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Title: On selecting the best features in a noisy environment (English)
Author: Flusser, Jan
Author: Suk, Tomáš
Language: English
Journal: Kybernetika
ISSN: 0023-5954
Volume: 34
Issue: 4
Year: 1998
Pages: [411]-416
Summary lang: English
Category: math
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 those 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. (English)
Keyword: Mahalanobis distance
Keyword: 1-D signals
MSC: 62H30
MSC: 62H99
MSC: 62M20
MSC: 65C60
MSC: 68T10
idZBL: Zbl 1274.62433
Date available: 2009-09-24T19:18:09Z
Last updated: 2015-03-28
Stable URL:
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