Visualizing High Dimensional Fuzzy Rules

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HOLVE, Rainer, Michael BERTHOLD, 2000. Visualizing High Dimensional Fuzzy Rules. In: MESS-, VDI/VDE-Gesellschaft, ed., AUTOMATISIERUNGSTECHNIK; GESELLSCHAFT FÜR INFORMATIK GI, ed.. Computational intelligence im industriellen Einsatz : Fuzzy Systeme, neuronale Netze, evolutionäre Algorithmen, Data mining ; Tagung Baden-Baden, 11. und 12. Mai 2000. Düsseldorf:VDI Verein Deutscher Ingenieure, pp. 21-25. ISBN 3-18-091526-9

@inproceedings{Holve2000Visua-24321, title={Visualizing High Dimensional Fuzzy Rules}, year={2000}, isbn={3-18-091526-9}, address={Düsseldorf}, publisher={VDI Verein Deutscher Ingenieure}, booktitle={Computational intelligence im industriellen Einsatz : Fuzzy Systeme, neuronale Netze, evolutionäre Algorithmen, Data mining ; Tagung Baden-Baden, 11. und 12. Mai 2000}, pages={21--25}, editor={Mess-, VDI/VDE-Gesellschaft and Automatisierungstechnik; Gesellschaft für Informatik GI}, author={Holve, Rainer and Berthold, Michael} }

<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/123456789/24321"> <dc:contributor>Berthold, Michael</dc:contributor> <dcterms:title>Visualizing High Dimensional Fuzzy Rules</dcterms:title> <dc:creator>Berthold, Michael</dc:creator> <dcterms:bibliographicCitation>Computational intelligence im industriellen Einsatz : Fuzzy Systeme, neuronale Netze, evolutionäre Algorithmen, Data mining; Tagung Baden-Baden, 11. und 12. Mai 2000 / VDI/VDE-Gesellschaft Mess- und Automatisierungstechnik ; Gesellschaft für Informatik GI. - Düsseldorf : VDI Verein Deutscher Ingenieure, 2000. - S. 21-25. - ISBN 3-18-091526-9</dcterms:bibliographicCitation> <dcterms:rights rdf:resource="http://nbn-resolving.org/urn:nbn:de:bsz:352-20140905103605204-4002607-1"/> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-26T12:05:51Z</dc:date> <dc:contributor>Holve, Rainer</dc:contributor> <dc:creator>Holve, Rainer</dc:creator> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/24321"/> <dc:language>eng</dc:language> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-26T12:05:51Z</dcterms:available> <dcterms:issued>2000</dcterms:issued> <dc:rights>deposit-license</dc:rights> <dcterms:abstract xml:lang="eng">In this paper we present an approach to visualize a potentially high-dimensional and large number of (fuzzy) rules in two dimensions. This visualization presents the entire set of rules to the user as one coherent picture. We use a gradient descent based algorithm to generate a 2D-view of the rule set which minimizes the error on the pair-wise fuzzy distances between all rules. This approach is superior to a simple projection and also most non-linear transformations in that it concentrates on the important feature, that is the inter-point distances. In order to make use of the uncertain nature of the underlying fuzzy rules, a new fuzzy distance-measure was developed. The visualizations of a rule set for the well-known IRIS dataset as well as fuzzy models for other benchmark data sets are illustrated and discussed.</dcterms:abstract> </rdf:Description> </rdf:RDF>

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