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Pattern Analysis and Applications

Erschienen in:

01.11.2015 | Theoretical Advances

A modified kernel clustering method with multiple factors

verfasst von: Changming Zhu, Daqi Gao

Erschienen in: Pattern Analysis and Applications | Ausgabe 4/2015

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Abstract

We propose a simple and effective method about kernel clustering. This method takes many factors about kernel clustering into account. These factors include the selection of the initial centers of kernels, the ways of how to compute widths of kernels and the distances between patterns, different growing ways of kernels, and different kernel clustering criterions. Experiments have validated that these factors have influence on the final experimental results while not each factor has a great influence. Furthermore, some classifiers with this proposed kernel clustering method have higher classification accuracies and lower generalization risks.

Vorheriger Artikel A GA-based feature selection and parameter optimization of an ANN in diagnosing breast cancer

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Titel: A modified kernel clustering method with multiple factors
verfasst von: Changming Zhu
Daqi Gao
Publikationsdatum: 01.11.2015
Verlag: Springer London
Erschienen in: Pattern Analysis and Applications / Ausgabe 4/2015
Print ISSN: 1433-7541
Elektronische ISSN: 1433-755X
DOI: https://doi.org/10.1007/s10044-014-0377-7

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