Feature selection using forest optimization algorithm based on contribution degree

作     者：Ma, Tinghuai Jia, Dongdong Zhou, Honghao Xue, Yu Cao, Jie 

作者机构：Nanjing Univ Informat Sci & Technol CICAEET Jiangsu Engn Ctr Network Monitoring Nanjing 210044 Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Sch Comp & Software Nanjing 210044 Jiangsu Peoples R China Nanjing Univ Informat Sci & Technol Sch Econ & Management Nanjing 210044 Jiangsu Peoples R China 

出 版 物：《INTELLIGENT DATA ANALYSIS》 (智能数据分析)

年 卷 期：2018年第22卷第6期

页      面：1189-1207页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Science Foundation of China National Social Science Foundation of China [16ZDA054] Special Public Sector Research Program of China [GYHY201506080] PAPD 

主　　题：Feature selection forest optimization algorithm contribution degree 

摘      要：As a combinatorial optimization problem, feature selection has been widely used in machine learning and data mining In this paper, a feature selection method using forest optimization algorithm based on contribution degree is proposed. The proposed method uses a contribution degree strategy which is embedded in forest optimization algorithm. The goal of the contribution degree is to guide the search process of the forest optimization algorithm to select features according to high class correlation and low redundancy between features. The proposed algorithm is verified on some data sets from the UCI repository and the experiments show that the proposed method improves the classification accuracy compared with some other methods.