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Recent feature selection methods in statistical pattern recognition.

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F02%3A16020201" target="_blank" >RIV/67985556:_____/02:16020201 - isvavai.cz</a>

  • Alternative codes found

    RIV/61384399:31160/03:00018186

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Recent feature selection methods in statistical pattern recognition.

  • Original language description

    The chapter is devoted to the problem of feature selection in statistical pattern recognition. A number of feature subset search strategies is reviewed, analyzed and compared. New algorithms are described (Fast Branch and Bound, Branch and Bound Algorithm with Partial Prediction, Floating Search, Adaptive Floating Search). Two feature selection methods based on approximating the unknown class conditional densities by finite mixtures of the factorized densities are presented.

  • Czech name

  • Czech description

Classification

  • Type

    C - Chapter in a specialist book

  • CEP classification

    BC - Theory and management systems

  • OECD FORD branch

Result continuities

  • Project

    Result was created during the realization of more than one project. More information in the Projects tab.

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2003

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Book/collection name

    Pattern Recognition and String Matching.

  • ISBN

    1-4020-0953-4

  • Number of pages of the result

    51

  • Pages from-to

    1-51

  • Number of pages of the book

  • Publisher name

    Kluwer

  • Place of publication

    Dordrecht

  • UT code for WoS chapter