Learning from Data Streams in Evolving Environments: Methods and Applications

Learning from Data Streams in Evolving Environments: Methods and Applications 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. Autor: Moamar Sayed-Mouchaweh Wydawnictwo: Springer Rok wydania: 2018 Okładka: twarda Liczba stron: 317 Wymiary: 15.5 x 23.5 x 1.9 cm Ilustracje: 96 Tables, color; 95 Illustrations, color; 36 Illustrations, black and white; VIII, 317 p. 131 illus., 95 illus. in color. Język: angielski ISBN: 9783319898025