Description
Classifier probabilities can be calibrated with Venn-Abers methods for binary and multiclass machine-learning problems. This library helps researchers and data scientists estimate more reliable probability outputs from predictive models.
It is imported by notebooks, experiments, and production ML code rather than opened directly. Calibration quality depends on data splits and model assumptions, so validate results before using them for decisions.