Depth-based Classification for Multivariate Data

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

Depth-based Classification for Multivariate Data

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Depth-based Classification for Multivariate Data

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA15-06991S" target="_blank" >GA15-06991S: Analýza funkcionálních dat a související témata</a><br>

Návaznosti

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

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název periodika

Austrian Journal of Statistics

ISSN

1026-597X

e-ISSN

—

Svazek periodika

46

Číslo periodika v rámci svazku

3-4

Stát vydavatele periodika

AT - Rakouská republika

Počet stran výsledku

12

Strana od-do

117-128

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85018266046