1.0 - 8.00 - LAR Arguments - Teradata Vantage

Teradata® Vantage Machine Learning Engine Analytic Function Reference

Product
Teradata Vantage
Release Number
1.0
8.00
Release Date
May 2019
Content Type
Programming Reference
Publication ID
B700-4003-098K
Language
English (United States)
OutputTable
Specify the name of the output table.
TargetColumns
Specify the names of the columns of the input table that contain the response and predictors.

This is the syntax of predictor_columns:

{col[,...] | [start_column:end_column]}[,...]

where col is a column name and start_column and end_column are the column indexes of the first and last columns in a range of columns. The range includes start_column and end_column.

The leftmost column has column index 0, the column to its immediate right has column index 1, and so on.

  • In a column range, brackets do not indicate optional elements. You must include the bracket characters (for example, '[2:6]').
  • This function can take at most 799 response and predictor variables.
FitMethod
[Optional] Specify the method to use for linear regression.
Default: 'lasso'
Intercept
[Optional] Specify whether an intercept is included in the model (and not penalized).
Default: 'true'
L2Normalization
[Optional] Specify whether each predictor is standardized to have unit L2 norm.
Default: 'true'
MaxIterNum
[Optional] Specify the maximum number of steps the function runs.
Default: 8*min(number_of_predictors, sample_size - intercept). For example, if the number of predictors is 11, the sample size (number of rows in the input table) is 1532, and the intercept is 1, then the default value is 8*min(11, 1532 - 1) = 88.