Non-deterministic outlier detection method based on the variable precision rough set model
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http://hdl.handle.net/10045/107890
Título: | Non-deterministic outlier detection method based on the variable precision rough set model |
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Autor/es: | Fernández Oliva, Alberto | Maciá Pérez, Francisco | Berna-Martinez, Jose Vicente | Abreu Ortega, Miguel |
Grupo/s de investigación o GITE: | GrupoM. Redes y Middleware |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Tecnología Informática y Computación |
Palabras clave: | Outliers | Rough Sets (RS) | RS Basic Model (RSBM) | Variable Precision Rough Set Model (VPRSM) | Data set | Data Mining |
Área/s de conocimiento: | Arquitectura y Tecnología de Computadores |
Fecha de publicación: | 2019 |
Editor: | CRL Publishing |
Cita bibliográfica: | International Journal of Computer Systems Science & Engineering. 2019, 3: 131-144 |
Resumen: | This study presents a method for the detection of outliers based on the Variable Precision Rough Set Model (VPRSM). The basis of this model is the generalisation of the standard concept of a set inclusion relation on which the Rough Set Basic Model (RSBM) is based. The primary contribution of this study is the improvement in detection quality, which is achieved due to the generalisation allowed by the classification system that allows a certain degree of uncertainty. From this method, a computationally efficient algorithm is proposed. The experiments performed with a real scenario and a comparison of the results with the RSBM-based method demonstrate the effectiveness of the method as well as the algorithm’s efficiency in diverse contexts, which also involve large amounts of data. |
Patrocinador/es: | This study was funded by grant TIN2016-78103-C2-2-R and University of Alicante GRE14-02. |
URI: | http://hdl.handle.net/10045/107890 |
ISSN: | 0267-6192 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | © 2019 CRL Publishing Ltd |
Revisión científica: | si |
Versión del editor: | http://crl-publishing.co.uk/csse-journal/ |
Aparece en las colecciones: | INV - GrupoM - Artículos de Revistas |
Archivos en este ítem:
Archivo | Descripción | Tamaño | Formato | |
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Fernandez-Oliva_etal_2019_ComputSystSciEng_final.pdf | Versión final | 5,55 MB | Adobe PDF | Abrir Vista previa |
Fernandez-Oliva_etal_2019_ComputSystSciEng_revised.pdf | Versión revisada | 1,31 MB | Adobe PDF | Abrir Vista previa |
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