dc.creator | Carrizosa Priego, Emilio José | es |
dc.creator | Martín Barragán, Belén | es |
dc.creator | Plastria, Frank | es |
dc.creator | Romero Morales, María Dolores | es |
dc.date.accessioned | 2021-04-26T08:12:08Z | |
dc.date.available | 2021-04-26T08:12:08Z | |
dc.date.issued | 2007-07-20 | |
dc.identifier.citation | Carrizosa Priego, E.J., Martín Barragán, B., Plastria, F. y Romero Morales, M.D. (2007). On the Selection of the Globally Optimal Prototype Subset for Nearest-Neighbor Classification. INFORMS JOURNAL ON COMPUTING, 19 (3), 470-479. | |
dc.identifier.issn | 1091-9856 | es |
dc.identifier.issn | 1526-5528 | es |
dc.identifier.uri | https://hdl.handle.net/11441/107714 | |
dc.description.abstract | The nearest-neighbor classifier has been shown to be a powerful tool for multiclass classification. We explore both theoretical properties and empirical behavior of a variant method, in which the nearest-neighbor rule is applied to a reduced set of prototypes. This set is selected a priori by fixing its cardinality and minimizing the empirical misclassification cost. In this way we alleviate the two serious drawbacks of the nearest-neighbor method: high storage requirements and time-consuming queries. Finding this reduced set is shown to be NP-hard. We provide mixed integer programming (MIP) formulations, which are theoretically compared and solved by a standard MIP solver for small problem instances. We show that the classifiers derived from these formulations are comparable to benchmark procedures. We solve large problem instances by a metaheuristic that yields good classification rules in reasonable time. Additional experiments indicate that prototype-based nearest-neighbor classifiers remain quite stable in the presence of missing values. | es |
dc.format | application/pdf | es |
dc.format.extent | 9 p. | es |
dc.language.iso | eng | es |
dc.publisher | Informs | es |
dc.relation.ispartof | INFORMS JOURNAL ON COMPUTING, 19 (3), 470-479. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | classification | es |
dc.subject | optimal prototype subset | es |
dc.subject | nearest neighbor | es |
dc.subject | dissimilarities | es |
dc.subject | integer programming | es |
dc.subject | variable neighborhood search | es |
dc.subject | missing values | es |
dc.title | On the Selection of the Globally Optimal Prototype Subset for Nearest-Neighbor Classification | 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 Estadística e Investigación Operativa | es |
dc.relation.publisherversion | https://doi.org/10.1287/ijoc.1060.0183 | es |
dc.identifier.doi | 10.1287/ijoc.1060.0183 | es |
dc.contributor.group | Universidad de Sevilla. FQM329: Optimización | es |
dc.journaltitle | INFORMS JOURNAL ON COMPUTING | es |
dc.publication.volumen | 19 | es |
dc.publication.issue | 3 | es |
dc.publication.initialPage | 470 | es |
dc.publication.endPage | 479 | es |