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Finite mixture modeling provides a framework for cluster analysis based on parsimonious Gaussian mixture models. Variable or feature selection is of particular importance in situations where only a subset of the available variables provide clustering information. This enables the selection of a more parsimonious model, yielding more efficient estimates, a clearer interpretation and, often, improved clustering partitions. This paper describes the R package clustvarsel which performs subsetdoi:10.18637/jss.v084.i01 pmid:30450020 pmcid:PMC6238955 fatcat:2v6ypaetgvdfxjxwobsp2iqsxu