# knn.impute: 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

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.