Random Forests were introduced by Leo Breiman  who was inspired by earlier work by Amit and Geman . Although not obvious from the description in , Random Forests are an extension of Breiman’s bagging idea  and were developed as a competitor to boosting. Random Forests can be used for either a categorical response variable, referred to in  as “classification,” or a continuous response, referred to as “regression.” Similarly, the predictor variables can be either categorical or continuous.
KeywordsRandom Forest Regression Tree Terminal Node Variable Importance Generalization Error
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