2003 | OriginalPaper | Chapter
Incrementally Assessing Cluster Tendencies with a~Maximum Variance Cluster Algorithm
Authors : Krzysztof Rzaḑca, Francesc J. Ferri
Published in: Pattern Recognition and Image Analysis
Publisher: Springer Berlin Heidelberg
Included in: Professional Book Archive
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A straightforward and efficient way to discover clustering tendencies in data using a recently proposed Maximum Variance Clustering algorithm is proposed. The approach shares the benefits of the plain clustering algorithm with regard to other approaches for clustering. Experiments using both synthetic and real data have been performed in order to evaluate the differences between the proposed methodology and the plain use of the Maximum Variance algorithm. According to the results obtained, the proposal constitutes an efficient and accurate alternative.