A note on constrained k-means algorithms

摘要

This paper describes extensions to the k-means algorithm for clustering data sets. By adding suitable constraints into the mathematical program formulation, an approach is developed, which allows the use of the k-means paradigm to efficiently cluster data sets with the fixed number of objects in each cluster. The new algorithm is presented and the effectiveness of the algorithm is demonstrated with experimental results.