Feature Selection for Data and Pattern Recognition

This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. Even though it has been the subject of interest for some time, feature selection remains one of act...

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Detalles Bibliográficos
Autor Corporativo: SpringerLink (-)
Otros Autores: Stańczyk, Urszula (-), Jain, Lakhmi C.
Formato: Libro electrónico
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg 2015.
Colección:Studies in Computational Intelligence ; 584.
Springer eBooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b3304949x*spi
Descripción
Sumario:This research book provides the reader with a selection of high-quality texts dedicated to current progress, new developments and research trends in feature selection for data and pattern recognition. Even though it has been the subject of interest for some time, feature selection remains one of actively pursued avenues of investigations due to its importance and bearing upon other problems and tasks. This volume points to a number of advances topically subdivided into four parts: estimation of importance of characteristic features, their relevance, dependencies, weighting and ranking; rough set approach to attribute reduction with focus on relative reducts; construction of rules and their evaluation; and data- and domain-oriented methodologies.
Descripción Física:XVIII, 355 p., 74 il., 20 il. col
Formato:Forma de acceso: World Wide Web.
ISBN:9783662456200