计算机工程与应用Issue(16)：135-139,5.DOI:10.3778/j.issn.1002-8331.1209-0299
基于互信息的分类属性数据特征选择算法
Mutual information-based feature selection algorithm for nominal data
顾文强 1李志华2
作者信息
- 1. 江南大学 物联网工程学院 轻工过程先进控制教育部重点实验室，江苏 无锡 214122
- 2. 物联网应用技术教育部工程研究中心，江苏 无锡 214122
- 折叠
摘要
Abstract
In this paper, a novel feature selection approach based on mutual information called More Relevance Less Redun-dancy(MRLR)algorithm for nominal data is proposed. By reconstructing the computation method of the amount of infor-mation, the conditional mutual information, the dependence between the features so that which can be suitable for compu-tation related the nominal data, and a new definition of the evaluation function of feature selection is given, as well as a new feature selection criterion is used to evaluate the importance of each feature, which takes into account both relevance and redundancy. In MRLR, experimental results show that the relevance and redundancy respectively use mutual informa-tion to measure the dependence of features on the latent class and the dependence between features, and it also enhance the correctness and the effectiveness of MRLR algorithm.关键词
分类属性数据/特征选择/互信息Key words
nominal data/feature selection/mutual information分类
信息技术与安全科学引用本文复制引用
顾文强,李志华..基于互信息的分类属性数据特征选择算法[J].计算机工程与应用,2014,(16):135-139,5.
