Feature selection based on maximal neighborhood discernibility-Reference-Cited by-同舟云学术

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Feature selection based on maximal neighborhood discernibility

Published:2017-08-16 Issue:11 Volume:9 Page:1929-1940
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Wang Changzhong,He Qiang,Shao Mingwen,Hu Qinghua

Funder

National Natural Science Foundation of China

Foundation of Educational Committee of Liaoning Province

Natural Science Foundation of Liaoning Province

Program for Liaoning Innovative Research Team in University

Macau Science and Technology Development Fund

Natural Science Foundation of BUCEA

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/article/10.1007/s13042-017-0712-6/fulltext.html

Reference64 articles.

1. Guyon I, Elisseeff A (2003) An introduction to variable and feature selection. J Mach Learn Res 3:1157–1182

2. Kohavi R (1994) Feature subset selection as search with probabilistic estimates. In: Proceeding AAAI fall symposium on relevance, pp 122–126

3. Kwak N, Choi C-H (2002) Input feature selection by mutual information based on Parzen window. IEEE Trans Pattern Anal Mach Intell 24(12):1667–1671

4. Parthalain N, Shen Q, ldquo RJ (2010) A distance measure approach to exploring the rough set boundary region for attribute reduction. IEEE Trans Knowl Data Eng 22(3):305–317

5. Qian Y, Li Y, Liang J, Lin G, Dang C (2015) Fuzzy granular structure distance. IEEE Trans Fuzzy Syst 23(6):2245–2259

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