[R] agglomerative coefficient in agnes (cluster)

Mulholland, Tom Tom.Mulholland at dpi.wa.gov.au
Thu Jan 27 04:48:47 CET 2005


Well I am not sure that can call a single figure a cluster. Sure it's not near the others but how can you conceptually measure it's cluster properties. It seems reasonable that there has to be some form of doubt about it.

Back to that Google search hit number 3 www.stat.ncu.edu.tw/teacher/ hungy/mva/notes/lecture-cluster-example.pdf  gives examples which are not close to 1. 

It is said that "The quality of an agglomerative clustering of the data can be measured by the agglomerative coefficient" this is ascribed to Kaufman L. and Rousseeuw P. (1990), "Finding Groups in Data, an Introduction to Cluster Analysis", Wiley, New York. After I had read some of the recent work on clustering I realised that clustering is as much art as it is anything else. There is a wealth of papers with arguments about which methods should be used to assess the effectiveness of the clustering process. I don't think it matters which type of evaluation method you use they are not absolute numbers, they need to be seen as relative. They also need to be seen as an attempt at modelling a method of quality assessment for which there is no clear winner. So the bottom line is that if for your purposes a single number on it's own should be classified as a group, you may well have to define your own method of evaluation.

Tom

> -----Original Message-----
> From: Weiguang Shi [mailto:wgshi2001 at yahoo.ca]
> Sent: Thursday, 27 January 2005 7:28 AM
> To: Liaw, Andy
> Cc: rhelp
> Subject: RE: [R] agglomerative coefficient in agnes (cluster)
> 
> 
> Thanks again Andy.
> 
> The definition of AC is understood, yet I have trouble
> picturing the amount of "clear clustering structure"
> it measures. To put things into perspective, for two
> series 
>    1,2,1000,1001
> and 
>    1,2,3,1000
> agnes(x, method="single") generates ac values of 
> 0.998998 and 0.0.7492477 respectively, yet it seems to
> me that both have fairly clear clustering structures.
> 
>  --- "Liaw, Andy" <andy_liaw at merck.com> wrote: 
> > BTW, I checked the book.  You're not going find much
> > more than that.
> > 
> Thanks for checking.
> 
> Weiguang
> 
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