PosteriorStandardDeviation

class baybe.acquisition.acqfs.PosteriorStandardDeviation

Bases: AcquisitionFunction

Posterior standard deviation.

Public methods

__init__([maximize])	Method generated by attrs for class PosteriorStandardDeviation.
from_dict(dictionary)	Create an object from its dictionary representation.
from_json(string)	Create an object from its JSON representation.
to_botorch(surrogate, searchspace, train_x, ...)	Create the botorch-ready representation of the function.
to_dict()	Create an object's dictionary representation.
to_json()	Create an object's JSON representation.

Public attributes and properties

maximize	If True, points with maximum posterior standard deviation are selected.
abbreviation	An alternative name for type resolution.
is_mc

__init__(maximize: bool = True)

Method generated by attrs for class PosteriorStandardDeviation.

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.

to_botorch(surrogate: Surrogate, searchspace: SearchSpace, train_x: DataFrame, train_y: DataFrame)

Create the botorch-ready representation of the function.

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.

abbreviation: ClassVar[str] = 'PSTD'

An alternative name for type resolution.

maximize: bool

If True, points with maximum posterior standard deviation are selected. If False, the acquisition function value is negated, yielding a selection with minimal posterior standard deviation.