This HTML5 document contains 40 embedded RDF statements represented using HTML+Microdata notation.

The embedded RDF content will be recognized by any processor of HTML5 Microdata.

Namespace Prefixes

PrefixIRI
dctermshttp://purl.org/dc/terms/
n6http://localhost/temp/predkladatel/
n18http://linked.opendata.cz/resource/domain/vavai/riv/tvurce/
n16http://linked.opendata.cz/resource/domain/vavai/subjekt/
n13http://linked.opendata.cz/ontology/domain/vavai/
shttp://schema.org/
rdfshttp://www.w3.org/2000/01/rdf-schema#
skoshttp://www.w3.org/2004/02/skos/core#
n3http://linked.opendata.cz/ontology/domain/vavai/riv/
n17http://bibframe.org/vocab/
n2http://linked.opendata.cz/resource/domain/vavai/vysledek/
rdfhttp://www.w3.org/1999/02/22-rdf-syntax-ns#
n19http://linked.opendata.cz/resource/domain/vavai/vysledek/RIV%2F00216208%3A11320%2F13%3A10173473%21RIV14-MSM-11320___/
n10http://linked.opendata.cz/ontology/domain/vavai/riv/klicoveSlovo/
n20http://linked.opendata.cz/ontology/domain/vavai/riv/duvernostUdaju/
xsdhhttp://www.w3.org/2001/XMLSchema#
n15http://linked.opendata.cz/ontology/domain/vavai/riv/jazykVysledku/
n7http://linked.opendata.cz/ontology/domain/vavai/riv/aktivita/
n9http://linked.opendata.cz/ontology/domain/vavai/riv/obor/
n5http://linked.opendata.cz/ontology/domain/vavai/riv/druhVysledku/
n12http://reference.data.gov.uk/id/gregorian-year/

Statements

Subject Item
n2:RIV%2F00216208%3A11320%2F13%3A10173473%21RIV14-MSM-11320___
rdf:type
n13:Vysledek skos:Concept
rdfs:seeAlso
http://www.hindawi.com/journals/jps/2013/629184/
dcterms:description
Halfspace depth became a popular nonparametric tool for statistical analysis of multivariate data during the last two decades. One of applications of data depth considered recently in literature is the classification problem. The data depth approach is used instead of the linear discriminant analysis mostly to avoid the parametric assumptions and to get better classifier for data whose distribution is not elliptically symmetric, for example, skewed data. In our paper, we suggest to use weighted version of halfspace depth rather than the halfspace depth itself in order to obtain lower misclassification rate in the case of %22nonconvex%22 distributions. Simulations show that the results of depth-based classifiers are comparable with linear discriminant analysis for two normal populations, while for nonelliptic distributions the classifier based on weighted halfspace depth outperforms both linear discriminant analysis and classifier based on the usual (nonweighted) halfspace depth. Halfspace depth became a popular nonparametric tool for statistical analysis of multivariate data during the last two decades. One of applications of data depth considered recently in literature is the classification problem. The data depth approach is used instead of the linear discriminant analysis mostly to avoid the parametric assumptions and to get better classifier for data whose distribution is not elliptically symmetric, for example, skewed data. In our paper, we suggest to use weighted version of halfspace depth rather than the halfspace depth itself in order to obtain lower misclassification rate in the case of %22nonconvex%22 distributions. Simulations show that the results of depth-based classifiers are comparable with linear discriminant analysis for two normal populations, while for nonelliptic distributions the classifier based on weighted halfspace depth outperforms both linear discriminant analysis and classifier based on the usual (nonweighted) halfspace depth.
dcterms:title
Depth-Based Classification for Distributions with Nonconvex Support Depth-Based Classification for Distributions with Nonconvex Support
skos:prefLabel
Depth-Based Classification for Distributions with Nonconvex Support Depth-Based Classification for Distributions with Nonconvex Support
skos:notation
RIV/00216208:11320/13:10173473!RIV14-MSM-11320___
n13:predkladatel
n16:orjk%3A11320
n3:aktivita
n7:I
n3:aktivity
I
n3:cisloPeriodika
September
n3:dodaniDat
n12:2014
n3:domaciTvurceVysledku
n18:3659372
n3:druhVysledku
n5:J
n3:duvernostUdaju
n20:S
n3:entitaPredkladatele
n19:predkladatel
n3:idSjednocenehoVysledku
68430
n3:idVysledku
RIV/00216208:11320/13:10173473
n3:jazykVysledku
n15:eng
n3:klicovaSlova
nonconvex support; classification; halfspace depth
n3:klicoveSlovo
n10:nonconvex%20support n10:halfspace%20depth n10:classification
n3:kodStatuVydavatele
EG - Egyptská arabská republika
n3:kontrolniKodProRIV
[52CD40AFA3E3]
n3:nazevZdroje
Journal of Probability and Statistics
n3:obor
n9:BA
n3:pocetDomacichTvurcuVysledku
1
n3:pocetTvurcuVysledku
2
n3:rokUplatneniVysledku
n12:2013
n3:svazekPeriodika
2013
n3:tvurceVysledku
Hlubinka, Daniel Vencálek, Ondřej
s:issn
1687-952X
s:numberOfPages
7
n17:doi
10.1155/2013/629184
n6:organizacniJednotka
11320