Seeding the Set of Cluster Centers

Any K-Means model may be used as seed value to Lloyd's algorithm. In fact, our clusterers accept multiple seed sets. The K-Means.train helper methods allows one to name an initialization method.

Two algorithms are implemented that produce viable seed sets. They may be constructed by using the apply method of the companion objectKMeansSelector".

Name	Algorithm
KMeansSelector.RANDOM	Random selection of initial k centers
KMeansSelector.K_MEANS_PARALLEL	a 5 step K-Means Parallel implementation

You may create a KMeansSelector using the apply method of the KMeansSelector companion object.

package com.massivedatascience.clusterer

object KMeansSelector {
  def apply(name: String): KMeansSelector = ???
}