Data Clustering: Theory, Algorithms, and Applications, Second Edition
Guojun Gan & Chaoqun Ma & Jianhong Wu
Language: English
Business & Economics Business & Productivity Software Computers Data Analytics Data Science Databases Games General Machine Theory Mathematics Probability & Statistics Programming Statistics Time Series
Publisher: SIAM
Published: Nov 10, 2020
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, 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.