The function 'missForest' in this package is used to impute missing values particularly in the case of mixed-type data. It uses a random forest trained on the observed values of a data matrix to predict the missing values. It can be used to impute continuous and/or categorical data including complex interactions and non-linear relations. It yields an out-of-bag (OOB) imputation error estimate without the need of a test set or elaborate cross-validation. It can be run in parallel to save computation time.
Documentation: Downloads: Reverse dependencies: Reverse depends: bartMachine, imp4p Reverse imports: ADAPTS, bartXViz, fastml, funspace, FuzzyImputationTest, GenoPop, highMLR, imanr, KarsTS, longit, MAI, MERO, missCompare, MSPrep, obliqueRSF, pmp, promor, simputation, speaq, streamDAG Reverse suggests: CALIBERrfimpute, DepInfeR, hdImpute, mrIML, MsCoreUtils, mvs, qmtools, tidyLPA Linking:Please use the canonical form https://CRAN.R-project.org/package=missForest to link to this page.
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