Partitional Clustering via Nonsmooth Optimization: Clustering via Optimization (1st ed. 2020) (Unsupervised and Semi-Supervised Learning)

By: Napsu Karmitsa and Sona Taheri and Adil M. Bagirov

Sign Up Now! Already a Member? Log In
You must be logged into Bookshare to access this title. Learn about membership options, or view our freely available titles.

Synopsis: This book describes optimization models of clustering problems and clustering algorithms based on optimization techniques, including their implementation, evaluation, and applications. The book gives a comprehensive and detailed description of optimization approaches for solving clustering problems; the authors' emphasis on clustering algorithms is based on deterministic methods of optimization. The book also includes results on real-time clustering algorithms based on optimization techniques, addresses implementation issues of these clustering algorithms, and discusses new challenges arising from big data. The book is ideal for anyone teaching or learning clustering algorithms. It provides an accessible introduction to the ﬁeld and it is well suited for practitioners already familiar with the basics of optimization.