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Learning from Data Streams in Dynamic Environments

This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Sayed-Mouchaweh, Moamar (Autor)
Autor Corporativo: SpringerLink (Online service)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2016.
Edición:1st ed. 2016.
Colección:SpringerBriefs in Applied Sciences and Technology,
Temas:
Acceso en línea:Texto Completo
Descripción
Sumario:This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.
Descripción Física:VIII, 75 p. 44 illus., 43 illus. in color. online resource.
ISBN:9783319256672
ISSN:2191-5318