Other packages > Find by keyword >

vimpclust  

Variable Importance in Clustering
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("vimpclust", "0.1.0")



Attach the package and use:
library("vimpclust")
Maintained by
Madalina Olteanu
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-01-08
Latest Update: 2021-01-08
Description:
An implementation of methods related to sparse clustering and variable importance in clustering. The package currently allows to perform sparse k-means clustering with a group penalty, so that it automatically selects groups of numerical features. It also allows to perform sparse clustering and variable selection on mixed data (categorical and numerical features), by preprocessing each categorical feature as a group of numerical features. Several methods for visualizing and exploring the results are also provided. M. Chavent, J. Lacaille, A. Mourer and M. Olteanu (2020)<https://www.esann.org/sites/default/files/proceedings/2020/ES2020-103.pdf>.
How to cite:
Madalina Olteanu (2021). vimpclust: Variable Importance in Clustering. R package version 0.1.0, https://cran.r-project.org/web/packages/vimpclust. Accessed 05 Aug. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited vimpclust R package
View vimpclust citation profile
Other R packages that vimpclust depends, imports, suggests or enhances
Complete documentation for vimpclust
Functions, R codes and Examples using the vimpclust R package
Some associated functions: DataMice . HDdata . check_fun_groupsparsw . groupsoft . groupsparsewkm . info_clust . plot.spwkm . recodmix . sparsewkm . weightedss . 
Some associated R codes: DataMice.R . HDdata.R . checkingconditions.R . groupsoft.R . groupsparsewkm.R . info_clust.R . plot.spwkm.R . recodmix.R . sparsewkm.R . weightedss.R .  Full vimpclust package functions and examples
Downloads during the last 30 days

Today's Hot Picks in Authors and Packages

noisyr  
Noise Quantification in High Throughput Sequencing Output
Quantifies and removes technical noise from high-throughput sequencing data. Two approaches are use ...
Download / Learn more Package Citations See dependency  
dhReg  
Dynamic Harmonic Regression
Building and forecasting time series data with multiple seasonality using Dynamic Harmonic Regressio ...
Download / Learn more Package Citations See dependency  
quickcode  
Quick and Essential 'R' Tricks for Better Scripts
The NOT functions, 'R' tricks and a compilation of some simple quick plus often used 'R' codes to im ...
Download / Learn more Package Citations See dependency  
kernelPSI  
Post-Selection Inference for Nonlinear Variable Selection
Different post-selection inference strategies for kernelselection as described in kernelPSI a Post-S ...
Download / Learn more Package Citations See dependency  
dcov  
A Fast Implementation of Distance Covariance
Efficient methods for computing distance covariance and relevant statistics. See Sz ...
Download / Learn more Package Citations See dependency  

28,083

R Packages

239,283

Dependencies

74,457

Author Associations

28,084

Publication Badges

© Copyright since 2022. All right reserved, rpkg.net.  Based in Cambridge, Massachusetts, USA