Anzeige
Erschienen in:
2010 | OriginalPaper | Buchkapitel
A Study of Strength and Correlation in Random Forests
verfasst von : Simon Bernard, Laurent Heutte, Sébastien Adam
Erschienen in: Advanced Intelligent Computing Theories and Applications
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
In this paper we present a study on the Random Forest (RF) family of classification methods, and more particularly on two important properties called
strength
and
correlation
. These two properties have been introduced by Breiman in the calculation of an upper bound of the generalization error. We thus propose to experimentally study the actual relation between these properties and the error rate in order to confirm and extend the Breiman theoretical results. We show that the error rate statistically decreases with the joint maximization of the
strength
and minimization of the
correlation
, and this for different sizes of RF.