Tesis
Uma contribuição ao estudo das categorias internas e de sua proliferação em redes ARTMAP
Date
2012-11-05Registration in:
ALVES, Robinson Luis de Souza. Uma contribuição ao estudo das categorias internas e de
sua proliferação em redes ARTMAP. 2012. 100 f. Tese (Doutorado em Automação e Sistemas; Engenharia de Computação; Telecomunicações) - Universidade Federal do Rio Grande do Norte, Natal, 2012.
Author
Alves, Robinson Luis de Souza
Institutions
Abstract
ART networks present some advantages: online learning; convergence in a few epochs of training;
incremental learning, etc. Even though, some problems exist, such as: categories proliferation,
sensitivity to the presentation order of training patterns, the choice of a good vigilance parameter, etc.
Among the problems, the most important is the category proliferation that is probably the most
critical. This problem makes the network create too many categories, consuming resources to store
unnecessarily a large number of categories, impacting negatively or even making the processing time
unfeasible, without contributing to the quality of the representation problem, i. e., in many cases, the
excessive amount of categories generated by ART networks makes the quality of generation inferior
to the one it could reach. Another factor that leads to the category proliferation of ART networks is
the difficulty of approximating regions that have non-rectangular geometry, causing a generalization
inferior to the one obtained by other methods of classification. From the observation of these
problems, three methodologies were proposed, being two of them focused on using a most flexible
geometry than the one used by traditional ART networks, which minimize the problem of categories
proliferation. The third methodology minimizes the problem of the presentation order of training
patterns. To validate these new approaches, many tests were performed, where these results
demonstrate that these new methodologies can improve the quality of generalization for ART
networks