Publikation: Visualizing High Dimensional Fuzzy Rules
Dateien
Datum
Autor:innen
Herausgeber:innen
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
URI (zitierfähiger Link)
DOI (zitierfähiger Link)
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Core Facility der Universität Konstanz
Titel in einer weiteren Sprache
Publikationstyp
Publikationsstatus
Erschienen in
Zusammenfassung
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.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
Schlagwörter
Konferenz
Rezension
Zitieren
ISO 690
BERTHOLD, Michael R., Rainer HOLVE, 2000. Visualizing High Dimensional Fuzzy Rules. PeachFuzz 2000. 19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS. Atlanta, GA, USA. In: PeachFuzz 2000. 19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.00TH8500). IEEE, 2000, pp. 64-68. ISBN 0-7803-6274-8. Available under: doi: 10.1109/NAFIPS.2000.877386BibTex
@inproceedings{Berthold2000Visua-24299, year={2000}, doi={10.1109/NAFIPS.2000.877386}, title={Visualizing High Dimensional Fuzzy Rules}, isbn={0-7803-6274-8}, publisher={IEEE}, booktitle={PeachFuzz 2000. 19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (Cat. No.00TH8500)}, pages={64--68}, author={Berthold, Michael R. and Holve, Rainer} }
RDF
<rdf:RDF xmlns:dcterms="http://purl.org/dc/terms/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dspace="http://digital-repositories.org/ontologies/dspace/0.1.0#" xmlns:foaf="http://xmlns.com/foaf/0.1/" xmlns:void="http://rdfs.org/ns/void#" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/server/rdf/resource/123456789/24299"> <dc:contributor>Holve, Rainer</dc:contributor> <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:language>eng</dc:language> <foaf:homepage rdf:resource="http://localhost:8080/"/> <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/24299"/> <dcterms:bibliographicCitation>19th International Conference of the North American Fuzzy Information Processing Society - NAFIPS (North American Fuzzy Information Processing Society) : Atlanta, Georgia, USA, July 13-15, 2000 / ed. by Thomas Whalen. - Piscataway, N.J. : IEEE Service Center, 2000. - S. 64-68. - ISBN 0-7803-6274-8</dcterms:bibliographicCitation> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-23T06:42:56Z</dcterms:available> <dcterms:rights rdf:resource="https://rightsstatements.org/page/InC/1.0/"/> <dcterms:issued>2000</dcterms:issued> <dc:creator>Holve, Rainer</dc:creator> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2013-08-23T06:42:56Z</dc:date> <dcterms:title>Visualizing High Dimensional Fuzzy Rules</dcterms:title> <dc:creator>Berthold, Michael R.</dc:creator> <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> <dc:rights>terms-of-use</dc:rights> <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/> <dc:contributor>Berthold, Michael R.</dc:contributor> </rdf:Description> </rdf:RDF>