Feature selection using tabu search with long-term memories and probabilistic neural networks

Pattern Recognition Letters

Volumn 30, Issue 7, 2009, Pages 661-670

  Wang, Yong ^a,b   Li, Lin ^a   Ni, Jun ^a   Huang, Shuhong ^b  

^a UNIVERSITY OF MICHIGAN   (United States)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Curse of dimensionality; Feature selection; Probabilistic neural network; Smoothing parameter; Tabu Search

Indexed keywords

BAYESIAN NETWORKS; DATA STORAGE EQUIPMENT; FEATURE EXTRACTION; LEARNING ALGORITHMS; TABU SEARCH;

BAYESIAN CLASSIFIERS; CLASSIFICATION ACCURACIES; COMPUTATIONAL TIME; CURSE OF DIMENSIONALITY; DIMENSIONALITY REDUCTIONS; FEATURE SELECTION; FEATURE SELECTION PROBLEMS; GLOBAL CONVERGENCES; HYBRID APPROACHES; LOCAL OPTIMAL SOLUTIONS; LONG-TERM MEMORIES; MEASUREMENT COSTS; MEMORY LENGTHS; PROBABILISTIC NEURAL NETWORK; REAL-WORLD DATUM; SHORT-TERM MEMORIES; SMOOTHING PARAMETER; TABU SEARCH ALGORITHMS;

NEURAL NETWORKS;

EID: 63149191148     PISSN: 01678655     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patrec.2009.02.001     Document Type: Article

References (28)

1. Asuncion, A., Newman, D.J., 2007. UCI Machine Learning Repository, University of California, Irvine. ().
2. Billings S.A., Wei H.L., and Balikhin M.A. Generalized multiscale radial basis function networks. Neural Networks 20 10 (2007) 1081-1094
3. Bishop C.M. Neural Networks for Pattern Recognition (1995), Oxford University Press, New York
4. Cover T.M., and Hart P.E. Nearest neighbor pattern classification IEEE trans. Inform. Theory 13 1 (1967) 21-27
5. Cover T.M., and Van Campenhout J.M. On the possible orderings in the measurement selection problem. IEEE Trans. Systems Man Cybernet. 7 9 (1997) 657-661
6. Dréo J., Pétrowski A., Siarry P., and Taill E. Metaheuristics For Hard Optimization (2006), Springer, New York
7. Foroutan I., and Sklansky J. Feature selection for automatic classification of non-Gaussian data. IEEE Trans. Systems Man Cybernet. 17 2 (1987) 187-198
8. Glover F. Future paths for integer programming and links to artificial intelligence. Comput. Oper. Res. 13 5 (1986) 533-549
9. Glover F., and Laguna M. Tabu Search (1997), Kluwer Academic Publishers, Boston
10. Guyon I. An introduction to variable and feature selection. J. Mach. Learn. Res. 3 (2003) 1157-1182
11. Huang, C.J., Liao, W.C., 2003. A comparative study of feature selection methods for probabilistic neural networks in cancer classification. In: Proc. 15th IEEE Internat. Conf. on Tools with Artificial Intelligence, ICTAI.
12. Jain A.K., Duin R.P.W., and Mao J. Statistical pattern recognition: A review. IEEE Trans. Pattern Anal. Mach. Intell. 22 1 (2000) 4-37
13. Kohavi R., and John G. Wrappers for feature selection. Artificial Intell. 97 1-2 (1997) 273-324
14. Kudo M., and Sklansky J. Comparison of algorithms that select features for pattern classifiers. Pattern Recognition Lett. 33 1 (2000) 25-41
15. Mao K.Z., Tan K.C., and Ser W. Probabilistic neural network structure determination for pattern classification. IEEE Trans. Neural Networks 11 4 (2000) 1009-1016
16. Narendra P.M., and Fukunaga K. A branch and bound algorithm for feature subset selection. IEEE Trans. Comput. 26 9 (1977) 917-922
17. Pudil P., Ferri F.J., Novovicova J., and Kittler J. Floating search methods for feature selection with nanmonotonic criterion functions. Pattern Recognition Lett. 2 (1994) 279-283
18. Pudil P., Novovicova J., and Kittler J. Floating search methods in feature selection. Pattern Recognition Lett. 15 11 (1994) 1119-1125
19. Ripley B.D. Pattern Recognition and Neural Networks (1996), Cambridge University Press, Cambridge
20. Siedlecki W., and Sklansky J. A note on genetic algorithm for large-scale feature selection. Pattern Recognition Lett. 10 11 (1989) 335-347
21. Somol P., Pudil P., Novovicova J., and Paclik P. Adaptive floating search methods in feature selection. Pattern Recognition Lett. 20 11-13 (1999) 1157-1163
22. Specht D.F. Probabilistic neural networks. Neural Networks 3 1 (1990) 109-118
23. Specht, D.F., 1992. Enhancements to probabilistic neural networks. In: Internat. Joint Conf. on Neural Networks, IJCNN.
24. Tahir M.A., Bouridane A., Kurugollu F., and Amira A. A novel prostate cancer classification technique using intermediate memory Tabu Search. EURASIP J. Appl. Signal Process. 14 (2005) 2241-2249
25. Tahir M.A., Bouridane A., and Kurugollu F. Simultaneous feature selection and feature weighting using hybrid tabu search/K-nearest neighbor classifier. Pattern Recognition Lett. 28 4 (2007) 438-446
26. Wasserman P.D. Advanced Methods in Neural Computing (1993), Van Nostrand Reinhold, New York
27. Yu B., and Yuan B. A more efficient branch and bound algorithm for feature selection. Pattern Recognition Lett. 26 6 (1993) 883-889
28. Zhang H., and Sun G. Feature selection using tabu search method. Pattern Recognition Lett. 35 3 (2002) 701-711