Calculates the F-beta score from a confusion matrix object with an option to include bootstrapped confidence intervals. The F-beta score is a generalization of the F1 score, allowing different importance to precision and recall via the beta parameter.
Arguments
- cm
A dx_cm object created by
dx_cm().- beta
The beta value determining the weight of precision in the F-score.
- detail
Character specifying the level of detail in the output: "simple" for raw estimate, "full" for detailed estimate including 95% confidence intervals.
- boot
Logical specifying if confidence intervals should be generated via bootstrapping. Note, this can be slow.
- bootreps
The number of bootstrap replications for calculating confidence intervals.
Value
Depending on the detail parameter, returns a single numeric value of
F-beta or a data frame with the F-beta and its confidence intervals.
Examples
cm <- dx_cm(dx_heart_failure$predicted, dx_heart_failure$truth,
threshold =
0.5, poslabel = 1
)
simple_f <- dx_fbeta(cm, beta = .5, detail = "simple")
detailed_f <- dx_fbeta(cm, beta = .5)
print(simple_f)
#> [1] 0.8056872
print(detailed_f)
#> # A tibble: 1 × 8
#> measure summary estimate conf_low conf_high fraction conf_type notes
#> <chr> <chr> <dbl> <dbl> <dbl> <chr> <chr> <chr>
#> 1 F0.5 Score 0.81 0.806 NA NA "" NA Specify `bo…