dc.creator | Álvarez de la Concepción, Miguel Ángel | es |
dc.creator | González Abril, Luis | es |
dc.creator | Soria Morillo, Luis Miguel | es |
dc.creator | Ortega Ramírez, Juan Antonio | es |
dc.date.accessioned | 2017-03-01T11:35:40Z | |
dc.date.available | 2017-03-01T11:35:40Z | |
dc.date.issued | 2013 | |
dc.identifier.citation | Álvarez de la Concepción, M.Á., González Abril, L., Soria Morillo, L.M. y Ortega Ramírez, J.A. (2013). An adaptive methodology to discretize and select features. Artificial Intelligence Research, 2 (2), 77-86. | |
dc.identifier.issn | 1927-6974 | es |
dc.identifier.uri | http://hdl.handle.net/11441/55021 | |
dc.description.abstract | A lot of significant data describing the behavior or/and actions of systems can be collected in several domains. These data
define some aspects, called features, that can be clustered in several classes. A qualitative or quantitative value for each
feature is stored from measurements or observations. In this paper, the problem of finding independent features for getting
the best accuracy on classification problems is considered. Obtaining these features is the main objective of this work,
where an automatic method to select features is proposed. The method extends the functionality of Ameva coefficient to
use it in other tasks of machine learning where it has not been defined. | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación ARTEMISA TIN2009-14378-C02-01 | es |
dc.description.sponsorship | Junta de Andalucia Simon TIC-8052 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | SciEdu Press | es |
dc.relation.ispartof | Artificial Intelligence Research, 2 (2), 77-86. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Ameva | es |
dc.subject | Feature selection | es |
dc.subject | Discretization | es |
dc.subject | Entropy | es |
dc.title | An adaptive methodology to discretize and select features | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/publishedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Economía Aplicada I | es |
dc.relation.projectID | ARTEMISA TIN2009-14378-C02-01 | es |
dc.relation.projectID | Simon TIC-8052 | es |
dc.relation.publisherversion | http://www.sciedu.ca/journal/index.php/air/article/view/1331 | es |
dc.identifier.doi | 10.5430/air.v2n2p77 | es |
idus.format.extent | 10 | es |
dc.journaltitle | Artificial Intelligence Research | es |
dc.publication.volumen | 2 | es |
dc.publication.issue | 2 | es |
dc.publication.initialPage | 77 | es |
dc.publication.endPage | 86 | es |
dc.contributor.funder | Ministerio de Ciencia e Innovación (MICIN). España | |
dc.contributor.funder | Junta de Andalucía | |