smac.model.gaussian_process.priors.gamma_prior

Classes

GammaPrior(a, scale, loc[, seed])

Implementation of gamma prior.

Interfaces

class smac.model.gaussian_process.priors.gamma_prior.GammaPrior(a, scale, loc, seed=0)[source]

Bases: AbstractPrior

Implementation of gamma prior.

f(x) = (x-loc)**(a-1) * e**(-(x-loc)) * (1/scale)**a / gamma(a)

Parameters:

  • a (float) – The shape parameter. Must be greater than 0.

  • scale (float) – The scale parameter (1/scale corresponds to parameter p in canonical form). Must be greather than 0.

  • loc (float) – Mean parameter for the distribution.

  • seed (int, defaults to 0) –

property meta: dict[str, Any]

Returns the meta data of the created object.

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