personalize_create_solution: By default, all new solutions use automatic training
In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

personalize_create_solution

R Documentation

By default, all new solutions use automatic training

Description

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,
  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`.
`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.