Thanks for the article, Jose! It looks very interesting.


On Mon, Jul 22, 2013 at 7:12 AM, Jose Iparraguirre <
Jose.Iparraguirre@ageuk.org.uk> 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.
>
> 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@r-project.org [mailto:r-help-bounces@r-project.org]
> On Behalf Of Cheng, Yi
> Sent: 22 July 2013 07:23
> To: r-help@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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