Learning from Data Streams in Evolving Environments

Methods and Applications

Themistocles M. Rassias (Redaktør) ; Themistocles M. Rassias (Redaktør)

This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. Les mer
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1619,-

(E-bok)
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Min side | Adobe Digital Editions
E-boken må lastes ned i løpet av 2 år

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E-bok
Legg i
Vår pris: 1619,-

(E-bok)
E-bøker kan leses umiddelbart etter kjøp
Min side | Adobe Digital Editions
E-boken må lastes ned i løpet av 2 år

Om boka

This edited book covers recent advances of techniques, methods and tools treating the problem of learning from data streams generated by evolving non-stationary processes. The goal is to discuss and overview the advanced techniques, methods and tools that are dedicated to manage, exploit and interpret data streams in non-stationary environments. The book includes the required notions, definitions, and background to understand the problem of learning from data streams in non-stationary environments and synthesizes the state-of-the-art in the domain, discussing advanced aspects and concepts and presenting open problems and future challenges in this field.Provides multiple examples to facilitate the understanding data streams in non-stationary environments;Presents several application cases to show how the methods solve different real world problems;Discusses the links between methods to help stimulate new research and application directions.

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