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...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Sayed-Mouchaweh, Moamar (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Cham : Springer International Publishing : Imprint: Springer, 2016.
Σειρά:SpringerBriefs in Applied Sciences and Technology,
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Learning from Data Streams in Dynamic Environments  |h [electronic resource] /  |c by Moamar Sayed-Mouchaweh. 
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505 0 |a Introduction to learning -- Learning in dynamic environment -- Handling concept drift -- Summary and final comments. 
520 |a 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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650 0 |a Artificial intelligence. 
650 0 |a Computational intelligence. 
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650 2 4 |a Artificial Intelligence (incl. Robotics). 
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