skactiveml.pool.expected_average_precision#

skactiveml.pool.expected_average_precision(classes, probas)[source]#

Calculate the expected average precision.

Parameters

classesarray-like, shape=(n_classes): Holds the label for each class.
probasnp.ndarray, shape=(n_X_cand, n_classes): The probabilistic estimation for each classes and all instance in candidates.

Returns

scorenp.ndarray, shape=(n_X_cand): The expected average precision score of all instances in candidates.

References

[1] Wang, Hanmo, et al. “Uncertainty sampling for action recognition: via maximizing expected average precision.” IJCAI International Joint Conference on Artificial Intelligence. 2018.