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VarSelLCM: 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 <doi:10.1007/s11222-016-9670-1>). 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.
Getting started
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Package details |
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| Author | Matthieu Marbac and Mohammed Sedki |
| Maintainer | Mohammed Sedki <mohammed.sedki@u-psud.fr> |
| License | GPL (>= 2) |
| Version | 2.1.3.1 |
| URL | http://varsellcm.r-forge.r-project.org/ |
| Package repository | View on CRAN |
| Installation |
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