VarSelLCM: an R/C++ package for variable selection in model-based clustering of mixed-data with missing values.

Abstract

VarSelLCM allows a full model selection (detection of the relevant features for clustering and selection of the number of clusters) in model-based clustering, according to classical information criteria. Data to be analyzed can be composed of continuous, integer and/or categorical features. Moreover, missing values are managed, without any pre-processing, by the model used to cluster with the assumption that values are missing completely at random. Thus, VarSelLCM also allows data imputation by using mixture models. A Shiny application is implemented to easily interpret the clustering results. VarSelLCM is available to download at https://CRAN.R-project.org/package=VarSelLCM/. vignette is available online at http://varsellcm.r-forge.r-project.org/. Supplementary data are available at Bioinformatics online.