CfnSolutionProps
- class aws_cdk.aws_personalize.CfnSolutionProps(*, dataset_group_arn, name, event_type=None, perform_auto_ml=None, perform_hpo=None, recipe_arn=None, solution_config=None)
- Bases: - object- Properties for defining a - CfnSolution.- Parameters:
- dataset_group_arn ( - str) – The Amazon Resource Name (ARN) of the dataset group that provides the training data.
- name ( - str) – The name of the solution.
- event_type ( - Optional[- str]) – The event type (for example, ‘click’ or ‘like’) that is used for training the model. If no- eventTypeis provided, Amazon Personalize uses all interactions for training with equal weight regardless of type.
- perform_auto_ml ( - Union[- bool,- IResolvable,- None]) –- We don’t recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see Determining your use case. When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration ( - recipeArnmust not be specified). When false (the default), Amazon Personalize uses- recipeArnfor training.
- perform_hpo ( - Union[- bool,- IResolvable,- None]) – Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is- false.
- recipe_arn ( - Optional[- str]) – The ARN of the recipe used to create the solution.
- solution_config ( - Union[- IResolvable,- SolutionConfigProperty,- Dict[- str,- Any],- None]) – Describes the configuration properties for the solution.
 
- Link:
- http://docs.aws.amazon.com/AWSCloudFormation/latest/UserGuide/aws-resource-personalize-solution.html 
- ExampleMetadata:
- fixture=_generated 
 - Example: - # The code below shows an example of how to instantiate this type. # The values are placeholders you should change. import aws_cdk.aws_personalize as personalize # auto_ml_config: Any # hpo_config: Any cfn_solution_props = personalize.CfnSolutionProps( dataset_group_arn="datasetGroupArn", name="name", # the properties below are optional event_type="eventType", perform_auto_ml=False, perform_hpo=False, recipe_arn="recipeArn", solution_config=personalize.CfnSolution.SolutionConfigProperty( algorithm_hyper_parameters={ "algorithm_hyper_parameters_key": "algorithmHyperParameters" }, auto_ml_config=auto_ml_config, event_value_threshold="eventValueThreshold", feature_transformation_parameters={ "feature_transformation_parameters_key": "featureTransformationParameters" }, hpo_config=hpo_config ) ) - Attributes - dataset_group_arn
- The Amazon Resource Name (ARN) of the dataset group that provides the training data. 
 - event_type
- The event type (for example, ‘click’ or ‘like’) that is used for training the model. - If no - eventTypeis provided, Amazon Personalize uses all interactions for training with equal weight regardless of type.
 - name
- The name of the solution. 
 - perform_auto_ml
- We don’t recommend enabling automated machine learning. - Instead, match your use case to the available Amazon Personalize recipes. For more information, see Determining your use case. - When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration ( - recipeArnmust not be specified). When false (the default), Amazon Personalize uses- recipeArnfor training.
 - perform_hpo
- Whether to perform hyperparameter optimization (HPO) on the chosen recipe. - The default is - false.
 - recipe_arn
- The ARN of the recipe used to create the solution. 
 - solution_config
- Describes the configuration properties for the solution.