Data Clustering: Theory, Algorithms, and Applications, Second Edition

by Guojun Gan, Chaoqun Ma, Jianhong Wu

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, covers the basics of data clustering, includes a list of popular clustering algorithms, and provides program code that helps users implement clustering algorithms. Data Clustering: Theory, Algorithms and Applications, Second Edition will be of interest to researchers, practitioners, and data scientists as well as undergraduate and graduate students.

406 pages, Paperback

First published May 30, 2007

Reviews

[Leonardo]

Lo recomendó Fran en el curso de Data Science de CEPAL