Ebook: Learning from Data Streams in Evolving Environments
Author: Moamar Sayed-Mouchaweh
- Tags: Engineering, Communications Engineering Networks, Quality Control Reliability Safety and Risk, Data Mining and Knowledge Discovery, Control
- Series: Studies in Big Data 41
- Year: 2019
- Publisher: Springer International Publishing
- Edition: 1st ed.
- Language: English
- pdf
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.
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