Identifying the most Informative Variables for Decision-Making Problems - a Survey of Recent Approaches and Accompanying Problems
Pavel Pudil, Petr Somol · Acta Oeconomica Pragensia · 2008
In the following paper, 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. Common research issues in management and medicineThough managers, economists and physicians have different priorities in research issues, there exist issues common to both the fields.They include the problem of selecting only that information which is necessary (and sufficient, if possible) for decision-making.37 P. Pudil -P.Somol Identifying the most informative variables for decision-making problems ...