imputation_predictive: Predictive imputation base

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Predictive imputation base

Description

Base class for supervised imputers that learn one target column from a set of source columns.

Usage

imputation_predictive(target, sources = NULL, method = c("median", "mean"))

Arguments

target	target column to impute
sources	optional vector of predictor column names
method	initial imputation method for numeric source columns: "median" or "mean"

Details

The target column is the attribute to be imputed. The source columns are the predictors used to estimate missing target values. If sources = NULL, all supported columns except the target are used. Missing values in source columns can be pre-imputed by a simpler method before fitting the predictive model.

Value

returns an object of class imputation_predictive

Examples

data(iris)
imp <- imputation_predictive(
  "Sepal.Length",
  sources = c("Sepal.Width", "Petal.Length", "Petal.Width", "Species")
)
class(imp)

daltoolbox documentation built on May 14, 2026, 9:06 a.m.