lenskit.metrics.ranking.ExposureGini
====================================

.. py:class:: lenskit.metrics.ranking.ExposureGini(n = None, *, k = None, items, weight = GeometricRankWeight())
   :canonical: lenskit.metrics.ranking._gini.ExposureGini

   Bases: :py:obj:`GiniBase`


   Measure exposure distribution of recommendations with the Gini coefficient.

   This uses a weighting model to compute the exposure of each item in each list,
   and computes the Gini coefficient of the total exposure.

   :param n: The maximum recommendation list length.
   :param items: The item vocabulary or a dataset from which to extract the items.
   :param weight: The rank weighting model to use.  Defaults to
                  :class:`GeometricRankWeight` with the specified patience parameter.

   :Stability: Caller


   .. py:attribute:: weight
      :type:  lenskit.metrics.ranking._weighting.RankWeight


   .. py:method:: measure_list(output, test)

      Compute measurements for a single list.

      :returns:

                - A float for simple metrics
                - Intermediate data for decomposed metrics
                - A dict mapping metric names to values for multi-metric classes