Fast and accurate feature selection using hybrid genetic strategies
作者： C. Guerra-Salcedo , S. Chen , D. Whitley , S. Smith
关键词:
摘要: When dealing with object classification, each is defined by a set of features (characteristics) that classify the to particular class. The problem how choose best subset characteristics provide an accurate classification. Previous research has shown decision tables are as C4.5 for classification purposes. Two different genetic search techniques, CHC and CF/RSC, applied this problem. Results shows CF/RSC very good combination when large feature spaces. also suggest better used problems noise added features.
sci-hub.se 参考文章(22)
Lawrence Davis, Bit-Climbing, Representational Bias, and Test Suite Design. ICGA. pp. 18- 23 ,(1991)
L. Darrell Whitley, Soraya B. Rana, Bit Representations with a Twist. ICGA. pp. 188- 195 ,(1997)
William F. Punch, Richard J. Enbody, Paul D. Hovland, Min Pei, Erik D. Goodman, Lai Chia-Shun, Further Research on Feature Selection and Classification Using Genetic Algorithms international conference on genetic algorithms. pp. 557- 564 ,(1993)
John H. Holland, Adaptation in natural and artificial systems ,(1992)
Steven L. Salzberg, Alberto Segre, Programs for Machine Learning ,(1994)
Soraya Rana, L. Darrell Whitley, Ronald Cogswell, Searching in the Presence of Noise parallel problem solving from nature. pp. 198- 207 ,(1996) , 10.1007/3-540-61723-X_984
Larry J. Eshelman, The CHC Adaptive Search Algorithm: How to Have Safe Search When Engaging in Nontraditional Genetic Recombination Foundations of Genetic Algorithms. ,vol. 1, pp. 265- 283 ,(1991) , 10.1016/B978-0-08-050684-5.50020-3
David W. Aha, Richard L. Bankert, A Comparative Evaluation of Sequential Feature Selection Algorithms Learning from Data. pp. 199- 206 ,(1996) , 10.1007/978-1-4612-2404-4_19
Ron Kohavi, Wrappers for Performance Enhancements and Oblivious Decision Graphs. Stanford University. ,(1995)
Richard A. Caruana, J. David Schaffer, Rajarshi Das, Larry J. Eshelman, A study of control parameters affecting online performance of genetic algorithms for function optimization international conference on genetic algorithms. pp. 51- 60 ,(1989)