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商品詳細
Learning from Data Streams in Evolving Environments: Methods and Applications. 2019 ed.
・ISBN 978-3-319-89802-5 hard EUR 99.99
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| 著者・編者 | Sayed-Mouchaweh, Moamar (ed.), |
|---|---|
| シリーズ | (Studies in Big Data) |
| 出版社 | (Springer International Publishing AG, SZ) |
| 出版年月 | 2018 |
| ページ数 | 317 pp. |
| 言語 | ENG |
| ニュース番号 | ＜A02-60104＞ |
解説
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.