Partitional Clustering via Nonsmooth Optimization - Clustering via Optimization (Paperback, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Unsupervised and Semi-Supervised Learning
Release date:	February 2021
First published:	2020
Authors:	Adil M. Bagirov • Napsu Karmitsa • Sona Taheri
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	336
Edition:	1st ed. 2020
ISBN-13:	978-3-03-037828-8
Categories:	Books > Science & Mathematics > Mathematics > Optimization > General
LSN:	3-03-037828-4
Barcode:	9783030378288

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