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710	2		_aSpringerLink (Online service) _9106996
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007			cr nn nnnaamaa
008			200224s2020 gw | s |||| 0|eng d
020			_a9783030378264
024	7		_a10.1007/978-3-030-37826-4 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aQA402.5 _b2020 EB
100	1		_aM. Bagirov, Adil _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673485
245	1	0	_aPartitional Clustering via Nonsmooth Optimization : _bClustering via Optimization _cby Adil M. Bagirov, Napsu Karmitsa, Sona Taheri.
250			_aFirst edition 2020.
264		1	_aCham _bSpringer International Publishing _c2020
300			_a1 recurso en línea (XX, 336 páginas) _b78 ilustraciones, 77 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_aArchivo de texto _bPDF
490	0		_aUnsupervised and Semi-Supervised Learning _x2522-848X
490	0		_aEngineering (Springer-11647)
505	0		_aIntroduction -- Introduction to Clustering -- Clustering Algorithms -- Nonsmooth Optimization Models in Cluster Analysis -- Nonsmooth Optimization -- Optimization based Clustering Algorithms -- Implementation and Numerical Results -- Conclusion.
520	3		_aThis 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.
988			_aSpringer_Engineering_31032020
650		7	_2embne _9145705 _aOptimización matemática
700	1		_aKarmitsa, Napsu _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673486
700	1		_aTaheri, Sona _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673487
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783030378257
776	0	8	_iPrinted edition: _z9783030378271
776	0	8	_iPrinted edition: _z9783030378288
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-030-37826-4 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2020 _dz _ek _zSI