This module contains classes to manage and learn utility functions for the computation of values.
Utilities evaluate functions over subsets of the training set ("samples"). As such, they are assumed to be invariant under permutations of the training data. The base class for all utilities is UtilityBase.
Utility for model-based methods¶
ModelUtility holds information about model and scoring function (the latter being what one usually understands under utility in the general definition of Shapley value). Model-based evaluation methods define the utility as a retraining of the model on a subset of the data, which is then scored. Please see the documentation on Computing Data Values for more information.
Utility learning¶
DataUtilityLearning adds support for learning the utility to avoid repeated re-training of the model to compute the score. Several methods exist to learn the utility function.
Caching¶
Utilities can be automatically cached across machines when the cache is so configured and enabled upon construction.