GoogleApi.MachineLearning.V1.Model.GoogleCloudMlV1_ParameterSpec (google_api_machine_learning v0.26.0) View Source
Represents a single hyperparameter to optimize.
Attributes
-
categoricalValues
(type:list(String.t)
, default:nil
) - Required if type isCATEGORICAL
. The list of possible categories. -
discreteValues
(type:list(float())
, default:nil
) - Required if type isDISCRETE
. A list of feasible points. The list should be in strictly increasing order. For instance, this parameter might have possible settings of 1.5, 2.5, and 4.0. This list should not contain more than 1,000 values. -
maxValue
(type:float()
, default:nil
) - Required if type isDOUBLE
orINTEGER
. This field should be unset if type isCATEGORICAL
. This value should be integers if type isINTEGER
. -
minValue
(type:float()
, default:nil
) - Required if type isDOUBLE
orINTEGER
. This field should be unset if type isCATEGORICAL
. This value should be integers if type is INTEGER. -
parameterName
(type:String.t
, default:nil
) - Required. The parameter name must be unique amongst all ParameterConfigs in a HyperparameterSpec message. E.g., "learning_rate". -
scaleType
(type:String.t
, default:nil
) - Optional. How the parameter should be scaled to the hypercube. Leave unset for categorical parameters. Some kind of scaling is strongly recommended for real or integral parameters (e.g.,UNIT_LINEAR_SCALE
). -
type
(type:String.t
, default:nil
) - Required. The type of the parameter.
Link to this section Summary
Functions
Unwrap a decoded JSON object into its complex fields.
Link to this section Types
Specs
Link to this section Functions
Specs
Unwrap a decoded JSON object into its complex fields.