Number of the records: 1

Selection of Most Informative Variables in Statistical Pattern Recognition

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, ORCID}
Issue 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

Number of the records: 1