libuplift.metrics.curves

Uplift and Qini curves.

Functions

uplift_curve(y_true, y_score, trt[, n_trt, pos_label, ...])	Uplift curve.
uplift_curve_j(y_true, y_score, trt[, n_trt, ...])	Uplift curve.
area_under_uplift_curve(y_true, y_score, trt[, n_trt, ...])
area_under_uplift_curve_j(y_true, y_score, trt[, ...])

Module Contents

libuplift.metrics.curves.uplift_curve(y_true, y_score, trt, n_trt=None, pos_label=None, sample_weight=None)

Uplift curve.

Unless specified explicitly, y_true is assumed to be 0-1, with 1 the positive outcome.

This function implements the variant used by Rzepakowski and Jaroszewicz, where treatment and control curves are computed separately and subtracted.

libuplift.metrics.curves.uplift_curve_j(y_true, y_score, trt, n_trt=None, pos_label=None, sample_weight=None)

Uplift curve.

Unless specified explicitly, y_true is assumed to be 0-1, with 1 the positive outcome.

This function implements the variant where scores are sorted jointly, see Verbeke, Nyberg, Verhelst.

libuplift.metrics.curves.area_under_uplift_curve(y_true, y_score, trt, n_trt=None, pos_label=None, sample_weight=None, subtract_diag=True)

libuplift.metrics.curves.area_under_uplift_curve_j(y_true, y_score, trt, n_trt=None, pos_label=None, sample_weight=None, subtract_diag=True)