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ClusterPoints3D

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Clusters 3D points using K Means Clustering method.

	Name	Type	Range	Description
	inPoints	Point3DArray		Array of points to cluster
	inClusters	Integer	2 - +	Number of clusters to extract
	inMaxIterations	Integer	10 - 1000	Maximal number of KMeans iterations
	inSeed	Integer*	0 - +	Seed used to initialize random number generators
	inRunCount	Integer	1 - +	Defines how many times the algorithm will be executed
	outClusters	Point3DArray?Array		Resulting Point3D clusters
	outCentroids	Point3D?Array		Center of found clusters
	outDistanceSum	Real		Sum of distance squares from points in array to its respective cluster center

Complexity Level