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Pattern Recognition and String Matching
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SYSNO ASEP 0410987 Document Type M - Monograph Chapter R&D Document Type Monograph Chapter Title Recent feature selection methods in statistical pattern recognition Author(s) Pudil, Pavel (UTIA-B) RID
Novovičová, Jana (UTIA-B)
Somol, Petr (UTIA-B) RIDIssue data Dordrecht: Kluwer, 2003 ISBN 1-4020-0953-4 Source Title Pattern Recognition and String Matching / Chen D. ; Cheng X. Pages s. 1-51 Number of pages 51 s. Language eng - English Country NL - Netherlands Keywords pattern recognition ; feature selection ; search methods Subject RIV BC - Control Systems Theory R&D Projects GA402/01/0981 GA ČR - Czech Science Foundation (CSF) KSK1019101 GA AV ČR - Academy of Sciences of the Czech Republic (AV ČR) CEZ AV0Z1075907 - UTIA-B Annotation The chapter is devoted to the problem of feature selection in statistical pattern recognition. A number of feature subset search strategies is reviewed, analyzed and compared. New algorithms are described (Fast Branch and Bound, Branch and Bound Algorithm with Partial Prediction, Floating Search, Adaptive Floating Search). Two feature selection methods based on approximating the unknown class conditional densities by finite mixtures of the factorized densities are presented. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
Number of the records: 1