Learning from Data Streams in Evolving Environments
Author | : Moamar Sayed-Mouchaweh |
Publisher | : Springer |
Total Pages | : 320 |
Release | : 2018-07-28 |
ISBN-10 | : 9783319898032 |
ISBN-13 | : 3319898035 |
Rating | : 4/5 (32 Downloads) |
Book excerpt: 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.