The goal of calibration is to adjust the predicted probabilities of a binary classification model so that they better reflect the true probabilities (i.e. empirical risk) of the positive class.
Usage
calibrate.Classification(
x,
predicted_probabilities,
true_labels,
algorithm = "isotonic",
hyperparameters = NULL,
verbosity = 1L,
...
)Arguments
- x
Classification object.
- predicted_probabilities
Numeric vector: Predicted probabilities.
- true_labels
Factor: True class labels.
- algorithm
Character: Algorithm to use to train calibration model.
- hyperparameters
Hyperparameters object: Setup using one of
setup_*functions.- verbosity
Integer: Verbosity level.
- ...
Not used