BayesianRecommender¶

class baybe.recommenders.pure.bayesian.base.BayesianRecommender[source]¶

Bases: PureRecommender, ABC

An abstract class for Bayesian Recommenders.

Public methods

`__init__`([surrogate_model, ...])	Method generated by attrs for class BayesianRecommender.
`recommend`(searchspace[, batch_size, ...])	Recommend a batch of points from the given search space.
`setup_acquisition_function`(searchspace[, ...])	Create the current acquisition function from provided training data.

Public attributes and properties

`surrogate_model`	The used surrogate model.
`acquisition_function_cls`	The used acquisition function class.
`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__(surrogate_model: Surrogate = NOTHING, acquisition_function_cls: Literal['PM', 'PI', 'EI', 'UCB', 'qPI', 'qEI', 'qUCB', 'VarUCB', 'qVarUCB'] = 'qEI', *, allow_repeated_recommendations: bool = False, allow_recommending_already_measured: bool = True)¶

Method generated by attrs for class BayesianRecommender.

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.

setup_acquisition_function(searchspace: SearchSpace, train_x: DataFrame | None = None, train_y: DataFrame | None = None)[source]¶

Create the current acquisition function from provided training data.

The acquisition function is stored in the private attribute _acquisition_function.

Parameters:

searchspace (SearchSpace) – The search space in which the experiments are to be conducted.
train_x (Optional[DataFrame]) – The features of the conducted experiments.
train_y (Optional[DataFrame]) – The corresponding response values.

Raises:

NotImplementedError – If the setup is attempted from empty training data

Return type:

None

acquisition_function_cls: Literal['PM', 'PI', 'EI', 'UCB', 'qPI', 'qEI', 'qUCB', 'VarUCB', 'qVarUCB']¶: The used acquisition function class.

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]¶: Class variable reflecting the search space compatibility.

surrogate_model: Surrogate¶: The used surrogate model.