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Learning from Data Streams in Dynamic Environments [electronic resource] / by Moamar Sayed-Mouchaweh.

By: Sayed-Mouchaweh, Moamar [author.].
Contributor(s): SpringerLink (Online service).
Material type: materialTypeLabelBookSeries: SpringerBriefs in Applied Sciences and Technology: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Edition: 1st ed. 2016.Description: VIII, 75 p. 44 illus., 43 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319256672.Subject(s): Computational intelligence | Artificial intelligence | Telecommunication | Computational Intelligence | Artificial Intelligence | Communications Engineering, NetworksAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online
Contents:
Introduction to learning -- Learning in dynamic environment -- Handling concept drift -- Summary and final comments.
In: Springer Nature eBookSummary: 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.
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Introduction to learning -- Learning in dynamic environment -- Handling concept drift -- Summary and final comments.

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.

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