Learning from Data Streams in Evolving Environments - Methods and Applications (Hardcover, 1st ed. 2019)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	Studies in Big Data, 41
Release date:	August 2018
First published:	2019
Editors:	Moamar Sayed-Mouchaweh
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	317
Edition:	1st ed. 2019
ISBN-13:	978-3-319-89802-5
Categories:	Books > Professional & Technical > Mechanical engineering & materials > Production engineering > Reliability engineering Books > Professional & Technical > Electronics & communications engineering > Communications engineering / telecommunications > General Books > Computing & IT > Applications of computing > Databases > Data mining Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Automatic control engineering > General Promotions
LSN:	3-319-89802-7
Barcode:	9783319898025

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