Title
Ellipsoid Art And Artmap For Incremental Unsupervised And Supervised Learning
Keywords
Adaptive resonance theory; Classification; Clustering; Fuzzy ART; Fuzzy ARTMAP; Self-organization
Abstract
We introduce Ellipsoid-ART (EA) and Ellipsoid-ARTMAP (EAM) as a generalization of Hyper-sphere ART and Hypersphere-ARTMAP respectively. Our novel architectures are based on ideas rooted in 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.
Publication Date
1-1-2001
Publication Title
Proceedings of SPIE - The International Society for Optical Engineering
Volume
4390
Number of Pages
293-304
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1117/12.421180
Copyright Status
Unknown
Socpus ID
0034942801 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/0034942801
STARS Citation
Anagnostopoulos, G. C. and Georgiopoulos, M., "Ellipsoid Art And Artmap For Incremental Unsupervised And Supervised Learning" (2001). Scopus Export 2000s. 562.
https://stars.library.ucf.edu/scopus2000/562