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By default, all new solutions use automatic training

Source: R/personalize_operations.R
personalize_create_solution.Rd

By default, all new solutions use automatic training. With automatic training, you incur training costs while your solution is active. To avoid unnecessary costs, when you are finished you can update the solution to turn off automatic training. For information about training costs, see Amazon Personalize pricing.

See https://www.paws-r-sdk.com/docs/personalize_create_solution/ for full documentation.

Usage

personalize_create_solution(
  name,
  performHPO = NULL,
  performAutoML = NULL,
  performAutoTraining = NULL,
  performIncrementalUpdate = NULL,
  recipeArn = NULL,
  datasetGroupArn,
  eventType = NULL,
  solutionConfig = NULL,
  tags = NULL
)

Arguments

name

[required] The name for the solution.

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.

performAutoML

We don't recommend enabling automated machine learning. Instead, match your use case to the available Amazon Personalize recipes. For more information, see Choosing a recipe.

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.

performAutoTraining

Whether the solution uses automatic training to create new solution versions (trained models). The default is True and the solution automatically creates new solution versions every 7 days. You can change the training frequency by specifying a schedulingExpression in the AutoTrainingConfig as part of solution configuration. For more information about automatic training, see Configuring automatic training.

Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training.

After training starts, you can get the solution version's Amazon Resource Name (ARN) with the list_solution_versions API operation. To get its status, use the describe_solution_version.

performIncrementalUpdate

Whether to perform incremental training updates on your model. When enabled, this allows the model to learn from new data more frequently without requiring full retraining, which enables near real-time personalization. This parameter is supported only for solutions that use the semantic-similarity recipe.

recipeArn

The Amazon Resource Name (ARN) of the recipe to use for model training. This is required when performAutoML is false. For information about different Amazon Personalize recipes and their ARNs, see Choosing a recipe.

datasetGroupArn

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

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.

If you do not provide an eventType, Amazon Personalize will use all interactions for training with equal weight regardless of type.

solutionConfig

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

Amazon Personalize doesn't support configuring the hpoObjective at this time.

tags

A list of tags to apply to the solution.