Transcription of Classification and Regression by randomForest
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Classification and Regression by randomForest
,December200218 ClassificationandRegressionbyrandomFores tAndyLiawandMatthewWienerIntroductionRec entlytherehasbeenalotofinterestin ensem-blelearning (see, ,Shapireetal.,1998)andbaggingBreiman(199 6) , , ,successivetreesdonotdependonearliertree s , (2001)proposedrandomforests, , , , ,includingdiscriminantanalysis,supportve ctorma-chinesandneuralnetworks,andisrobu stagainstoverfitting(Breiman,2001).Inadd ition,itisveryuser-friendlyinthesensetha tithasonlytwoparam-eters(thenumberofvari ablesintherandomsubsetateachnodeandthenu mberoftreesintheforest), ( ).
ging, successive trees do not depend on earlier trees — each is independently constructed using a boot-strap sample of the data set. In the end, a simple majority vote is taken for prediction. Breiman (2001) proposed random forests, which add an additional layer of …
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