A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers

Mineichi Kudo; Jack Sklansky

Kybernetika (1998)

  • Volume: 34, Issue: 4, page [429]-434
  • ISSN: 0023-5954

Abstract

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Needs of feature selection in medium and large problems increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not satisfactory in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large variety of algorithms. Our results show that the sequential floating algorithms promises for up to medium problems and genetic algorithms for medium and large problems.

How to cite

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Kudo, Mineichi, and Sklansky, Jack. "A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers." Kybernetika 34.4 (1998): [429]-434. <http://eudml.org/doc/33373>.

@article{Kudo1998,
abstract = {Needs of feature selection in medium and large problems increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not satisfactory in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large variety of algorithms. Our results show that the sequential floating algorithms promises for up to medium problems and genetic algorithms for medium and large problems.},
author = {Kudo, Mineichi, Sklansky, Jack},
journal = {Kybernetika},
keywords = {feature selection; pattern classifiers; feature selection; pattern classifiers},
language = {eng},
number = {4},
pages = {[429]-434},
publisher = {Institute of Information Theory and Automation AS CR},
title = {A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers},
url = {http://eudml.org/doc/33373},
volume = {34},
year = {1998},
}

TY - JOUR
AU - Kudo, Mineichi
AU - Sklansky, Jack
TI - A comparative evaluation of medium- and large-scale feature selectors for pattern classifiers
JO - Kybernetika
PY - 1998
PB - Institute of Information Theory and Automation AS CR
VL - 34
IS - 4
SP - [429]
EP - 434
AB - Needs of feature selection in medium and large problems increases in many fields including medical and image processing fields. Previous comparative studies of feature selection algorithms are not satisfactory in problem size and in criterion function. In addition, no way has not shown to compare algorithms with different objectives. In this study, we propose a unified way to compare a large variety of algorithms. Our results show that the sequential floating algorithms promises for up to medium problems and genetic algorithms for medium and large problems.
LA - eng
KW - feature selection; pattern classifiers; feature selection; pattern classifiers
UR - http://eudml.org/doc/33373
ER -

References

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  1. Ferri F. J., Pudil P., Hatef M., Kittler J., 1994, Comparative study of techniques for large–scale feature selection. In: Pattern Recognition in Practice IV (E. S. Gelsema and L. N. Kanal, eds.), Elsevier Science B. V. 1994, pp. 403–413 (1994) 
  2. Foroutan I., Sklansky J., 10.1109/TSMC.1987.4309029, IEEE. Trans. Systems Man Cybernet. 17 (1987), 187–198 (1987) DOI10.1109/TSMC.1987.4309029
  3. Kittler J., 1978, Feature set search algorithms. In: Pattern Recognition and Signal Processing (C. H. Chen, ed.), Sijthoff and Noordhoff, Alphen aan den Rijn 1978, pp. 41–60 (1978) 
  4. Murphy P. M., Aha D. W., UCI Repository of machine learning databases [Machine–readable dta repository], Department of Information and Computation Science University of California, Irivne 1996 
  5. Pudil P., Novovičová J., Kittler J., 10.1016/0167-8655(94)90127-9, Pattern Recognition Lett. 15 (1994), 1119–1125 (1994) DOI10.1016/0167-8655(94)90127-9
  6. Siedlecki W., Sklansky J., 10.1016/0167-8655(89)90037-8, Pattern Recognition Lett. 10 (1989), 335–347 (1989) Zbl0942.68690DOI10.1016/0167-8655(89)90037-8
  7. Sklansky J., Siedlecki W., Large–scale feature selection, In: Handbook of Pattern Recognition and Computer Vision (L. F. Pau, C. H. Chen and P. S. P. Wang, eds.), Chapter 1.3, World Scientific 1993, pp. 61–123 (1993) 
  8. Vriesenga M. R., Genetic Selection and Neureal Modeling for Designing Pattern Classifier, Doctor Thesis, University of California, Irvine 1995 
  9. Yu B., Yuan B., 10.1016/0031-3203(93)90054-Z, Pattern Recognition 26 (1993), 6, 883–889 (1993) DOI10.1016/0031-3203(93)90054-Z
  10. Zongker D., Jain A., Algorithms for feature selection: An evaluation, In: 13th International Conference on Pattern Recognition 1996, pp. 18–22 (1996) 

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