libuplift.metrics.curves
========================

.. py:module:: libuplift.metrics.curves

.. autoapi-nested-parse::

   Uplift and Qini curves.

   ..
       !! processed by numpydoc !!


Functions
---------

.. autoapisummary::

   libuplift.metrics.curves.uplift_curve
   libuplift.metrics.curves.uplift_curve_j
   libuplift.metrics.curves.area_under_uplift_curve
   libuplift.metrics.curves.area_under_uplift_curve_j


Module Contents
---------------

.. py:function:: 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.















   ..
       !! processed by numpydoc !!

.. py:function:: 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.















   ..
       !! processed by numpydoc !!

.. py:function:: area_under_uplift_curve(y_true, y_score, trt, n_trt=None, pos_label=None, sample_weight=None, subtract_diag=True)

.. py:function:: area_under_uplift_curve_j(y_true, y_score, trt, n_trt=None, pos_label=None, sample_weight=None, subtract_diag=True)