Fit a probability calibrator

Usage

fit_gazepoint_calibrator(
  truth,
  probability,
  positive = NULL,
  method = c("platt", "isotonic")
)

Arguments

truth: Observed binary outcome values.
probability: Uncalibrated positive-class probabilities.
positive: Label representing the positive class.
method: Calibration method: Platt scaling or isotonic regression.

Value

A fitted gp3ml_calibrator object containing the calibration method, fitted model, and outcome labels.

Examples

truth <- factor(
  rep(c("pass", "review"), 6),
  levels = c("pass", "review")
)
probability <- c(
  0.20, 0.70, 0.60, 0.55, 0.30, 0.80,
  0.65, 0.45, 0.40, 0.75, 0.50, 0.60
)
calibrator <- fit_gazepoint_calibrator(
  truth = truth,
  probability = probability,
  positive = "review",
  method = "platt"
)
calibrator
#> $method
#> [1] "platt"
#> 
#> $fit
#> 
#> Call:  stats::glm(formula = y ~ stats::qlogis(p), family = stats::binomial())
#> 
#> Coefficients:
#>      (Intercept)  stats::qlogis(p)  
#>          -0.4921            2.2699  
#> 
#> Degrees of Freedom: 11 Total (i.e. Null);  10 Residual
#> Null Deviance:	    16.64 
#> Residual Deviance: 11.77 	AIC: 15.77
#> 
#> $positive
#> [1] "review"
#> 
#> $negative
#> [1] "pass"
#> 
#> attr(,"class")
#> [1] "gp3ml_calibrator"