Constructing Fuzzy Graphs from Examples

Berthold, Michael R.; Huber, Klaus-Peter

Constructing Fuzzy Graphs from Examples

Dateien

BeHu99_fuzzygraph_idaij.pdfGröße: 225.48 KBDownloads: 1462

Datum

1999

Autor:innen

Berthold, Michael R.

Huber, Klaus-Peter

Open Access-Veröffentlichung

Open Access Green

Sammlungen

Informatik und Informationswissenschaft

Publikationstyp

Zeitschriftenartikel

Publikationsstatus

Published

Erschienen in

Intelligent Data Analysis. 1999, 3(1), pp. 37-53. Available under: doi: 10.1016/S1088-467X(99)00004-9

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.

Fachgebiet (DDC)

004 Informatik

Schlagwörter

Fuzzy Graphs, Learning, Rule Extraction, Function Approximation, Interpretation

Zitieren

ISO 690

BERTHOLD, 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}
}

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