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