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CrySSMEx, a novel rule extractor for recurrent neural networks: Overview and case study
University of Skövde, School of Humanities and Informatics.
University of Skövde, School of Humanities and Informatics.ORCID iD: 0000-0001-6883-2450
2005 (English)In: Artificial Neural Networks: Formal Models and Their Applications: ICANN 2005 15th International Conference, Warsaw, Poland, September 11-15, 2005, Proceedings, Part II / [ed] Włodzisław Duch, Janusz Kacprzyk, Erkki Oja, Sławomir Zadrożny, Springer Berlin/Heidelberg, 2005, 503-508 p.Conference paper, (Refereed)
Abstract [en]

In this paper, it will be shown that it is feasible to extract finite state machines in a domain of, for rule extraction, previously unencountered complexity. The algorithm used is called the Crystallizing Substochastic Sequential Machine Extractor, or CrySSMEx. It extracts the machine from sequence data generated from the RNN in interaction with its domain. CrySSMEx is parameter free, deterministic and generates a sequence of increasingly deterministic extracted stochastic models until a fully deterministic machine is found.

Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2005. 503-508 p.
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 3697
National Category
Engineering and Technology
Research subject
Technology
Identifiers
URN: urn:nbn:se:his:diva-1705DOI: 10.1007/11550907_79ISI: 000232196000079Scopus ID: 2-s2.0-33646251391ISBN: 3-540-28755-8 ISBN: 978-3-540-28755-1 ISBN: 978-3-540-28756-8 OAI: oai:DiVA.org:his-1705DiVA: diva2:31981
Conference
15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005; Warsaw; 11 September 2005 through 15 September 2005
Available from: 2008-02-08 Created: 2008-02-08 Last updated: 2015-01-16Bibliographically approved

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CiteExportLink to record
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Citation style
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