VarSelLCM (2.1.1)

Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing Values.

Full model selection (detection of the relevant features and estimation of the number of clusters) for model-based clustering (see reference here ). Data to analyze can be continuous, categorical, integer or mixed. Moreover, missing values can occur and do not necessitate any pre-processing. Shiny application permits an easy interpretation of the results.

Maintainer: Mohammed Sedki
Author(s): Matthieu Marbac and Mohammed Sedki

License: GPL (>= 2)

Uses: ggplot2, mgcv, Rcpp, shiny, plyr, scales, knitr, dplyr, htmltools, rmarkdown

Released about 1 year ago.