Dynamic Graph Learning for Dimension Reduction and Data Clustering - Couverture rigide
- ÉditeurSpringer International Publishing AG
- Date d'édition2023
- ISBN 10 3031423127
- ISBN 13 9783031423123
- ReliureRelié
- Nombre de pages143
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Dynamic Graph Learning for Dimension Reduction and Data Clustering
Edité par
Springer Nature Switzerland Okt 2023, 2023
ISBN 10 : 3031423127
ISBN 13 : 9783031423123
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering. 168 pp. Englisch. N° de réf. du vendeur 9783031423123
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Dynamic Graph Learning for Dimension Reduction and Data Clustering
Edité par
Springer Nature Switzerland, Springer International Publishing, 2023
ISBN 10 : 3031423127
ISBN 13 : 9783031423123
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book illustrates how to achieve effective dimension reduction and data clustering. The authors explain how to accomplish this by utilizing the advanced dynamic graph learning technique in the era of big data. The book begins by providing background on dynamic graph learning. The authors discuss why it has attracted considerable research attention in recent years and has become well recognized as an advanced technique. After covering the key topics related to dynamic graph learning, the book discusses the recent advancements in the area. The authors then explain how these techniques can be practically applied for several purposes, including feature selection, feature projection, and data clustering. N° de réf. du vendeur 9783031423123
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Dynamic Graph Learning for Dimension Reduction and Data Clustering
Edité par
Springer Nature Switzerland, 2023
ISBN 10 : 3031423127
ISBN 13 : 9783031423123
Neuf
Couverture rigide
Vendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides thorough background information on dynamic graph learning and the recent advancements in the areaDescribes the benefits of utilizing dynamic graph learning, as compared to a fixed graph approachCovers several practical applications. N° de réf. du vendeur 945398625
Quantité disponible : Plus de 20 disponibles