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VarSelLCM  

Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing Values
View on CRAN: Click here


Download and install VarSelLCM package within the R console
Install from CRAN:
install.packages("VarSelLCM")

Install from Github:
library("remotes")
install_github("cran/VarSelLCM")

Install by package version:
library("remotes")
install_version("VarSelLCM", "2.1.3.1")



Attach the package and use:
library("VarSelLCM")
Maintained by
Mohammed Sedki
[Scholar Profile | Author Map]
First Published: 2015-03-19
Latest Update: 2020-10-14
Description:
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.
How to cite:
Mohammed Sedki (2015). VarSelLCM: Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing Values. R package version 2.1.3.1, https://cran.r-project.org/web/packages/VarSelLCM. Accessed 20 Feb. 2025.
Previous versions and publish date:
1.0 (2015-03-19 23:47), 1.1 (2015-05-22 18:55), 1.2 (2015-06-10 19:00), 2.0.1 (2017-10-16 12:16), 2.0 (2017-09-22 17:38), 2.1.0 (2018-03-19 09:37), 2.1.1 (2018-04-12 10:42), 2.1.2 (2018-06-20 19:37), 2.1.3 (2018-08-29 12:24)
Other packages that cited VarSelLCM R package
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Complete documentation for VarSelLCM
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