Train an ensemble of classifiers using a subset of the data for each base classifier. Parameters ---------- b

Decision tree node which always predicts the same value.

Decision tree which only inspects a random subset of the features at each split. Uses Gini impurity to compare possible data splits. Para

A decision tree whose splits are hyperplanes. Used as base learner for oblique random forests. For more information, see 'On oblique random

Do not use this directly, instead train an ObliqueTree

Basic decision tree interior node.

Base class for ClusteredRegression and ClusteredClassifier