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Proceedings Paper

Experiments to compare rough sets and vector quantization with the self-organizing algorithm
Author(s): Raisa R. Szabo
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Paper Abstract

This paper presents a comparison study of the rough set approach and Kohonen's vector quantization with the self- organizing algorithm. The main idea behind this research is the fact that neither the rough set nor Kohonen's neural network approaches require a prior knowledge of data distribution. The paradigms are compared in terms of their methods for the calculation of an accuracy of approximation and classification, reduction of non-significant attributes, minimal subset of attributes, and the uncertainty associated with the decision making process.

Paper Details

Date Published: 25 March 1998
PDF: 11 pages
Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); doi: 10.1117/12.304826
Show Author Affiliations
Raisa R. Szabo, Nova Southeastern Univ. (United States)

Published in SPIE Proceedings Vol. 3390:
Applications and Science of Computational Intelligence
Steven K. Rogers; David B. Fogel; James C. Bezdek; Bruno Bosacchi, Editor(s)

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