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Consider partitioning clustering and the following constraint on clusters: the number of objects in each cluster must be between n k(1 −δ) and n k(1 +δ), where n is the total number of objects in the data set, k is the number of clusters desired, and δ in [0,1) is a parameter. can you extend the k-means method to handle this constraint? discuss situations where the constraint is hard and soft.

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