國立虎尾科技大學 |

Partitional Clustering via Nonsmooth Optimization = Clustering via Optimization /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Partitional Clustering via Nonsmooth Optimization/ by Adil M. Bagirov, Napsu Karmitsa, Sona Taheri.
其他題名:	Clustering via Optimization /
作者:	M. Bagirov, Adil.
其他作者:	Taheri, Sona.
面頁冊數:	XX, 336 p. 78 illus., 77 illus. in color.online resource. :
Contained By:	Springer Nature eBook
標題:	Data Mining and Knowledge Discovery. -
電子資源:	https://doi.org/10.1007/978-3-030-37826-4
ISBN:	9783030378264

Partitional Clustering via Nonsmooth Optimization = Clustering via Optimization /
M. Bagirov, Adil.

Partitional Clustering via Nonsmooth OptimizationClustering via Optimization /[electronic resource] :by Adil M. Bagirov, Napsu Karmitsa, Sona Taheri. - 1st ed. 2020. - XX, 336 p. 78 illus., 77 illus. in color.online resource. - Unsupervised and Semi-Supervised Learning,2522-848X. - Unsupervised and Semi-Supervised Learning,.

Introduction -- Introduction to Clustering -- Clustering Algorithms -- Nonsmooth Optimization Models in Cluster Analysis -- Nonsmooth Optimization -- Optimization based Clustering Algorithms -- Implementation and Numerical Results -- Conclusion.

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. 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 from big data Describes implementation and evaluation of optimization based clustering algorithms.

ISBN: 9783030378264

Standard No.: 10.1007/978-3-030-37826-4doiSubjects--Topical Terms:

677765
Data Mining and Knowledge Discovery.

LC Class. No.: TK1-9971

Dewey Class. No.: 621.382

Partitional Clustering via Nonsmooth Optimization = Clustering via Optimization /
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