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).


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Reference manual

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install.packages("NADIA")

0.4.1 by Jan Borowski, 9 months ago


Report a bug at https://github.com/ModelOriented/EMMA/issues


Browse source code at https://github.com/cran/NADIA


Authors: Jan Borowski , Piotr Fic


Documentation:   PDF Manual  


Task views: Missing Data


GPL license


Imports mlr3learners, missForest, missMDA, doParallel, testthat, Amelia, VIM, softImpute, missRanger, methods, mice, data.table, foreach, glmnet

Depends on mlr3, mlr3pipelines, paradox

Suggests knitr, rmarkdown, kableExtra, magrittr


See at CRAN