Comments (2)
Alternative solution (not tested):
x.sub <- X[clus.labels == clID, , drop=FALSE]
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Ok, I had to change a few more things with how it calculates distances between clusters, but that should be fine now. Just be aware that when it says "Using adjusted diagonal covariance matrix," that means it's only using the true covariance matrix up to the number of dimensions equal to the smallest cluster size. So if the smallest cluster size is 1, it's really just using the diagonal covariance matrix (which may make for some unintuitive connections in the tree).
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