dx_f1: Calculate F1 Score with Confidence Intervals

In overdodactyl/diagnosticSummary: Diagnostic Summaries

Calculate F1 Score with Confidence Intervals

Description

Calculates the F1 score from a confusion matrix object with an option to include bootstrapped confidence intervals. The F1 score is the harmonic mean of precision and recall.

Usage

dx_f1(cm, detail = "full", boot = FALSE, bootreps = 1000)

Arguments

cm	A dx_cm object created by dx_cm().
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 F1 or a data frame with the F1 and its confidence intervals.

See Also

dx_fbeta(), dx_f2() for other F-beta scores.

Examples

cm <- dx_cm(dx_heart_failure$predicted, dx_heart_failure$truth,
  threshold =
    0.5, poslabel = 1
)
simple_f <- dx_f1(cm, detail = "simple")
detailed_f <- dx_f1(cm)
print(simple_f)
print(detailed_f)

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