Package: FeatureImpCluster 0.1.5

FeatureImpCluster: Feature Importance for Partitional Clustering

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: <https://christophm.github.io/interpretable-ml-book/feature-importance.html>.

Authors:Oliver Pfaffel [aut, cre]

FeatureImpCluster_0.1.5.tar.gz
FeatureImpCluster_0.1.5.zip(r-4.5)FeatureImpCluster_0.1.5.zip(r-4.4)FeatureImpCluster_0.1.5.zip(r-4.3)
FeatureImpCluster_0.1.5.tgz(r-4.5-any)FeatureImpCluster_0.1.5.tgz(r-4.4-any)FeatureImpCluster_0.1.5.tgz(r-4.3-any)
FeatureImpCluster_0.1.5.tar.gz(r-4.5-noble)FeatureImpCluster_0.1.5.tar.gz(r-4.4-noble)
FeatureImpCluster_0.1.5.tgz(r-4.4-emscripten)FeatureImpCluster_0.1.5.tgz(r-4.3-emscripten)
FeatureImpCluster.pdf |FeatureImpCluster.html
FeatureImpCluster/json (API)
NEWS

# Install 'FeatureImpCluster' in R:
install.packages('FeatureImpCluster', repos = c('https://o1iv3r.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/o1iv3r/featureimpcluster/issues

On CRAN:

Conda:

3.58 score 4 stars 19 scripts 316 downloads 1 mentions 3 exports 29 dependencies

Last updated 3 years agofrom:f66ba1c064. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-winOKApr 01 2025
R-4.5-macOKApr 01 2025
R-4.5-linuxOKApr 01 2025
R-4.4-winOKApr 01 2025
R-4.4-macOKApr 01 2025
R-4.4-linuxOKApr 01 2025
R-4.3-winOKApr 01 2025
R-4.3-macOKApr 01 2025

Exports:create_random_dataFeatureImpClusterPermMisClassRate

Dependencies:clicolorspacedata.tablefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr