knn.impute {bnstruct} | R Documentation |

## Perform imputation of a data frame using k-NN.

### Description

Perform imputation of missing data in a data frame using the k-Nearest Neighbour algorithm. For discrete variables we use the mode, for continuous variables the median value is instead taken.

### Usage

```
knn.impute(
data,
k = 10,
cat.var = 1:ncol(data),
to.impute = 1:nrow(data),
using = 1:nrow(data)
)
```

### Arguments

`data` |
a numerical matrix. |

`k` |
number of neighbours to be used; for categorical variables the mode of the neighbours is used, for continuous variables the median value is used instead. Default: 10. |

`cat.var` |
vector containing the indices of the variables to be considered as categorical. Default: all variables. |

`to.impute` |
vector indicating which rows of the dataset are to be imputed. Default: impute all rows. |

`using` |
vector indicating which rows of the dataset are to be used to search for neighbours. Default: use all rows. |

### Value

imputed matrix.

[Package

*bnstruct*version 1.0.15 Index]