Počet záznamů: 1

Efficient Feature Subset Selection and Subset Size Optimization

  1. 1.
    0342820 - UTIA-B 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 MŠk 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
    http://library.utia.cas.cz/separaty/2010/RO/somol-efficient feature subset selection and subset size optimization.pdf 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