calibrate.ClassificationRes: Calibrate Cross-validated Binary Classification Models
In egenn/rtemis: Machine Learning and Visualization
calibrate.ClassificationRes R Documentation
Calibrate Cross-validated 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.
Arguments
x
ClassificationRes object.
algorithm
Character: Algorithm to use to train calibration model.
hyperparameters
Hyperparameters object: Setup using one of setup_* functions.
resampler_parameters
ResamplerParameters
verbosity
Integer: Verbosity level.
...
Not used
Author(s)
EDG
egenn/rtemis documentation built on June 14, 2025, 11:54 p.m.
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| calibrate.ClassificationRes | R Documentation |
Calibrate Cross-validated 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.
Arguments
x |
ClassificationRes object. |
algorithm |
Character: Algorithm to use to train calibration model. |
hyperparameters |
Hyperparameters object: Setup using one of |
resampler_parameters |
ResamplerParameters |
verbosity |
Integer: Verbosity level. |
... |
Not used |
Author(s)
EDG
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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