lenskit.als.BiasedMFScorer
==========================

.. py:class:: lenskit.als.BiasedMFScorer(config = None, **kwargs)
   :canonical: lenskit.als._explicit.BiasedMFScorer

   Bases: :py:obj:`lenskit.als._common.ALSBase`


   Biased matrix factorization trained with alternating least squares
   :cite:p:`NetflixALS,ExplicitALS`.  This is a prediction-oriented algorithm
   suitable for explicit feedback data, using the alternating least squares
   approach to compute :math:`P` and :math:`Q` to minimize the regularized
   squared reconstruction error of the ratings matrix.

   See the base class :class:`ALSBase` for documentation on the estimated
   parameters you can extract from a trained model. See :class:`BiasedMFConfig`
   and :class:`ALSConfig` for the configuration options for this component.

   :Stability: Caller


   .. py:attribute:: config
      :type:  BiasedMFConfig

      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:attribute:: bias
      :type:  lenskit.basic.BiasModel


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

      Create a model trainer to train this model.



   .. py:method:: new_user_embedding(user_num, items)

      Generate an embedding for a user given their current ratings.



   .. py:method:: finalize_scores(user_num, items, user_bias)

      Perform any final transformation of scores prior to returning them.