Amazon Personalize
Developer Guide

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CreateSolution

Creates the configuration for training a model. A trained model is known as a solution. After the configuration is created, you train the model (create a solution) by calling the CreateSolutionVersion operation. Every time you call CreateSolutionVersion, a new version of the solution is created.

After creating a solution version, you check its accuracy by calling GetSolutionMetrics. When you are satisfied with the version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API.

To train a model, Amazon Personalize requires training data and a recipe. The training data comes from the dataset group that you provide in the request. A recipe specifies the training algorithm and a feature transformation. You can specify one of the predefined recipes provided by Amazon Personalize. Alternatively, you can specify performAutoML and Amazon Personalize will analyze your data and select the optimum USER_PERSONALIZATION recipe for you.

Status

A solution can be in one of the following states:

  • CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

  • DELETE PENDING > DELETE IN_PROGRESS

To get the status of the solution, call DescribeSolution. Wait until the status shows as ACTIVE before calling CreateSolutionVersion.

Request Syntax

{ "datasetGroupArn": "string", "eventType": "string", "name": "string", "performAutoML": boolean, "performHPO": boolean, "recipeArn": "string", "solutionConfig": { "algorithmHyperParameters": { "string" : "string" }, "autoMLConfig": { "metricName": "string", "recipeList": [ "string" ] }, "eventValueThreshold": "string", "featureTransformationParameters": { "string" : "string" }, "hpoConfig": { "algorithmHyperParameterRanges": { "categoricalHyperParameterRanges": [ { "name": "string", "values": [ "string" ] } ], "continuousHyperParameterRanges": [ { "maxValue": number, "minValue": number, "name": "string" } ], "integerHyperParameterRanges": [ { "maxValue": number, "minValue": number, "name": "string" } ] }, "hpoObjective": { "metricName": "string", "metricRegex": "string", "type": "string" }, "hpoResourceConfig": { "maxNumberOfTrainingJobs": "string", "maxParallelTrainingJobs": "string" } } } }

Request Parameters

The request accepts the following data in JSON format.

datasetGroupArn

The Amazon Resource Name (ARN) of the dataset group that provides the training data.

Type: String

Length Constraints: Maximum length of 256.

Pattern: arn:([a-z\d-]+):personalize:.*:.*:.+

Required: Yes

eventType

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.

Type: String

Length Constraints: Maximum length of 256.

Required: No

name

The name for the solution.

Type: String

Length Constraints: Minimum length of 1. Maximum length of 63.

Pattern: ^[a-zA-Z0-9][a-zA-Z0-9\-_]*

Required: Yes

performAutoML

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.

Type: Boolean

Required: No

performHPO

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.

Type: Boolean

Required: No

recipeArn

The ARN of the recipe to use for model training. Only specified when performAutoML is false.

Type: String

Length Constraints: Maximum length of 256.

Pattern: arn:([a-z\d-]+):personalize:.*:.*:.+

Required: No

solutionConfig

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

Type: SolutionConfig object

Required: No

Response Syntax

{ "solutionArn": "string" }

Response Elements

If the action is successful, the service sends back an HTTP 200 response.

The following data is returned in JSON format by the service.

solutionArn

The ARN of the solution.

Type: String

Length Constraints: Maximum length of 256.

Pattern: arn:([a-z\d-]+):personalize:.*:.*:.+

Errors

InvalidInputException

Provide a valid value for the field or parameter.

HTTP Status Code: 400

LimitExceededException

The limit on the number of requests per second has been exceeded.

HTTP Status Code: 400

ResourceAlreadyExistsException

The specified resource already exists.

HTTP Status Code: 400

ResourceInUseException

The specified resource is in use.

HTTP Status Code: 400

ResourceNotFoundException

Could not find the specified resource.

HTTP Status Code: 400

See Also

For more information about using this API in one of the language-specific AWS SDKs, see the following: