A filter-dominating hybrid sequential forward floating search method for feature subset selection in high-dimensional space-Reference-Cited by-同舟云学术

A filter-dominating hybrid sequential forward floating search method for feature subset selection in high-dimensional space

Published:2012-12-13 Issue:3 Volume:5 Page:413-423
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Gan John Q.,Awwad Shiekh Hasan Bashar,Tsui Chun Sing Louis

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

http://link.springer.com/content/pdf/10.1007/s13042-012-0139-z.pdf

Reference21 articles.

1. Liu H, Yu L (2005) Toward integrating feature selection algorithms for classification and clustering. IEEE Trans Knowl Data Eng 17(4):491–502

2. Gan JQ (2006) Feature dimensionality reduction by manifold learning in brain-computer interface design. In: 3rd international workshop on brain-computer interfaces. Graz, Austria, pp 28–29

3. Gheyas IA, Smith LS (2010) Feature subset selection in large dimensionality domains. Pattern Recogn 43(1):5–13

4. Awwad Shiekh Hasan B, Gan JQ, Zhang Q (2010) Multi-objective evolutionary methods for channel selection in brain-computer interfaces: some preliminary experimental results. In: IEEE congress on evolutionary computation. Barcelona, Spain, pp 3339–3344

5. Tong DL, Mintram R (2010) Genetic algorithm-neural network (GANN): a study of neural network activation functions and depth of genetic algorithm search applied to feature selection. Int J Mach Learn Cybern 1(1–4):75–87

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