Ellipsoid ART and ARTMAP for incremental unsupervised and supervised learning
Georgios C. Anagnostopoulos, Michael Georgiopoulos · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2001
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.