Compute average confusion matrix across resamples
Source:R/conf_mat_resampled.R
conf_mat_resampled.Rd
For classification problems, conf_mat_resampled()
computes a separate
confusion matrix for each resample then averages the cell counts.
Arguments
- x
An object with class
tune_results
that was used with a classification model that was run withcontrol_*(save_pred = TRUE)
.- ...
Currently unused, must be empty.
- parameters
A tibble with a single tuning parameter combination. Only one tuning parameter combination (if any were used) is allowed here.
- tidy
Should the results come back in a tibble (
TRUE
) or aconf_mat
object likeyardstick::conf_mat()
(FALSE
)?
Examples
library(parsnip)
library(rsample)
library(dplyr)
data(two_class_dat, package = "modeldata")
set.seed(2393)
res <-
logistic_reg() %>%
set_engine("glm") %>%
fit_resamples(
Class ~ .,
resamples = vfold_cv(two_class_dat, v = 3),
control = control_resamples(save_pred = TRUE)
)
conf_mat_resampled(res)
#> # A tibble: 4 × 3
#> Prediction Truth Freq
#> <fct> <fct> <dbl>
#> 1 Class1 Class1 123
#> 2 Class1 Class2 25.7
#> 3 Class2 Class1 22.7
#> 4 Class2 Class2 92.3
conf_mat_resampled(res, tidy = FALSE)
#> Class1 Class2
#> Class1 123.00000 25.66667
#> Class2 22.66667 92.33333