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Soft Computing

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01.10.2013 | Methodologies and Application

Extension of the gap statistics index to fuzzy clustering

verfasst von: Shihong Yue, Penglong Wang, JeenShing Wang, Ti Huang

Erschienen in: Soft Computing | Ausgabe 10/2013

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Abstract

The well-known gap statistic index proposed by Tibshirani et al. has successfully applied in many clustering evaluations. However, the gap statistic index cannot evaluate the clustering partitions from any fuzzy clustering algorithm. This is because fuzzy clustering cannot provide the within-cluster similarity measure that is used in the gas statistic index. Thus, the applicable range of the gap statistic index is very limited. In this paper, we present a new method that extends the gap statistic index to fuzzy clustering by using fuzzy membership notations. Our proposed method can extend the applicability of the gap statistic index, and outperform other existing fuzzy indices in several aspects. Experiments on eight sets of synthetic and real datasets are used to verify the applicability and efficiency of the proposed method.

Vorheriger Artikel A multiclassifier approach for topology-based WiFi indoor localization

Nächster Artikel Robust adaptive fuzzy control of twin rotor MIMO system

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Titel: Extension of the gap statistics index to fuzzy clustering
verfasst von: Shihong Yue
Penglong Wang
JeenShing Wang
Ti Huang
Publikationsdatum: 01.10.2013
Verlag: Springer Berlin Heidelberg
Erschienen in: Soft Computing / Ausgabe 10/2013
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI: https://doi.org/10.1007/s00500-013-1023-9

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