lenskit.hpf.HPFScorer#
- classlenskit.hpf.HPFScorer(config=None, **kwargs)#
Bases:
lenskit.pipeline.Component[lenskit.data.ItemList],lenskit.training.TrainableHierarchical Poisson factorization, provided by hpfrec
Todo
Right now, this uses the ‘rating’ as a count. Actually use counts (🐞 656).
- Stability:
Experimental
- Parameters:
features – the number of features
kwargs (Any) – additional arguments to pass to
hpfrec.HPF.config (object | None)
- config:HPFConfig #
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.
- users:lenskit.data.Vocabulary #
- user_features:numpy.ndarray [tuple [int ,int ],numpy.dtype [numpy.float64]]#
- items:lenskit.data.Vocabulary #
- item_features:numpy.ndarray [tuple [int ,int ],numpy.dtype [numpy.float64]]#
- 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: