AWS Native v0.54.0, Mar 21 23

aws-native.personalize.Solution

Resource schema for AWS::Personalize::Solution.

Create Solution Resource

new Solution(name: string, args: SolutionArgs, opts?: CustomResourceOptions);

@overload
def Solution(resource_name: str,
             opts: Optional[ResourceOptions] = None,
             dataset_group_arn: Optional[str] = None,
             event_type: Optional[str] = None,
             name: Optional[str] = None,
             perform_auto_ml: Optional[bool] = None,
             perform_hpo: Optional[bool] = None,
             recipe_arn: Optional[str] = None,
             solution_config: Optional[SolutionConfigArgs] = None)
@overload
def Solution(resource_name: str,
             args: SolutionArgs,
             opts: Optional[ResourceOptions] = None)

func NewSolution(ctx *Context, name string, args SolutionArgs, opts ...ResourceOption) (*Solution, error)

public Solution(string name, SolutionArgs args, CustomResourceOptions? opts = null)

public Solution(String name, SolutionArgs args)
public Solution(String name, SolutionArgs args, CustomResourceOptions options)

type: aws-native:personalize:Solution
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

name string: The unique name of the resource.
args SolutionArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

resource_name str: The unique name of the resource.
args SolutionArgs: The arguments to resource properties.
opts ResourceOptions: Bag of options to control resource's behavior.

ctx Context: Context object for the current deployment.
name string: The unique name of the resource.
args SolutionArgs: The arguments to resource properties.
opts ResourceOption: Bag of options to control resource's behavior.

name string: The unique name of the resource.
args SolutionArgs: The arguments to resource properties.
opts CustomResourceOptions: Bag of options to control resource's behavior.

name String: The unique name of the resource.
args SolutionArgs: The arguments to resource properties.
options CustomResourceOptions: Bag of options to control resource's behavior.

Solution Resource Properties

To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

Inputs

The Solution resource accepts the following input properties:

DatasetGroupArn string: The ARN of the dataset group that provides the training data.
EventType 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.
Name string: The name for the solution
PerformAutoML bool: Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
PerformHPO bool: 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.
RecipeArn string: The ARN of the recipe to use for model training. Only specified when performAutoML is false.
SolutionConfig Pulumi.AwsNative.Personalize.Inputs.SolutionConfigArgs

DatasetGroupArn string: The ARN of the dataset group that provides the training data.
EventType 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.
Name string: The name for the solution
PerformAutoML bool: Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
PerformHPO bool: 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.
RecipeArn string: The ARN of the recipe to use for model training. Only specified when performAutoML is false.
SolutionConfig SolutionConfigArgs

datasetGroupArn String: The ARN of the dataset group that provides the training data.
eventType 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.
name String: The name for the solution
performAutoML Boolean: Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
performHPO 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.
recipeArn String: The ARN of the recipe to use for model training. Only specified when performAutoML is false.
solutionConfig SolutionConfigArgs

datasetGroupArn string: The ARN of the dataset group that provides the training data.
eventType 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.
name string: The name for the solution
performAutoML boolean: Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
performHPO 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.
recipeArn string: The ARN of the recipe to use for model training. Only specified when performAutoML is false.
solutionConfig SolutionConfigArgs

dataset_group_arn str: The ARN of the dataset group that provides the training data.
event_type str: 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.
name str: The name for the solution
perform_auto_ml bool: Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
perform_hpo bool: 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 str: The ARN of the recipe to use for model training. Only specified when performAutoML is false.
solution_config SolutionConfigArgs

datasetGroupArn String: The ARN of the dataset group that provides the training data.
eventType 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.
name String: The name for the solution
performAutoML Boolean: Whether to perform automated machine learning (AutoML). The default is false. For this case, you must specify recipeArn.
performHPO 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.
recipeArn String: The ARN of the recipe to use for model training. Only specified when performAutoML is false.
solutionConfig Property Map

Outputs

All input properties are implicitly available as output properties. Additionally, the Solution resource produces the following output properties:

Id string: The provider-assigned unique ID for this managed resource.
SolutionArn string

Id string: The provider-assigned unique ID for this managed resource.
SolutionArn string

id String: The provider-assigned unique ID for this managed resource.
solutionArn String

id string: The provider-assigned unique ID for this managed resource.
solutionArn string

id str: The provider-assigned unique ID for this managed resource.
solution_arn str

id String: The provider-assigned unique ID for this managed resource.
solutionArn String

Supporting Types

SolutionCategoricalHyperParameterRange

Name string: The name of the hyperparameter.
Values List<string>: A list of the categories for the hyperparameter.

Name string: The name of the hyperparameter.
Values []string: A list of the categories for the hyperparameter.

name String: The name of the hyperparameter.
values List<String>: A list of the categories for the hyperparameter.

name string: The name of the hyperparameter.
values string[]: A list of the categories for the hyperparameter.

name str: The name of the hyperparameter.
values Sequence[str]: A list of the categories for the hyperparameter.

name String: The name of the hyperparameter.
values List<String>: A list of the categories for the hyperparameter.

SolutionConfig

AlgorithmHyperParameters object: Lists the hyperparameter names and ranges.
AutoMLConfig Pulumi.AwsNative.Personalize.Inputs.SolutionConfigAutoMLConfigProperties: The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
EventValueThreshold string: Only events with a value greater than or equal to this threshold are used for training a model.
FeatureTransformationParameters object: Lists the feature transformation parameters.
HpoConfig Pulumi.AwsNative.Personalize.Inputs.SolutionConfigHpoConfigProperties: Describes the properties for hyperparameter optimization (HPO)

AlgorithmHyperParameters interface{}: Lists the hyperparameter names and ranges.
AutoMLConfig SolutionConfigAutoMLConfigProperties: The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
EventValueThreshold string: Only events with a value greater than or equal to this threshold are used for training a model.
FeatureTransformationParameters interface{}: Lists the feature transformation parameters.
HpoConfig SolutionConfigHpoConfigProperties: Describes the properties for hyperparameter optimization (HPO)

algorithmHyperParameters Object: Lists the hyperparameter names and ranges.
autoMLConfig SolutionConfigAutoMLConfigProperties: The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
eventValueThreshold String: Only events with a value greater than or equal to this threshold are used for training a model.
featureTransformationParameters Object: Lists the feature transformation parameters.
hpoConfig SolutionConfigHpoConfigProperties: Describes the properties for hyperparameter optimization (HPO)

algorithmHyperParameters any: Lists the hyperparameter names and ranges.
autoMLConfig SolutionConfigAutoMLConfigProperties: The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
eventValueThreshold string: Only events with a value greater than or equal to this threshold are used for training a model.
featureTransformationParameters any: Lists the feature transformation parameters.
hpoConfig SolutionConfigHpoConfigProperties: Describes the properties for hyperparameter optimization (HPO)

algorithm_hyper_parameters Any: Lists the hyperparameter names and ranges.
auto_ml_config SolutionConfigAutoMLConfigProperties: The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
event_value_threshold str: Only events with a value greater than or equal to this threshold are used for training a model.
feature_transformation_parameters Any: Lists the feature transformation parameters.
hpo_config SolutionConfigHpoConfigProperties: Describes the properties for hyperparameter optimization (HPO)

algorithmHyperParameters Any: Lists the hyperparameter names and ranges.
autoMLConfig Property Map: The AutoMLConfig object containing a list of recipes to search when AutoML is performed.
eventValueThreshold String: Only events with a value greater than or equal to this threshold are used for training a model.
featureTransformationParameters Any: Lists the feature transformation parameters.
hpoConfig Property Map: Describes the properties for hyperparameter optimization (HPO)

SolutionConfigAutoMLConfigProperties

MetricName string: The metric to optimize.
RecipeList List<string>: The list of candidate recipes.

MetricName string: The metric to optimize.
RecipeList []string: The list of candidate recipes.

metricName String: The metric to optimize.
recipeList List<String>: The list of candidate recipes.

metricName string: The metric to optimize.
recipeList string[]: The list of candidate recipes.

metric_name str: The metric to optimize.
recipe_list Sequence[str]: The list of candidate recipes.

metricName String: The metric to optimize.
recipeList List<String>: The list of candidate recipes.

SolutionConfigHpoConfigProperties

AlgorithmHyperParameterRanges Pulumi.AwsNative.Personalize.Inputs.SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties: The hyperparameters and their allowable ranges
HpoObjective Pulumi.AwsNative.Personalize.Inputs.SolutionConfigHpoConfigPropertiesHpoObjectiveProperties: The metric to optimize during HPO.
HpoResourceConfig Pulumi.AwsNative.Personalize.Inputs.SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties: Describes the resource configuration for hyperparameter optimization (HPO).

AlgorithmHyperParameterRanges SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties: The hyperparameters and their allowable ranges
HpoObjective SolutionConfigHpoConfigPropertiesHpoObjectiveProperties: The metric to optimize during HPO.
HpoResourceConfig SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties: Describes the resource configuration for hyperparameter optimization (HPO).

algorithmHyperParameterRanges SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties: The hyperparameters and their allowable ranges
hpoObjective SolutionConfigHpoConfigPropertiesHpoObjectiveProperties: The metric to optimize during HPO.
hpoResourceConfig SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties: Describes the resource configuration for hyperparameter optimization (HPO).

algorithmHyperParameterRanges SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties: The hyperparameters and their allowable ranges
hpoObjective SolutionConfigHpoConfigPropertiesHpoObjectiveProperties: The metric to optimize during HPO.
hpoResourceConfig SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties: Describes the resource configuration for hyperparameter optimization (HPO).

algorithm_hyper_parameter_ranges SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties: The hyperparameters and their allowable ranges
hpo_objective SolutionConfigHpoConfigPropertiesHpoObjectiveProperties: The metric to optimize during HPO.
hpo_resource_config SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties: Describes the resource configuration for hyperparameter optimization (HPO).

algorithmHyperParameterRanges Property Map: The hyperparameters and their allowable ranges
hpoObjective Property Map: The metric to optimize during HPO.
hpoResourceConfig Property Map: Describes the resource configuration for hyperparameter optimization (HPO).

SolutionConfigHpoConfigPropertiesAlgorithmHyperParameterRangesProperties

CategoricalHyperParameterRanges List<Pulumi.AwsNative.Personalize.Inputs.SolutionCategoricalHyperParameterRange>: The categorical hyperparameters and their ranges.
ContinuousHyperParameterRanges List<Pulumi.AwsNative.Personalize.Inputs.SolutionContinuousHyperParameterRange>: The continuous hyperparameters and their ranges.
IntegerHyperParameterRanges List<Pulumi.AwsNative.Personalize.Inputs.SolutionIntegerHyperParameterRange>: The integer hyperparameters and their ranges.

CategoricalHyperParameterRanges []SolutionCategoricalHyperParameterRange: The categorical hyperparameters and their ranges.
ContinuousHyperParameterRanges []SolutionContinuousHyperParameterRange: The continuous hyperparameters and their ranges.
IntegerHyperParameterRanges []SolutionIntegerHyperParameterRange: The integer hyperparameters and their ranges.

categoricalHyperParameterRanges List<SolutionCategoricalHyperParameterRange>: The categorical hyperparameters and their ranges.
continuousHyperParameterRanges List<SolutionContinuousHyperParameterRange>: The continuous hyperparameters and their ranges.
integerHyperParameterRanges List<SolutionIntegerHyperParameterRange>: The integer hyperparameters and their ranges.

categoricalHyperParameterRanges SolutionCategoricalHyperParameterRange[]: The categorical hyperparameters and their ranges.
continuousHyperParameterRanges SolutionContinuousHyperParameterRange[]: The continuous hyperparameters and their ranges.
integerHyperParameterRanges SolutionIntegerHyperParameterRange[]: The integer hyperparameters and their ranges.

categorical_hyper_parameter_ranges Sequence[SolutionCategoricalHyperParameterRange]: The categorical hyperparameters and their ranges.
continuous_hyper_parameter_ranges Sequence[SolutionContinuousHyperParameterRange]: The continuous hyperparameters and their ranges.
integer_hyper_parameter_ranges Sequence[SolutionIntegerHyperParameterRange]: The integer hyperparameters and their ranges.

categoricalHyperParameterRanges List<Property Map>: The categorical hyperparameters and their ranges.
continuousHyperParameterRanges List<Property Map>: The continuous hyperparameters and their ranges.
integerHyperParameterRanges List<Property Map>: The integer hyperparameters and their ranges.

SolutionConfigHpoConfigPropertiesHpoObjectiveProperties

MetricName string: The name of the metric
MetricRegex string: A regular expression for finding the metric in the training job logs.
Type Pulumi.AwsNative.Personalize.SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType: The type of the metric. Valid values are Maximize and Minimize.

MetricName string: The name of the metric
MetricRegex string: A regular expression for finding the metric in the training job logs.
Type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType: The type of the metric. Valid values are Maximize and Minimize.

metricName String: The name of the metric
metricRegex String: A regular expression for finding the metric in the training job logs.
type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType: The type of the metric. Valid values are Maximize and Minimize.

metricName string: The name of the metric
metricRegex string: A regular expression for finding the metric in the training job logs.
type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType: The type of the metric. Valid values are Maximize and Minimize.

metric_name str: The name of the metric
metric_regex str: A regular expression for finding the metric in the training job logs.
type SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType: The type of the metric. Valid values are Maximize and Minimize.

metricName String: The name of the metric
metricRegex String: A regular expression for finding the metric in the training job logs.
type "Maximize" | "Minimize": The type of the metric. Valid values are Maximize and Minimize.

SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesType

Maximize: Maximize
Minimize: Minimize

SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesTypeMaximize: Maximize
SolutionConfigHpoConfigPropertiesHpoObjectivePropertiesTypeMinimize: Minimize

Maximize: Maximize
Minimize: Minimize

Maximize: Maximize
Minimize: Minimize

MAXIMIZE: Maximize
MINIMIZE: Minimize

"Maximize": Maximize
"Minimize": Minimize

SolutionConfigHpoConfigPropertiesHpoResourceConfigProperties

MaxNumberOfTrainingJobs string: The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
MaxParallelTrainingJobs string: The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

MaxNumberOfTrainingJobs string: The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
MaxParallelTrainingJobs string: The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

maxNumberOfTrainingJobs String: The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
maxParallelTrainingJobs String: The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

maxNumberOfTrainingJobs string: The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
maxParallelTrainingJobs string: The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

max_number_of_training_jobs str: The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
max_parallel_training_jobs str: The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

maxNumberOfTrainingJobs String: The maximum number of training jobs when you create a solution version. The maximum value for maxNumberOfTrainingJobs is 40.
maxParallelTrainingJobs String: The maximum number of parallel training jobs when you create a solution version. The maximum value for maxParallelTrainingJobs is 10.

SolutionContinuousHyperParameterRange

MaxValue double: The maximum allowable value for the hyperparameter.
MinValue double: The minimum allowable value for the hyperparameter.
Name string: The name of the hyperparameter.

MaxValue float64: The maximum allowable value for the hyperparameter.
MinValue float64: The minimum allowable value for the hyperparameter.
Name string: The name of the hyperparameter.

maxValue Double: The maximum allowable value for the hyperparameter.
minValue Double: The minimum allowable value for the hyperparameter.
name String: The name of the hyperparameter.

maxValue number: The maximum allowable value for the hyperparameter.
minValue number: The minimum allowable value for the hyperparameter.
name string: The name of the hyperparameter.

max_value float: The maximum allowable value for the hyperparameter.
min_value float: The minimum allowable value for the hyperparameter.
name str: The name of the hyperparameter.

maxValue Number: The maximum allowable value for the hyperparameter.
minValue Number: The minimum allowable value for the hyperparameter.
name String: The name of the hyperparameter.

SolutionIntegerHyperParameterRange

MaxValue int: The maximum allowable value for the hyperparameter.
MinValue int: The minimum allowable value for the hyperparameter.
Name string: The name of the hyperparameter.

MaxValue int: The maximum allowable value for the hyperparameter.
MinValue int: The minimum allowable value for the hyperparameter.
Name string: The name of the hyperparameter.

maxValue Integer: The maximum allowable value for the hyperparameter.
minValue Integer: The minimum allowable value for the hyperparameter.
name String: The name of the hyperparameter.

maxValue number: The maximum allowable value for the hyperparameter.
minValue number: The minimum allowable value for the hyperparameter.
name string: The name of the hyperparameter.

max_value int: The maximum allowable value for the hyperparameter.
min_value int: The minimum allowable value for the hyperparameter.
name str: The name of the hyperparameter.

maxValue Number: The maximum allowable value for the hyperparameter.
minValue Number: The minimum allowable value for the hyperparameter.
name String: The name of the hyperparameter.

Package Details

Repository: AWS Native pulumi/pulumi-aws-native
License: Apache-2.0