Ellipsoid ART and ARTMAP for incremental clustering and classification

Author

Anagnostopoulos, Georgios C. ; Georgiopoulos, Michael

Author_Institution

Sch. of Electr. Eng. & Comput. Sci., Central Florida Univ., Orlando, FL, USA

Volume

2

fYear

2001

fDate

2001

Firstpage

1221

Abstract

We introduce ellipsoid-ART (EA) and ellipsoid-ARTMAP (EAM) as a generalization of hypersphere ART (HA) and hypersphere-ARTMAP (HAM) respectively. As was the case with HA/HAM, these novel architectures are based on ideas rooted in fuzzy-ART (FA) and fuzzy-ARTMAP (FAM). While FA/FAM aggregate 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 respectively

Keywords

ART neural nets; fuzzy neural nets; generalisation (artificial intelligence); learning (artificial intelligence); pattern classification; pattern clustering; ART neural nets; data clustering; ellipsoid-ART; ellipsoid-ARTMAP; fuzzy neural nets; generalization; hyper-ellipsoids; hyper-rectangles; hypersphere ART; hypersphere-ARTMAP; learning rules,; Aggregates; Buildings; Clustering algorithms; Computer science; Ellipsoids; Feedforward neural networks; Feedforward systems; Neural networks; Resonance; Subspace constraints;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on

Conference_Location

Washington, DC

ISSN

1098-7576

Print_ISBN

0-7803-7044-9

Type

conf

DOI

10.1109/IJCNN.2001.939535

Filename

939535