smac.acquisition.function.confidence_bound

Classes

LCB([beta])

Computes the lower confidence bound for a given x over the best so far value as acquisition value.

Interfaces

class smac.acquisition.function.confidence_bound.LCB(beta=1.0)[source]

Bases: AbstractAcquisitionFunction

Computes the lower confidence bound for a given x over the best so far value as acquisition value.

\(LCB(X) = \mu(\mathbf{X}) - \sqrt(\beta_t)\sigma(\mathbf{X})\) [SKKS10]

with

\(\beta_t = 2 \log( |D| t^2 / \beta)\)

\(\text{Input space} D\) \(\text{Number of input dimensions} |D|\) \(\text{Number of data points} t\) \(\text{Exploration/exploitation tradeoff} \beta\)

Returns -LCB(X) as the acquisition_function optimizer maximizes the acquisition value.

Parameters:

beta (float, defaults to 1.0) – Controls the balance between exploration and exploitation of the acquisition function.

_beta

Exploration-exploitation trade-off parameter.

Type:

float

_num_data

Number of data points seen so far.

Type:

int

property meta: dict[str, Any]

Returns the meta data of the created object.

property name: str

Returns the full name of the acquisition function.