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.
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curl https://depscope.dev/api/check/conda/r-missforestFirst published · 2021-05-24 20:42:56.452000+00:00
Last updated · 2025-10-26 15:49:23.766000+00:00