InstanceRank: Bringing order to datasets

In this paper we present InstanceRank, a ranking algorithm that reflects the relevance of the instances within a dataset. InstanceRank applies a similar solution to that used by PageRank, the web pages ranking algorithm in the Google search engine. We also present ISR, an instance selection techniqu...

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Detalles Bibliográficos
Autores: García Vallejo, Carlos Antonio, Troyano Jiménez, José Antonio, Ortega Rodríguez, Francisco Javier
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2010
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/100070
Acceso en línea:https://hdl.handle.net/11441/100070
https://doi.org/10.1016/j.patrec.2009.09.022
Access Level:acceso abierto
Palabra clave:Instance-based learning
Instance reduction
Nearest neighbor
PageRank Classification
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spelling InstanceRank: Bringing order to datasetsGarcía Vallejo, Carlos AntonioTroyano Jiménez, José AntonioOrtega Rodríguez, Francisco JavierInstance-based learningInstance reductionNearest neighborPageRank ClassificationIn this paper we present InstanceRank, a ranking algorithm that reflects the relevance of the instances within a dataset. InstanceRank applies a similar solution to that used by PageRank, the web pages ranking algorithm in the Google search engine. We also present ISR, an instance selection technique that uses InstanceRank. This algorithm chooses the most representative instances from a learning database. Experiments show that ISR algorithm, with InstanceRank as ranking criteria, obtains similar results in accuracy to other instance reduction techniques, noticeably reducing the size of the instance set.Ministerio de Educación y Ciencia HUM2007-66607-C04-04ElsevierLenguajes y Sistemas InformáticosMinisterio de Educación y Ciencia (MEC). España2010info:eu-repo/semantics/articleinfo:eu-repo/semantics/submittedVersionapplication/pdfapplication/pdfhttps://hdl.handle.net/11441/100070https://doi.org/10.1016/j.patrec.2009.09.022reponame:idUS. Depósito de Investigación de la Universidad de Sevillainstname:Universidad de Sevilla (US)InglésPattern Recognition Letters, 31 (2), 133-142.HUM2007-66607-C04-04https://www.sciencedirect.com/science/article/pii/S0167865509002566info:eu-repo/semantics/openAccessoai:idus.us.es:11441/1000702026-06-17T12:51:07Z
dc.title.none.fl_str_mv InstanceRank: Bringing order to datasets
title InstanceRank: Bringing order to datasets
spellingShingle InstanceRank: Bringing order to datasets
García Vallejo, Carlos Antonio
Instance-based learning
Instance reduction
Nearest neighbor
PageRank Classification
title_short InstanceRank: Bringing order to datasets
title_full InstanceRank: Bringing order to datasets
title_fullStr InstanceRank: Bringing order to datasets
title_full_unstemmed InstanceRank: Bringing order to datasets
title_sort InstanceRank: Bringing order to datasets
dc.creator.none.fl_str_mv García Vallejo, Carlos Antonio
Troyano Jiménez, José Antonio
Ortega Rodríguez, Francisco Javier
author García Vallejo, Carlos Antonio
author_facet García Vallejo, Carlos Antonio
Troyano Jiménez, José Antonio
Ortega Rodríguez, Francisco Javier
author_role author
author2 Troyano Jiménez, José Antonio
Ortega Rodríguez, Francisco Javier
author2_role author
author
dc.contributor.none.fl_str_mv Lenguajes y Sistemas Informáticos
Ministerio de Educación y Ciencia (MEC). España
dc.subject.none.fl_str_mv Instance-based learning
Instance reduction
Nearest neighbor
PageRank Classification
topic Instance-based learning
Instance reduction
Nearest neighbor
PageRank Classification
description In this paper we present InstanceRank, a ranking algorithm that reflects the relevance of the instances within a dataset. InstanceRank applies a similar solution to that used by PageRank, the web pages ranking algorithm in the Google search engine. We also present ISR, an instance selection technique that uses InstanceRank. This algorithm chooses the most representative instances from a learning database. Experiments show that ISR algorithm, with InstanceRank as ranking criteria, obtains similar results in accuracy to other instance reduction techniques, noticeably reducing the size of the instance set.
publishDate 2010
dc.date.none.fl_str_mv 2010
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/11441/100070
https://doi.org/10.1016/j.patrec.2009.09.022
url https://hdl.handle.net/11441/100070
https://doi.org/10.1016/j.patrec.2009.09.022
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Pattern Recognition Letters, 31 (2), 133-142.
HUM2007-66607-C04-04
https://www.sciencedirect.com/science/article/pii/S0167865509002566
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:idUS. Depósito de Investigación de la Universidad de Sevilla
instname:Universidad de Sevilla (US)
instname_str Universidad de Sevilla (US)
reponame_str idUS. Depósito de Investigación de la Universidad de Sevilla
collection idUS. Depósito de Investigación de la Universidad de Sevilla
repository.name.fl_str_mv
repository.mail.fl_str_mv
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