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

.. py:class:: lenskit.metrics.ranking.ILS(dataset, attribute, n = None)
   :canonical: lenskit.metrics.ranking._ils.ILS

   Bases: :py:obj:`lenskit.metrics.ranking._base.ListMetric`, :py:obj:`lenskit.metrics.ranking._base.RankingMetricBase`


   Evaluate recommendation diversity using intra-list similarity (ILS).

   This metric measures the average pairwise cosine similarity between item
   vectors in a recommendation list. Lower values indicate more diverse
   recommendations, while higher values indicate less diverse recommendations.

   :param dataset: The LensKit dataset containing item entities and their attributes.
   :param attribute: Name of the attribute or vector source (e.g., 'genre', 'tag').
   :param n: Recommendation list length to evaluate.

   :Stability: Caller


   .. py:attribute:: attribute
      :type:  str


   .. py:property:: label

      The metric's default label in output.
      The base implementation returns the class name by default.


   .. py:method:: measure_list(recs, 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