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ACIVS
2008
Springer

Knee Point Detection in BIC for Detecting the Number of Clusters

12 years 6 months ago
Knee Point Detection in BIC for Detecting the Number of Clusters
Bayesian Information Criterion (BIC) is a promising method for detecting the number of clusters. It is often used in model-based clustering in which a decisive first local maximum is detected as the number of clusters. In this paper, we re-formulate the BIC in partitioning based clustering algorithm, and propose a new knee point finding method based on it. Experimental results show that the proposed method detects the correct number of clusters more robustly and accurately than the original BIC and performs well in comparison to several other cluster validity indices.
Qinpei Zhao, Ville Hautamäki, Pasi Fränt
Added 01 Jun 2010
Updated 01 Jun 2010
Type Conference
Year 2008
Where ACIVS
Authors Qinpei Zhao, Ville Hautamäki, Pasi Fränti
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