lenskit.implicit.BaseRec
========================

.. py:class:: lenskit.implicit.BaseRec(config = None, **kwargs)
   

   Bases: :py:obj:`lenskit.pipeline.Component`\ [\ :py:obj:`lenskit.data.ItemList`\ ], :py:obj:`lenskit.training.Trainable`


   Base class for Implicit-backed recommenders.

   :Stability: Caller


   .. py:attribute:: config
      :type:  ImplicitConfig

      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:: weight
      :type:  float
      :value: 1.0



   .. py:attribute:: matrix
      :type:  scipy.sparse.csr_matrix

      The user-item rating matrix from training.


   .. py:attribute:: users
      :type:  lenskit.data.Vocabulary

      The user ID mapping from training.


   .. py:attribute:: items
      :type:  lenskit.data.Vocabulary

      The item ID mapping from training.


   .. py:attribute:: user_embeddings
      :type:  numpy.typing.NDArray[numpy.float32]


   .. py:attribute:: item_embeddings
      :type:  numpy.typing.NDArray[numpy.float32]


   .. py:method:: is_trained()

      Query if this component has already been trained.



   .. py:method:: train(data, options = TrainingOptions())

      Train the model to learn its parameters from a training dataset.

      :param data: The training dataset.
      :param options: The training options.



   .. py:method:: __call__(query, items)

      Run the pipeline's operation and produce a result.  This is the key
      method for components to implement.