Exploitation of surrogate variables in random forests for unbiased analysis of mutual impact and importance of features

Abstract Motivation Random forest is a popular machine learning approach for the analysis of high-dimensional data because it is flexible and provides variable importance measures for the selection of relevant features. However, the complex relationships between the features are usually not consider...

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Veröffentlicht in:	Bioinformatics (Oxford, England) England), 2023-08, Vol.39 (8)
Hauptverfasser:	Voges, Lucas F, Jarren, Lukas C, Seifert, Stephan
Format:	Artikel
Sprache:	eng
Schlagworte:	Original Paper
Online-Zugang:	Volltext
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