Navigating random forests and related advances in algorithmic modeling

Research output: Contribution to journalArticle

76 Citations (Scopus)

Abstract

This article addresses current methodological research on non-parametric Random Forests. It provides a brief intellectual history of Random Forests that covers CART, boosting and bagging methods. It then introduces the primary methods by which researchers can visualize results, the relationships between covariates and responses, and the out-of-bag test set error. In addition, the article considers current research on universal consistency and importance tests in Random Forests. Finally, several uses for Random Forests are discussed, and available software is identified.

Original languageEnglish (US)
Pages (from-to)147-163
Number of pages17
JournalStatistics Surveys
Volume3
DOIs
StatePublished - 2009
Externally publishedYes

Fingerprint

Random Forest
Modeling
Bagging
Boosting
Test Set
Covariates
Cover
Software

Keywords

  • Algorithmic methods
  • Bagging
  • Boosting
  • CART
  • Ensemble and committee methods
  • Non-parametrics
  • Random forests

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

Navigating random forests and related advances in algorithmic modeling. / Siroky, David.

In: Statistics Surveys, Vol. 3, 2009, p. 147-163.

Research output: Contribution to journalArticle

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