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Data clustering. Theory, algorithms, and applications. 2nd edition. (English) Zbl 07314177
Mathematics in Industry (Philadelphia) 5. Philadelphia, PA: Society for Industrial and Applied Mathematics (SIAM) (ISBN 978-1-61197-632-8/pbk; 978-1-61197-633-5/ebook). xxiii, 406 p. (2021).
Preliminary review / Publisher’s description: Data clustering, also known as cluster analysis, is an unsupervised process that divides a set of objects into homogeneous groups. Since the publication of the first edition of this monograph in 2007, development in the area has exploded, especially in clustering algorithms for big data and open-source software for cluster analysis. This second edition reflects these new developments.
This book:
covers the basics of data clustering,
includes a list of popular clustering algorithms, and
provides program code that helps users implement clustering algorithms.

This book will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.
For the first edition see [Zbl 1185.68274].
MSC:
68-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to computer science
62-01 Introductory exposition (textbooks, tutorial papers, etc.) pertaining to statistics
62H30 Classification and discrimination; cluster analysis (statistical aspects)
62R07 Statistical aspects of big data and data science
68T05 Learning and adaptive systems in artificial intelligence
68T09 Computational aspects of data analysis and big data
68T10 Pattern recognition, speech recognition
92-08 Computational methods for problems pertaining to biology
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