SVMDense Example | Teradata Vantage - SVMDense Example: Linear Model - Teradata Vantage

Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
9.02
9.01
2.0
1.3
Published
February 2022
Language
English (United States)
Last Update
2022-02-10
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rnn1580259159235.ditamap
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dita:id
B700-4003
lifecycle
previous
Product Category
Teradata Vantageā„¢

The dense SVM linear model is similar to the model created by the sparse SVM function.

SQL Call

DROP TABLE densesvm_iris_linear_model;

SELECT * FROM SVMDense (
  ON svm_iris_train AS InputTable
  OUT TABLE ModelTable (densesvm_iris_linear_model)
  USING
  IDColumn ('id')
  TargetColumns ('[1:4]')
  ResponseColumn ('species')
  RegularizationLambda (1)
  Bias (0)
  KernelFunction ('linear')
  MaxIternum (10000)
  StopThreshold (0.01)
  Seed (9230842)
) AS dt;

Output

message                                                                                   --------------------------------------------------------------------------------- 
Model table is created successfully
The model is trained with 120 samples and 4 unique attributes
There are 3 different classes in the training set
The model is not converged after 10000 steps with epsilon 0.01, the average value of the loss function for the training set is 31.728128146251176
The corresponding training parameters are cost:1.0 bias:0.0

Download a zip file of all examples and a SQL script file that creates their input tables.