Comparison of algorithms that select features for pattern classifiers

Pattern Recognition

Volumn 33, Issue 1, 2000, Pages 25-41

  Kudo, Mineichi ^a   Sklansky, Jack ^b,c  

^a HOKKAIDO UNIVERSITY   (Japan)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c KING DREW MEDICAL CENTER   (United States)

Author keywords

Feature selection; Genetic algorithms; k nearest neighbor method; Leave one out method; Monotonicity

Indexed keywords

GENETIC ALGORITHMS; IMAGE PROCESSING;

NEAREST NEIGHBOR METHOD; PATTERN CLASSIFIERS;

FEATURE EXTRACTION;

EID: 0033640901     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/S0031-3203(99)00041-2     Document Type: Article

References (16)

1. J. Kittler, Feature set search algorithms, in: C.H. Chen (Ed.), Pattern Recognition and Signal Processing, Sijthoff and Noordhoff, Alphen aan den Rijn, Netherlands, 1978, pp. 41-60.
2. F.J. Ferri, P. Pudil, M. Hatef, J. Kittler, Comparative study of techniques for large-scale feature selection, in: E.S. Gelsema, L.N. Kanal (Eds.), Pattern Recognition in Practice IV, Elsevier Science B.V., Amsterdam, 1994, pp. 403-413.
3. P. Pudil, J. Novovičová, J. Kittler, Floating search methods in feature selection, Pattern Recognition Lett. 15 (1994) 1119-1125.
4. P. Pudil, F.J. Ferri, J. Novovičová, J. Kittler, Floating search methods for feature selection with nonmonotonic criterion functions, 12th International Conference on Pattern Recognition, 1994, pp. 279-283.
5. A. Jain, D. Zongker, Feature selection: evaluation, application, and small sample performance, IEEE Trans. Pattern Anal. Mach. Intell. 19 (1997) 153-157.
6. P.M. Narendra, K. Fukunaga, A branch and bound algorithm for feature subset selection, IEEE Trans. Computers 26 (1977) 917-922.
7. B. Yu, B. Yuan, A more efficient branch and bound algorithm for feature selection, Pattern Recognition 26 (6) (1993) 883-889.
8. I. Foroutan, J. Sklansky, Feature selection for automatic classification of non-gaussian data, IEEE Trans. Systems Man Cybernet. 17 (1987) 187-198.
9. M. R. Vriesenga, Genetic selection and neureal modeling for designing pattern classifier, Doctor thesis, University of California, Irvine, 1995.
10. W. Siedlecki, J. Sklansky, A note on genetic algorithms for large-scale feature selection, Pattern Recognition Lett. 10 (1989) 335-347.
11. J. Sklansky, W. Siedlecki, Large-scale feature selection, in: L.F. Pau, P.S. Chen, P.S.P. Wang (Eds.), Handbook of Pattern Recognition and Computer Vision, World Scientific, Singapore, 1993, pp. 61-123 (Chapter 1.3).
12. D. Zongker, A. Jain, Algorithms for feature selection: an evaluation, 13th International Conference on Pattern Recognition 2 (1996) 18-22.
13. M. Kudo, M. Shimbo, Feature selection based on the structural indices of categories, Pattern Recognition 26 (1993) 891-901.
14. H.J. Holz, M.H. Loew, Relative feature importance: A classifier-independent approach to feature selection, in: E.S. Gelsema, L.N. Kanal (Eds.), Pattern Recognition in Practice IV, Elsevier, Amsterdam, 1994, pp. 473-487.
15. M. Kudo, J. Sklansky, Classifier-independent feature selection for two-stage feature selection, in: A. Amin D. Dori, P. Pudil, H. Freeman (Eds.), vol. 1451, Lecture Notes in Computer Science, Springer, Berlin (Advances in Pattern Recognition 1998), pp. 548-554.
16. P.M. Murphy, D.W. Aha, UCI Repository of machine learning databases [machine-readable data repository], University of California, Irivne, Department of Information and Computation Science, 1996.