Statistical and machine learning approaches for network analysis

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and grap...

Descripción completa

Detalles Bibliográficos
Autores principales: Dehmer, Matthias, Basak, Subhash C
Lenguaje:eng
Publicado: John Wiley & Sons 2012
Materias:
Mathematical Physics and Mathematics
Acceso en línea:http://cds.cern.ch/record/1487364
_version_ 1780926217553182720
author Dehmer, Matthias
Basak, Subhash C
author_facet Dehmer, Matthias
Basak, Subhash C
author_sort Dehmer, Matthias
collection CERN
description Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internation
id cern-1487364
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2012
publisher John Wiley & Sons
record_format invenio
spelling cern-14873642021-04-22T00:14:03Zhttp://cds.cern.ch/record/1487364engDehmer, MatthiasBasak, Subhash CStatistical and machine learning approaches for network analysisMathematical Physics and Mathematics Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification. By providing different approaches based on experimental data, the book uniquely sets itself apart from the current literature by exploring the application of machine learning techniques to various types of complex networks. Comprised of chapters written by internationJohn Wiley & Sonsoai:cds.cern.ch:14873642012
spellingShingle Mathematical Physics and Mathematics
Dehmer, Matthias
Basak, Subhash C
Statistical and machine learning approaches for network analysis
title Statistical and machine learning approaches for network analysis
title_full Statistical and machine learning approaches for network analysis
title_fullStr Statistical and machine learning approaches for network analysis
title_full_unstemmed Statistical and machine learning approaches for network analysis
title_short Statistical and machine learning approaches for network analysis
title_sort statistical and machine learning approaches for network analysis
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1487364
work_keys_str_mv AT dehmermatthias statisticalandmachinelearningapproachesfornetworkanalysis
AT basaksubhashc statisticalandmachinelearningapproachesfornetworkanalysis

Ejemplares similares