mikropml (version 1.6.1)

bootstrap_performance: Calculate a bootstrap confidence interval for the performance on a single train/test split

Description

Uses rsample::bootstraps(), rsample::int_pctl(), and furrr::future_map()

Usage

bootstrap_performance(
  ml_result,
  outcome_colname,
  bootstrap_times = 10000,
  alpha = 0.05
)

Value

a data frame with an estimate (.estimate), lower bound (.lower), and upper bound (.upper) for each performance metric (term).

Arguments

ml_result

result returned from a single run_ml() call

outcome_colname

Column name as a string of the outcome variable (default NULL; the first column will be chosen automatically).

bootstrap_times

the number of boostraps to create (default: 10000)

alpha

the alpha level for the confidence interval (default 0.05 to create a 95% confidence interval)

Author

Kelly Sovacool,

Examples

bootstrap_performance(otu_mini_bin_results_glmnet, "dx",
  bootstrap_times = 10, alpha = 0.10
)
if (FALSE) {
outcome_colname <- "dx"
run_ml(otu_mini_bin, "rf", outcome_colname = "dx") %>%
  bootstrap_performance(outcome_colname,
    bootstrap_times = 10000,
    alpha = 0.05
  )
}