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portada Partitional Clustering via Nonsmooth Optimization: Clustering via Optimization (Unsupervised and Semi-Supervised Learning)
Type
Physical Book
Publisher
Author
Language
English
Pages
415
Format
Hardcover
ISBN13
9783031765117
Edition No.
2

Partitional Clustering via Nonsmooth Optimization: Clustering via Optimization (Unsupervised and Semi-Supervised Learning)

Adil Bagirov; Napsu Karmitsa; Sona Taheri (Author) · Springer · Hardcover

Partitional Clustering via Nonsmooth Optimization: Clustering via Optimization (Unsupervised and Semi-Supervised Learning) - Adil Bagirov; Napsu Karmitsa; Sona Taheri

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Synopsis "Partitional Clustering via Nonsmooth Optimization: Clustering via Optimization (Unsupervised and Semi-Supervised Learning)"

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 field and it is well suited for practitioners already familiar with the basics of optimization.

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