calibrate: Calibrate parameters

In biokNN: Bi-Objective k-Nearest Neighbors Imputation for Multilevel Data

Description

This function returns a vector with the two parameters requiered by the biokNN method where the first value is the weighting parameter and the second the number of neighbors

Usage

calibrate(
  data,
  className,
  prop_valid = 0.1,
  nIter = 10,
  distance = "gower",
  weight_space = NULL,
  k_space = NULL,
  print = FALSE
)

Arguments

data	A dataframe with missing values
className	name of the variable that contains the classes
prop_valid	proportion of missing values
nIter	number of iterations, default = 10
distance	distance function used to get the k-nearest neighbors
weight_space	vector with the calibration values to test for the weight parameter
k_space	vector with the calibration values to test for the number of neighbors
print	option to print the RMSE values of the parameters used for calibration (print = TRUE).

Value

A dataframe with the imputed data

Examples

data(data.example)
calibrate(data.example,
          "class",
          prop_valid = 0.3,
          weight_space = c(0.5, 0.7, 0.9),
          k_space = c(10, 15),
          print = TRUE)

biokNN documentation built on April 22, 2021, 9:07 a.m.