Mostrar el registro sencillo del ítem
Capítulo de Libro
Discovering decision rules from numerical data streams
dc.creator | Ferrer Troyano, Francisco Javier | es |
dc.creator | Aguilar Ruiz, Jesús Salvador | es |
dc.creator | Riquelme Santos, José Cristóbal | es |
dc.date.accessioned | 2016-04-07T09:50:33Z | |
dc.date.available | 2016-04-07T09:50:33Z | |
dc.date.issued | 2004 | |
dc.identifier.uri | http://hdl.handle.net/11441/39691 | |
dc.description.abstract | This paper presents a scalable learning algorithm to classify numerical, low dimensionality, high-cardinality, time-changing data streams. Our approach, named SCALLOP, provides a set of decision rules on demand which improves its simplicity and helpfulness for the user. SCALLOP updates the knowledge model every time a new example is read, adding interesting rules and removing out-of-date rules. As the model is dynamic, it maintains the tendency of data. Experimental results with synthetic data streams show a good performance with respect to running time, accuracy and simplicity of the model. | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.relation.ispartof | SAC '04 Proceedings of the 2004 ACM symposium on Applied computing, pp. 649-653 (2004) | es |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.title | Discovering decision rules from numerical data streams | es |
dc.type | info:eu-repo/semantics/bookPart | es |
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.identifier.doi | http://dx.doi.org/10.1145/967900.968036 | es |
dc.identifier.idus | https://idus.us.es/xmlui/handle/11441/39691 |
Ficheros | Tamaño | Formato | Ver | Descripción |
---|---|---|---|---|
Discovering decision.pdf | 146.1Kb | [PDF] | Ver/ | |