Build decision trees and random forests for classification and regression. The implementation strikes a balance between minimizing computing efforts and maximizing the expected predictive accuracy, thus scales well to large data sets. Multi-threading is available through 'OpenMP'.
brif to build a random forest and (optionally) make predictions.
brifTree to build a single decision tree.
printRules to print out the decision rules of a tree.
predict.brif to make predictions using a brif model (tree or forest).