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Proceedings Paper

Ellipsoid ART and ARTMAP for incremental unsupervised and supervised learning
Author(s): Georgios C. Anagnostopoulos; Michael Georgiopoulos
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Paper Abstract

We introduce Ellipsoid-ART, EA and Ellipsoid-ARTMAP, EAM as a generalization of Hyper-sphere ART and Hypersphere-ARTMAP respectively. Our novel archetectures are based on ideas rooted on Fuzzy-ART, FA and Fuzzy-ARTMAP, FAM. While FA/FAM summarize input data using hyper-rectangles, EA/EAM utilize hyper-ellipsoids for the same purpose. Due to their learning rules, EA and EAM share virtually all properties and characteristics of their FA/FAM counterparts. Preliminary experimentation implies that EA and EAM are to be viewed as good alternatives to FA and FAM for data clustering and classification tasks. Extensive pseudo-code is provided in the appendices for computationally efficient implementations of EA/EAM training and performance phases.

Paper Details

Date Published: 21 March 2001
PDF: 12 pages
Proc. SPIE 4390, Applications and Science of Computational Intelligence IV, (21 March 2001); doi: 10.1117/12.421180
Show Author Affiliations
Georgios C. Anagnostopoulos, Univ. of Central Florida (United States)
Michael Georgiopoulos, Univ. of Central Florida (United States)


Published in SPIE Proceedings Vol. 4390:
Applications and Science of Computational Intelligence IV
Kevin L. Priddy; Paul E. Keller; Peter J. Angeline, Editor(s)

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