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missForest: Nonparametric Missing Value Imputation using Random Forest
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.
Getting started
Browse package contents
Package details |
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| Author | Daniel J. Stekhoven <stekhoven@stat.math.ethz.ch> |
| Maintainer | Daniel J. Stekhoven <stekhoven@stat.math.ethz.ch> |
| License | GPL (>= 2) |
| Version | 1.5 |
| URL | https://www.r-project.org https://github.com/stekhoven/missForest |
| Package repository | View on CRAN |
| Installation |
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