Stepwise Regression
Variable selection in linear regression model using stepwise
regression
Stepwise regression is a dimensionality reduction method in which less
important predictor variables are successively removed in an automatic
iterative process. You can perform stepwise regression with or without the
LinearModel
object, or by using the Regression Learner app.
Apps
Regression Learner | Train regression models to predict data using supervised machine learning |
Functions
Objects
LinearModel | Linear regression model |
Topics
- Stepwise Regression
In stepwise regression, predictors are automatically added to or trimmed from a model.
- Linear Regression with Interaction Effects
Construct and analyze a linear regression model with interaction effects and interpret the results.
- Wilkinson Notation
Wilkinson notation provides a way to describe regression and repeated measures models without specifying coefficient values.