1.1 - 8.10 - SVMDense Example: Linear Model - Teradata Vantage

Teradata Vantage™ - Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.1
8.10
Release Date
October 2019
Content Type
Programming Reference
Publication ID
B700-4003-079K
Language
English (United States)

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 (100)
  Seed (1)
) 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 converged after 54 steps with epsilon 0.01, the average value of the loss function for the training set is 48.19309231543506
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 from the attachment in the left sidebar.