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Cluster analysis is the task of partitioning data into subsets of objects according to their mutual "similarity," without using preexisting knowledge such as class labels. [Clustered-standard-errors and/or cluster-samples should be tagged as such; do NOT use the "clustering" tag for them.]

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Clustering procedure where each cluster has an equal number of points?

It's easy to think of a lot of clustering procedures that satisfy one or the other of these, but does anyone know of a way to get both at once? …
Not Durrett's user avatar