prior
field for each continuous parameter. By default, SigOpt assumes that all parameters have a uniform prior distribution. You can inspect the probability density function of the prior belief distributions and generate the corresponding code snippet using the interactive tool below.2
are twice as likely to be suggested as those with PDF value 1
. The effect of prior belief is most notable during the initial portion of an experiment.log_learning_rate
parameter exhibits properties indicating that the highest performing values are normally distributed.