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Class: Aws::Personalize::Types::SolutionConfig
- Inherits:
-
Struct
- Object
- Struct
- Aws::Personalize::Types::SolutionConfig
- Defined in:
- (unknown)
Overview
When passing SolutionConfig as input to an Aws::Client method, you can use a vanilla Hash:
{
event_value_threshold: "EventValueThreshold",
hpo_config: {
hpo_objective: {
type: "HPOObjectiveType",
metric_name: "MetricName",
metric_regex: "MetricRegex",
},
hpo_resource_config: {
max_number_of_training_jobs: "HPOResource",
max_parallel_training_jobs: "HPOResource",
},
algorithm_hyper_parameter_ranges: {
integer_hyper_parameter_ranges: [
{
name: "ParameterName",
min_value: 1,
max_value: 1,
},
],
continuous_hyper_parameter_ranges: [
{
name: "ParameterName",
min_value: 1.0,
max_value: 1.0,
},
],
categorical_hyper_parameter_ranges: [
{
name: "ParameterName",
values: ["CategoricalValue"],
},
],
},
},
algorithm_hyper_parameters: {
"ParameterName" => "ParameterValue",
},
feature_transformation_parameters: {
"ParameterName" => "ParameterValue",
},
auto_ml_config: {
metric_name: "MetricName",
recipe_list: ["Arn"],
},
}
Describes the configuration properties for the solution.
Returned by:
Instance Attribute Summary collapse
-
#algorithm_hyper_parameters ⇒ Hash<String,String>
Lists the hyperparameter names and ranges.
-
#auto_ml_config ⇒ Types::AutoMLConfig
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
-
#event_value_threshold ⇒ String
Only events with a value greater than or equal to this threshold are used for training a model.
-
#feature_transformation_parameters ⇒ Hash<String,String>
Lists the feature transformation parameters.
-
#hpo_config ⇒ Types::HPOConfig
Describes the properties for hyperparameter optimization (HPO).
Instance Attribute Details
#algorithm_hyper_parameters ⇒ Hash<String,String>
Lists the hyperparameter names and ranges.
#auto_ml_config ⇒ Types::AutoMLConfig
The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
#event_value_threshold ⇒ String
Only events with a value greater than or equal to this threshold are used for training a model.
#feature_transformation_parameters ⇒ Hash<String,String>
Lists the feature transformation parameters.
#hpo_config ⇒ Types::HPOConfig
Describes the properties for hyperparameter optimization (HPO).