PROBABILISTIC DISTANCE CLUSTERING ADJUSTED FOR CLUSTER SIZE

摘要

The probabilistic distance clustering method of [1] works well if the cluster sizes are approximately equal. We modify that method to deal with clusters of arbitrary size and for problems where the cluster sizes are themselves unknowns that need to be estimated. In the latter case, our method is a viable alternative to the expectation-maximization (EM) method.