Title

On The Design Of An Ellipsoid Artmap Classifier Within The Fuzzy Adaptive System Art Framework

Abstract

In this paper we present the design of Fuzzy Adaptive System Ellipsoid ARTMAP (FASEAM), a novel neural architecture based on Ellipsoid ARTMAP (EAM) that is equipped with concepts utilized in the Fuzzy Adaptive System ART (FASART) architecture. More specifically, we derive a new category choice function appropriate for EAM categories that is non-constant in a category's representation region. Additionally, we augment the EAM category description with a centroid vector, whose learning rate is inversely proportional to the number of training patterns accessing the category. Finally, we demonstrate the merits of our design choices by comparing FASART, EAM and FASEAM in terms of generalization performance and final structural complexity on a set of classification problems. © 2005 IEEE.

Publication Date

12-1-2005

Publication Title

Proceedings of the International Joint Conference on Neural Networks

Volume

1

Number of Pages

469-474

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/IJCNN.2005.1555876

Socpus ID

33745961888 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/33745961888

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