On feature selection with measurement cost and grouped features

Conference paper (2002)

Authors

P. Paclik ImPhys/Quantitative Imaging
R.P.W. Duin ImPhys/Quantitative Imaging
GMP van Kempen ImPhys/Quantitative Imaging
R Kohlus External organisation
Research Group
ImPhys/Quantitative Imaging
More Info
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Published Date

2002

Language

Undefined/Unknown

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Research Group

ImPhys/Quantitative Imaging

Abstract

Feature selection is an important tool reducing necessary feature acquisition time in some applications. Standard methods, proposed in the literature, do not cope with the measurement cost issue. Including the measurement cost into the feature selection process is difficult when features are grouped together due to the implementation. If one feature from a group is requested, all others are available for zero additional measurement cost. In the paper, we investigate two approaches how to use the measurement cost and feature grouping in the selection process. We show, that employing grouping improves the performance significantly for low measurement costs. We discuss an application where limiting the computation time is a very important topic: the segmentation of backscatter images in product analysis.