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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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Lenguaje: | eng |
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Springer
2016
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Acceso en línea: | https://dx.doi.org/10.1007/978-3-319-25667-2 http://cds.cern.ch/record/2120202 |
_version_ | 1780949300961869824 |
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author | Sayed-Mouchaweh, Moamar |
author_facet | Sayed-Mouchaweh, Moamar |
author_sort | Sayed-Mouchaweh, Moamar |
collection | CERN |
description | 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. |
id | cern-2120202 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2016 |
publisher | Springer |
record_format | invenio |
spelling | cern-21202022021-04-21T19:56:04Zdoi:10.1007/978-3-319-25667-2http://cds.cern.ch/record/2120202engSayed-Mouchaweh, MoamarLearning from data streams in dynamic environmentsEngineeringThis 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.Springeroai:cds.cern.ch:21202022016 |
spellingShingle | Engineering Sayed-Mouchaweh, Moamar Learning from data streams in dynamic environments |
title | Learning from data streams in dynamic environments |
title_full | Learning from data streams in dynamic environments |
title_fullStr | Learning from data streams in dynamic environments |
title_full_unstemmed | Learning from data streams in dynamic environments |
title_short | Learning from data streams in dynamic environments |
title_sort | learning from data streams in dynamic environments |
topic | Engineering |
url | https://dx.doi.org/10.1007/978-3-319-25667-2 http://cds.cern.ch/record/2120202 |
work_keys_str_mv | AT sayedmouchawehmoamar learningfromdatastreamsindynamicenvironments |