lenskit.implicit.BaseRec

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

Bases: lenskit.pipeline.Component[lenskit.data.ItemList], lenskit.training.Trainable

Base class for Implicit-backed recommenders.

Stability:

Caller (see Stability Levels).

Parameters:

• config (object | None)

• kwargs (Any)

config: 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.

weight: float = 1.0

matrix: scipy.sparse.csr_matrix

The user-item rating matrix from training.

users: lenskit.data.Vocabulary

The user ID mapping from training.

items: lenskit.data.Vocabulary

The item ID mapping from training.

user_embeddings: numpy.typing.NDArray[numpy.float32]

item_embeddings: numpy.typing.NDArray[numpy.float32]

is_trained()

Query if this component has already been trained.

train(data, options=TrainingOptions())

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

Parameters:

• data (lenskit.data.Dataset) – The training dataset.

• options (lenskit.training.TrainingOptions) – The training options.

__call__(query, items)

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

Parameters:

• query (lenskit.data.QueryInput)

• items (lenskit.data.ItemList)

Return type:

lenskit.data.ItemList