Thanks Guys , 
I am able to generate the distance matrix for mixed column values ( categorical and ordinal ) using daisy function 

But can anyone tell me how to generate clusters out of it , The point being i dont know the number of cluster beforehand 

Let me give an overview of the problem i am trying to solve is 

Given a dataset , something like below 


                    var1         var2       var3             Size
element1-1   yes            x         present          100
element1-2   no             y         absent            294
element1-3   maybe       x         absent            45


The first 3 variables being categorical and last one being ordinal 

I need to do the following 
1 )  Generate clusters out of it  ( let say they are "training clusters" ) 
             I am able to compute distance matrix ( using daisy ) , but not sure how to create unknown numbers of clusters ,  dbscan work on a distance matrix 
2 )  Once that is done i want to spread some new data points in the above plot space ( lets say these are "test points" ) 
3)   Find out which "test points" are lying within a boundary  of any above discovered training clusters   

If anyone know how to get this done then please let me know 
Its for an academic project and i am unable to make any progress 

Thanks and Regards
K



________________________________
From: Ingmar Visser <i.visser@uva.nl>

Sent: Fri, 11 June, 2010 2:19:33 PM
Subject: Re: [R] Finding distance matrix for categorical data

latent class analysis may be more appropriate depending on your hypotheses,
best, Ingmar



e:

All,
>
>>How can we find a distance matrix for categorical data
>
>>ie.  given a csv below
>
>>                   var1         var2    var3    var4
>>element1-1   yes            x         a         k
>>element1-2   no             y         b         l
>>element1-3   maybe       y         c          m
>
>>how can i compute the distance matrix between all the elements
>
>>Actually i need it to create clusters on top of it
>
>>Thanks & Regards
>>Kapil
>
>
>>        [[alternative HTML version deleted]]
>
>>______________________________________________
>R-help@r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>>and provide commented, minimal, self-contained, reproducible code.
>



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