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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.