Inelligible neural networks with BP-SOM

A.J.M.M. Weijters, A.P.J. Bosch, van den, H.J. Herik, van den

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)


Interpretation of models induced by artificial neural networks is often a difficult task. In this paper we focus on a relatively novel neural network architecture and learning algorithm, bp-som that offers possibilities to overcome this difficulty. It is shown that networks trained with BP-SOM show interesting regularities, in that hidden-unit activations become restricted to discrete values, and that the som part can be exploited for automatic rule extraction.
Original languageEnglish
Title of host publicationMachine learning : ECML-98 : 10th European conference on machine learning, Chemnitz, Germany, April 21-23, 1998 : proceedings
EditorsC. Nédellec, C. Rouveirol
Place of PublicationBerlin
ISBN (Print)978-3-540-64417-0
Publication statusPublished - 1998

Publication series

NameLecture notes in artificial intelligence


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