Subspace and projected clustering: experimental evaluation and analysis

Authors:
Gabriela Moise;Arthur Zimek;Peer Kröger;Hans-Peter Kriegel;Jörg Sander
Affiliations:
University of Alberta, Department of Computing Science, T6G 2E8, Edmonton, AB, Canada;Ludwig-Maximilians-Universität München, Munich, Germany;Ludwig-Maximilians-Universität München, Munich, Germany;Ludwig-Maximilians-Universität München, Munich, Germany;University of Alberta, Department of Computing Science, T6G 2E8, Edmonton, AB, Canada
Venue:
Knowledge and Information Systems
Year:
2009

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Abstract

Subspace and projected clustering have emerged as a possible solution to the challenges associated with clustering in high-dimensional data. Numerous subspace and projected clustering techniques have been proposed in the literature. A comprehensive evaluation of their advantages and disadvantages is urgently needed. In this paper, we evaluate systematically state-of-the-art subspace and projected clustering techniques under a wide range of experimental settings. We discuss the observed performance of the compared techniques, and we make recommendations regarding what type of techniques are suitable for what kind of problems.