An On-Line Learning Algorithm with Dimension Selection Using Minimal Hyper Basis Function Networks View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2004

AUTHORS

Kyosuke Nishida , Koichiro Yamauchi , Takashi Omori

ABSTRACT

In this study, we extend a minimal resource-allocating network (MRAN) which is an on-line learning system for Gaussian radial basis function networks (GRBFs) with growing and pruning strategies so as to realize dimension selection and low computational complexity. We demonstrate that the proposed algorithm outperforms conventional algorithms in terms of both accuracy and computational complexity via some experiments. More... »

PAGES

502-507

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-540-30499-9_77

DOI

http://dx.doi.org/10.1007/978-3-540-30499-9_77

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1008882254


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