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Pattern Recognition, Recent Advances
- 1.
SYSNO ASEP 0342820 Druh ASEP M - Kapitola v monografii Zařazení RIV C - Kapitola v knize Název Efficient Feature Subset Selection and Subset Size Optimization Tvůrce(i) Somol, Petr (UTIA-B) RID
Novovičová, Jana (UTIA-B)
Pudil, Pavel (UTIA-B) RIDZdroj.dok. Pattern Recognition, Recent Advances. - Vukovar, Croatia : In-Teh, 2010 / Herout A. - ISBN 978-953-7619-90-9 Rozsah stran s. 75-98 Poč.str. 23 s. Poč.výt. 201 Poč.str.knihy 524 Jazyk dok. eng - angličtina Země vyd. HR - Chorvatsko Klíč. slova dimensionality reduction ; pattern recognition ; machine learning ; feature selection ; optimization ; subset search ; classification Vědní obor RIV BD - Teorie informace CEP 1M0572 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy GA102/08/0593 GA ČR - Grantová agentura ČR GA102/07/1594 GA ČR - Grantová agentura ČR CEZ AV0Z10750506 - UTIA-B (2005-2011) Anotace 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. Pracoviště Ústav teorie informace a automatizace Kontakt Markéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201. Rok sběru 2011
Počet záznamů: 1