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《Computer Engineering and Applications》 2004-15
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Research on Feature Selection Using Genetic Algorithms

Zhao Yun Liu Weiyi (Department of Computer Science,Yunnan University,Kunming650091)  
Selecting a set of features which is optimal for a given task is a problem which plays an important role in a wide variety of contents including pattern recognition,knowledge discovery,and machine learning.These problems require selection of a subset of attributes or features(from a much larger set)to represent the patterns to be classified.This paper presents an approach to the combination optimization and multi-criteria optimization problem of feature selection using genetic algorithms.The approach described here involves the use of genetic algorithms as a″front end″to a classification or recognition system in order to find the best subset of features and reduce the number of features used to represent the problem spaces.
【Fund】: 国家自然科学基金(编号:60263006);; 云南省自然科学基金(编号:2002F0063M);; 科学院智能信息处理开放实验室基金(编号:IIP2002—2)
【CateGory Index】: TP18
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