impute_nas_knn: Impute missing values with kNN

In specmine: Metabolomics and Spectral Data Analysis and Mining

Impute missing values with kNN

Description

Replace missing values using k-nearest neighbors imputation.

Usage

impute_nas_knn(dataset, k = 10, ...)

Arguments

dataset	A dataset object to modify.
k	Number of neighbors to use in the imputation procedure.
...	Additional arguments passed to 'impute::impute.knn()'.

Value

A dataset object with the same structure as the input, where missing values in 'dataset$data' have been imputed using the k-nearest neighbors method implemented in 'impute::impute.knn()'. The returned object preserves the remaining dataset components unchanged.

Examples

data <- matrix(
  c(1,  2, NA, 4,
    2,  3,  4, 5,
    3, NA,  5, 6,
    4,  5,  6, 7),
  nrow = 4,
  byrow = TRUE,
  dimnames = list(c("x1", "x2", "x3", "x4"), c("s1", "s2", "s3", "s4"))
)
dataset <- list(data = data)
impute_nas_knn(dataset, k = 2)

specmine documentation built on Aug. 5, 2026, 5:06 p.m.