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ON AN ADJACENCY CLUSTER MERIT
Date
2010-02-04
Author
Volkovich, Zeev (Vladimir)
Weber, Gerhard Wilhelm
Avros, Renata
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This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
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This work is addressed to the problem of cluster validation to determine the right number of clusters. We consider a cluster stability property based on the k nearest neighbor type coincidences model. Cluster quality is measured by the deviations from this model such that good constructed clusters are typified by small departures values. The true number of clusters corresponds to the empirical deviation distribution having shortest right tail. The experiments carried out on synthetic and real databases demonstrate the effectiveness of the approach.
Subject Keywords
Clustering
,
Nearest Neighbors
,
Data Mining
,
Two Sample Test
,
Cluster Stability
URI
https://hdl.handle.net/11511/53976
DOI
https://doi.org/10.1063/1.3459773
Collections
Graduate School of Applied Mathematics, Conference / Seminar