A decision forest is a model composed of multiple decision trees whose predictions are aggregated to produce a final output. Common forms include random forests and gradient-boosted trees, which can improve predictive performance and robustness compared with a single tree.
A model created from multiple decision trees. A decision forest makes a prediction by aggregating the predictions of its decision trees. Popular types of decision forests include random forests and gradient boosted trees. See the Decision Forests section in the Decision Forests course for more information.