NADIA: NA Data Imputation Algorithms

Creates a uniform interface for several advanced imputations missing data methods. Every available method can be used as a part of 'mlr3' pipelines which allows easy tuning and performance evaluation. Most of the used functions work separately on the training and test sets (imputation is trained on the training set and impute training data. After that imputation is again trained on the test set and impute test data).

Version: 0.4.1
Depends: R (≥ 3.5.0), mlr3, mlr3pipelines, paradox
Imports: mlr3learners, missForest, missMDA, doParallel, testthat, Amelia, VIM, softImpute, missRanger, methods, mice, data.table, foreach, glmnet
Suggests: knitr, rmarkdown, kableExtra, magrittr
Published: 2021-01-06
Author: Jan Borowski, Piotr Fic
Maintainer: Jan Borowski <janborowka7 at gmail.com>
BugReports: https://github.com/ModelOriented/EMMA/issues
License: GPL-2 | GPL-3 [expanded from: GPL]
NeedsCompilation: no
In views: MissingData
CRAN checks: NADIA results

Downloads:

Reference manual: NADIA.pdf
Vignettes: Errors Statistic and Handling
NADIA examples and motivation
Package source: NADIA_0.4.1.tar.gz
Windows binaries: r-devel: NADIA_0.4.1.zip, r-release: NADIA_0.4.1.zip, r-oldrel: NADIA_0.4.1.zip
macOS binaries: r-release: NADIA_0.4.1.tgz, r-oldrel: NADIA_0.4.1.tgz
Old sources: NADIA archive

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