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.