Accelerating training of radial basis function networks with Cascade-Correlation algorithm

M. Lehtokangas, Jukka P. Saarinen, Kimmo Kaski

Research output: Contribution to journalArticleScientificpeer-review

7 Citations (Scopus)

Abstract

Cascade-Correlation learning method has conventionally been used for training feedforward multilayer networks with sigmoidal activation in the hidden units. We have developed a modification of the Cascade-Correlation method and applied it successfully in training radial basis function networks. This method works in a similar way as the orthogonal least squares method which has been utilized for training radial basis function networks. Our experiments show that with the modified Cascade-Correlation training approximately the same error level can be reached but significantly faster than with the orthogonal least squares training.
Original languageEnglish
Pages (from-to)207-213
JournalNeurocomputing
Volume9
Issue number2
DOIs
Publication statusPublished - 1995
MoE publication typeA1 Journal article-refereed

Keywords

  • neural networks
  • radial basis function network
  • cascade-correlation

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