IDENTIFYING THE MOST INFORMATIVE VARIABLES FOR DECISION-MAKING PROBLEMS - A SURVEY OF RECENT APPROACHES AND ACCOMPANYING PROBLEMS

Pavel Pudil and Petr Somol

Acta Oeconomica Pragensia, 2008, vol. 2008, issue 4, pages 37-55

Abstract: We 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.

Keywords: variable selection; machine learning; feature selection; decision rules; classification (search for similar items in EconPapers)
JEL-codes: C60 C80 (search for similar items in EconPapers)
Date: 2008
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