|  | ## Linear Regression

#### Synopsis

Linear regression.

#### Description

This operator calculates a linear regression model. It uses the Akaike criterion for model selection.

#### Input

- training set: expects: ExampleSet

#### Output

- model:
- exampleSet:
- weights:

#### Parameters

- feature selection: The feature selection method used during regression.
- eliminate colinear features: Indicates if the algorithm should try to delete colinear features during the regression.
- use bias: Indicates if an intercept value should be calculated.
- min standardized coefficient: The minimum standardized coefficient for the removal of colinear feature elimination.
- ridge: The ridge parameter used during ridge regression.

#### ExampleProcess