Validity measures for the fuzzy cluster analysis of orientations

Validity measures for the fuzzy cluster analysis of orientations

Fuzzy K-means clustering can be applied to the automatic identification of sets in discontinuity data after suitable adaptation of the algorithm. To establish the number of clusters in a data set, modified versions of the validity measures of Gath and Geva (1989), Xie-Beni (1991) and Fukuyama-Sugeno...

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Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence 2000-12, Vol.22 (12), p.1467-1472
Hauptverfasser: Hammah, R.E., Curran, J.H.
Format: Artikel
Sprache:eng
Schlagworte:
Algorithm design and analysis
Algorithms
Clustering algorithms
Clusters
Data analysis
Density measurement
Discontinuity
Euclidean distance
Fuzzy
Fuzzy logic
Fuzzy set theory
Fuzzy sets
Intelligence
Mechanical variables measurement
Partitioning algorithms
Pattern analysis
Performance analysis
Prototypes
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Beschreibung
Zusammenfassung:Fuzzy K-means clustering can be applied to the automatic identification of sets in discontinuity data after suitable adaptation of the algorithm. To establish the number of clusters in a data set, modified versions of the validity measures of Gath and Geva (1989), Xie-Beni (1991) and Fukuyama-Sugeno are presented in this paper.
ISSN:0162-8828
1939-3539
DOI:10.1109/34.895981