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 noeventType
is 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 (
recipeArn
must not be specified). When false (the default), Amazon Personalize usesrecipeArn
for training.perform_hpo (
Union
[bool
,IResolvable
,None
]) – Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default isfalse
.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
eventType
is 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 (
recipeArn
must not be specified). When false (the default), Amazon Personalize usesrecipeArn
for 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.