smac.acquisition.function.confidence_bound¶
Classes¶
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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:
AbstractAcquisitionFunctionComputes 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.