NDLI: A Minimum Sphere Covering Approach to Pattern Classification

Content Provider	IEEE Xplore Digital Library
Author	Jigang Wang Neskovic, P. Cooper, L.N.
Copyright Year	2006
Description	Author affiliation: Dept. of Phys., Brown Univ., Providence, RI (Jigang Wang; Neskovic, P.; Cooper, L.N.)
Abstract	In this paper we present a minimum sphere covering approach to pattern classification that seeks to construct a minimum number of spheres to represent the training data and formulate it as an integer programming problem. Using soft threshold functions, we further derive a linear programming problem whose solution gives rise to radial basis function (RBF) classifiers and sigmoid function classifiers. In contrast to traditional RBF and sigmoid function networks, in which the number of units is specified a priori, our method provides a new way to construct RBF and sigmoid function networks that explicitly minimizes the number of base units in the resulting classifiers. Our approach is advantageous compared to SVMs with Gaussian kernels in that it provides a natural construction of kernel matrices and it directly minimizes the number of basis functions. Experiments using real-world datasets demonstrate the competitiveness of our method in terms of classification performance and sparsity of the solution
Sponsorship	IEEE CPS
Starting Page	433
Ending Page	436
File Size	123392
Page Count	4
File Format	PDF
ISBN	0769525210
ISSN	10514651
DOI	10.1109/ICPR.2006.102
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Pattern classification Linear programming Kernel Training data Partitioning algorithms Radial basis function networks Physics Degradation Multilayer perceptrons Data compression
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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