Learning from Data Streams in Evolving Environments
Methods and Applications
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Beschreibung
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.
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.
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 Includes supplementary material: sn.pub/extras
Autor*in
Moamar Sayed-Mouchaweh
Themen in »Learning from Data Streams in Evolving Environments«
Machine Learning Neural Networks and Learning Systems Artificial Intelligence Data streams in non-stationary environments Concept drift and concept evolution in data streams quality control, reliability, safety and risk