Fuzzy logic in KNIME - modules for approximate reasoning

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BERTHOLD, Michael, Bernd WISWEDEL, Thomas GABRIEL, 2013. Fuzzy logic in KNIME - modules for approximate reasoning. In: International Journal of Computational Intelligence Systems. 6(sup1), pp. 34-45. ISSN 1875-6891. eISSN 1875-6883

@article{Berthold2013Fuzzy-26484, title={Fuzzy logic in KNIME - modules for approximate reasoning}, year={2013}, doi={10.1080/18756891.2013.818186}, number={sup1}, volume={6}, issn={1875-6891}, journal={International Journal of Computational Intelligence Systems}, pages={34--45}, author={Berthold, Michael and Wiswedel, Bernd and Gabriel, Thomas} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/26484"> <dcterms:bibliographicCitation>International journal of computational intelligence systems ; 6 (2013), Supplement 1. - S. 34-45</dcterms:bibliographicCitation> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-21T13:12:34Z</dcterms:available> <dc:creator>Wiswedel, Bernd</dc:creator> <dc:rights>deposit-license</dc:rights> <dcterms:title>Fuzzy logic in KNIME - modules for approximate reasoning</dcterms:title> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2014-02-21T13:12:34Z</dc:date> <dcterms:rights rdf:resource="http://nbn-resolving.org/urn:nbn:de:bsz:352-20140905103605204-4002607-1"/> <dc:contributor>Wiswedel, Bernd</dc:contributor> <dc:creator>Berthold, Michael</dc:creator> <dc:contributor>Berthold, Michael</dc:contributor> <dc:contributor>Gabriel, Thomas</dc:contributor> <dc:language>eng</dc:language> <dc:creator>Gabriel, Thomas</dc:creator> <dcterms:issued>2013</dcterms:issued> <dcterms:abstract xml:lang="eng">In this paper we describe the open source data analytics platform KNIME, focusing particularly on extensions and modules supporting fuzzy sets and fuzzy learning algorithms such as fuzzy clustering algorithms, rule induction methods, and interactive clustering tools. In addition we outline a number of experimental extensions, which are not yet part of the open source release and present two illustrative examples from real world applications to demonstrate the power of the KNIME extensions.</dcterms:abstract> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/26484"/> </rdf:Description> </rdf:RDF>

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