Jaccard dissimilarity matrix for PCA

[Flabbergaster]

Hi
I have a large dataset, containing a wide range of binary variables.
I would like first of all to compute a jaccard matrix, then do a PCA on this matrix, so that I finally can do a hierarchical clustering on the principal components.
My problem is, that I don't know how to compute the jaccard dissimilarity matrix in R? Which package to use, and so on...
Can anybody help me?
Alternatively I'm search for another way to explore the clusters present in my data.
Another problem is, that I have cases with missing values on different variables.

Jacob

[Marcelo Luiz de Laia]

Flabbergaster <jlunding <at> gmail.com> writes:
> My problem is, that I don't know how to compute the jaccard dissimilarity
> matrix in R? Which package to use, and so on...

http://rss.acs.unt.edu/Rdoc/library/arules/html/dissimilarity.html

http://cc.oulu.fi/~jarioksa/softhelp/vegan/html/vegdist.html

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[David L Lorenz]

Jacob,
  You might have a look at the vegan package. It might compute the Jaccard
distance and it might have some other toolsa that you might be interested
in.
Dave




From:
Flabbergaster <[hidden email]>
To:
[hidden email]
Date:
12/28/2010 08:26 AM
Subject:
[R] Jaccard dissimilarity matrix for PCA
Sent by:
[hidden email]




Hi
I have a large dataset, containing a wide range of binary variables.
I would like first of all to compute a jaccard matrix, then do a PCA on
this
matrix, so that I finally can do a hierarchical clustering on the
principal
components.
My problem is, that I don't know how to compute the jaccard dissimilarity
matrix in R? Which package to use, and so on...
Can anybody help me?
Alternatively I'm search for another way to explore the clusters present
in
my data.
Another problem is, that I have cases with missing values on different
variables.

Jacob
--
View this message in context:
http://r.789695.n4.nabble.com/Jaccard-dissimilarity-matrix-for-PCA-tp3165982p3165982.html

Sent from the R help mailing list archive at Nabble.com.

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and provide commented, minimal, self-contained, reproducible code.



        [[alternative HTML version deleted]]

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[Christian Hennig]

jaccard in package prabclus computes a Jaccard matrix for you.

By the way, if you want to do hierarchical clustering, it doesn't seem to
be a good idea to me to run PCA first. Why
not cluster the dissimilarity matrix directly without information loss by
PCA? (I should not make too general statements on this because generally
how to cluster data always depends on the aim of clustering, the cluster
concept you are interested in etc.)

prabclus also contains clustering methods for such data; have a
look at the functions prabclust and hprabclust (however, they are
documented as functions for clustering species distribution ranges, so if
your application is different, you may have to think about whether and how
to adapt them).

Hope this helps,
Christian




On Tue, 28 Dec 2010, Flabbergaster wrote:

>
> Hi
> I have a large dataset, containing a wide range of binary variables.
> I would like first of all to compute a jaccard matrix, then do a PCA on this
> matrix, so that I finally can do a hierarchical clustering on the principal
> components.
> My problem is, that I don't know how to compute the jaccard dissimilarity
> matrix in R? Which package to use, and so on...
> Can anybody help me?
> Alternatively I'm search for another way to explore the clusters present in
> my data.
> Another problem is, that I have cases with missing values on different
> variables.
>
> Jacob
> --
> View this message in context: http://r.789695.n4.nabble.com/Jaccard-dissimilarity-matrix-for-PCA-tp3165982p3165982.html
> Sent from the R help mailing list archive at Nabble.com.
>
> ______________________________________________
> [hidden email] 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.
>

*** --- ***
Christian Hennig
University College London, Department of Statistical Science
Gower St., London WC1E 6BT, phone [phone]
[hidden email], www.homepages.ucl.ac.uk/~ucakche

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[Flabbergaster]

This sounds like something I could use..
I'm kind of new with R, meaning I've having some minor troubles all the time...
Say I have a range of binary(0,1) variables X1 to Xn, with missing data for different cases.
At the moment my data is a binary indicator matrix; rows representing the i individuals or subjects, columns representing presence(1)/absence(0) of various characteristics.
Actually I have 5 groups of variables (102 variables in total), describing different aspects of the subject(s) I'm studying (people; i.e. refugees).
O -> O1 to O43
A -> A1 to A38
R -> R1 to R6
AP -> AP1 to AP8
PT -> PT1 to PT7

Can someone help me with the programming of a jaccard matrix in prabclus (or in any other package). I'm having troubles defining the input-object to the function, I think?
I get error messages like:
'x' must be an array of at least two dimensions
ERROR:  argument is not a matrix

Jacob

Christian Hennig wrote

jaccard in package prabclus computes a Jaccard matrix for you.