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Co-clustering: models, algorithms and applications
Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approach...
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Lenguaje: | eng |
Publicado: |
Wiley
2013
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Acceso en línea: | http://cds.cern.ch/record/2122947 |
_version_ | 1780949497108496384 |
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author | Govaert, Gérard Nadif, Mohamed |
author_facet | Govaert, Gérard Nadif, Mohamed |
author_sort | Govaert, Gérard |
collection | CERN |
description | Cluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach.<br /> Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixture |
id | cern-2122947 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2013 |
publisher | Wiley |
record_format | invenio |
spelling | cern-21229472021-04-21T19:52:10Zhttp://cds.cern.ch/record/2122947engGovaert, GérardNadif, MohamedCo-clustering: models, algorithms and applicationsMathematical Physics and MathematicsCluster or co-cluster analyses are important tools in a variety of scientific areas. The introduction of this book presents a state of the art of already well-established, as well as more recent methods of co-clustering. The authors mainly deal with the two-mode partitioning under different approaches, but pay particular attention to a probabilistic approach.<br /> Chapter 1 concerns clustering in general and the model-based clustering in particular. The authors briefly review the classical clustering methods and focus on the mixture model. They present and discuss the use of different mixtureWileyoai:cds.cern.ch:21229472013 |
spellingShingle | Mathematical Physics and Mathematics Govaert, Gérard Nadif, Mohamed Co-clustering: models, algorithms and applications |
title | Co-clustering: models, algorithms and applications |
title_full | Co-clustering: models, algorithms and applications |
title_fullStr | Co-clustering: models, algorithms and applications |
title_full_unstemmed | Co-clustering: models, algorithms and applications |
title_short | Co-clustering: models, algorithms and applications |
title_sort | co-clustering: models, algorithms and applications |
topic | Mathematical Physics and Mathematics |
url | http://cds.cern.ch/record/2122947 |
work_keys_str_mv | AT govaertgerard coclusteringmodelsalgorithmsandapplications AT nadifmohamed coclusteringmodelsalgorithmsandapplications |