Partitional Clustering via Nonsmooth Optimization
Adil M. Bagirov, Sona Taheri, Napsu Karmitsa, et al.
Springer International Publishing 
Naturwissenschaften, Medizin, Informatik, Technik / Elektronik, Elektrotechnik, Nachrichtentechnik
Beschreibung
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.
Kundenbewertungen
Clustering algorithms based on metaheuristics, Real-time clustering algorithms, Optimization models of clustering problems, Clustering with different similarity measures, Heuristic clustering algorithms, Nonsmooth optimization based clustering algorithms, Visualization of clustering results, Global optimization based clustering algorithms, Application of clustering algorithms, Clustering in very large data sets