NRAE#
- mlquantify.metrics.NRAE(prev_real, prev_pred, eps=0.0)[source]#
Compute the normalized relative absolute error between the real and predicted prevalences.
- Parameters:
- prev_realarray-like of shape (n_classes,)
True prevalence values for each class.
- prev_predarray-like of shape (n_classes,)
Predicted prevalence values for each class.
- epsfloat, default=0.0
Additive (Laplace) smoothing applied to both prevalence vectors; see
RAE. Needed when the true prevalence can be zero (e.g. under APP), since the normalisation also divides bymin(prev_real).
- Returns:
- errorfloat
Normalized relative absolute error across all classes.