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FeatureImpCluster  

Feature Importance for Partitional Clustering
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("FeatureImpCluster", "0.1.5")



Attach the package and use:
library("FeatureImpCluster")
Maintained by
Oliver Pfaffel
[Scholar Profile | Author Map]
First Published: 2020-05-18
Latest Update: 2021-10-20
Description:
Implements a novel approach for measuring feature importance in k-means clustering. Importance of a feature is measured by the misclassification rate relative to the baseline cluster assignment due to a random permutation of feature values. An explanation of permutation feature importance in general can be found here: .
How to cite:
Oliver Pfaffel (2020). FeatureImpCluster: Feature Importance for Partitional Clustering. R package version 0.1.5, https://cran.r-project.org/web/packages/FeatureImpCluster. Accessed 27 Feb. 2025.
Previous versions and publish date:
0.1.2 (2020-05-18 11:40), 0.1.4 (2021-06-03 13:00)
Other packages that cited FeatureImpCluster R package
View FeatureImpCluster citation profile
Other R packages that FeatureImpCluster depends, imports, suggests or enhances
Complete documentation for FeatureImpCluster
Functions, R codes and Examples using the FeatureImpCluster R package
Some associated functions: FeatureImpCluster . PermMisClassRate . create_random_data . plot . 
Some associated R codes: create_random_data.R . featureimpcluster.R . permmisclassrate.R .  Full FeatureImpCluster package functions and examples
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