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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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Incremental hierarchical clustering

If you use a hierarchical clustering algorithm instead of a partitional clustering algorithm like K-means, then a tree-like data structure is already generated for you. … In particular, BIRCH clustering might be a good fit for this, as it scales well and produces a balanced tree. My apologies if I'm missing something. …
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