Contents

MLBoostedTreeClassifier

A classifier based on a collection of decision trees combined with gradient boosting.

Declaration

struct MLBoostedTreeClassifier

Overview

A boosted tree classifier combines several MLDecisionTreeClassifier models (a technique known as ensemble learning) by training each model to correct the errors of the preceding model.

This model is useful for handling numerical and categorical features, but is less suitable for sparse data such as text.

Topics

Training a boosted tree classifier asynchronously

Creating a boosted tree classifier from a checkpoint

Training a boosted tree classifier synchronously

Evaluating a boosted tree classifier

Testing a boosted tree classifier

Saving a boosted tree classifier

Inspecting a boosted tree classifier

Describing a boosted tree classifier

Default Implementations

See Also

Supporting classifier types