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Regression Learner App

Interactively train, validate, and tune regression models

Choose between various algorithms to train and validate regression models. After training multiple models, compare their validation errors side-by-side, and then choose the best model. To help you decide which algorithm to use, see Train Regression Models in Regression Learner App.


Regression LearnerTrain regression models to predict data using supervised machine learning


Regression Workflow

Train Regression Models in Regression Learner App

Workflow for training, comparing and improving regression models, including automated, manual, and parallel training.

Select Data and Validation for Regression Problem

Import data into Regression Learner from the workspace or files, find example data sets, and choose cross-validation or holdout validation options.

Choose Regression Model Options

In Regression Learner, automatically train a selection of models, or compare and tune options of linear regression models, regression trees, support vector machines, Gaussian process regression models, and ensembles of regression trees.

Feature Selection and Feature Transformation Using Regression Learner App

Identify useful predictors using plots, manually select features to include, and transform features using PCA in Regression Learner.

Assess Model Performance in Regression Learner

Compare model statistics and visualize results.

Export Plots in Regression Learner App

Export and customize plots created before and after training.

Export Regression Model to Predict New Data

After training In Regression Learner, export models to the workspace or generate MATLAB® code.

Regression Examples

Train Regression Trees Using Regression Learner App

Create and compare regression trees, and export trained models to make predictions for new data.

Related Information