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
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Czech description
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Classification
Type
J<sub>SC</sub> - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
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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
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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
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EID of the result in the Scopus database
2-s2.0-85018266046