by eliminating the noise samples of training data with validity to improve the effect of classification, while it ignores the associations of properties. In consideration of the associations of properties, an improved method that is classification algorithm for Naive Bayes based on validity and correlation (CANBBVC) is proposed to delete more noise samples with validity and correlation, thus resulting in better classification performance. Experimental results show this model has higher classification accuracy comparing the one based on validity solely.

引用

页码：1609 / 1612

页数：4

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