Anzeige
Erschienen in:
2006 | OriginalPaper | Buchkapitel
Improving the Expert Networks of a Modular Multi-Net System for Pattern Recognition
verfasst von : Mercedes Fernández-Redondo, Joaquín Torres-Sospedra, Carlos Hernández-Espinosa
Erschienen in: Artificial Neural Networks – ICANN 2006
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
A
Modular
Multi-Net System consists on some networks which solve partially a problem. The original problem has been decomposed into subproblems and each network focuses on solving a subproblem. The
Mixture of Neural Networks
consist on some expert networks which solve the subproblems and a gating network which weights the outputs of the expert networks. The expert networks and the gating network are trained all together in order to reduce the correlation among the networks and minimize the error of the system. In this paper we present the
Mixture of Multilayer Feedforward
(
MixMF
) a method based on
MixNN
which uses
Multilayer Feedfoward
networks for the expert level. Finally, we have performed a comparison among
Simple Ensemble
,
MixNN
and
MixMF
and the results show that
MixMF
is the best performing method.