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| 基于关联规则的贝叶斯网络分类器 | |
| 引用本文： | 张子义,王德亮. 基于关联规则的贝叶斯网络分类器[J]. 计算机应用, 2009, 29(Z1) |
| 作者姓名： | 张子义 王德亮 |
| 作者单位： | 1. 青岛大学,软件技术学院,山东,青岛,266061 2. 山东理工大学,计算机科学与技术学院,山东,淄博,255049 |
| 摘 要： | 关联规则分类器(CBA)利用关联规则来构造分类算法,但其没有考虑分类问题中的不确定性.提出一种基于关联规则的贝叶斯网络分类算法.该算法利用关联规则挖掘算法提取初始的候选网络边集,通过贪心算法学习网络结构,得到比经典的贝叶斯网络分类器TAN更好的拓扑结构.通过在15个UCI数据集上的实验结果表明,该算法取得了比TAN,CBA更好的分类性能. |
| 关 键 词： | 关联规则分类器 贝叶斯网络分类器 结构学习 |
Bayesian network classifier with association rules |
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| ZHANG Zi-yi,WANG De-liang. Bayesian network classifier with association rules[J]. Journal of Computer Applications, 2009, 29(Z1) | |
| Authors: | ZHANG Zi-yi WANG De-liang |
| Affiliation: | 1.Software Technical College;Qingdao University;Qingdao Shandong 266061;China;2.College of Computer Science and Technology;Shandong University of Technology;Zibo Shandong 255049;China |
| Abstract: | Classification Based on Association(CBA) algorithm built a classifier based on the association rules,without considering the uncertainty in the classification problem.This paper proposed a Bayesian network classifier based on the association rules.The improved algorithm initialized the graph structure with candidate edges,which was extracted by Apriori algorithm,and obtained a better network structure than Tree-Augmented Network(TAN) classifier with the greedy search.The empirical study on 15 UCI datasets s... |
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| 本文献已被 CNKI 万方数据 等数据库收录！ | |