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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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146 views

Densest subgraph : density of an intersection

I found an exercice in my textbook and I can't find the answer : $G = (V;E)$ an undirected graph. $H_1 = (V_1;E_1)$ and $H_2 = (V_2;E_2)$ are two densest subgraphs in G, i.e., for any subgraph $H = …
azenor23's user avatar
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1 answer
148 views

Questions about a k-means variant : recompute centroids after each point is reasigned

I have a variant of k-means, where the points are reassigned incrementally and I have a few questions about it. Each time we reassign a point (we move the point from cluster $C_1 $to $C_2$), we …
azenor23's user avatar