Hierarchical clustering based on the information bottleneck method using a control process
dc.contributor.author
dc.date.accessioned
2015-09-18T08:38:01Z
dc.date.available
2015-09-18T08:38:01Z
dc.date.issued
2015-08-24
dc.identifier.issn
1433-7541
dc.identifier.uri
dc.description.abstract
Clustering techniques aim organizing data into groups whose members are similar. A key element of these techniques is the definition of a similarity measure. The information bottleneck method provides us a full solution of the clustering problem with no need to define a similarity measure, since a variable is clustered depending on a control variable by maximizing the mutual information between them. In this paper, we propose a hierarchical clustering algorithm based on the information bottleneck method such that, instead of using a control variable, the different possible values of a Markov process are clustered by maximally preserving the mutual information between two consecutive states of the Markov process. These two states can be seen as the input and the output of an information channel that is used as a control process, similarly to how the variable is used as a control variable in the original information bottleneck algorithm. We present both agglomerative and divisive versions of our hierarchical clustering approach and two different applications. The first one, to quantize an image by grouping intensity bins of the image histograms, is tested on synthetic, photographic and medical images and compared with hand-labelled images, hierarchical clustering using Euclidean distance and non-negative matrix factorization methods. The second one, to cluster brain regions by grouping them depending on their connectivity, is tested on medical data. In all the applications, the obtained results demonstrate the efficacy of the method in getting clusters with high mutual information.
dc.description.sponsorship
This work was supported by the Spanish Government (Grant No. TIN2013-47276-C6-1-R) and by the Catalan Government (Grant No. 2014-SGR-1232)
dc.format.mimetype
application/pdf
dc.language.iso
eng
dc.publisher
Springer Verlag
dc.relation
info:eu-repo/grantAgreement/MINECO//TIN2013-47276-C6-1-R/ES/AVANCES EN CONTENIDOS DIGITALES PARA JUEGOS SERIOS/
AGAUR/2014-2016/2014 SGR-1232
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Reproducció digital del document publicat a: http://dx.doi.org/10.1007/s10044-015-0467-1
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© Pattern Analysis and Applications, 2015, vol. 18, núm. 3, p. 619-637
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Articles publicats (D-IMA)
dc.rights
Tots els drets reservats
dc.subject
dc.title
Hierarchical clustering based on the information bottleneck method using a control process
dc.type
info:eu-repo/semantics/article
dc.rights.accessRights
info:eu-repo/semantics/embargoedAccess
dc.embargo.terms
Cap
dc.date.embargoEndDate
info:eu-repo/date/embargoEnd/2026-01-01
dc.type.version
info:eu-repo/semantics/publishedVersion
dc.identifier.doi
dc.identifier.idgrec
023494
dc.contributor.funder
dc.relation.ProjectAcronym
dc.identifier.eissn
1433-755X