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Title: A simple upper bound to the Bayes error probability for feature selection (English)
Author: Bruzzone, Lorenzo
Author: Serpico, Sebastiano B.
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 34
Issue: 4
Year: 1998
Pages: [387]-392
Summary lang: English
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Category: math
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Summary: In this paper, feature selection in multiclass cases for classification of remote-sensing images is addressed. A criterion based on a simple upper bound to the error probability of the Bayes classifier for the minimum error is proposed. This criterion has the advantage of selecting features having a link with the error probability with a low computational load. Experiments have been carried out in order to compare the performances provided by the proposed criterion with the ones of some of the widely used feature-selection criteria presented in the remote-sensing literature. These experiments confirm the effectiveness of the proposed criterion, which performs slightly better than all the others considered in the paper. (English)
Keyword: Bayes error probability
Keyword: feature selection
MSC: 62H30
MSC: 68G10
MSC: 68T10
idZBL: Zbl 1274.68377
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Date available: 2009-09-24T19:17:37Z
Last updated: 2015-03-28
Stable URL: http://hdl.handle.net/10338.dmlcz/135220
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Reference: [1] Bruzzone L., Roli F., Serpico S. B.: An extension of the Jeffreys–Matusita distance to multiclass cases for feature selection.IEEE Trans. Geoscience Remote Sensing 33 (1995), 6, 1318–1321 10.1109/36.477187
Reference: [2] Bruzzone L., Serpico S. B.: Feature selection in multiclass cases: a proposal and an experimental investigation.In: Proceedings of the 1st Workshop on Statistical Techniques in Pattern Recognition, Prague 1997, pp. 19–24
Reference: [3] Fukunaga K.: Introduction to Statistical Pattern Recognition.Second edition. Academic, New York 1990 Zbl 0711.62052, MR 1075415
Reference: [4] Liu S. S., Jernigan M. E.: Texture analysis and discrimination in additive noise.Computer Vision Image Processing 49 (1990), 52–67 10.1016/0734-189X(90)90162-O
Reference: [5] Swain P. H., Davis S. M.: Remote Sensing: The Quantitative Approach.McGraw–Hill, New York 1994
Reference: [6] Tou J. T., Gonzalez R. C.: Pattern Recognition Principles.Addison–Wesley, London 1974 Zbl 0299.68058, MR 0449069
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