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
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;
Conference_Titel :
Computer Science and Education (ICCSE), 2010 5th International Conference on
Conference_Location :
Hefei
Print_ISBN :
978-1-4244-6002-1
DOI :
10.1109/ICCSE.2010.5593712
