A flexible and powerful Python library for dataset shift analysis and characterization, providing supervised and unsupervised evaluation of temporal and multi-source data shifts, visualization tools, and statistical insights for data integrity and model performance monitoring
WaX: explainable Wasserstein distances. Attributes a Wasserstein distance to instances, features and subspaces (Naumann, Kauffmann and Montavon, TPAMI 2026).
