Téléchargez le livre : Partitional Clustering via Nonsmooth Optimization

Partitional Clustering via Nonsmooth Optimization

Clustering via Optimization de

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Éditeur :

Springer


Collection :

Unsupervised and Semi-Supervised Learning

Paru le : 2024-12-16

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Description

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.
Pages
395 pages
Collection
Unsupervised and Semi-Supervised Learning
Parution
2024-12-16
Marque
Springer
EAN papier
9783031765117
EAN PDF
9783031765124
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
39
Taille du fichier
16108 Ko
Prix
147,69 €
EAN EPUB
9783031765124
Informations sur l'ebook
Nombre pages copiables
3
Nombre pages imprimables
39
Taille du fichier
53268 Ko
Prix
147,69 €

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