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, **kwargs)¶ Train a model using the specified ratings (or similar) data.
- Parameters
ratings (pandas.DataFrame) – The ratings data.
kwargs – Additional training data the algorithm may require. Algorithms should avoid using the same keyword arguments for different purposes, so that they can be more easily hybridized.
- 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