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The eigenspace separation transform for neural-network classifiers

✍ Scribed by Don Torrieri

Publisher: Elsevier Science
Year: 1999
Tongue: English
Weight: 156 KB
Volume: 12
Category: Article
ISSN: 0893-6080
DOI: 10.1016/s0893-6080(98)00138-5

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✦ Synopsis

This paper presents a linear transform that compresses data in a manner designed to improve the performance of a neural network used as a binary classifier. The classifier is intended to accommodate data distributions that may be non-normal, may have equal class means, may be multimodal, and have unknown a priori probabilities for the two classes. The transform, which is called the eigenspace separation transform, allows the reduction of the size of a neural network while enhancing its generalization accuracy as a binary classifier. Published by Elsevier Science Ltd.

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