Consider partitioning clustering and the following constraint on clusters: The number of objects in each cluster must

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Consider partitioning clustering and the following constraint on clusters: The number of objects in each cluster must be between \(\frac{n}{k}(1-\delta)\) and \(\frac{n}{k}(1+\delta)\), where \(n\) is the total number of objects in the data set, \(k\) is the number of clusters desired, and \(\delta\) 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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Data Mining Concepts And Techniques

ISBN: 9780128117613

4th Edition

Authors: Jiawei Han, Jian Pei, Hanghang Tong

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