smac.acquisition.function.expected_improvement

Classes

EI([xi, log])	Computes the expected improvement for a given x.
EIPS([xi])	Computess for a given x the expected improvement as acquisition value.

Interfaces

class smac.acquisition.function.expected_improvement.EI(xi=0.0, log=False)

Bases: AbstractAcquisitionFunction

Computes the expected improvement for a given x.

\(EI(X) := \mathbb{E}\left[ \max\{0, f(\mathbf{X^+}) - f_{t+1}(\mathbf{X}) - \xi \} \right]\), with \(f(X^+)\) as the best location.

Parameters:

• xi (float, defaults to 0.0) – Controls the balance between exploration and exploitation of the acquisition function.

• log (bool, defaults to False) – Whether the function values are in log-space.

property meta: dict[str, Any]

Returns the meta data of the created object.

Return type:

dict[str, Any]

property name: str

Returns the full name of the acquisition function.

Return type:

str

class smac.acquisition.function.expected_improvement.EIPS(xi=0.0)

Bases: EI

Computess for a given x the expected improvement as acquisition value.

\(EI(X) := \frac{\mathbb{E}\left[\max\{0,f(\mathbf{X^+})-f_{t+1}(\mathbf{X})-\xi\right]\}]}{np.log(r(x))}\), with \(f(X^+)\) as the best location and \(r(x)\) as runtime.

Parameters:

xi (float, defaults to 0.0) – Controls the balance between exploration and exploitation of the acquisition function.

property name: str

Returns the full name of the acquisition function.

Return type:

str

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