计算机工程与应用Issue(9)：116-122,7.DOI:10.3778/j.issn.1002-8331.1311-0469
改进的最大相关最小冗余特征选择方法研究
Study on feature selection method of modified maximal relevance mini-mal redundancy
摘要
Abstract
Feature selection as an important preliminary work has been concerned in various fields. Through analyzing the existing feature selection methods, the problem is improved that the single redundancy and relevance evaluation method and feature dimension cannot be set according to user requirements. A novel simple and fast computing method is presented in the redundant calculation process;the weight is calculated according to the data different choice of different evaluation methods;the novel evaluation function is used in feature selection. With five different databases(FERET、CASIA、ORL、CMU PIE and Extended YaleB), the effectiveness and feasibility of the algorithm are proved. The experimental results demonstrate the advantage of the MMRMR.关键词
特征选择/最大相关最小冗余(MRMR)/生物认证/评价函数/经典数据库Key words
feature selection/Minimal Redundancy Maximal Relevance(MRMR)/biometric identification/evaluation function/regular databases分类
信息技术与安全科学引用本文复制引用
姚明海,王娜,齐妙,李妍..改进的最大相关最小冗余特征选择方法研究[J].计算机工程与应用,2014,(9):116-122,7.基金项目
辽宁省社会科学规划基金项目（No.L13BXW006）；吉林省科技发展计划项目青年科研基金（No.201201070）。 （）
