evaluator

Create an evaluator object for imputation quality

evaluator(true_data, imputed_data, method)

Arguments

true_data

A named list of numeric vectors with actual (ground truth) values.

imputed_data

A named list of numeric vectors with imputed values.

method

A string giving the imputation method name (e.g., "mean", "knn").

Value

An object of class "evaluator" containing per-column and global metrics.

Examples

true_data <- list(
  age = c(25, 30, 40),
  income = c(50000, 60000, 70000)
)
imputed_data <- list(
  age = c(25, 31, 39),
  income = c(50000, 61000, 69000)
)
result <- evaluator(true_data, imputed_data, "mean")
print(result)
#> Evaluation for method: mean 
#> Global Metrics:
#>   RMSE       : 408.6565 
#>   MAE        : 333.6667 
#>   R^2        : 0.9864 
#>   Correlation: 0.995 
#>   KS         : 0.3333 
#>   Accuracy   : 0.3333 
#> 
#> Per-column metrics available in x$metrics