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A Simple Iterative Algorithm for Parsimonious Binary Kernel Fisher Discrimination

Record type: Article

By applying recent results in optimization theory variously known as optimization transfer or majorize/minimize algorithms, an algorithm for binary, kernel, Fisher discriminant analysis is introduced that makes use of a non-smooth penalty on the coefficients to provide a parsimonious solution. The problem is converted into a smooth optimization that can be solved iteratively with no greater overhead than iteratively re-weighted least-squares. The result is simple, easily programmed and is shown to perform, in terms of both accuracy and parsimony, as well as or better than a number of leading machine learning algorithms on two well-studied and substantial benchmarks.

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Citation

Harrison, Robert F. and Pasupa, Kitsuchart (2010) A Simple Iterative Algorithm for Parsimonious Binary Kernel Fisher Discrimination Pattern Analysis & Applications, 13, (1), pp. 15-22. (doi:10.1007/s10044-009-0162-1).

More information

Published date: 1 February 2010
Keywords: Kernel machines, Fisher discriminant analysis, majorize-minimize algorithms, sparsity, parsimony
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 266573
URI: http://eprints.soton.ac.uk/id/eprint/266573
PURE UUID: cf30cbbc-b2eb-4b3b-87a6-b61799d061ac

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Date deposited: 14 Aug 2008 12:04
Last modified: 18 Jul 2017 07:15

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Contributors

Author: Robert F. Harrison
Author: Kitsuchart Pasupa

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