dc.creator | Riquelme Santos, José Cristóbal | es |
dc.creator | Aguilar Ruiz, Jesús Salvador | es |
dc.creator | Valle Sevillano, Carmelo del | es |
dc.date.accessioned | 2016-06-29T08:47:15Z | |
dc.date.available | 2016-06-29T08:47:15Z | |
dc.date.issued | 2003 | |
dc.identifier.citation | Riquelme Santos, J.C., Aguilar Ruiz, J.S. y Valle Sevillano, C.d. (2003). Supervised learning by means of accuracy-aware evolutionary algorithms. Information Sciences : Informatics and Computer Science Intelligent Systems Applications, 156 (3-4), 173-188. | |
dc.identifier.issn | 0020-0255 | es |
dc.identifier.uri | http://hdl.handle.net/11441/42890 | |
dc.description.abstract | This paper describes a new approach, HIerarchical DEcision Rules (HIDER), for
learning generalizable rules in continuous and discrete domains based on evolutionary
algorithms. The main contributions of our approach are the integration of both binary
and real evolutionary coding; the use of specific operators; the relaxing coefficient to
construct more flexible classifiers by indicating how general, with respect to the errors,
decision rules must be; the coverage factor in the fitness function, which makes possible
a quick expansion of the rule size; and the implicit hierarchy when rules are being
obtained. HIDER is accuracy-aware since it can control the maximum allowed error for
each decision rule. We have tested our system on real data from the UCI Repository.
The results of a 10-fold cross-validation are compared to C4.5’s and they show a significant
improvement with respect to the number of rules and the error rate. | es |
dc.description.sponsorship | CICYT TIC2001-1143-C03-02 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Information Sciences : Informatics and Computer Science Intelligent Systems Applications, 156 (3-4), 173-188. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | evolutionary algorithms | es |
dc.subject | supervised learning | es |
dc.subject | decision trees | es |
dc.title | Supervised learning by means of accuracy-aware evolutionary algorithms | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/acceptedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | TIC2001-1143-C03-02 | es |
dc.relation.publisherversion | http://dx.doi.org/10.1016/S0020-0255(03)00175-0 | |
dc.identifier.doi | 10.1016/S0020-0255(03)00175-0 | es |
idus.format.extent | 16 | es |
dc.journaltitle | Information Sciences : Informatics and Computer Science Intelligent Systems Applications | es |
dc.publication.volumen | 156 | es |
dc.publication.issue | 3-4 | es |
dc.publication.initialPage | 173 | es |
dc.publication.endPage | 188 | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/42890 | |
dc.contributor.funder | Comisión Interministerial de Ciencia y Tecnología (CICYT). España | |