NaiveHybridSpaceRecommender¶

class baybe.recommenders.naive.NaiveHybridSpaceRecommender[source]¶

Bases: PureRecommender

Recommend points by independent optimization of subspaces.

This recommender splits the hybrid search space in the discrete and continuous subspace. Each of the subspaces is optimized on its own, and the recommenders for those subspaces can be chosen upon initialization. If this recommender is used on a non-hybrid space, it uses the corresponding recommender.

Public methods

`__init__`([disc_recommender, ...])	Method generated by attrs for class NaiveHybridSpaceRecommender.
`recommend`(searchspace[, batch_size, ...])	Recommend a batch of points from the given search space.

Public attributes and properties

`disc_recommender`	The recommender used for the discrete subspace.
`cont_recommender`	The recommender used for the continuous subspace.
`allow_recommending_already_measured`	Allow to make recommendations that were measured previously.
`allow_repeated_recommendations`	Allow to make recommendations that were already recommended earlier.
`compatibility`	Class variable reflecting the search space compatibility.

__init__(disc_recommender: PureRecommender = NOTHING, cont_recommender: BayesianRecommender = NOTHING, *, allow_repeated_recommendations: bool = False, allow_recommending_already_measured: bool = True)¶

Method generated by attrs for class NaiveHybridSpaceRecommender.

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)[source]¶

Recommend a batch of points from the given search space.

Parameters:

searchspace (SearchSpace) – The search space from which to recommend the points.
batch_size (int) – The number of points to be recommended.
train_x (Optional[DataFrame]) – Optional training inputs for training a model.
train_y (Optional[DataFrame]) – Optional training labels for training a model.

Return type:

DataFrame

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] = 'HYBRID'¶: Class variable reflecting the search space compatibility.

cont_recommender: BayesianRecommender¶: The recommender used for the continuous subspace. Default: baybe.recommenders.pure.bayesian.sequential_greedy.SequentialGreedyRecommender

disc_recommender: PureRecommender¶: The recommender used for the discrete subspace. Default: baybe.recommenders.pure.bayesian.sequential_greedy.SequentialGreedyRecommender