lift_score#

empulse.metrics.lift_score(y_true, y_score, *, fraction=0.1, check_input=True)[source]#

Compute the lift score for the top fraction of predictions.

Parameters:
y_true1D array-like, shape=(n_samples,)

Binary target values (‘positive’: 1, ‘negative’: 0).

y_score1D array-like, shape=(n_samples,)

Target scores, can either be probability estimates or non-thresholded decision values.

fractionfloat, optional, default: 0.1

Fraction of data to consider. Must be between 0 and 1.

check_inputbool, default=True

Perform input validation. Turning off improves performance, useful when using this metric as a loss function.

Returns:
lift_scorefloat

Lift score for the top fraction of the data.