Resource schema for AWS::Personalize::Solution.
dataset_group_arn
(String) The ARN of the dataset group that provides the training data.name
(String) The name for the solutionevent_type
(String) 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.perform_auto_ml
(Boolean) Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.perform_hpo
(Boolean) 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.recipe_arn
(String) The ARN of the recipe to use for model training. Only specified when performAutoML is false.solution_config
(Attributes) The configuration to use with the solution. When performAutoML is set to true, Amazon Personalize only evaluates the autoMLConfig section of the solution configuration. (see below for nested schema)id
(String) Uniquely identifies the resource.solution_arn
(String) The ARN of the solutionsolution_config
Optional:
algorithm_hyper_parameters
(Map of String) Lists the hyperparameter names and ranges.auto_ml_config
(Attributes) The AutoMLConfig object containing a list of recipes to search when AutoML is performed. (see below for nested schema)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
(Map of String) Lists the feature transformation parameters.hpo_config
(Attributes) Describes the properties for hyperparameter optimization (HPO) (see below for nested schema)solution_config.auto_ml_config
Optional:
metric_name
(String) The metric to optimize.recipe_list
(List of String) The list of candidate recipes.solution_config.hpo_config
Optional:
algorithm_hyper_parameter_ranges
(Attributes) The hyperparameters and their allowable ranges (see below for nested schema)hpo_objective
(Attributes) The metric to optimize during HPO. (see below for nested schema)hpo_resource_config
(Attributes) Describes the resource configuration for hyperparameter optimization (HPO). (see below for nested schema)solution_config.hpo_config.algorithm_hyper_parameter_ranges
Optional:
categorical_hyper_parameter_ranges
(Attributes List) The categorical hyperparameters and their ranges. (see below for nested schema)continuous_hyper_parameter_ranges
(Attributes List) The continuous hyperparameters and their ranges. (see below for nested schema)integer_hyper_parameter_ranges
(Attributes List) The integer hyperparameters and their ranges. (see below for nested schema)solution_config.hpo_config.algorithm_hyper_parameter_ranges.categorical_hyper_parameter_ranges
Optional:
name
(String) The name of the hyperparameter.values
(List of String) A list of the categories for the hyperparameter.solution_config.hpo_config.algorithm_hyper_parameter_ranges.continuous_hyper_parameter_ranges
Optional:
max_value
(Number) The maximum allowable value for the hyperparameter.min_value
(Number) The minimum allowable value for the hyperparameter.name
(String) The name of the hyperparameter.solution_config.hpo_config.algorithm_hyper_parameter_ranges.integer_hyper_parameter_ranges
Optional:
max_value
(Number) The maximum allowable value for the hyperparameter.min_value
(Number) The minimum allowable value for the hyperparameter.name
(String) The name of the hyperparameter.solution_config.hpo_config.hpo_objective
Optional:
metric_name
(String) The name of the metricmetric_regex
(String) A regular expression for finding the metric in the training job logs.type
(String) The type of the metric. Valid values are Maximize and Minimize.solution_config.hpo_config.hpo_resource_config
Optional:
max_number_of_training_jobs
(String) The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.max_parallel_training_jobs
(String) The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.Import is supported using the following syntax:
$ terraform import awscc_personalize_solution.example <resource ID>