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Depth-based Classification for Multivariate Data

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F17%3A73586461" target="_blank" >RIV/61989592:15310/17:73586461 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.ajs.or.at/index.php/ajs/article/view/vol46-3-4-12/554" target="_blank" >https://www.ajs.or.at/index.php/ajs/article/view/vol46-3-4-12/554</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.17713/ajs.v46i3-4.677" target="_blank" >10.17713/ajs.v46i3-4.677</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Depth-based Classification for Multivariate Data

  • Original language description

    Concept of data depth provides one possible approach to the analysis of multivariate data. Among other it can be also used for classification purposes. The present paper is an overview of the research in the field of depth-based classification for multivariate data. It provides a short summary of current state of knowledge in the field of depth-based classification followed by detailed discussion of four main directions in the depth-based classification, namely semiparametric depth-based classifiers, maximal depth classifier, (maximal depth) classifiers which use local depth functions and finally advanced depth-based classifiers. We do not restrict our attention only on proposed classifiers. The paper rather aims to overview the ideas connected with depth-based classification and problems that were discussed in this context.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

    <a href="/en/project/GA15-06991S" target="_blank" >GA15-06991S: Functional data analysis and related topics</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2017

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Austrian Journal of Statistics

  • ISSN

    1026-597X

  • e-ISSN

  • Volume of the periodical

    46

  • Issue of the periodical within the volume

    3-4

  • Country of publishing house

    AT - AUSTRIA

  • Number of pages

    12

  • Pages from-to

    117-128

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-85018266046