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Performance evaluation of some clustering algorithms and validity indices

โœ Scribed by Maulik, U.; Bandyopadhyay, S.

Book ID
117930977
Publisher
IEEE
Year
2002
Tongue
English
Weight
286 KB
Volume
24
Category
Article
ISSN
0162-8828

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By using a kernel function, data that are not easily separable in the original space can be clustered into homogeneous groups in the implicitly transformed high-dimensional feature space. Kernel k-means algorithms have recently been shown to perform better than conventional k-means algorithms in uns