Ranking Methods¶
The lenskit.algorithms.ranking
module contains various ranking methods:
algorithms that can use scores to produce ranks. This includes primary rankers, like
TopN
, and some re-rankers as well.
Top-N Recommender¶
The TopN
class implements a standard top-N recommender that wraps a
Predictor
and CandidateSelector
and returns the top N
candidate items by predicted rating. It is the type of recommender returned by
Recommender.adapt()
if the provided algorithm is not a recommender.
Stochastic Recommenders¶
The PlackettLuce
class implements a stochastic recommender. The underlying
relevance scores are kept the same, but the rankings are sampled from a Plackett-Luce
distribution instead using a deterministic top-N policy.