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Learning from Data Streams in Evolving Environments

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Learning from Data Streams in Evolving Environments Synopsis

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.

About This Edition

ISBN: 9783319898025
Publication date: 9th August 2018
Author: Moamar SayedMouchaweh
Publisher: Springer an imprint of Springer International Publishing
Format: Hardback
Pagination: 317 pages
Series: Studies in Big Data
Genres: Communications engineering / telecommunications
Security and fire alarm systems
Automatic control engineering
Expert systems / knowledge-based systems
Data mining