code: public static StandardKMeans_F64 kMeans_F64( KMeansInitializers initializer,
  												 int maxIterations, int maxConverge , double convergeTol) {
  		InitializeKMeans_F64 seed;
  
  		if( initializer == null ) {
  			seed = new InitializePlusPlus();
  		} else {
  			switch (initializer) {
  				case PLUS_PLUS:
  					seed = new InitializePlusPlus();
  					break;
  
  				case STANDARD:
  					seed = new InitializeStandard_F64();
  					break;
  
  				default:
  					throw new RuntimeException("Unknown initializer " + initializer);
  			}
  		}
  		return new StandardKMeans_F64(maxIterations,maxConverge,convergeTol,seed);
  	}
docs: High level interface for creating k-means cluster.  If more flexibility is needed (e.g. custom seeds)
  then create and instance of {@link org.ddogleg.clustering.kmeans.StandardKMeans_F64} directly
  
  @param initializer Specify which method should be used to select the initial seeds for the clusters.  null means default.
  @param maxIterations Maximum number of iterations it will perform.
  @param maxConverge Maximum iterations allowed before convergence.  Re-seeded if it doesn't converge.
  @param convergeTol Distance based convergence tolerance.  Try 1e-8
  @return StandardKMeans_F64