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...
| Autor principal: | |
|---|---|
| Otros Autores: | |
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Hoboken, N.J. :
Wiley
2012.
|
| Edición: | 1st edition |
| Colección: | Wiley Series in Computational Statistics
|
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009628538506719 |
| Sumario: | "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"-- |
|---|---|
| Notas: | Description based upon print version of record. |
| Descripción Física: | 1 online resource (345 p.) |
| Bibliografía: | Includes bibliographical references and index. |
| ISBN: | 9781280872716 9786613714022 9781118346983 9781118346990 9781118347010 |
