• Anglický jazyk

Learning from Data Streams in Evolving Environments

Autor: Moamar Sayed-Mouchaweh

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... Viac o knihe

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O knihe

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.





  • Vydavateľstvo: Springer International Publishing
  • Rok vydania: 2018
  • Formát: Hardback
  • Rozmer: 241 x 160 mm
  • Jazyk: Anglický jazyk
  • ISBN: 9783319898025

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