Prior Object
A prior belief distribution of a Parameter. By default, SigOpt assumes the parameter to be uniformly distributed. SigOpt allows users to specify the following distributions on
double
parameters. Refer to the Prior Beliefs documentation for more information.SigOpt implements the generalized Beta distribution, which normalizes the Beta distribution to the parameter bounds.
SigOpt implements the truncated Normal distribution, which truncates the Normal distribution to the parameter bounds.
Key | Type | Value |
---|---|---|
mean | float | Only supported for normal prior. Mean of the truncated Normal distribution. |
name | string | The name of the prior distribution. Currently only supports beta and normal priors. |
scale | float | Only supported for normal prior. Standard deviation of the truncated Normal distribution. |
shape_a | float | Only supported for beta prior. Shape parameter α of the Beta distribution. |
shape_b | float | Only supported for beta prior. Shape parameter β of the Beta distribution. |
{
"name": "beta",
"object": "beta_prior",
"shape_a": 2,
"shape_b": 4.5
}
{
"name": "normal",
"object": "normal_prior",
"mean": 0.5,
"scale": 1.2
}
Last modified 1yr ago