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Selection of Most Informative Variables in Statistical Pattern Recognition
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SYSNO ASEP 0083328 Document Type V - Research Report R&D Document Type The record was not marked in the RIV Title Selection of Most Informative Variables in Statistical Pattern Recognition Title Výběr nejinformativnějších proměnných ve statistickém rozpoznávání Author(s) Pudil, Pavel (UTIA-B) RID
Somol, Petr (UTIA-B) RID
Haindl, Michal (UTIA-B) RID, ORCIDIssue data Plzeň: UWB, 2007 Series MATEO -The European Network of Mechatronics Centres and Industrial Controllers Number of pages 87 s. Language eng - English Country CZ - Czech Republic Keywords feture selection Subject RIV BD - Theory of Information R&D Projects MAT-12-C4 GA MMR - Ministry for Regional Development (MMR) 1M0572 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) 2C06019 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) CEZ AV0Z10750506 - UTIA-B (2005-2011) Annotation The research report gives an overview of feature selection techniques in statistical pattern recognition with particular emphasis to methods developed by the researchers participating in MATEO Centre of Mechatronics project. Besides discussing the advances in methodology it attempts to put them into a taxonomical framework. The methods discussed include the latest variants of the optimal algorithms, enhanced sub-optimal techniques and the simultaneous semi-parametric probability density function modelling and feature space selection method. Some related issues are illustrated on real data by means of the Feature Selection Toolbox software. Workplace Institute of Information Theory and Automation Contact Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Year of Publishing 2008
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