Input - Aster Analytics

Teradata Aster Analytics Foundation User Guide

Product
Aster Analytics
Release Number
6.21
Published
November 2016
Language
English (United States)
Last Update
2018-04-14
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kiu1466024880662.ditamap
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AA-notempfilter_pdf_output.ditaval
dita:id
B700-1021
lifecycle
previous
Product Category
Software
The GMMFit function has these input tables:
  • input_table
  • [Optional] init_params
GMMFit input_table Schema
Column Name Data Type Description
id Any Leftmost column, which identifies the data point.
dim_n SQL numeric data type The table has one such column for each dimension (n has the values 1 through D).

You can specify initial values for the weight, mean, and covariance of each cluster using the optional init_params table. If you want the function to automatically determine the initial values, you must use the clauseON (SELECT 1) AS init_params. Do not provide an empty table for init_params, or the function terminates without executing and produces no output table.

GMMFit init_params Table Schema
Column Name Data Type Description
weight SQL numeric data type Initial weight of the cluster. If you do not specify this value, then the function gives all clusters the same initial weight.
dim_n SQL numeric data type Initial mean of the cluster. If you do not specify this value, then the function selects the initial means from a multivariate standard normal distributed centered at the origin.

The table has one such column for each dimension (n has the values 1 through D).

covariance VARCHAR Initial covariance of the cluster. Possible values depend on CovarianceType:

'spherical': Positive numeric value (for example, 1.0.)

'diagonal': JSON representation of a DOUBLE PRECISION array (for example, [1.0,2.0,3.0,4.0])

'tied' or 'full': JSON representation of a two-dimensional DOUBLE PRECISION array (for example, [[1.0,2.0],[2.0,4.0]])

If you do not specify this value, then the function assigns each cluster an initial covariance matrix equal to the covariance matrix.