SequentialMetaRecommender

class baybe.recommenders.meta.sequential.SequentialMetaRecommender

Bases: MetaRecommender

A meta recommender that uses a pre-defined sequence of recommenders.

A new recommender is taken from the sequence whenever at least one new measurement is available, until all recommenders are exhausted. More precisely, a recommender change is triggered whenever the size of the training dataset increases; the actual content of the dataset is ignored.

Note

The provided sequence of recommenders will be internally pre-collected into a list. If this is not acceptable, consider using baybe.recommenders.meta.sequential.StreamingSequentialMetaRecommender instead.

Raises:

• RuntimeError – If the training dataset size decreased compared to the previous call.

• NoRecommendersLeftError – If more recommenders are requested than there are recommenders available and mode="raise".

Public methods

__init__(recommenders[, mode, _step, ...])	Method generated by attrs for class SequentialMetaRecommender.
from_dict(dictionary)	Create an object from its dictionary representation.
from_json(string)	Create an object from its JSON representation.
get_current_recommender()	Get the current recommender, if available.
get_next_recommender(batch_size, searchspace)	Get the recommender for the next recommendation.
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	A finite-length sequence of recommenders to be used.
mode	Defines what shall happen when the last recommender in the sequence has been consumed but additional recommender changes are triggered:

__init__(recommenders, mode: Literal['raise', 'reuse_last', 'cyclic'] = 'raise', _step: int = -1, _n_last_measurements: int = -1)

Method generated by attrs for class SequentialMetaRecommender.

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

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.

get_current_recommender()

Get the current recommender, if available.

Return type:

PureRecommender

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

Get the recommender for the next recommendation.

Returns the next recommender in row that has not yet been used for generating recommendations. In case of multiple consecutive calls, this means that the same recommender instance is returned until its recommend() method is called.

See baybe.recommenders.base.RecommenderProtocol.recommend() for details on the method arguments.

Return type:

PureRecommender

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

Select a pure recommender for the given experimentation context.

See baybe.recommenders.base.RecommenderProtocol.recommend() for details on the method arguments.

Return type:

PureRecommender

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.

mode: Literal['raise', 'reuse_last', 'cyclic']

Defines what shall happen when the last recommender in the sequence has been consumed but additional recommender changes are triggered:

• "raise": An error is raised.

• "reuse_last": The last recommender in the sequence is used indefinitely.

• "cycle": The selection restarts from the beginning of the sequence.

recommenders: list[PureRecommender]

A finite-length sequence of recommenders to be used. For infinite-length iterables, see baybe.recommenders.meta.sequential.StreamingSequentialMetaRecommender.