This node outputs the cluster centers for a predefined number of
clusters (no dynamic number of clusters).
K-means performs a crisp
clustering that assigns a data
vector to exactly one cluster. The
algorithm terminates when the
cluster assignments do not change
The clustering algorithm uses the Euclidean distance on the selected attributes. The data is not normalized by the node (if required, you should consider to use the "Normalizer" as a preprocessing step).
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