Determination of the Number of Clusters in a Data Set: A Stopping Rule × Clustering Algorithm Comparison

The accuracy of “stopping rules” for determining the number of clusters in a data set is examined as a function of the underlying clustering algorithm being used. Using a Monte Carlo study, various stopping rules, used in conjunction with six clustering algorithms, are compared to determine which ru...

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Bibliographic Details
Published in:	International journal of strategic decision sciences Vol. 2; no. 4; pp. 1 - 13
Main Author:	Boone, Derrick S
Format:	Journal Article
Language:	English
Published:	Hershey IGI Global 01.10.2011
Subjects:	Algorithms Analysis Clustering Datasets Outliers (statistics)
ISSN:	1947-8569, 1947-8577
Online Access:	Get full text
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