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Identifying The Most Informative Variables For Decision-Making Problems - A Survey Of Recent Approaches And Accompanying Problems

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Author Info
Pavel Pudil
Petr Somol
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.

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Publisher Info
Article provided by University of Economics, Prague in its journal Acta Oeconomica Pragensia.

Volume (Year): 2008 (2008)
Issue (Month): 4 ()
Pages: 37-55
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Handle: RePEc:prg:jnlaop:v:2008:y:2008:i:4:id:131:p:37-55

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Related research
Keywords: variable selection; machine learning; feature selection; decision rules; classification;

Find related papers by JEL classification:
C60 - Mathematical and Quantitative Methods - - Mathematical Methods and Programming - - - General
C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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