| 书目名称 | Learning from Data Streams in Evolving Environments | | 副标题 | Methods and Applicat | | 编辑 | Moamar Sayed-Mouchaweh | | 视频video | | | 概述 | 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.Di | | 丛书名称 | Studies in Big Data | | 图书封面 |  | | 描述 | .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... | | 出版日期 | Book 2019 | | 关键词 | Machine Learning; Neural Networks and Learning Systems; Artificial Intelligence; Data streams in non-st | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-89803-2 | | isbn_softcover | 978-3-030-07862-1 | | isbn_ebook | 978-3-319-89803-2Series ISSN 2197-6503 Series E-ISSN 2197-6511 | | issn_series | 2197-6503 | | copyright | Springer International Publishing AG, part of Springer Nature 2019 |
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发表于 2025-3-21 16:32:39
