Handbook of mixed membership models and their applications

In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling t...

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Detalles Bibliográficos
Autores principales: Airoldi, Edoardo M, Blei, David, Erosheva, Elena A, Fienberg, Stephen E
Lenguaje:eng
Publicado: Taylor and Francis 2014
Materias:
Mathematical Physics and Mathematics
Acceso en línea:http://cds.cern.ch/record/1974849
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author Airoldi, Edoardo M
Blei, David
Erosheva, Elena A
Fienberg, Stephen E
author_facet Airoldi, Edoardo M
Blei, David
Erosheva, Elena A
Fienberg, Stephen E
author_sort Airoldi, Edoardo M
collection CERN
description In response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology.Through examples using real data sets, yo
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publishDate 2014
publisher Taylor and Francis
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spelling cern-19748492021-04-21T20:41:12Zhttp://cds.cern.ch/record/1974849engAiroldi, Edoardo MBlei, DavidErosheva, Elena AFienberg, Stephen EHandbook of mixed membership models and their applicationsMathematical Physics and MathematicsIn response to scientific needs for more diverse and structured explanations of statistical data, researchers have discovered how to model individual data points as belonging to multiple groups. Handbook of Mixed Membership Models and Their Applications shows you how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology.Through examples using real data sets, yoTaylor and Francisoai:cds.cern.ch:19748492014
spellingShingle Mathematical Physics and Mathematics
Airoldi, Edoardo M
Blei, David
Erosheva, Elena A
Fienberg, Stephen E
Handbook of mixed membership models and their applications
title Handbook of mixed membership models and their applications
title_full Handbook of mixed membership models and their applications
title_fullStr Handbook of mixed membership models and their applications
title_full_unstemmed Handbook of mixed membership models and their applications
title_short Handbook of mixed membership models and their applications
title_sort handbook of mixed membership models and their applications
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1974849
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