About: Depth-Based Classification for Distributions with Nonconvex Support

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An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
rdfs:seeAlso	http://www.hindawi.com/journals/jps/2013/629184/
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. (en)
Title	Depth-Based Classification for Distributions with Nonconvex Support Depth-Based Classification for Distributions with Nonconvex Support (en)
skos:prefLabel	Depth-Based Classification for Distributions with Nonconvex Support Depth-Based Classification for Distributions with Nonconvex Support (en)
skos:notation	RIV/00216208:11320/13:10173473!RIV14-MSM-11320___
http://linked.open...avai/predkladatel	Matematicko-fyzikální fakulta
http://linked.open...avai/riv/aktivita	I
http://linked.open...avai/riv/aktivity	I
http://linked.open...iv/cisloPeriodika	September
http://linked.open...vai/riv/dodaniDat	2014
http://linked.open...aciTvurceVysledku	Hlubinka, Daniel
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Univerzita Karlova v Praze / Matematicko-fyzikální fakulta
http://linked.open...dnocenehoVysledku	68430
http://linked.open...ai/riv/idVysledku	RIV/00216208:11320/13:10173473
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	nonconvex support; classification; halfspace depth (en)
http://linked.open.../riv/klicoveSlovo	nonconvex support halfspace depth classification
http://linked.open...odStatuVydavatele	EG - Egyptská arabská republika
http://linked.open...ontrolniKodProRIV	[52CD40AFA3E3]
http://linked.open...i/riv/nazevZdroje	Journal of Probability and Statistics
http://linked.open...in/vavai/riv/obor	BA
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	2 (xsd:int)
http://linked.open...UplatneniVysledku	2013
http://linked.open...v/svazekPeriodika	2013
http://linked.open...iv/tvurceVysledku	Vencálek, Ondřej Hlubinka, Daniel
issn	1687-952X
number of pages	7 (xsd:int)
http://bibframe.org/vocab/doi	10.1155/2013/629184
http://localhost/t...ganizacniJednotka	11320

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