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ClusterPoints3D


Module: FoundationPro

Clusters 3D points using K Means Clustering method.

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

Complexity Level

This filter is available on Expert Complexity Level.