K Means VAL

The function performs fast K-Means clustering algorithm and returns cluster means and averages. Specifically, the rows associated with positive cluster IDs in output contain the average values of each of the clustered columns and the count for each cluster ID. The rows associated with negative cluster IDs contain the variance of each of the clustered columns for each cluster ID. There is an additional optional input table that specifies the dataset containing clustering output.

Options

Centers
Specifies the number of clusters to be contained in the cluster model.
Input Columns
Specifies the name(s) of the column(s) to be used in clustering.
Maximum Iterations
Specifies the maximum number of iterations to perform during clustering.
Threshold
Specifies the value which determines if the algorithm has converged based on how much the cluster centroids change from one iteration to the next.
Output Schema
Output Schema, if Volatile is true then use user login as the schema.
Output Table
Output Table
VAL Location
VAL Location

Input Ports

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Connection to a Teradata Database Instance
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K Means VAL input
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K Means VAL input

Output Ports

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K Means VAL output

Nodes

Extensions

Links

Download

To use this component in KNIME, download it from the below URL and open it in KNIME:

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On NodePit since: 2023-12-01
Last update: 2026-01-10
Created with KNIME version: v4.7.0

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