MixCluster: MixCluster performs the clustering of mixed-type data sets (data sets with different natures of variables) with missing values.

MixCluster performs the cluster analysis of mixed-type data (data set composed by different natures of variables). More precisely, it can analyze data whose the variables are continuous, integer, binary or ordinal. MixCluster models the data distribution by a mixture model of Gaussian copulas (Marbac and al, 2015). Therefore, it takes the intra-class dependencies into account and the one-dimensional margins of its components follow classical distributions (Gaussian, Poisson or multinomial). The inference is performed by a Gibbs sampler implemented in MixCluster. Moreover, tool-functions are focused on the data visualization. They used the latent variables related to the Gaussian copulas in order to obtain a scatterplot of the individuals per class by using PCA-type visualization. This approach also permit to summarize the intra-class dependencies.

AuthorMatthieu Marbac & Christophe Biernacki & Vincent Vandewalle
Date of publication2015-09-24 15:29:58
MaintainerMatthieu Marbac <matthieu.marbac-lourdelle@inria.fr>
LicenseGPL (>=2)

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forestfires Man page
MixClusClustering Man page
MixClusData-class Man page
MixClusModel_hetero-class Man page
MixClusModel_homo-class Man page
MixClusModel_indpt-class Man page
MixClusParam-class Man page
MixClusParam_continuous-class Man page
MixClusParam_integer-class Man page
MixClusParam_ordinal-class Man page
MixClusPrior_continuous-class Man page
MixClusPrior_integer-class Man page
MixClusPrior_ordinal-class Man page
MixClusResults-class Man page
MixCluster Man page
MixCluster-package Man page
MixClusUpdateForVisu Man page
MixClusVisu Man page
plot Man page
plot,MixClusResults,ANY-method Man page
saheart Man page
simu Man page
summary Man page
summary,MixClusResults-method Man page

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