On selecting the best features in a noisy environment. (English) Zbl 1274.62433

Summary: This paper introduces a novel method for selecting a feature subset yielding an optimal trade-off between class separability and feature space dimensionality. We assume the following feature properties: (a) the features are ordered into a sequence, (b) robustness of the features decreases with an increasing order and (c) higher-order features supply more detailed information about the objects. We present a general algorithm how to find under these assumptions the optimal feature subset. Its performance is demonstrated experimentally in the space of moment-based descriptors of 1-D signals, which are invariant to linear filtering.


62H99 Multivariate analysis
62M20 Inference from stochastic processes and prediction
62H30 Classification and discrimination; cluster analysis (statistical aspects)
65C60 Computational problems in statistics (MSC2010)
Full Text: Link


[1] Fukunaga K.: Introduction to Statistical Pattern Recognition. Academic Press, New York 1972 · Zbl 0711.62052
[2] Devijver P. A., Kittler J.: Pattern Recognition: A Statistical Approach. Prentice Hall, London 1982 · Zbl 0542.68071
[3] Abu-Mostafa Y. S., Psaltis D.: Recognitive aspects of moment invariants. IEEE Trans. Pattern Anal. Mach. Intell. 6 (1984), 698-706 · doi:10.1109/TPAMI.1984.4767594
[4] Teh C. H., Chin R. T.: On image analysis by the methods of moments. IEEE Trans. Pattern Anal. Mach. Intell. 10 (1988), 496-512 · Zbl 0709.94543 · doi:10.1109/34.3913
[5] Pawlak M.: On the reconstruction aspects of moment descriptors. IEEE Trans. Inform. Theory 38 (1992), 1698-1708 · Zbl 0761.68104 · doi:10.1109/18.165444
[6] Liao S. X., Pawlak M.: On image analysis by moments. IEEE Trans. Pattern Anal. Mach. Intell. 18 (1996), 254-266 · doi:10.1109/34.485554
[7] Flusser J., Suk T.: Invariants for recognition of degraded 1-D digital signals. Proc. 13th ICPR, Vienna 1996, vol. II, pp. 389-393
[8] Flusser J., Suk T.: Classification of degraded signals by the method of invariants. Signal Processing 60 (1997), 243-249 · Zbl 1006.94512 · doi:10.1016/S0165-1684(97)00075-3
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.