baybe.recommenders.pure.bayesian.botorch.discrete.recommend_discrete_with_subsets¶
- baybe.recommenders.pure.bayesian.botorch.discrete.recommend_discrete_with_subsets(recommender: BotorchRecommender, subspace_discrete: SubspaceDiscrete, candidates_exp: DataFrame, batch_size: int)[source]¶
Recommend from a discrete space with subset-generating constraints.
Splits the candidate set into subsets according to subset-generating constraints, runs optimization on each feasible subset, and returns the batch with the highest joint acquisition value. Subsets with fewer candidates than
batch_sizeare skipped.- Parameters:
recommender (
BotorchRecommender) – The recommender instance.subspace_discrete (
SubspaceDiscrete) – The discrete subspace from which to generate recommendations.candidates_exp (
DataFrame) – The experimental representation of candidates.batch_size (
int) – The size of the recommendation batch.
- Return type:
Index- Returns:
The dataframe indices of the recommended points.