GMM Example 1: Basic GMM, Spherical Covariance, Packed Output - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
8.00
1.0
Published
May 2019
Language
English (United States)
Last Update
2019-11-22
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blj1506016597986.ditamap
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B700-4003
lifecycle
previous
Product Category
Teradata Vantage™

SQL Call

SELECT * FROM GMM (
  ON (SELECT 1) AS init_params PARTITION BY 1
  ON gmm_iris_train AS InputTable
  OUT TABLE OutputTable (gmm_output_ex1)
  USING
  ClusterNum (3)
  CovarianceType ('spherical')
  MaxIterNum (10)
  PackOutput (1)
) AS dt;

Output

Because the SQL call specifies PackOutput (1), a single mean column displays a vector containing the mean value for each dimension.

Output Message Table
property value
Output Table Table Name Specified in OutputTable argument
Algorithm Used Basic GMM
   
Stopping Criterion Iteration limit reached
Delta Log Likelihood 0.001690
Number of Iterations 10
Number of Clusters 3
Covariance Type spherical
   
Number of Data Points 120
Global Mean [5.866, 3.055, 3.770, 1.205]
Global Covariance [[0.7197, -0.04204, 1.326, 0.5265], [-0.04204, 0.1916, -0.3241, -0.1213], [1.326, -0.3241, 3.167, 1.298], [0.5265, -0.1213, 1.298, 0.5708]]
   
Log Likelihood -355.212
Akaike Information Criterion 744.425 on 17 parameters
Bayesian Information Criterion 791.812 on 17 parameters

This query returns the following table:

SELECT * FROM gmm_output_ex1 ORDER BY cluster_id;
gmm_output_ex1
cluster_id points_assigned covariance_type weight mean covariance determinant prec
0 1 spherical 0.00833333333333333 [4.5, 2.299999952316284, 1.2999999523162842, 0.30000001192092896] 1.0E-12 1e-48 1.0E12
1 39 spherical 0.324999998499867 [5.010256409188803, 3.446153855805786, 1.44615384307372, 0.2512820560787926] 0.07235370835810885 2.74058439183871e-05 13.820991662937034
2 80 spherical 0.6666666681668 [6.299999998810371, 2.873750007907585, 4.9337499775605185, 1.6812499819268993] 0.3514238290308256 0.0152519307815099 2.84556685514995