lenskit.basic.history#

Components that look up user history from the training data.

Classes#

LookupConfig

UserTrainingHistoryLookup

Look up a user's history from the training data.

KnownRatingConfig

KnownRatingScorer

Score items by returning their values from the training data.

Module Contents#

class lenskit.basic.history.LookupConfig#
interaction_class: str | None = None#

The name of the interaction class to use. Leave None to use the dataset’s default interaction class.

class lenskit.basic.history.UserTrainingHistoryLookup(config=None, **kwargs)#

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

Look up a user’s history from the training data.

Stability:
Caller (see Stability Levels).
Parameters:

  • config (object | None)

  • kwargs (Any)

config: LookupConfig#

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.

interactions: lenskit.data.MatrixRelationshipSet | None#
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:
__call__(query)#

Look up the user’s data from the training history (if needed), and ensure a fully-populated RecQuery.

Parameters:

query (lenskit.data.QueryInput)

Return type:

lenskit.data.RecQuery

class lenskit.basic.history.KnownRatingConfig#

Bases: LookupConfig

score: Literal['rating', 'indicator'] | None = None#

The field name to use to score items, or "indicator" to score with 0/1 based on presence in the training data. The default, None, uses ratings if available, and otherwise scores with ` for interacted items and leaves un-interacted items unscored.

source: Literal['training', 'query'] = 'training'#

Whether to get the known ratings from the training data or from the query.

class lenskit.basic.history.KnownRatingScorer(config=None, **kwargs)#

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

Score items by returning their values from the training data.

Stability:
Caller (see Stability Levels).
Parameters:

  • config (object | None)

  • kwargs (Any)

config: KnownRatingConfig#

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.

interactions: lenskit.data.MatrixRelationshipSet#
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:
__call__(query, items)#

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

Parameters:
Return type:

lenskit.data.ItemList

Exported Aliases#

class lenskit.basic.history.Dataset#

Re-exported alias for lenskit.data.Dataset.

class lenskit.basic.history.ItemList#

Re-exported alias for lenskit.data.ItemList.

class lenskit.basic.history.MatrixRelationshipSet#

Re-exported alias for lenskit.data.MatrixRelationshipSet.

lenskit.basic.history.QueryInput#

Re-exported alias for lenskit.data.QueryInput.

class lenskit.basic.history.RecQuery#

Re-exported alias for lenskit.data.RecQuery.

exception lenskit.basic.history.DataError#

Re-exported alias for lenskit.diagnostics.DataError.

lenskit.basic.history.get_logger()#

Re-exported alias for lenskit.logging.get_logger().

lenskit.basic.history.trace()#

Re-exported alias for lenskit.logging.trace().

class lenskit.basic.history.Component#

Re-exported alias for lenskit.pipeline.Component.

class lenskit.basic.history.Trainable#

Re-exported alias for lenskit.training.Trainable.

class lenskit.basic.history.TrainingOptions#

Re-exported alias for lenskit.training.TrainingOptions.