bootstrap_performance: Calculate a bootstrap confidence interval for the performance...
In mikropml: User-Friendly R Package for Supervised Machine Learning Pipelines

bootstrap_performance

R Documentation

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
)

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)

Value

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

Author(s)

Kelly Sovacool, sovacool@umich.edu

Examples

bootstrap_performance(otu_mini_bin_results_glmnet, "dx",
  bootstrap_times = 10, alpha = 0.10
)
## Not run: 
outcome_colname <- "dx"
run_ml(otu_mini_bin, "rf", outcome_colname = "dx") %>%
  bootstrap_performance(outcome_colname,
    bootstrap_times = 10000,
    alpha = 0.05
  )

## End(Not run)

mikropml documentation built on Aug. 21, 2023, 5:10 p.m.