现代电子技术Issue(12)：1-4,4.
基于改进SFS特征选择BP识别算法
BP network recognition algorithm based on improved SFS feature selection
摘要
Abstract
Feature selection plays an important role in the BP neural network algorithm. Sequence forward selection(SFS) algorithm can realize the compression of sample feature dimension by using a way of forward search superimposition to get the most efficient main feature of classification recognition algorithm from numerous original features. An improved SFS feature selec⁃tion algorithm is proposed in this paper. Weighted discriminant function was designed and feedback stopping criterion was tested. The experimental results show that the improved algorithm can effectively compress the sample feature dimension,as well as im⁃prove BP network astringency and correct recognition rate.关键词
特征选择/SFS/BP网络/收敛速度Key words
feature selection/SFS/BP/astringency分类
信息技术与安全科学引用本文复制引用
朱旭东,梁光明,冯雁..基于改进SFS特征选择BP识别算法[J].现代电子技术,2015,(12):1-4,4.基金项目
湖南省创新基金支持项目 （）
