aif360.sklearn.metrics.smoothed_base_rate

aif360.sklearn.metrics.smoothed_base_rate(y_true, y_pred=None, *, concentration=1.0, pos_label=1, sample_weight=None)

Compute the smoothed base rate, \(\frac{P + \alpha}{P + N + |R_Y|\alpha}\).

Parameters:

• y_true (array-like) – Ground truth (correct) target values.

• y_pred (array-like, optional) – Estimated targets. Ignored.

• concentration (scalar) – Dirichlet smoothing concentration parameter \(|R_Y|\alpha\) (must be non-negative).

• pos_label (scalar, optional) – The label of the positive class.

• sample_weight (array-like, optional) – Sample weights.

Returns:

float – Smoothed base rate.