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.
personalize_create_solution(
name,
performHPO = NULL,
performAutoML = NULL,
performAutoTraining = NULL,
recipeArn = NULL,
datasetGroupArn,
eventType = NULL,
solutionConfig = NULL,
tags = NULL
)[required] The name for the solution.
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.
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.
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.
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.
[required] The Amazon Resource Name (ARN) of the dataset group that provides the training data.
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.
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.
A list of tags to apply to the solution.