R: Rough Imputation of Missing Values

na.roughfix {randomForest} | R Documentation

## Rough Imputation of Missing Values

### Description

Impute Missing Values by median/mode.

### Usage

    na.roughfix(object, ...)

### Arguments

`object` | a data frame or numeric matrix.
`...` | further arguments special methods could require.

### Value

A completed data matrix or data frame. For numeric variables, `NA`s are replaced with column medians. For factor variables, `NA`s are replaced with the most frequent levels (breaking ties at random). If `object` contains no `NA`s, it is returned unaltered.

### Note

This is used as a starting point for imputing missing values by random forest.

### Author(s)

Andy Liaw

### See Also

`rfImpute`, `randomForest`.

### Examples

    data(iris)
    iris.na <- iris
    set.seed(111)
    ## artificially drop some data values.
    for (i in 1:4) iris.na[sample(150, sample(20)), i] <- NA
    iris.roughfix <- na.roughfix(iris.na)
    iris.narf <- randomForest(Species ~ ., iris.na, na.action=na.roughfix)
    print(iris.narf)

[Package randomForest version 4.6-14 Index]