Constructing Fuzzy Graphs from Examples

Lade...
Vorschaubild
Dateien
BeHu99_fuzzygraph_idaij.pdf
BeHu99_fuzzygraph_idaij.pdfGröße: 225.48 KBDownloads: 1448
Datum
1999
Autor:innen
Huber, Klaus-Peter
Herausgeber:innen
Kontakt
ISSN der Zeitschrift
Electronic ISSN
ISBN
Bibliografische Daten
Verlag
Schriftenreihe
Auflagebezeichnung
ArXiv-ID
Internationale Patentnummer
Angaben zur Forschungsförderung
Projekt
Open Access-Veröffentlichung
Open Access Green
Core Facility der Universität Konstanz
Gesperrt bis
Titel in einer weiteren Sprache
Forschungsvorhaben
Organisationseinheiten
Zeitschriftenheft
Publikationstyp
Zeitschriftenartikel
Publikationsstatus
Published
Erschienen in
Zusammenfassung

Methods to build function approximators from example data have gained considerable interest in the past. Especially methodologies that build models that allow an interpretation have attracted attention. Most existing algorithms, however, are either complicated to use or infeasible for high-dimensional problems. This article presents an efficient and easy to use algorithm to construct fuzzy graphs from example data. The resulting fuzzy graphs are based on locally independent fuzzy rules that operate solely on selected, important attributes. This enables the application of these fuzzy graphs also to problems in high dimensional spaces. Using illustrative examples and a real world data set it is demonstrated how the resulting fuzzy graphs offer quick insights into the structure of the example data, that is, the underlying model. The underlying algorithm is demonstrated using several Java applets, which can be found under "Electronic annexes" on www.elsevier.com/locate/ida.

Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
004 Informatik
Schlagwörter
Fuzzy Graphs, Learning, Rule Extraction, Function Approximation, Interpretation
Konferenz
Rezension
undefined / . - undefined, undefined
Zitieren
ISO 690BERTHOLD, Michael R., Klaus-Peter HUBER, 1999. Constructing Fuzzy Graphs from Examples. In: Intelligent Data Analysis. 1999, 3(1), pp. 37-53. Available under: doi: 10.1016/S1088-467X(99)00004-9
BibTex
@article{Berthold1999Const-5413,
  year={1999},
  doi={10.1016/S1088-467X(99)00004-9},
  title={Constructing Fuzzy Graphs from Examples},
  number={1},
  volume={3},
  journal={Intelligent Data Analysis},
  pages={37--53},
  author={Berthold, Michael R. and Huber, Klaus-Peter}
}
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/123456789/5413">
    <dc:language>eng</dc:language>
    <dc:format>application/pdf</dc:format>
    <dcterms:issued>1999</dcterms:issued>
    <dcterms:isPartOf rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <dc:contributor>Berthold, Michael R.</dc:contributor>
    <dcterms:bibliographicCitation>First publ. in: Intelligent Data Analysis 3 (1999), 1, pp. 37-53</dcterms:bibliographicCitation>
    <dc:creator>Berthold, Michael R.</dc:creator>
    <dcterms:abstract xml:lang="eng">Methods to build function approximators from example data have gained considerable interest in the past. Especially methodologies that build models that allow an interpretation have attracted attention. Most existing algorithms, however, are either complicated to use or infeasible for high-dimensional problems. This article presents an efficient and easy to use algorithm to construct fuzzy graphs from example data. The resulting fuzzy graphs are based on locally independent fuzzy rules that operate solely on selected, important attributes. This enables the application of these fuzzy graphs also to problems in high dimensional spaces. Using illustrative examples and a real world data set it is demonstrated how the resulting fuzzy graphs offer quick insights into the structure of the example data, that is, the underlying model. The underlying algorithm is demonstrated using several Java applets, which can be found under "Electronic annexes" on www.elsevier.com/locate/ida.</dcterms:abstract>
    <dspace:isPartOfCollection rdf:resource="https://kops.uni-konstanz.de/server/rdf/resource/123456789/36"/>
    <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5413"/>
    <dcterms:rights rdf:resource="http://creativecommons.org/licenses/by-nc-nd/2.0/"/>
    <dcterms:title>Constructing Fuzzy Graphs from Examples</dcterms:title>
    <dc:creator>Huber, Klaus-Peter</dc:creator>
    <dcterms:hasPart rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5413/1/BeHu99_fuzzygraph_idaij.pdf"/>
    <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:09Z</dcterms:available>
    <dc:contributor>Huber, Klaus-Peter</dc:contributor>
    <dc:rights>Attribution-NonCommercial-NoDerivs 2.0 Generic</dc:rights>
    <dspace:hasBitstream rdf:resource="https://kops.uni-konstanz.de/bitstream/123456789/5413/1/BeHu99_fuzzygraph_idaij.pdf"/>
    <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:55:09Z</dc:date>
    <void:sparqlEndpoint rdf:resource="http://localhost/fuseki/dspace/sparql"/>
    <foaf:homepage rdf:resource="http://localhost:8080/"/>
  </rdf:Description>
</rdf:RDF>
Interner Vermerk
xmlui.Submission.submit.DescribeStep.inputForms.label.kops_note_fromSubmitter
Kontakt
URL der Originalveröffentl.
Prüfdatum der URL
Prüfungsdatum der Dissertation
Finanzierungsart
Kommentar zur Publikation
Allianzlizenz
Corresponding Authors der Uni Konstanz vorhanden
Internationale Co-Autor:innen
Universitätsbibliographie
Nein
Begutachtet
Diese Publikation teilen