Package: VarSelLCM 2.1.3.1

Mohammed Sedki

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.

Authors:Matthieu Marbac and Mohammed Sedki

VarSelLCM_2.1.3.1.tar.gz
VarSelLCM_2.1.3.1.tar.gz(r-4.5-noble)VarSelLCM_2.1.3.1.tar.gz(r-4.4-noble)
VarSelLCM_2.1.3.1.tgz(r-4.4-emscripten)VarSelLCM_2.1.3.1.tgz(r-4.3-emscripten)
VarSelLCM.pdf |VarSelLCM.html✨
VarSelLCM/json (API)
NEWS

# Install 'VarSelLCM' in R:
install.packages('VarSelLCM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://r-forge.r-project.org/projects/varsellcm

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • heart - Statlog (Heart) Data Set

4.22 score 2 stars 2 packages 46 scripts 387 downloads 3 mentions 16 exports 52 dependencies

Last updated 4 years agofrom:0b5096967d. Checks:OK: 1 WARNING: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-linux-x86_64WARNINGNov 20 2024

Exports:AICARIBICcoefcoefficientsfittedfitted.valuesICLMICLplotpredictprintsummaryVarSelClusterVarSelImputationVarSelShiny

Dependencies:base64encbslibcachemclicolorspacecommonmarkcrayondigestfansifarverfastmapfontawesomefsggplot2gluegtablehtmltoolshttpuvisobandjquerylibjsonlitelabelinglaterlatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigpromisesR6rappdirsRColorBrewerRcppRcppArmadillorlangsassscalesshinysourcetoolstibbleutf8vctrsviridisLitewithrxtable

Vignette VarSelLCM

Rendered fromVarSelLCM.Rmdusingknitr::rmarkdownon Nov 20 2024.

Last update: 2018-06-20
Started: 2018-03-19

Readme and manuals

Help Manual

Help pageTopics
Variable Selection for Model-Based Clustering of Mixed-Type Data Set with Missing ValuesVarSelLCM-package VarSelLCM
AIC criterion.AIC AIC,VSLCMresults-method
Adjusted Rand IndexARI
BIC criterion.BIC BIC,VSLCMresults-method
Extract the parameterscoef coef,VSLCMresults-method
Extract the parameterscoefficients coefficients,VSLCMresults-method
Extract the partition or the probabilities of classificationfitted fitted,VSLCMresults-method
Extract the partition or the probabilities of classificationfitted.values fitted.values,VSLCMresults-method
Statlog (Heart) Data Setheart
ICL criterionICL
MICL criterionMICL
Plots of an instance of 'VSLCMresults'plot plot,VSLCMresults,ANY-method plot,VSLCMresults,character-method plot,VSLCMresults-method
Prediction of the cluster membershipspredict predict,VSLCMresults-method
Print function.print print,VSLCMresults-method
Summary function.summary summary,VSLCMresults-method
Variable selection and clustering.VarSelCluster
Imputation of missing valuesVarSelImputation
Shiny app for analyzing results from VarSelClusterVarSelShiny
Constructor of 'VSLCMcriteria' classVSLCMcriteria-class
Constructor of 'VSLCMdata' classVSLCMdata-class
Constructor of 'VSLCMmodel' classVSLCMmodel-class
Constructor of 'VSLCMparam' classVSLCMparam-class
Constructor of 'VSLCMparamCategorical' classVSLCMparamCategorical-class
Constructor of 'VSLCMparamContinuous' classVSLCMparamContinuous-class
Constructor of 'VSLCMparamInteger' classVSLCMparamInteger-class
Constructor of 'VSLCMpartitions' classVSLCMpartitions-class
Constructor of 'VSLCMresults' classVSLCMresults-class
Constructor of 'VSLCMstrategy' classVSLCMstrategy-class