Počet záznamů: 1  

Evaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality

  1. 1.
    SYSNO ASEP0348726
    Druh ASEPJ - Článek v odborném periodiku
    Zařazení RIVJ - Článek v odborném periodiku
    Poddruh JČlánek ve WOS
    NázevEvaluating Stability and Comparing Output of Feature Selectors that Optimize Feature Subset Cardinality
    Tvůrce(i) Somol, Petr (UTIA-B) RID
    Novovičová, Jana (UTIA-B)
    Zdroj.dok.IEEE Transactions on Pattern Analysis and Machine Intelligence. - : IEEE Computer Society - ISSN 0162-8828
    Roč. 32, č. 11 (2010), s. 1921-1939
    Poč.str.19 s.
    Jazyk dok.eng - angličtina
    Země vyd.US - Spojené státy americké
    Klíč. slovafeature selection ; feature stability ; stability measures ; similarity measures ; sequential search ; individual ranking ; feature subset-size optimization ; high dimensionality ; small sample size
    Vědní obor RIVBD - Teorie informace
    CEP1M0572 GA MŠMT - Ministerstvo školství, mládeže a tělovýchovy
    GA102/08/0593 GA ČR - Grantová agentura ČR
    GA102/07/1594 GA ČR - Grantová agentura ČR
    CEZAV0Z10750506 - UTIA-B (2005-2011)
    UT WOS000281990900001
    EID SCOPUS78149286082
    DOI10.1109/TPAMI.2010.34.
    AnotaceStability (robustness) of feature selection methods is a topic of recent interest, yet often neglected importance, with direct impact on the reliability of machine learning systems. We investigate the problem of evaluating the stability of feature selection processes yielding subsets of varying size. We introduce several novel feature selection stability measures and adjust some existing measures in a unifying framework that offers broad insight into the stability problem. We study in detail the properties of considered measures and demonstrate on various examples what information about the feature selection process can be gained. We also introduce an alternative approach to feature selection evaluation in the form of measures that enable comparing the similarity of two feature selection processes. These measures enable comparing, e.g., the output of two feature selection methods or two runs of one method with different parameters.
    PracovištěÚstav teorie informace a automatizace
    KontaktMarkéta Votavová, votavova@utia.cas.cz, Tel.: 266 052 201.
    Rok sběru2011
Počet záznamů: 1  

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