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.
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 |