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wkNNMI
View on CRAN: Click
here
Download and install wkNNMI package within the R console
Install from CRAN:
install.packages("wkNNMI")
Install from Github:
library("remotes")
install_github("cran/wkNNMI") Install by package version:
library("remotes")
install_version("wkNNMI", "1.0.0") Attach the package and use:
library("wkNNMI")
Maintained by
Sebastian Daberdaku
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-01-31
Latest Update:
Description:
Implementation of an adaptive weighted k-nearest neighbours wk-NN imputation algorithm for clinical register data developed to explicitly handle missing values of continuousordinalcategorical and staticdynamic features conjointly. For each subject with missing data to be imputed the method creates a feature vector constituted by the information collected over hisher first windowsize time units of visits. This vector is used as sample in a k-nearest neighbours procedure in order to select among the other patients the ones with the most similar temporal evolution of the disease over time. An ad hoc similarity metric was implemented for the sample comparison capable of handling the different nature of the data the presence of multiple missing values and include the cross-information among features.
How to cite:
Sebastian Daberdaku (2020). wkNNMI: A Mutual Information-Weighted k-NN Imputation Algorithm. R package version 1.0.0, https://cran.r-project.org/web/packages/wkNNMI. Accessed 16 Jul. 2026.
Previous versions and publish date:
(2026-07-09 07:00), 1.0.0 (2020-01-31 15:20)
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Other R packages that wkNNMI depends,
imports, suggests or enhances
Functions, R codes and Examples using
the wkNNMI R package
Some associated functions: impute.subject . impute.wknn . new.patient . patient.data . wkNNMI .
Some associated R codes: imputation.wknn.mi.R . new.patient.R . patient.data.R . Full wkNNMI package functions and examples
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