calibrate.Classification: Calibrate Binary Classification Models

In egenn/rtemis: Machine Learning and Visualization

Calibrate Binary Classification Models

Description

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

Details

Important: The calibration model's training data should be different from the classification model's training data.

Value

CalibratedClassification object.

Author(s)

EDG

egenn/rtemis documentation built on June 14, 2025, 11:54 p.m.