Título

General framework for class-specific feature selection

Autor

BARBARA BERENICE PINEDA BAUTISTA

Jesús Ariel Carrasco Ochoa

José Francisco Martínez Trinidad

Nivel de Acceso

Acceso Abierto

Licencia

http://creativecommons.org/licenses/by-nc-nd/4.0

Materias

Class-specific feature selection - (CLASS-SPECIFIC FEATURE SELECTION) Feature selection - (FEATURE SELECTION) Supervised classification - (SUPERVISED CLASSIFICATION) Classifier ensemble - (CLASSIFIER ENSEMBLE) CIENCIAS FÍSICO MATEMÁTICAS Y CIENCIAS DE LA TIERRA - (CTI) MATEMÁTICAS - (CTI) CIENCIA DE LOS ORDENADORES - (CTI) CIENCIA DE LOS ORDENADORES - (CTI)

Resumen o descripción

Commonly, when a feature selection algorithm is applied, a single feature subset is selected for all the classes, but this subset could be inadequate for some classes. Class-specific feature selection allows selecting a possible different feature subset for each class. However, all the class-specific feature selection algorithms have been proposed for a particular classifier, which reduce their applicability. In this paper, a general framework for using any traditional feature selector for doing class-specific feature selection, which allows using any classifier, is proposed. Experimental results and a comparison against traditional feature selectors showing the suitability of the proposed framework are included.

Editor

Elsevier Ltd.

Fecha de publicación

2011

Tipo de publicación

Artículo

Versión de la publicación

Versión aceptada

Recurso de información

http://inaoe.repositorioinstitucional.mx/jspui/handle/1009/1593

Formato

application/pdf

Idioma

Inglés

Audiencia

Estudiantes

Investigadores

Público en general

Sugerencia de citación

Pineda-Bautista, B.B., et al., (2011). General framework for class-specific feature selection, Expert Systems with Applications, (38): 10018–10024

Repositorio Orígen

Repositorio Institucional del INAOE

Descargas

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