Partitional clustering nonsmooth optimization von bagirov adil (20 Ergebnisse)

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Taschenbuch. Zustand: Neu. Partitional Clustering via Nonsmooth Optimization | Clustering via Optimization | Adil Bagirov (u. a.) | Taschenbuch | Unsupervised and Semi-Supervised Learning | xx | Englisch | 2025 | Springer | EAN 9783031765148 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

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Buch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This updated 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 challengesarising from very large data and data with noise and outliers. 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. 416 pp. Englisch.…

Buch. Zustand: Neu. Partitional Clustering via Nonsmooth Optimization | Clustering via Optimization | Adil Bagirov (u. a.) | Buch | Unsupervised and Semi-Supervised Learning | xx | Englisch | 2024 | Springer | EAN 9783031765117 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. …

Buch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This updated 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 very large data and data with noise and outliers. The book is ideal for anyone teaching or learning clustering algorithms. It provides an accessible introduction to the ¿eld and it is well suited for practitioners already familiar with the basics of optimization.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 416 pp. Englisch.…

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