书目名称 | Partitional Clustering via Nonsmooth Optimization |
副标题 | Clustering via Optim |
编辑 | Adil M. Bagirov,Napsu Karmitsa,Sona Taheri |
视频video | |
概述 | Provides a comprehensive description of clustering algorithms based on nonsmooth and global optimization techniques.Addresses problems of real-time clustering in large data sets and challenges arising |
丛书名称 | Unsupervised and Semi-Supervised Learning |
图书封面 |  |
描述 | .This book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering problems; the authors‘ emphasis on clustering algorithms is based on deterministic methods of optimization. The book also includes results on real-time clustering algorithms based on optimization techniques, addresses implementation issues of these clustering algorithms, and discusses new challenges arising from big data. The book is ideal for anyone teaching or learning clustering algorithms. It provides an accessible introduction to the field and it is well suited for practitioners already familiar with the basics of optimization.. |
出版日期 | Book 20201st edition |
关键词 | Optimization models of clustering problems; Clustering with different similarity measures; Clustering |
版次 | 1 |
doi | https://doi.org/10.1007/978-3-030-37826-4 |
isbn_softcover | 978-3-030-37828-8 |
isbn_ebook | 978-3-030-37826-4Series ISSN 2522-848X Series E-ISSN 2522-8498 |
issn_series | 2522-848X |
copyright | Springer Nature Switzerland AG 2020 |