%0 Journal Article
%A GUO Zhong-wen
%A LIU Qing
%A LIU Ying-jian
%A QIU Li-ke
%A QIU Zhi-jin
%T Feature Selection Algorithm Based on Redundancy Analysis
%D 2017
%R 10.13190/j.jbupt.2017.01.006
%J Journal of Beijing University of Posts and Telecommunications
%P 36-41
%V 40
%N 1
%X Aiming at the problem of redundant feature identification, this article analyzes the internal relationship between two kinds of correlation (correlation between feature and feature, correlation between feature and target value) and provides criterions for redundant feature determination. Approximate redundant feature is defined and a feature selection method based on redundancy is presented thereafter. The algorithm is divided into two steps to remove irrelevant features and redundant features respectively. Simulatios demonstrate that the proposed feature selection algorithms can effectively reduce feature dimension, and improve the accuracy.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2017.01.006