Yikes, you are correct!  Thank you so much.  I reran the analysis with the
rows and columns switched and it took no time at all.

Thank you again for your help.

On Tue, Nov 17, 2009 at 12:04 PM, Charles C. Berry <cberry@tajo.ucsd.edu>wrote:

> On Tue, 17 Nov 2009, akonla wrote:
>
>
>> Hi,
>>
>> I am new to clustering in R and I have a dataset with approximately 17,000
>> rows and 8 columns with each data point a numerical character with three
>> decimal places.  I would like to cluster the 8 columns so that I get a
>> dendrogram as an output.  So, I am simply creating a distance matrix of my
>> data, using the 'hclust' function, and then plotting the results (see
>> below,
>> my data is contained in the text file).
>>
>> x<-read.table('SEP_IR_1113_3.txt', header=TRUE,sep="\t')
>> x.dist=dist(x)
>>
>
>
> See
>
>        ?dist
>
> which explains
>
>
>     This function computes and returns the distance matrix computed by
>     using the specified distance measure to compute the distances
>     between the rows of a data matrix.
>
> You are trying to cluster 17,000 rows.
>
> No wonder it (dist) is taking its time!
>
> Chuck
>
>  hc=hclust(x.dist,method="average")
>> plot(hc, hang=-1)
>>
>> Unfortunately, the hclust function, although it produces no error terms,
>> takes a very long time to run  (>4 hours) and my computer kills the
>> program
>> before it finishes.  I don't think this data set is so large to cause such
>> a
>> long computing time, and I have plenty of memory since I am running this
>> analysis on our university computing cluster.
>>
>> Has anyone run into this problem before and does anyone have any tips on
>> how
>> I can speed up processing?  I can provide extra information if necessary
>> regarding my problem.
>>
>> Thank you!
>> --
>> View this message in context:
>> http://old.nabble.com/hclust-too-slow--tp26395774p26395774.html
>> Sent from the R help mailing list archive at Nabble.com.
>>
>> ______________________________________________
>> 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.
>>
>>
> Charles C. Berry                            (858) 534-2098
>                                            Dept of Family/Preventive
> Medicine
> E mailto:cberry@tajo.ucsd.edu               UC San Diego
> http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901
>
>
>

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