class Aws::Personalize::Types::CreateSolutionRequest

@note When making an API call, you may pass CreateSolutionRequest

data as a hash:

    {
      name: "Name", # required
      perform_hpo: false,
      perform_auto_ml: false,
      recipe_arn: "Arn",
      dataset_group_arn: "Arn", # required
      event_type: "EventType",
      solution_config: {
        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"],
        },
        optimization_objective: {
          item_attribute: "ItemAttribute",
          objective_sensitivity: "LOW", # accepts LOW, MEDIUM, HIGH, OFF
        },
      },
    }

@!attribute [rw] name

The name for the solution.
@return [String]

@!attribute [rw] perform_hpo

Whether to perform hyperparameter optimization (HPO) on the
specified or selected recipe. The default is `false`.

When performing AutoML, this parameter is always `true` and you
should not set it to `false`.
@return [Boolean]

@!attribute [rw] perform_auto_ml

Whether to perform automated machine learning (AutoML). The default
is `false`. For this case, you must specify `recipeArn`.

When set to `true`, Amazon Personalize analyzes your training data
and selects the optimal USER\_PERSONALIZATION recipe and
hyperparameters. In this case, you must omit `recipeArn`. Amazon
Personalize determines the optimal recipe by running tests with
different values for the hyperparameters. AutoML lengthens the
training process as compared to selecting a specific recipe.
@return [Boolean]

@!attribute [rw] recipe_arn

The ARN of the recipe to use for model training. Only specified when
`performAutoML` is false.
@return [String]

@!attribute [rw] dataset_group_arn

The Amazon Resource Name (ARN) of the dataset group that provides
the training data.
@return [String]

@!attribute [rw] event_type

When your have multiple event types (using an `EVENT_TYPE` schema
field), this parameter specifies which event type (for example,
'click' or 'like') is used for training the model.

If you do not provide an `eventType`, Amazon Personalize will use
all interactions for training with equal weight regardless of type.
@return [String]

@!attribute [rw] solution_config

The configuration to use with the solution. When `performAutoML` is
set to true, Amazon Personalize only evaluates the `autoMLConfig`
section of the solution configuration.

<note markdown="1"> Amazon Personalize doesn't support configuring the `hpoObjective`
at this time.

 </note>
@return [Types::SolutionConfig]

@see docs.aws.amazon.com/goto/WebAPI/personalize-2018-05-22/CreateSolutionRequest AWS API Documentation

Constants

SENSITIVE