English español
Búsqueda
 

Repositorio de la Universidad de Oviedo > Producción Bibliográfica de UniOvi: RECOPILA > Ponencias, Discursos y Conferencias >

Use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10651/31230

Título : Feature subset selection for learning preferences: a case study
Autor(es) y otros: Bahamonde Rionda, Antonio
Fernández Bayón, Gustavo
Díez Peláez, Jorge
Quevedo Pérez, José Ramón
Luaces Rodríguez, Óscar
Coz Velasco, Juan José del
Alonso González, Jaime
Goyache, Félix
Fecha de publicación : 2004
Editorial : ACM
Versión del editor: http://dx.doi.org/10.1145/1015330.1015378
Resumen : In this paper we tackle a real world problem, the search of a function to evaluate the merits of beef cattle as meat producers. The independent variables represent a set of live animals’ measurements; while the outputs cannot be captured with a single number, since the available experts tend to assess each animal in a relative way, comparing animals with the other partners in the same batch. Therefore, this problem can not be solved by means of regression methods; our approach is to learn the preferences of the experts when they order small groups of animals. Thus, the problem can be reduced to a binary classifi- cation, and can be dealt with a Support Vector Machine (SVM) improved with the use of a feature subset selection (FSS) method. We develop a method based on Recursive Feature Elimination (RFE) that employs an adaptation of a metric based method devised for model selection (ADJ). Finally, we discuss the extension of the resulting method to more general settings, and provide a comparison with other possible alternatives
URI : http://hdl.handle.net/10651/31230
ISBN : 1-58113-838-5
Aparece en las colecciones: Ponencias, Discursos y Conferencias
Informática

Ficheros en este ítem:

Fichero Descripción Tamaño Formato
icml2004_BahamondeBDQLCAG04.pdf618 kBAdobe PDFVisualizar/Abrir


Exportar a Mendeley


Este ítem está sujeto a una licencia Creative Commons Licencia Creative Commons
Creative Commons

Los ítems de DSpace están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.

 

Base de Datos de Autoridades Biblioteca Universitaria Consultas / Sugerencias