Algorithms for classification based on k-NN

In this paper we focus on methods that solve classification tasks based on distances, and we introduce some variants of the basic k-NN method adding up to 3 characteristics. The experiments reveal a relationship between the accuracy of 1-NN (distances) and the accuracy of the methods based on those...

Descripción completa

Detalles Bibliográficos
Autores: Laguía, Manuel, Castro, Juan L.
Tipo de recurso: artículo
Fecha de publicación:2007
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2099/10929
Acceso en línea:https://hdl.handle.net/2099/10929
Access Level:acceso abierto
Palabra clave:Algorithms
Algorismes
Classificació AMS::68 Computer science::68W Algorithms
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
id ES_aa9574e18f202f54a2bf101bbdfb0ccc
oai_identifier_str oai:upcommons.upc.edu:2099/10929
network_acronym_str ES
network_name_str España
repository_id_str
spelling Algorithms for classification based on k-NNLaguía, ManuelCastro, Juan L.AlgorithmsAlgorismesClassificació AMS::68 Computer science::68W AlgorithmsÀrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitatIn this paper we focus on methods that solve classification tasks based on distances, and we introduce some variants of the basic k-NN method adding up to 3 characteristics. The experiments reveal a relationship between the accuracy of 1-NN (distances) and the accuracy of the methods based on those distances. We propose a heuristics according to this observation and test its correctness. We study the usefulness of the proposed methods epsilon-ball, epsilon-ball^{k-NN} and epsilon-ball^{1-NN}, and make an exhaustive comparison using six different distance functions and 68 data sets, including UCI--Repository and artificial data sets. The proposed methods are useful and significantly outperform k-NN frequently. We have also found some evidence about the weakness of k-NN when the optimal value of $k$ varies in different regions along the space.Peer ReviewedUniversitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica20072007-01-0120112011-10-14journal articlehttp://purl.org/coar/resource_type/c_6501NAhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/2099/10929reponame:UPCommons. Portal del coneixement obert de la UPCinstname:Universitat Politècnica de Catalunya (UPC)Inglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution-NonCommercial-NoDerivs 3.0 Spainhttp://creativecommons.org/licenses/by-nc-nd/3.0/es/info:eu-repo/semantics/openAccessoai:upcommons.upc.edu:2099/109292026-05-27T15:37:01Z
dc.title.none.fl_str_mv Algorithms for classification based on k-NN
title Algorithms for classification based on k-NN
spellingShingle Algorithms for classification based on k-NN
Laguía, Manuel
Algorithms
Algorismes
Classificació AMS::68 Computer science::68W Algorithms
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
title_short Algorithms for classification based on k-NN
title_full Algorithms for classification based on k-NN
title_fullStr Algorithms for classification based on k-NN
title_full_unstemmed Algorithms for classification based on k-NN
title_sort Algorithms for classification based on k-NN
dc.creator.none.fl_str_mv Laguía, Manuel
Castro, Juan L.
author Laguía, Manuel
author_facet Laguía, Manuel
Castro, Juan L.
author_role author
author2 Castro, Juan L.
author2_role author
dc.subject.none.fl_str_mv Algorithms
Algorismes
Classificació AMS::68 Computer science::68W Algorithms
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
topic Algorithms
Algorismes
Classificació AMS::68 Computer science::68W Algorithms
Àrees temàtiques de la UPC::Informàtica::Informàtica teòrica::Algorísmica i teoria de la complexitat
description In this paper we focus on methods that solve classification tasks based on distances, and we introduce some variants of the basic k-NN method adding up to 3 characteristics. The experiments reveal a relationship between the accuracy of 1-NN (distances) and the accuracy of the methods based on those distances. We propose a heuristics according to this observation and test its correctness. We study the usefulness of the proposed methods epsilon-ball, epsilon-ball^{k-NN} and epsilon-ball^{1-NN}, and make an exhaustive comparison using six different distance functions and 68 data sets, including UCI--Repository and artificial data sets. The proposed methods are useful and significantly outperform k-NN frequently. We have also found some evidence about the weakness of k-NN when the optimal value of $k$ varies in different regions along the space.
publishDate 2007
dc.date.none.fl_str_mv 2007
2007-01-01
2011
2011-10-14
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
NA
http://purl.org/coar/version/c_be7fb7dd8ff6fe43
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/2099/10929
url https://hdl.handle.net/2099/10929
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Attribution-NonCommercial-NoDerivs 3.0 Spain
http://creativecommons.org/licenses/by-nc-nd/3.0/es/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
publisher.none.fl_str_mv Universitat Politècnica de Catalunya. Secció de Matemàtiques i Informàtica
dc.source.none.fl_str_mv reponame:UPCommons. Portal del coneixement obert de la UPC
instname:Universitat Politècnica de Catalunya (UPC)
instname_str Universitat Politècnica de Catalunya (UPC)
reponame_str UPCommons. Portal del coneixement obert de la UPC
collection UPCommons. Portal del coneixement obert de la UPC
repository.name.fl_str_mv
repository.mail.fl_str_mv
_version_ 1869416194532966400
score 15,300719

Similares en LA Referencia