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

.. py:module:: lenskit.metrics.ranking

.. autoapi-nested-parse::

   LensKit ranking (and list) metrics.



Classes
-------

.. toctree::
   :hidden:

   /api/lenskit/metrics/ranking/RankingMetricBase
   /api/lenskit/metrics/ranking/DCG
   /api/lenskit/metrics/ranking/NDCG
   /api/lenskit/metrics/ranking/Entropy
   /api/lenskit/metrics/ranking/RankBiasedEntropy
   /api/lenskit/metrics/ranking/ExposureGini
   /api/lenskit/metrics/ranking/ListGini
   /api/lenskit/metrics/ranking/Hit
   /api/lenskit/metrics/ranking/ILS
   /api/lenskit/metrics/ranking/AveragePrecision
   /api/lenskit/metrics/ranking/MeanPopRank
   /api/lenskit/metrics/ranking/Precision
   /api/lenskit/metrics/ranking/Recall
   /api/lenskit/metrics/ranking/RBP
   /api/lenskit/metrics/ranking/RecipRank
   /api/lenskit/metrics/ranking/GeometricRankWeight
   /api/lenskit/metrics/ranking/LogRankWeight
   /api/lenskit/metrics/ranking/RankWeight

.. autoapisummary::

   lenskit.metrics.ranking.RankingMetricBase
   lenskit.metrics.ranking.DCG
   lenskit.metrics.ranking.NDCG
   lenskit.metrics.ranking.Entropy
   lenskit.metrics.ranking.RankBiasedEntropy
   lenskit.metrics.ranking.ExposureGini
   lenskit.metrics.ranking.ListGini
   lenskit.metrics.ranking.Hit
   lenskit.metrics.ranking.ILS
   lenskit.metrics.ranking.AveragePrecision
   lenskit.metrics.ranking.MeanPopRank
   lenskit.metrics.ranking.Precision
   lenskit.metrics.ranking.Recall
   lenskit.metrics.ranking.RBP
   lenskit.metrics.ranking.RecipRank
   lenskit.metrics.ranking.GeometricRankWeight
   lenskit.metrics.ranking.LogRankWeight
   lenskit.metrics.ranking.RankWeight


Functions
---------

.. autoapisummary::

   lenskit.metrics.ranking.rank_biased_precision



Package Contents
----------------

.. py:function:: rank_biased_precision(good, weights, normalization = 1.0)

   Compute rank-biased precision given explicit weights.

   :param good: Boolean array indicating relevant items at each position.
   :param weights: Weight for each item position (same length as good).
   :param normalization: Optional normalization factor, defaults to 1.0.

   :returns: RBP score