Dynamic Graph Learning for Dimension Reduction and Data Clustering

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Éditeur :

Springer


Paru le : 2023-09-20

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Description

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.
Pages
143 pages
Collection
n.c
Parution
2023-09-20
Marque
Springer
EAN papier
9783031423123
EAN PDF
9783031423130

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
14
Taille du fichier
2550 Ko
Prix
42,19 €
EAN EPUB
9783031423130

Informations sur l'ebook
Nombre pages copiables
1
Nombre pages imprimables
14
Taille du fichier
17848 Ko
Prix
42,19 €

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