dx_fbeta: Calculate F-beta Score with Confidence Intervals

In overdodactyl/diagnosticSummary: Diagnostic Summaries

Calculate F-beta Score with Confidence Intervals

Description

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.

Usage

dx_fbeta(cm, beta = 1, detail = "full", boot = FALSE, bootreps = 1000)

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.

See Also

dx_f1(), dx_f2() for specific F-beta scores.

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)
print(detailed_f)

overdodactyl/diagnosticSummary documentation built on Jan. 28, 2024, 10:07 a.m.