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.
|Author||Daniel J. Stekhoven <[email protected]>|
|Maintainer||Daniel J. Stekhoven <[email protected]>|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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