random_parameter_sampling {azuremlsdk} | R Documentation |
Define random sampling over a hyperparameter search space
Description
In random sampling, hyperparameter values are randomly selected from the defined search space. Random sampling allows the search space to include both discrete and continuous hyperparameters.
Usage
random_parameter_sampling(parameter_space, properties = NULL)
Arguments
parameter_space |
A named list containing each parameter and its
distribution, e.g. |
properties |
A named list of additional properties for the algorithm. |
Value
The RandomParameterSampling
object.
Details
In this sampling algorithm, parameter values are chosen from a set of
discrete values or a distribution over a continuous range. Functions you can
use include:
choice()
, randint()
, uniform()
, quniform()
, loguniform()
,
qloguniform()
, normal()
, qnormal()
, lognormal()
, and qlognormal()
.
See Also
choice()
, randint()
, uniform()
, quniform()
, loguniform()
,
qloguniform()
, normal()
, qnormal()
, lognormal()
, qlognormal()
Examples
## Not run:
param_sampling <- random_parameter_sampling(list("learning_rate" = normal(10, 3),
"keep_probability" = uniform(0.05, 0.1),
"batch_size" = choice(c(16, 32, 64, 128))))
## End(Not run)