| Argument | Category | Description |
|---|---|---|
| InputTable | Required | Specifies the name of the table that contains the features by which to cluster the data. |
| OutputTable | Required | Specifies the name of the table in which to output the centroids of the clusters. |
| ClusteredOutput | Optional | Specifies the name of the table in which to store the clustered output. If you omit this argument, the function does not generate a table of clustered output. |
| UnpackColumns | Optional | Specifies whether the means for each centroid appear unpacked (that is, in separate columns) in output_table. By default, the function concatenates the means for the centroids and outputs the result in a single VARCHAR column. |
| InitialSeeds | Optional | Specifies the initial seed means as strings of underscore-delimited DOUBLE PRECISION values. For example, this clause initializes eight clusters in eight-dimensional space: Means('50_50_50_50_50_50_50_50', '150_150_150_150_150_150_150_150', '250_250_250_250_250_250_250_250', '350_350_350_350_350_350_350_350', '450_450_450_450_450_450_450_450', '550_550_550_550_550_550_550_550', '650_650_650_650_650_650_650_650', '750_750_750_750_750_750_750_750') The dimensionality of the means must match the dimensionality of the data (that is, each mean must have n numbers in it, where n is the number of input columns minus one). By default, the algorithm chooses the initial seed means randomly. With InitialSeeds, the function uses a deterministic algorithm and the function supports up to 1596 dimensions.
|
| NumClusters | Optional | Specifies the number of clusters to generate from the data. Note: With NumClusters, the function uses a nondeterministic algorithm and the function supports up to 1543 dimensions. |
| CentroidsTable | Optional | The table that contains the initial seed means for the clusters. The schema of the centroids table depends on the value of the UnpackColumns argument. With CentroidsTable, the function uses a deterministic algorithm and the function supports up to 1596 dimensions.
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| Threshold | Optional | Specifies the convergence threshold. When the centroids move by less than this amount, the algorithm has converged. The default value is 0.0395. |
| MaxIterNum | Optional | Specifies the maximum number of iterations that the algorithm runs before quitting if the convergence threshold has not been met. The default value is 10. |