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Nonparametric Classification of Noisy Functions

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F12%3A10125854" target="_blank" >RIV/00216208:11320/12:10125854 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Nonparametric Classification of Noisy Functions

  • Original language description

    The classification task for data coming from certain subspaces of continuous functions are discussed. This functions are of noisy nature and no further assumptions about the distributions are stated. Special attention is paid to depth-based classification and its possible generalizations. Several established depth functionals are compared. The outcoming drawbacks of these methods are fixed by considering the derivatives of the smoothed versions of functions, although the observations don't have to be differentiable itself.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    BA - General mathematics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2012

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of the 27th International Workshop on Statistical Modelling

  • ISBN

    978-80-263-0250-6

  • ISSN

  • e-ISSN

  • Number of pages

    6

  • Pages from-to

    233-238

  • Publisher name

    Tribun EU

  • Place of publication

    Brno

  • Event location

    Praha

  • Event date

    Jul 16, 2012

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article