crepes 0.7.0

v0.7.0 (27/06/2024)

Features

• The class MondrianCategorizer was added to crepes.extras, for generating categories to be used by Mondrian conformal classifiers, regressors and predictive systems. See the documentation for the interface to objects of the class through the fit and apply methods.

• The class WrapRegressor has been updated so that the method calibrate allows for specifying an (optional) difficulty estimator and (optional) Mondrian categorizer, which are used both for calibration and making predictions, instead of requiring that difficulty estimates and Mondrian categories are provided separately for these tasks. The methods predict_int, predict_cps and evaluate no longer require sigmas and bins to be provided for normalized and Mondrian conformal regressors and predictive systems. Thanks to @tuvelofstrom for suggestions along these lines.

• The class WrapClassifier has been updated so that the method calibrate allows for specifying an (optional) Mondrian categorizer, which is used both for calibration and making predictions. The methods predict_p, predict_set and evaluate no longer require bins to be provided for Mondrian conformal classifiers.

Fix

• Label vectors represented by pandas.Series are converted to NumPy arrays to avoid indexing issues. Thanks to @valeman for pointing this out.