TD_KMeans Output - Teradata Vantage

Teradata® VantageCloud Lake
Deployment
VantageCloud
Edition
Lake
Product
Teradata Vantage
Published
January 2023
Language
English (United States)
Last Update
2024-04-03
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Output Table Schema

If the OutputClusterAssignment value is set to False:

Column Data Type Description
TD_CLUSTERID_KMEANS BIGINT The unique identifier of the cluster.
TargetColumns REAL The columns that contain the centroid value for each feature.
TD_SIZE_KMEANS BIGINT The number of points in the cluster.
TD_WITHINSS_KMEANS REAL The within-cluster-sum-of-squares, that is, the sum of squared differences of each point from its cluster centroid.
Id_Column BYTEINT The unique identifier column name copied from the InputTable. This column contains only NULL values in the output.
TD_MODELINFO_KMEANS VARCHAR(128) CHARACTER SET LATIN The following information related to the model is saved:
  • Converged: True or False
  • Number of Iterations: The number of iterations performed by the function.
  • Number of Clusters: The number of clusters produced.
  • Total_WithinSS: The total within cluster sum of squares.
  • Between_SS: Between sum of squares, that is, the sum of squared distances of centroids to global mean, where squared distance of each mean to global mean is multiplied by the number of data points it represents.
  • Method for InitialCentroids: 'Random' or 'KMeans++' or 'Externally supplied InitialCentroidsTable'.

If the OutputClusterAssignment value is set to True:

Column Data Type Description
Id_Column Any The unique identifier of input rows copied from the input table.
TD_CLUSTERID_KMEANS BIGINT The ClusterId assigned to the input row.