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Create a Template of Model Labels

Source: R/compare_to_leader.R
initialize_keys.Rd

compare_to_leader() can relabel models for plotting through its key argument. initialize_keys() builds a template for that argument with one row per model, ready to have its label column edited.

Usage

initialize_keys(x)

Arguments

x

An object produced by perf_mod().

Value

A tibble with one row per model and two columns: model, holding the model names recorded in x, and label, initialized to the same values.

Details

Leave the model column alone. Those names are what compare_to_leader() joins on, and every model in x has to be represented, so editing or dropping them will produce an error. Edit the label column to whatever should appear on the plot.

Rows may be reordered and extra columns may be added; both are ignored. Labels do not have to be unique.

See also

compare_to_leader()

Examples

library(parsnip)
library(rsample)
library(workflowsets)

set.seed(1)
folds <- vfold_cv(mtcars, v = 5)

# \donttest{
mpg_models <-
  workflow_set(
    preproc = list(
      small = mpg ~ wt,
      medium = mpg ~ wt + hp,
      large = mpg ~ .
    ),
    models = list(lm = linear_reg())
  ) |>
  workflow_map("fit_resamples", resamples = folds, seed = 2)

set.seed(4321)
mpg_post <- perf_mod(mpg_models, metric = "rmse", refresh = 0, chains = 2)

mpg_keys <- initialize_keys(mpg_post)
mpg_keys
#> # A tibble: 3 × 2
#>   model     label    
#>   <chr>     <chr>    
#> 1 small_lm  small_lm 
#> 2 medium_lm medium_lm
#> 3 large_lm  large_lm 

# Edit the labels, then pass the result along:
mpg_keys$label <- c("1 predictor", "2 predictors", "all predictors")

mpg_post |>
  compare_to_leader(size = 0.5, key = mpg_keys, seed = 2) |>
  autoplot()

# }