文献类型：期刊文献

英文题名：A two-stage feature selection method with its application

作者：Zhao, Xuehua[1];Li, Daoliang[2];Yang, Bo[3];Chen, Huiling[4];Yang, Xinbin[1];Yu, Chenglong[1];Liu, Shuangyin[5]

机构：[1]Shenzhen Inst Informat Technol, Sch Digital Media, Shenzhen 518172, Peoples R China;[2]China Agr Univ, Coll Informat & Elect Engn, Beijing 100083, Peoples R China;[3]Jilin Univ, Coll Comp Sci & Technol, Changchun 130012, Peoples R China;[4]Wenzhou Univ, Coll Phys & Elect Informat, Wenzhou 325035, Peoples R China;[5]Guangdong Ocean Univ, Coll Informat, Zhanjiang 524025, Peoples R China

年份：2015

卷号：47

起止页码：114

外文期刊名：COMPUTERS & ELECTRICAL ENGINEERING

收录：SCI-EXPANDED(收录号：WOS:000367637200008)、、EI(收录号：20160501860125)、Scopus(收录号：2-s2.0-84955269715)、WOS

基金：This research is supported by the National Natural Science Foundation of China (NSFC) (61303113, 61373053, 61402195, 61471133, 61571444 and 61572226). This research is also funded by the Special Fund for Agro-scientific Research in the Public Interest (201203017), National Science and Technology Supporting Plan Project (2012BAD35B07), National Natural Science Foundation Framework Project (61471133), Guangdong Science and Technology Plan Project (20138090500127 and 2013B021600014), Guangdong Natural Science Foundation (S2013010014790), and Science and Technology Plan Project of Wenzhou of China under Grant No (G20140048).

语种：英文

外文关键词：Foreign fibers; Feature selection; Information gain; Binary particle swarm optimization

外文摘要：Foreign fibers in cotton seriously affect the quality of cotton products. Online detection systems of foreign fibers based on machine vision are the efficient tools to minimize the harmful effects of foreign fibers. The optimum feature set with small size and high accuracy can efficiently improve the performance of online detection systems. To find the optimal feature sets, a two-stage feature selection algorithm combining IG (Information Gain) approach and BPSO (Binary Particle Swarm Optimization) is proposed for foreign fiber data. In the first stage, IG approach is used to filter noisy features, and the BPSO uses the classifier accuracy as a fitness function to select the highly discriminating features in the second stage. The proposed algorithm is tested on foreign fiber dataset The experimental results show that the proposed algorithm can efficiently find the feature subsets with smaller size and higher accuracy than other algorithms. (C) 2015 Elsevier Ltd. All rights reserved.