A random forest guided tour

The random forest algorithm, proposed by L. Breiman in 2001, has been extremely successful as a general-purpose classification and regression method. The approach, which combines several randomized decision trees and aggregates their predictions by averaging, has shown excellent performance in setti...

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Veröffentlicht in:	Test (Madrid, Spain) Jg. 25; H. 2; S. 197 - 227
Hauptverfasser:	Biau, Gérard, Scornet, Erwan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.06.2016 Springer Nature B.V Spanish Society of Statistics and Operations Research/Springer
Schlagworte:	Aggregates Algorithms Classification Datasets Decision trees Distance learning Economics Finance Insurance Invited Paper Learning Management Mathematical analysis Mathematics Mathematics and Statistics Regression Regression analysis Statistical Theory and Methods Statistics Statistics for Business Studies Survival analysis Tasks United States > US Randomization Resampling Variable importance 62G02 Parameter tuning Random forests
ISSN:	1133-0686, 1863-8260
Online-Zugang:	Volltext
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