Hierarchical Poisson Factorization

This module provides a LensKit bridge to the hpfrec library implementing hierarchical Poisson factorization [GHB2013].

[GHB2013]Prem Gopalan, Jake M. Hofman, and David M. Blei. 2013. Scalable Recommendation with Poisson Factorization. arXiv:1311.1704 [cs, stat] (November 2013). Retrieved February 9, 2017 from http://arxiv.org/abs/1311.1704.
class lenskit.algorithms.hpf.HPF(features, **kwargs)

Hierarchical Poisson factorization, provided by hpfrec.

Parameters:
  • features (int) – the number of features
  • **kwargs – arguments passed to hpfrec.HPF.
fit(ratings)

Train a model using the specified ratings (or similar) data.

Parameters:
  • ratings (pandas.DataFrame) – The ratings data.
  • args – Additional training data the algorithm may require.
  • kwargs – Additional training data the algorithm may require.
Returns:

The algorithm object.

predict_for_user(user, items, ratings=None)

Compute predictions for a user and items.

Parameters:
  • user – the user ID
  • items (array-like) – the items to predict
  • ratings (pandas.Series) – the user’s ratings (indexed by item id); if provided, they may be used to override or augment the model’s notion of a user’s preferences.
Returns:

scores for the items, indexed by item id.

Return type:

pandas.Series