FPSRecommender¶
- class baybe.recommenders.pure.nonpredictive.sampling.FPSRecommender[source]¶
Bases:
NonPredictiveRecommender
An initial recommender that selects candidates via Farthest Point Sampling.
Public methods
__init__
(*[, ...])Method generated by attrs for class NonPredictiveRecommender.
recommend
(searchspace[, batch_size, ...])Recommend a batch of points from the given search space.
Public attributes and properties
Allow to make recommendations that were measured previously.
Allow to make recommendations that were already recommended earlier.
Class variable reflecting the search space compatibility.
- __init__(*, allow_repeated_recommendations: bool = False, allow_recommending_already_measured: bool = True)¶
Method generated by attrs for class NonPredictiveRecommender.
For details on the parameters, see Public attributes and properties.
- recommend(searchspace: SearchSpace, batch_size: int = 1, train_x: DataFrame | None = None, train_y: DataFrame | None = None)¶
Recommend a batch of points from the given search space.
- Parameters:
- Return type:
- Returns:
A dataframe containing the recommendations as individual rows.
- allow_recommending_already_measured: bool¶
Allow to make recommendations that were measured previously. This only has an influence in discrete search spaces.
- allow_repeated_recommendations: bool¶
Allow to make recommendations that were already recommended earlier. This only has an influence in discrete search spaces.
-
compatibility:
ClassVar
[SearchSpaceType
] = 'DISCRETE'¶ Class variable reflecting the search space compatibility.