VarSelLCM (2.1.3)

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

http://varsellcm.r-forge.r-project.org/
http://cran.r-project.org/web/packages/VarSelLCM

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.


8 previous versions

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