sklift.metrics.qini_curve¶
- sklift.metrics.metrics.qini_curve(y_true, uplift, treatment)[source]¶
Compute Qini curve.
For computing the area under the Qini Curve, see
qini_auc_score()
.- Parameters
y_true (1d array-like) – Correct (true) binary target values.
uplift (1d array-like) – Predicted uplift, as returned by a model.
treatment (1d array-like) – Treatment labels.
- Returns
Points on a curve.
- Return type
array (shape = [>2]), array (shape = [>2])
See also
uplift_curve()
: Compute the area under the Qini curve.perfect_qini_curve()
: Compute the perfect Qini curve.plot_qini_curves()
: Plot Qini curves from predictions..uplift_curve()
: Compute Uplift curve.References
Nicholas J Radcliffe. (2007). Using control groups to target on predicted lift: Building and assessing uplift model. Direct Marketing Analytics Journal, (3):14–21, 2007.
Devriendt, F., Guns, T., & Verbeke, W. (2020). Learning to rank for uplift modeling. ArXiv, abs/2002.05897.