Sandia National Laboratories

# regression_type

Type of solver for forming function train approximations by regression

Specification

- Alias: None

- Arguments: None

Child Keywords:

Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description
--- | --- | --- | ---
Required (Choose One) | Regression Type | ls | Use least squares solver for forming function train approximations by regression
rls2 | Use regularized regression solver for forming function train approximations

Description

Function train approximations are formed based on regression for the set of coefficients described at `function_train`. Solver options include least squares and regularized regression, where the latter penalizes high-order terms to mitigate overfitting.

Default Behavior

The default regression solver is least squares.

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