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KmeansClustering3 Node

KmeansClustering2 node groups the data into clusters based on the values of the three input features.

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Category

Terrain Features/Clustering

Inputs

Name Type Description
feature 1 VirtualArray First measurable property or characteristic of the data points being analyzed (e.g elevation, gradient norm, etc...
feature 2 VirtualArray First measurable property or characteristic of the data points being analyzed (e.g elevation, gradient norm, etc...
feature 3 VirtualArray Third measurable property or characteristic of the data points being analyzed (e.g elevation, gradient norm, etc...

Outputs

Name Type Description
output VirtualArray Cluster labelling.

Parameters

Name Type Description
nclusters Integer Number of clusters.
normalize_inputs Bool Determine whether the feature amplitudes are normalized before the clustering.
Seed Random seed number Random seed number. The random seed is an offset to the randomized process. A different seed will produce a new result.
weights.x Float Weight of the first feature.
weights.y Float Weight of the third feature.
weights.z Float TODO

Example

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