clustvarsel: Variable Selection for Model-Based Clustering A function which implements variable selection methodology for model-based clustering which allows to find the (locally) optimal subset of variables in a dataset that have group/cluster information. A greedy or headlong search can be used, either in a forward-backward or backward-forward direction, with or without sub-sampling at the hierarchical clustering stage for starting Mclust models. By default the algorithm uses a sequential search, but parallelization is also available.