Learning from Data Streams in Dynamic Environments / by Moamar Sayed-Mouchaweh
By: Sayed-Mouchaweh, Moamar
Contributor(s): SpringerLink (Online service)
Material type:
E-bookSeries: SpringerBriefs in Applied Sciences and TechnologyPublisher: Cham : Springer International Publishing, 2016Edition: 1st ed.Description: 1 recurso en línea (VIII, 75 p.) : 44 ilustraciones, 43 ilustraciones en color.ISBN: 9783319256672.Subject: Aprendizaje automático
| Item type | Current library | Collection | Call number | Copy number | Status | Date due | Barcode | Item holds | |
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LIBRO-E NO PRÉSTAMO
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Madrid Digital Acceso Electrónico (UEM) | Ciencias e Ingeniería | Q325.5 .S29 2016 EB (Browse shelf(Opens below)) | .i1158810x | Acceso electrónico | eBOOK .i1158810x |
Browsing Madrid Digital shelves, Shelving location: Acceso Electrónico (UEM) Close shelf browser (Hides shelf browser)
| Q325.5 M334 2016 EB Machine Intelligence and Signal Processing | Q325.5 M376 2016 EB Machine Learning Techniques for Gait Biometric Recognition : Using the Ground Reaction Force | Q325.5 .M87 2016 EB Support Vector Machines and Perceptrons : Learning, Optimization, Classification, and Application to Social Networks | Q325.5 .S29 2016 EB Learning from Data Streams in Dynamic Environments | Q325.5 .T67 2016 EB Topics in Grammatical Inference | Q325.5 U578 2016 EB Unsupervised Learning Algorithms | Q325.5 V476 2017 EB Roadside video data analysis : deep learning |
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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