[R] about mix type clust algorithm

Jose Iparraguirre Jose.Iparraguirre at ageuk.org.uk
Mon Jul 22 13:12:25 CEST 2013


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 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


	[[alternative HTML version deleted]]

______________________________________________
R-help at 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.

The Wireless from Age UK | Radio for grown-ups.

www.ageuk.org.uk/thewireless


If you’re looking for a radio station that offers real variety, tune in to The Wireless from Age UK. 
Whether you choose to listen through the website at www.ageuk.org.uk/thewireless, on digital radio (currently available in London and Yorkshire) or through our TuneIn Radio app, you can look forward to an inspiring mix of music, conversation and useful information 24 hours a day.



 
-------------------------------
Age UK is a registered charity and company limited by guarantee, (registered charity number 1128267, registered company number 6825798). 
Registered office: Tavis House, 1-6 Tavistock Square, London WC1H 9NA.

For the purposes of promoting Age UK Insurance, Age UK is an Appointed Representative of Age UK Enterprises Limited, Age UK is an Introducer 
Appointed Representative of JLT Benefit Solutions Limited and Simplyhealth Access for the purposes of introducing potential annuity and health 
cash plans customers respectively.  Age UK Enterprises Limited, JLT Benefit Solutions Limited and Simplyhealth Access are all authorised and 
regulated by the Financial Services Authority. 
------------------------------

This email and any files transmitted with it are confidential and intended solely for the use of the individual or entity to whom they are 
addressed. If you receive a message in error, please advise the sender and delete immediately.

Except where this email is sent in the usual course of our business, any opinions expressed in this email are those of the author and do not 
necessarily reflect the opinions of Age UK or its subsidiaries and associated companies. Age UK monitors all e-mail transmissions passing 
through its network and may block or modify mails which are deemed to be unsuitable.

Age Concern England (charity number 261794) and Help the Aged (charity number 272786) and their trading and other associated companies merged 
on 1st April 2009.  Together they have formed the Age UK Group, dedicated to improving the lives of people in later life.  The three national 
Age Concerns in Scotland, Northern Ireland and Wales have also merged with Help the Aged in these nations to form three registered charities: 
Age Scotland, Age NI, Age Cymru.






More information about the R-help mailing list