[R] about mix type clust algorithm

[David Winsemius]

On Jul 22, 2013, at 4:12 AM, Jose Iparraguirre wrote:

> Dear Cheng,
> 
> This question exceeds the topics of this group. However, you may benefit from this recent (and excellent) paper along with the discussions:
> 
> Henning, C. and T. Liao (2013). "How to find an appropriate clustering for mixed-type variables with application to socio-economy stratification", Journal of Applied Statistics, Vol. 62, Part 3, pp. 309-369.
> 

Might be easier to find with the correct author citation:

C. Hennig and T. F. Liao

The first author makes a copy available at his website;
http://www.homepages.ucl.ac.uk/~ucakche/pp.html

-- 
David.
> Regards,
> 
> José
> 
> Prof. José Iparraguirre
> Chief Economist
> Age UK
> 
> Profesor de Economía
> Universidad de Morón
> Morón, Buenos Aires, Argentina
> 
> 
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org] On Behalf Of Cheng, Yi
> Sent: 22 July 2013 07:23
> To: r-help at r-project.org
> Subject: [R] about mix type clust algorithm
> 
> Hi:
> I have tried to find the appropriate clust algorithm for mixed type of data.
> The suggested way I see is:
> 
> 1.       use daisy to get the dissimilarity matrix
> 
> 2.       use PAM/hclust by providing the dissimilarity matrix, to get the clusters
> but by following this, when the data set grows bigger say 10,000 rows of data, the dissimilarity matrix will be O(n^2), and out of memory will occur.
> I am wondering is there any better ways to do the mixed type cluster?
> 
> Cheng Yi
> 
> 
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David Winsemius
Alameda, CA, USA