Genetic algorithm with fuzzy operators for feature subset selection

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences

Volumn E85-A, Issue 9, 2002, Pages 2089-2092

  Chakraborty, Basabi ^a  

^a IWATE PREFECTURAL UNIVERSITY   (Japan)

Author keywords

Feature subset selection; Fuzzy fitness function; Fuzzy measure; Genetic algorithm

Indexed keywords

COMPUTER SIMULATION; DATA MINING; DATA STRUCTURES; FUZZY SETS; LEARNING SYSTEMS; PATTERN RECOGNITION;

FEATURE SUBSET SELECTION; FUZZY OPERATORS;

GENETIC ALGORITHMS;

EID: 0036739083     PISSN: 09168508     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Conference Paper

References (16)

1. P.A. Devijver and J. Kittler, Pattern Recognition: A Statistical Approach, Prentice-Hall International, 1982.
2. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
3. J.H. Holland, Adaptation in Natural and Artificial Systems, University of Michigan Press, Ann Arbor, 1975.
4. W. Siedlecki and J. Sklansky, "A note on genetic algorithms for large scale feature selection," Pattern Recognition Letter, vol. 10, pp.335-347, 1989.
5. J. Yang and V. Honavar, Feature Subset Selection using a Genetic Algorithm, Feature Extraction, Construction and Selection: A data Mining Perspective, pp.117-136, Kluwer Academic Publishers, 1998.
6. H. Vafaie and K. de Jong, "Genetic algorithms as a tool for feature selection in machine learning," Proc. 4th International Conference on Tools with Artificial Intelligence, Nov. 1992.
7. H. Vafaie and K. de Jong, "Genetic algorithms as a tool for restructuring feature space representation," Proc. 7th International Conference on Tools with Artificial Intelligence, 1995.
8. J.D. Kelly and L. Davis, "Hybridizing the genetic algorithm and the k-nearest neighbours classification algorithm," Proc. 4th International Conference on genetic Algorithms and their Applications, pp.377-383, 1991.
9. F.Z. Brill, D. E. Brown, and W.N. Martin, "Fast genetic selection of features for neural network classifiers," IEEE Trans. NN, vol.3, no.2, pp.324-328, March 1992.
10. M.J. Martin-Bausita and M.A. Vila, "Applying genetic algorithms to the feature selection problem in information retrieval," Lecture Notes on Artificial Intelligence, Springer-Verlag, 1998.
11. S.K. Pal and B. Chakraborty, "Fuzzy set theoretic measure for automatic feature selection," IEEE Trans. Syst., Man. & Cybern., vol.SMC-16, no.5, pp. 754-760, Sept./Oct. 1986.
12. A. Deluca and S. Termini, "A definition of a nonprobabilistic entropy in the setting of a fuzzy sets theory," Inf. Control, vol.20, pp.301-312, 1972.
13. S.K. Pal and P.K. Pramanik, "Fuzzy measures in determining seed points in clustering," Pattern Recognition Letter, vol.4, pp.159-164, 1986.
14. B. Chakraborty, On Some Fuzzy Set Theoretic Measures and Knowledge Based Approach for Feature Selection in A Pattern Recognition System, Ph.D. dessertation, 1994.
15. R.P. Gorman and T.J. Sejnowski, "Analysis of hidden units in a layered network trained to classify sonar targets," Neural Networks, vol.1, pp.75-89, 1988.
16. B. Chakraborty and G. Chakraborty, "A neuro fuzzy algorithm for feature subset selection," IEICE Trans. Fundamentals, vol.E84-A, no.9, pp.2182-2188, Sept. 2001.