| 书目名称 | Learning from Data Streams in Dynamic Environments |
| 编辑 | Moamar Sayed-Mouchaweh |
| 视频video | |
| 概述 | Examines the problem of learning in non-stationary environments, its interests, its applications and challenges.Compares methods and techniques in order to show their complementarities and to define s |
| 丛书名称 | SpringerBriefs in Applied Sciences and Technology |
| 图书封面 |  |
| 描述 | This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments. |
| 出版日期 | Book 2016 |
| 关键词 | Adaptive Modeling; Data Streams; Drift Monitoring and Handling; Evolving Systems; Incremental Learning; N |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-3-319-25667-2 |
| isbn_softcover | 978-3-319-25665-8 |
| isbn_ebook | 978-3-319-25667-2Series ISSN 2191-530X Series E-ISSN 2191-5318 |
| issn_series | 2191-530X |
| copyright | The Author 2016 |
发表于 2025-3-21 16:14:39
