0342820 - ÚTIA 2011 RIV HR eng M - Část monografie knihy
Somol, Petr - Novovičová, Jana - Pudil, Pavel
Efficient Feature Subset Selection and Subset Size Optimization.
Pattern Recognition, Recent Advances. Vukovar, Croatia: In-Teh, 2010 - (Herout, A.), s. 75-98. ISBN 978-953-7619-90-9
Grant CEP: GA MŠMT 1M0572; GA ČR GA102/08/0593; GA ČR GA102/07/1594
Grant ostatní: GA MŠk(CZ) 2C06019
Výzkumný záměr: CEZ:AV0Z10750506
Klíčová slova: dimensionality reduction * pattern recognition * machine learning * feature selection * optimization * subset search * classification
Kód oboru RIV: BD - Teorie informace
Web výsledku:
http://library.utia.cas.cz/separaty/2010/RO/somol-efficient feature subset selection and subset size optimization.pdf

A broad class of decision-making problems can be solved by learning approach. This can be a feasible alternative when neither an analytical solution exists nor the mathematical model can be constructed. In these cases the required knowledge can be gained from the past data which form the so-called learning or training set. Then the formal apparatus of statistical pattern recognition can be used to learn the decision-making. The first and essential step of statistical pattern recognition is to solve the problem of feature selection (FS) or more generally dimensionality reduction (DR). The chapter summarizes the state of art in feature selection, addressing key topics including: FS categorization, FS criteria, FS search strategies, FS stability.
Trvalý link: http://hdl.handle.net/11104/0185446