lenskit.basic.bias.BiasScorer

class lenskit.basic.bias.BiasScorer(config=None, **kwargs)

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

A user-item bias rating prediction model. This component uses BiasModel to predict ratings for users and items.

Parameters:

• config (object | None) – The component configuration.

• kwargs (Any)

Stability:

Caller (see Stability Levels).

config: BiasConfig

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.

model: BiasModel

is_trained()

Query if this component has already been trained.

train(data, options=TrainingOptions())

Train the bias model on some rating data.

Parameters:

• ratings – The training data (must have ratings).

• data (lenskit.data.Dataset)

• options (lenskit.training.TrainingOptions)

Returns:

The trained bias object.

__call__(query, items)

Compute predictions for a user and items. Unknown users and items are assumed to have zero bias.

Parameters:

• query (lenskit.data.QueryInput) – The recommendation query. If the query has an item list with ratings, those ratings are used to compute a new bias instead of using the user’s historical bias.

• items (lenskit.data.ItemList) – The items to score.

Returns:

Scores for items.

Return type:

lenskit.data.ItemList