New neighborhood based classification rules for metric spaces and their use in ensemble classification
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Título: | New neighborhood based classification rules for metric spaces and their use in ensemble classification |
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Autor/es: | Mazón, Jose-Norberto | Micó, Luisa | Moreno Seco, Francisco |
Grupo/s de investigación o GITE: | Reconocimiento de Formas e Inteligencia Artificial |
Centro, Departamento o Servicio: | Universidad de Alicante. Departamento de Lenguajes y Sistemas Informáticos |
Palabras clave: | Ensemble classifiers | Classification rules | Nearest neighbour |
Área/s de conocimiento: | Lenguajes y Sistemas Informáticos | Ciencia de la Computación e Inteligencia Artificial |
Fecha de publicación: | 2007 |
Editor: | Springer Berlin / Heidelberg |
Cita bibliográfica: | MAZÓN LÓPEZ, José Norberto; MICÓ ANDRÉS, Luisa; MORENO SECO, Francisco. "New neighborhood based classification rules for metric spaces and their use in ensemble classification". En: Pattern Recognition and Image Analysis : Third Iberian Conference, IbPRIA 2007, Girona, Spain, June 6-8, 2007, Proceedings, Part I. Berlin : Springer, 2007. (Lecture Notes in Computer Science; 4477/2007). ISBN 978-3-540-72846-7, pp. 354-361 |
Resumen: | The k-nearest-neighbor rule is a well known pattern recognition technique with very good results in a great variety of real classification tasks. Based on the neighborhood concept, several classification rules have been proposed to reduce the error rate of the k-nearest-neighbor rule (or its time requirements). In this work, two new geometrical neighborhoods are defined and the classification rules derived from them are used in several real data classification tasks. Also, some voting ensembles of classifiers based on these new rules have been tested and compared. |
Patrocinador/es: | This work has been supported in part by grant DPI2006-15542-C04-01 from the Spanish CICYT (Ministerio de Ciencia y Tecnología), GV06/166 from Generalitat Valenciana, and the IST Programme of the European Community, under the Pascal Network of Excellence, IST-2002-506778. |
URI: | http://hdl.handle.net/10045/8773 |
ISBN: | 978-3-540-72846-7 |
ISSN: | 0302-9743 (Print) | 1611-3349 (Online) |
DOI: | 10.1007/978-3-540-72847-4_46 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Derechos: | The original publication is available at www.springerlink.com |
Revisión científica: | si |
Versión del editor: | http://dx.doi.org/10.1007/978-3-540-72847-4_46 |
Aparece en las colecciones: | INV - GRFIA - Artículos de Revistas INV - LUCENTIA - Artículos de Revistas INV - WaKe - Artículos de Revistas |
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