Dakota Reference Manual: regression_type

| Dakota Reference Manual Version 6.15 Explore and Predict with Confidence

- Main Page
- Related Pages

All Pages
regression_type

Type of solver for forming function train approximations by regression

## Specification

Alias: none

Argument(s): none

Child Keywords:

| Required/Optional | Description of Group | Dakota Keyword | Dakota Keyword Description
--- | --- | --- | --- | ---
| Required (Choose One) | Regression Type (Group 1) | 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.