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Statistical and machine learning approaches for network analysis /

"This book explores novel graph classes and presents novel methods to classify networks. It particularly addresses the following problems: exploration of novel graph classes and their relationships among each other; existing and classical methods to analyze networks; novel graph similarity and...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Dehmer, Matthias, 1968-
Otros Autores: Basak, Subhash C., 1945-
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Hoboken, N.J. : Wiley, 2012.
Colección:Wiley series in computational statistics ; 707
Temas:
Acceso en línea:Texto completo
Texto completo

MARC

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245 1 0 |a Statistical and machine learning approaches for network analysis /  |c Matthias Dehmer, Subhash C. Basak. 
260 |a Hoboken, N.J. :  |b Wiley,  |c 2012. 
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490 0 |a Wiley series in computational statistics ;  |v 707 
520 |a "This book explores novel graph classes and presents novel methods to classify networks. It particularly addresses the following problems: exploration of novel graph classes and their relationships among each other; existing and classical methods to analyze networks; novel graph similarity and graph classification techniques based on machine learning methods; and applications of graph classification and graph mining. Key topics are addressed in depth including the mathematical definition of novel graph classes, i.e. generalized trees and directed universal hierarchical graphs, and the application areas in which to apply graph classes to practical problems in computational biology, computer science, mathematics, mathematical psychology, etc"--  |c Provided by publisher. 
504 |a Includes bibliographical references and index. 
588 0 |a Print version record and CIP data provided by publisher. 
505 0 |a Statistical and Machine Learning Approaches for Network Analysis; Contents; Preface; Contributors; 1 A Survey of Computational Approaches to Reconstruct and Partition Biological Networks; 1.1 INTRODUCTION; 1.2 BIOLOGICAL NETWORKS; 1.2.1 Directed Networks; 1.2.2 Undirected Networks; 1.3 GENOME-WIDE MEASUREMENTS; 1.3.1 Gene Expression Data; 1.3.2 Gene Sets; 1.4 RECONSTRUCTION OF BIOLOGICAL NETWORKS; 1.4.1 Reconstruction of Directed Networks; 1.4.1.1 Boolean Networks; 1.4.1.2 Probabilistic Boolean Networks; 1.4.1.3 Bayesian Networks; 1.4.1.4 Collaborative Graph Model; 1.4.1.5 Frequency Method. 
546 |a English. 
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650 0 |a Research  |x Statistical methods. 
650 0 |a Machine theory. 
650 0 |a Communication  |x Network analysis  |x Graphic methods. 
650 0 |a Information science  |x Statistical methods. 
650 6 |a Recherche  |x Méthodes statistiques. 
650 6 |a Théorie des automates. 
650 6 |a Communication  |x Analyse de réseau  |x Méthodes graphiques. 
650 7 |a MATHEMATICS  |x Probability & Statistics  |x General.  |2 bisacsh 
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650 7 |a Machine theory  |2 fast 
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