计算机工程与应用Issue(2)：170-174,185,6.DOI:10.3778/j.issn.1002-8331.1401-0302
一种启发式的局部随机特征选择算法
A kind of heuristic local random feature selection algorithm
摘要
Abstract
Two kinds of feature selection algorithms are further studied, i.e., the characteristic of large margin is the simi-larity between samples and the entropy is the correlation between features, an effective feature selection algorithm via fus-ing large margin and information entropy is proposed. The features are ranked by employing the algorithm of Relief, and the ranked feature list is partitioned into a few sections. Based on the heuristic factor of symmetric uncertainty, the feature subset in each local random subspace is obtained by setting the sampling rate of each section. The final feature subset is obtained by merging all feature subsets. Experimental results show that the proposed algorithm is superior to several fea-ture selection algorithms.关键词
特征选择/大间隔/对称不确定性/局部随机子空间Key words
feature selection/large margin/symmetric uncertainty/local random subspace分类
信息技术与安全科学引用本文复制引用
刘景华,林梦雷,张佳,林耀进..一种启发式的局部随机特征选择算法[J].计算机工程与应用,2016,(2):170-174,185,6.基金项目
国家自然科学基金（No.61303131，No.61379021）；福建省自然科学基金（No.2013J01028）；漳州市科技项目（No.ZZ2013J04）。 （）
