To interactively grow a regression tree, use the Regression Learner app. For greater flexibility, grow a regression tree using fitrtree at the command line. After growing a regression tree, predict responses by passing the tree and new predictor data to predict.
| Regression Learner | Train regression models to predict data using supervised machine learning |
RegressionTree | Regression tree |
CompactRegressionTree | Compact regression tree |
RegressionPartitionedModel | Cross-validated regression model |
Train Regression Trees Using Regression Learner App
Create and compare regression trees, and export trained models to make predictions for new data.
Supervised Learning Workflow and Algorithms
Understand the steps for supervised learning and the characteristics of nonparametric classification and regression functions.
Understand decision trees and how to fit them to data.
To grow decision trees, fitctree and
fitrtree apply the standard CART algorithm by default to
the training data.
Create and view a text or graphic description of a trained decision tree.
Improving Classification Trees and Regression Trees
Tune trees by setting name-value pair arguments in
fitctree and fitrtree.
Prediction Using Classification and Regression Trees
Predict class labels or responses using trained classification and regression trees.
Predict Out-of-Sample Responses of Subtrees
Predict responses for new data using a trained regression tree, and then plot the results.