Téléchargez le livre : Unsupervised Learning Algorithms
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Description

This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity among researchers and practitioners. The authors outline how these algorithms have found numerous applications including pattern recognition, market basket analysis, web mining, social network analysis, information retrieval, recommender systems, market research, intrusion detection, and fraud detection. They present how the difficulty of developing theoretically sound approaches that are amenable to objective evaluation have resulted in the proposal of numerous unsupervised learning algorithms over the past half-century. The intended audience includes researchers and practitioners who are increasingly using unsupervised learning algorithms to analyze their data. Topics of interest includeanomaly detection, clustering, feature extraction, and applications of unsupervised learning. Each chapter is contributed by a leading expert in the field.
Pages
558 pages
Collection
n.c
Parution
2016-04-29
Marque
Springer
EAN papier
9783319242095
EAN EPUB
9783319242118
Informations sur l'ebook
Nombre pages copiables
5
Nombre pages imprimables
55
Taille du fichier
7741 Ko
Ce livre est accessible aux handicaps Voir les informations sur l'accessibilité
Prix
105,49 €

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