crepes 0.7.1

v0.7.1 (21/09/2024)

Features

• The calibrate methods of the classes WrapClassifier and WrapRegressor now take an additional argument seed, for setting the state of the random number generator. This allows for predict_p and predict_set of the former class and predict_int and predict_cps of the latter class as well as evaluate for both classes to become deterministic. The methods predict_p, predict_set, predict_int ,predict_cps and evaluate of these classes also have an argument seed, which can be used to over-ride any setting by the calibrate method. In addition, the corresponding methods of the classes ConformalClassifier and ConformalPredictiveSystem also include the argument seed for the same purpose. (The methods of ConformalRegressor currently contains no stochastic components and there is hence no need for a seed.) Thanks to @egonmedhatten and @tuvelofstrom for suggesting this extension.

• The predict_p methods of the classes ConformalClassifier and WrapClassifier now takes an optional argument smoothing to allow for generating both smoothed and non-smoothed p-values (default: smoothing=True).

• The default value for the parameter smoothing of the predict_set and evaluate methods has been changed to True.

• The class DifficultyEstimator in crepes.extras now includes a parameter f for providing a function to compute the difficulty estimates.

Fixes

• The documentation for the class MondrianCategorizer in crepes.extras has been corrected.