DocumentCode
2453914
Title
An improved combination feature selection based on ReliefF and genetic algorithm
Author
Wang, Xu ; Wang, Beizhan ; Shi, Liang ; Chen, Minkui
Author_Institution
Software Sch., Xiamen Univ., Xiamen, China
fYear
2010
fDate
24-27 Aug. 2010
Firstpage
1340
Lastpage
1343
Abstract
Feature selection is a hot topic in current information science, especially in the field of pattern recognition. In this paper, a combination feature selection Algorithm, ReGA, which merges the feature selection technique, ReliefF, into Genetic Algorithms Method, is presented. Experiments show that the new method improves the fitness of initial population, it can find the optimal solution more quickly, and improve the efficiency of SGA.
Keywords
feature extraction; genetic algorithms; information science; pattern classification; ReliefF; feature selection technique; genetic algorithm; information science; pattern recognition; Algorithm design and analysis; Classification algorithms; Encoding; Genetic algorithms; Genetics; Nearest neighbor searches; Pattern recognition; Feature Selection; Genetic Algorithms; ReGA; ReliefF;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Science and Education (ICCSE), 2010 5th International Conference on
Conference_Location
Hefei
Print_ISBN
978-1-4244-6002-1
Type
conf
DOI
10.1109/ICCSE.2010.5593712
Filename
5593712
Link To Document