Martin,
The cutree() function returns the cluster membership as a vector.
To get a similar result from pam() (and other functions in library
cluster) you need to extract the component $clustering, e.g.
> clustersA <- pam(distances, nkA, diss=TRUE)
> filenameclu = paste("filenameclu", ".txt")
> write.table(clustersA$clustering, file=filenameclu,sep=",")
Note the $clustering appended to the pam object.
Dave R.
Martin Tomko wrote:
> Hello list,
>
> the following approach did not work:
>
> clustersA <- pam(distances, nkA, diss=TRUE);
> gc();
> filenameclu = paste("filenameclu", ".txt");
> write.table(clustersA , file=filenameclu,sep=",");
>
> although it worked with
> clustersA <- hclust(distances, method="ward");
> and a consecutive
> kclassA <- cutree(clustersA, k=nkA);
> filename = paste("clusters", ".txt");
> write.table(kclassA,file=filename,sep=",",col.names=TRUE,row.names=TRUE);
>
> Is there a <em>generic</em> method to export cluster object? I know that
> pam is different (cluster object and some more data)- how can I extract
> & export the clustering into a table with two columns, ID =
> dissimilarity matrix row, and cluster = number of the cluster?
>
> I waas using sink to get the data, but for large matrices it involves a
> huge amount of manual formatting afterwards, let's say in excel.
>
> Thanks many times
> Martin
>
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>
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