personalize_create_solution: Creates the configuration for training a model
In paws.machine.learning: 'Amazon Web Services' Machine Learning Services

personalize_create_solution

R Documentation

Creates the configuration for training a model

Description

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

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

Usage

personalize_create_solution(
  name,
  performHPO = NULL,
  performAutoML = 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 Determining your use case. 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.
`recipeArn`	The ARN of the recipe to use for model training. This is required when `performAutoML` is false.
`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 to use with 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.