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008 210817s2021 si o 000 0 eng d
040 _aWSPC
_beng
_cWSPC
020 _a9789811241208
_q(ebook)
020 _a9811241201
_q(ebook)
020 _z9789811241192
_q(hbk.)
020 _z9811241198
_q(hbk.)
050 4 _aQA278
_b.S611 2021
072 7 _aCOM
_x094000
_2bisacsh
072 7 _aCOM
_x025000
_2bisacsh
072 7 _aCOM
_x051300
_2bisacsh
082 0 4 _a519.53
_223
049 _aMAIN
100 1 _aSimovici, Dan A.
_93696
245 1 0 _aClustering
_h[electronic resource] :
_btheoretical and practical aspects /
_cDan A. Simovici.
260 _aSingapore :
_bWorld Scientific,
_c2021.
300 _a1 online resource (884 p.).
505 0 _aIntroduction -- Set-theoretical preliminaries -- Dissimilarities, metrics, and ultrametrics -- Convexity -- Graphs and hypergraphs -- Partitional clustering -- Statistical approaches to clustering -- Hierarchical clustering -- Density-based clustering -- Categorical data clustering -- Spectral clustering -- Correlation and consensus clustering -- Clustering quality -- Clustering axiomatization -- Biclustering -- Semi-supervised clustering.
520 _a"This unique compendium gives an updated presentation of clustering, one of the most challenging tasks in machine learning. The book provides a unitary presentation of classical and contemporary algorithms ranging from partitional and hierarchical clustering up to density-based clustering, clustering of categorical data, and spectral clustering. Most of the mathematical background is provided in appendices, highlighting algebraic and complexity theory, in order to make this volume as self-contained as possible. A substantial number of exercises and supplements makes this a useful reference textbook for researchers and students."--
_cPublisher's website.
538 _aMode of access: World Wide Web.
538 _aSystem requirements: Adobe Acrobat Reader.
650 0 _aCluster analysis.
_926336
655 0 _aElectronic books.
_93294
856 4 0 _uhttps://www.worldscientific.com/worldscibooks/10.1142/12394#t=toc
_zAccess to full text is restricted to subscribers.
942 _cEBK
999 _c97810
_d97810