Identifying the most Informative Variables for Decision-Making Problems - a Survey of Recent Approaches and Accompanying Problems
AbstractWe provide an overview of problems related to variable selection (also known as feature selection) techniques in decision-making problems based on machine learning with a particular emphasis on recent knowledge. Several popular methods are reviewed and assigned to a taxonomical context. Issues related to the generalization-versus-performance trade-off, inherent in currently used variable selection approaches, are addressed and illustrated on real-world examples.
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Bibliographic InfoArticle provided by University of Economics, Prague in its journal Acta Oeconomica Pragensia.
Volume (Year): 2008 (2008)
Issue (Month): 4 ()
Postal: Redakce Acta Oeconomica Pragensia, Vysoká škola ekonomická v Praze, nám. W. Churchilla 4, 130 67 Praha 3
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- Dernoncourt, David & Hanczar, Blaise & Zucker, Jean-Daniel, 2014. "Analysis of feature selection stability on high dimension and small sample data," Computational Statistics & Data Analysis, Elsevier, Elsevier, vol. 71(C), pages 681-693.
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