Constructing a speculative kernel machine for pattern classification

Abstract

We propose and investigate the performance of a new geometry-based algorithm designed to identify potentially informative data points for classification. An incremental QR update scheme is used to build a classifier using a subset of these points as radial basis function centers. The minimum descriptive length and the leave-one-out error criteria are… (More)
DOI: 10.1016/j.neunet.2005.06.051

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