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ClustImpute

K-Means Clustering with Build-in Missing Data Imputation

v0.2.4 · May 31, 2021 · GPL-3

Description

This k-means algorithm is able to cluster data with missing values and as a by-product completes the data set. The implementation can deal with missing values in multiple variables and is computationally efficient since it iteratively uses the current cluster assignment to define a plausible distribution for missing value imputation. Weights are used to shrink early random draws for missing values (i.e., draws based on the cluster assignments after few iterations) towards the global mean of each feature. This shrinkage slowly fades out after a fixed number of iterations to reflect the increasing credibility of cluster assignments. See the vignette for details.

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Maintainer: ‘Oliver Pfaffel <opfaffel@gmail.com>’

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CRAN incoming feasibility

Maintainer: ‘Oliver Pfaffel <opfaffel@gmail.com>’

No Authors@R field in DESCRIPTION.
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  Authors@R: person(given = "Oliver",
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                    email = "opfaffel@gmail.com")
as necessary.

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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Oliver Pfaffel <opfaffel@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Oliver",
                    family = "Pfaffel",
                    role = c("aut", "cre"),
                    email = "opfaffel@gmail.com")
as necessary.

Package CITATION file contains call(s) to old-style citEntry().  Please
use bibentry() instead.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Oliver Pfaffel <opfaffel@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: person(given = "Oliver",
                    family = "Pfaffel",
                    role = c("aut", "cre"),
                    email = "opfaffel@gmail.com")
as necessary.

Package CITATION file contains call(s) to old-style citEntry().  Please
use bibentry() instead.

Reverse Dependencies (1)

Dependency Network

Dependencies Reverse dependencies ClusterR copula dplyr magrittr tidyr ggplot2 rlang knitr FeatureImpCluster ClustImpute

Version History

new 0.2.4 Mar 10, 2026