We propose a novel clustering technique based on kernel methods. We exploit the geometric properties of normalized kernel spaces to automatically detect the correct number of clusters, thus avoiding the requirement of an initial estimate of this parameter, as required instead in many popular algorithms.
Kernel-Based Clustering
PICIARELLI, Claudio;MICHELONI, Christian;FORESTI, Gian Luca
2013-01-01
Abstract
We propose a novel clustering technique based on kernel methods. We exploit the geometric properties of normalized kernel spaces to automatically detect the correct number of clusters, thus avoiding the requirement of an initial estimate of this parameter, as required instead in many popular algorithms.File in questo prodotto:
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