安庆师范学院学报（自然科学版）Issue(1)：36-40,5.
基于粗糙集理论的贝叶斯网络分类算法
The Method of Bayesian Network Based on the Rough Set Theory
李翔 1程玉胜 1丁美文1
作者信息
- 1. 安庆师范学院 数学与计算科学学院，安徽 安庆 246133
- 折叠
摘要
Abstract
With the problem of vast data information in the life , people usually simplify the data for eliminating the redundant part by the rough set.But most studies did not consider the effect of reduction on the original classification .The naive Bayesian method is hard to obtain the prior probability .Based on the above problems, a method of Bayesian network based on the rough set is proposed in this paper.Firstly, we reduce the attribution for eliminating the redundant data by the dependencies between deci-sion attribution and conditional attribution in rough set .Then, we mine knowledge from the simplified data by the method of naive Bayesian network.Finally, we compare the data with the original system's one and find that the method improves the accuracy well.It solves the problems of the traditional naïve Bayesian hard to obtain the prior probability and require the conditional inde-pendences between each characteristic property, and improves the ability of data mining evidently.关键词
粗糙集/数据挖掘/故障源Key words
rough set/data mining/fault source引用本文复制引用
李翔,程玉胜,丁美文..基于粗糙集理论的贝叶斯网络分类算法[J].安庆师范学院学报（自然科学版）,2014,(1):36-40,5.
