VarSelLCM (version 2.1.1)
Variable Selection for Model-Based Clustering of Mixed-Type Data
Set with Missing Values
Description
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.