lenskit.flexmf.FlexMFImplicitScorer
===================================

.. py:class:: lenskit.flexmf.FlexMFImplicitScorer(config = None, **kwargs)
   :canonical: lenskit.flexmf._implicit.FlexMFImplicitScorer

   Bases: :py:obj:`lenskit.flexmf._base.FlexMFScorerBase`


   Implicit-feedback rating prediction with FlexMF.  This is capable of
   realizing multiple models, including:

   - BPR-MF (Bayesian personalized ranking) :cite:p:`BPR` (with ``"pairwise"`` loss)
   - Logistic matrix factorization :cite:p:`LogisticMF` (with ``"logistic"`` loss)

   All use configurable negative sampling, including the sampling approach from WARP.

   :Stability: Experimental


   .. py:attribute:: config
      :type:  FlexMFImplicitConfig

      The component configuration object.  Component classes that support
      configuration **must** redefine this attribute with their specific
      configuration class type, which can be a Python dataclass or a Pydantic
      model class.


   .. py:method:: create_trainer(data, options)

      Create a model trainer to train this model.