Random Forests BT - Ensemble Machine Learning: Methods and Applications

Abstract

Random Forests were introduced by Leo Breiman [6] who was inspired by earlier work by Amit and Geman [2]. Although not obvious from the description in [6], Random Forests are an extension of Breiman’s bagging idea [5] and were developed as a competitor to boosting. Random Forests can be used for either a categorical response variable, referred to in [6] as “classification,” or a continuous response, referred to as “regression.” Similarly, the predictor variables can be either categorical or continuous.