000			03292nam a2200421 a 4500
001			00013968
003			WSP
005			20260416153415.0
007			cr bnu|||unuuu
008			240725s2025 si a ob 001 0 eng d
010			_a 2024033300
040			_aWSPC _beng _cWSPC
020			_a9789811297489 _q(ebook)
020			_a9811297487 _q(ebook)
020			_z9789811297472 _q(hbk.)
020			_z9811297479 _q(hbk.)
050	0	0	_aQA278 _b.R65 2025
072		7	_aCOM _x021030 _2bisacsh
072		7	_aCOM _x094000 _2bisacsh
072		7	_aCOM _x089000 _2bisacsh
082	0	0	_a519.5/302855133 _223
049			_aMAIN
100	1		_aRokach, Lior.
245	1	0	_aCluster analysis : _ba primer using R / _cLior Rokach.
260			_aSingapore : _bWorld Scientific Publishing, _c©2025.
300			_a1 online resource (304 p.) : _bill.
504			_aIncludes bibliographical references and index.
505	2		_aIntroduction to data clustering -- Similarity measures -- Partitioning methods for minimizing distance measures -- Hierarchical methods -- Clustering visualization -- Cluster validity : evaluation of clustering algorithms -- Mixture densities-based clustering -- Graph clustering -- Grid-based clustering methods -- Deep learning for clustering -- Spectral clustering.
520			_a"Cluster analysis is a fundamental data analysis task that aims to group similar data points together, revealing the inherent structure and patterns within complex datasets. This book serves as a comprehensive and accessible guide, taking readers on a captivating journey through the foundational principles of cluster analysis. At its core, the book delves deeply into various clustering algorithms, covering partitioning methods, hierarchical methods, and advanced techniques such as mixture density-based clustering, graph clustering, and grid-based clustering. Each method is presented with clear, concise explanations, supported by illustrative examples and hands-on implementations in the R programming language - a popular and powerful tool for data analysis and visualization. Recognizing the importance of cluster validation and evaluation, the book devotes a dedicated chapter to exploring a wide range of internal and external quality criteria, equipping readers with the necessary tools to assess the performance of clustering algorithms. For those eager to stay at the forefront of the field, the book also presents deep learning-based clustering methods, showcasing the remarkable capabilities of neural networks in uncovering hidden structures within complex, high-dimensional data. Whether you are a student seeking to expand your knowledge, a data analyst looking to enhance your toolbox, or a researcher exploring the frontiers of data analysis, this book will provide you with a solid foundation in cluster analysis and empower you to tackle a wide range of data-driven problems"-- _cPublisher's website.
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat reader.
650		0	_aCluster analysis.
650		0	_aCluster analysis _xData processing.
650		0	_aR (Computer program language)
655		0	_aElectronic books.
856	4	0	_uhttps://www.worldscientific.com/worldscibooks/10.1142/13968#t=toc
942			_cE-BOOK
999			_c49779 _d49779