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Re: Clustering algorithm Mathematica 7

• To: mathgroup at smc.vnet.net
• Subject: [mg105105] Re: [mg105081] Clustering algorithm Mathematica 7
• From: Darren Glosemeyer <darreng at wolfram.com>
• Date: Sat, 21 Nov 2009 03:33:24 -0500 (EST)
• References: <200911201139.GAA03443@smc.vnet.net>

Jan Baetens wrote:
> Hi all,
>
> Currently, I'm using the built-in clustering algorithm of Mathematica 7, 
> though it isn't clear for me which algorithm it actually is since this 
> is not mentioned in the extended help pages. Presumably, it's the normal 
> K-means clustering but I'm not sure. 
>
> As such, I'd like know whether someone knows which implementation is 
> used in Mathematica 7 for data clustering.
>
> Thanks,
>
> Jan
>
>   

The default is k-medoids. Agglomerative clustering is also included as a 
method option. Brief discussion of the methods is included in the 
documentation. This can be found by entering

tutorial/PartitioningDataIntoClusters

in the Documentation Center or online at

http://reference.wolfram.com/mathematica/tutorial/PartitioningDataIntoClusters.html

Here are some references about the methods that you might also find useful:

L. Kaufman and P. J. Rousseeuw, Finding Groups in Data: An Introduction
to Cluster Analysis, New York: John Wiley & Sons, 1990.

P. J. Rousseeuw, ?Silhouettes: A Graphical Aid to the Interpretation and
Validation of Cluster Analysis,? J Comput. Appl. Math., 20, 1987, 53?65.

R. Tibshirani, G. Walther, and T. Hastie, ?Estimating the Number of
Clusters in a Dataset Via the Gap Statistic.? Stanford Univ. Tech.
report. March 2000. (published Journal of the Royal Statistical Society,
B, 63, 2001, 411?423.)


Darren Glosemeyer
Wolfram Research

• References:
  • Clustering algorithm Mathematica 7
    • From: Jan Baetens <jan.baetens@ugent.be>