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CrySSMEx, a novel rule extractor for recurrent neural networks: Overview and case study
Högskolan i Skövde, Institutionen för kommunikation och information.
Högskolan i Skövde, Institutionen för kommunikation och information.ORCID-id: 0000-0001-6883-2450
2005 (engelsk)Inngår i: 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, s. 503-508Konferansepaper, Publicerat paper (Fagfellevurdert)
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.

sted, utgiver, år, opplag, sider
Springer Berlin/Heidelberg, 2005. s. 503-508
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Lecture Notes in Computer Science, ISSN 0302-9743 ; 3697
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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, id: diva2:31981
Konferanse
15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005; Warsaw; 11 September 2005 through 15 September 2005
Tilgjengelig fra: 2008-02-08 Laget: 2008-02-08 Sist oppdatert: 2017-11-27bibliografisk kontrollert

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