Provides common functionality for building decision trees, irrespective of the predicted
Output. Also has implementations of Random Forests and Extra Trees.
ClassDescriptionAbstractCARTTrainer<T extends Output<T>>Base class for
Trainer's that use an approximation of the CART algorithm to build a decision tree.Deprecated.AbstractTrainingNode<T extends Output<T>>Base class for decision tree nodes used at training time.Contains parameters needed to determine whether a node is a leaf.DecisionTreeTrainer<T extends Output<T>>A tag interface for a
Trainerso the random forests trainer can check if it's actually a tree.ExtraTreesTrainer<T extends Output<T>>A trainer which produces an Extremely Randomized Tree Ensemble.An immutable leaf
Nodethat can create a prediction.A node in a decision tree.RandomForestTrainer<T extends Output<T>>A trainer which produces a random forest.An immutable
Nodewith a split and two child nodes.