StreamingSequentialMetaRecommender

class baybe.recommenders.meta.sequential.StreamingSequentialMetaRecommender

Bases: MetaRecommender

A meta recommender that switches between recommenders from an iterable.

Similar to baybe.recommenders.meta.sequential.SequentialMetaRecommender but without explicit list conversion. Consequently, it supports arbitrary iterables, possibly of infinite length. The downside is that serialization is not supported.

Raises:

NoRecommendersLeftError – If more recommenders are requested than there are recommenders available.

Public methods

__init__(recommenders)	Method generated by attrs for class StreamingSequentialMetaRecommender.
default_iterator()	Initialize the recommender iterator.
from_dict(dictionary)	Create an object from its dictionary representation.
from_json(string)	Create an object from its JSON representation.
recommend(batch_size, searchspace[, ...])	See baybe.recommenders.base.RecommenderProtocol.recommend().
select_recommender(batch_size[, ...])	Select a pure recommender for the given experimentation context.
to_dict()	Create an object's dictionary representation.
to_json()	Create an object's JSON representation.

Public attributes and properties

recommenders

An iterable providing the recommenders to be used.

__init__(recommenders: Iterable[PureRecommender])

Method generated by attrs for class StreamingSequentialMetaRecommender.

For details on the parameters, see Public attributes and properties.

default_iterator()

Initialize the recommender iterator.

classmethod from_dict(dictionary: dict)

Create an object from its dictionary representation.

Parameters:

dictionary (dict) – The dictionary representation.

Return type:

TypeVar(_T)

Returns:

The reconstructed object.

classmethod from_json(string: str)

Create an object from its JSON representation.

Parameters:

string (str) – The JSON representation of the object.

Return type:

TypeVar(_T)

Returns:

The reconstructed object.

recommend(batch_size: int, searchspace: SearchSpace, objective: Objective | None = None, measurements: DataFrame | None = None)

See baybe.recommenders.base.RecommenderProtocol.recommend().

Return type:

DataFrame

select_recommender(batch_size: int, searchspace: SearchSpace | None = None, objective: Objective | None = None, measurements: DataFrame | None = None)

Select a pure recommender for the given experimentation context.

Parameters:

• batch_size (int) – See baybe.recommenders.meta.base.MetaRecommender.recommend().

• searchspace (Optional[SearchSpace]) – See baybe.recommenders.meta.base.MetaRecommender.recommend().

• objective (Optional[Objective]) – See baybe.recommenders.meta.base.MetaRecommender.recommend().

• measurements (Optional[DataFrame]) – See baybe.recommenders.meta.base.MetaRecommender.recommend().

Return type:

PureRecommender

Returns:

The selected recommender.

to_dict()

Create an object’s dictionary representation.

Return type:

dict

to_json()

Create an object’s JSON representation.

Return type:

str

Returns:

The JSON representation as a string.

recommenders: Iterable[PureRecommender]

An iterable providing the recommenders to be used.