English, Article edition: IDENTIFYING THE MOST INFORMATIVE VARIABLES FOR DECISION-MAKING PROBLEMS - A SURVEY OF RECENT APPROACHES AND ACCOMPANYING PROBLEMS Pavel Pudil; Petr Somol

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Bookmark: http://trove.nla.gov.au/version/197187
Physical Description
  • article
Language
  • English

Edition details

Title
  • IDENTIFYING THE MOST INFORMATIVE VARIABLES FOR DECISION-MAKING PROBLEMS - A SURVEY OF RECENT APPROACHES AND ACCOMPANYING PROBLEMS
Author
  • Pavel Pudil
  • Petr Somol
Physical Description
  • article
Notes
  • 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.
  • variable selection, feature selection, machine learning, decision rules, classification
  • RePEc:prg:jnlaop:v:2008:y:2008:i:4:id:131:p:37-55
Language
  • English
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