k-Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989592%3A15310%2F13%3A33158099" target="_blank" >RIV/61989592:15310/13:33158099 - isvavai.cz</a>
Result on the web
<a href="http://dml.cz/bitstream/handle/10338.dmlcz/143544/ActaOlom_52-2013-2_11.pdf" target="_blank" >http://dml.cz/bitstream/handle/10338.dmlcz/143544/ActaOlom_52-2013-2_11.pdf</a>
DOI - Digital Object Identifier
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Result language
angličtina
Original language name
k-Depth-nearest Neighbour Method and its Performance on Skew-normal Distributons
Original language description
In the present paper we investigate performance of the k-depth-nearest classifier. This classifier, proposed recently by Vencalek, uses the concept of data depth to improve the classification method known as the k-nearest neighbour. Simulation study which is presented here deals with the two-class classification problem in which the considered distributions belong to the family of skewed normal distributions.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
BA - General mathematics
OECD FORD branch
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Project
<a href="/en/project/EE2.3.20.0170" target="_blank" >EE2.3.20.0170: Building of Research Team in the Field of Environmental Modeling and the Use of Geoinformation Systems with the Consequence in Participation in International Networks and Programs</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2013
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical
Acta Universitatis Palackianae Olomucensis, Facultas Rerum Naturalium, Mathematica
ISSN
0231-9721
e-ISSN
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Volume of the periodical
52
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
9
Pages from-to
121-129
UT code for WoS article
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EID of the result in the Scopus database
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