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
anymore.
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).
Options
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PMML Writer3 %- Excel Writer2 %
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Map Viewer< 1 %- HTML Parser< 1 %
Views
- Cluster View
- Displays the cluster prototypes in a tree-like structure, with each node containing the coordinates of the cluster center.
Workflows
(3D) Fragment library design workflowKNIME Hub- 01_AnalyticsKNIME Hub
- 01_AnalyticsKNIME Hub
- 01_B2B_Customer_AnalyticsKNIME Hub
- 01_Basic_Customer_Segmentation_Use_CaseKNIME Hub
- Show all 657 workflows
Links
- No links available
Developers
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