Values.SolutionSourceBy 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. An object that provides information about a solution. A solution includes the custom recipe, customized parameters, and trained models (Solution Versions) that Amazon Personalize uses to generate recommendations. After you create a solution, you can’t change its configuration. If you need to make changes, you can clone the solution with the Amazon Personalize console or create a new one.
type nonrec t = {name : Name.t option;The name of the solution.
*)solutionArn : Arn.t option;The ARN of the solution.
*)performHPO : PerformHPO.t option;Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.
*)performAutoML : PerformAutoML.t option;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. When true, Amazon Personalize performs a search for the best USER_PERSONALIZATION recipe from the list specified in the solution configuration (recipeArn must not be specified). When false (the default), Amazon Personalize uses recipeArn for training.
*)performAutoTraining : PerformAutoTraining.t option;Specifies whether the solution automatically creates solution versions. The default is True and the solution automatically creates new solution versions every 7 days. For more information about auto training, see Creating and configuring a solution.
*)performIncrementalUpdate : PerformIncrementalUpdate.t option;A Boolean value that indicates whether incremental training updates are performed on the 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 : Arn.t option;The ARN of the recipe used to create the solution. This is required when performAutoML is false.
*)datasetGroupArn : Arn.t option;The Amazon Resource Name (ARN) of the dataset group that provides the training data.
*)eventType : EventType.t option;The event type (for example, 'click' or 'like') that is used for training the model. If no eventType is provided, Amazon Personalize uses all interactions for training with equal weight regardless of type.
*)solutionConfig : SolutionConfig.t option;Describes the configuration properties for the solution.
*)autoMLResult : AutoMLResult.t option;When performAutoML is true, specifies the best recipe found.
*)status : Status.t option;The status of the solution. A solution can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS
*)creationDateTime : Date.t option;The creation date and time (in Unix time) of the solution.
*)lastUpdatedDateTime : Date.t option;The date and time (in Unix time) that the solution was last updated.
*)latestSolutionVersion : SolutionVersionSummary.t option;Describes the latest version of the solution, including the status and the ARN.
*)latestSolutionUpdate : SolutionUpdateSummary.t option;Provides a summary of the latest updates to the solution.
*)}val make :
?name:??? ->
?solutionArn:??? ->
?performHPO:??? ->
?performAutoML:??? ->
?performAutoTraining:??? ->
?performIncrementalUpdate:??? ->
?recipeArn:??? ->
?datasetGroupArn:??? ->
?eventType:??? ->
?solutionConfig:??? ->
?autoMLResult:??? ->
?status:??? ->
?creationDateTime:??? ->
?lastUpdatedDateTime:??? ->
?latestSolutionVersion:??? ->
?latestSolutionUpdate:??? ->
unit ->
tval to_value :
t ->
[> `Structure of
(string
* [> `Boolean of PerformHPO.t
| `String of Name.t
| `Structure of
(string
* [> `Boolean of PerformAutoTraining.t
| `Enum of string
| `Map of
([> `String of ParameterName.t ]
* [> `String of ParameterValue.t ])
list
| `String of EventValueThreshold.t
| `Structure of
(string
* [> `Enum of string
| `List of
[> `String of Arn.t
| `Structure of
(string
* [> `Double of EventTypeThresholdValue.t
| `String of EventType.t ])
list ]
list
| `Map of
([> `String of DatasetType.t ]
* [> `List of [> `String of ColumnName.t ] list ])
list
| `String of MetricName.t
| `Structure of
(string
* [> `List of
[> `Structure of
(string
* [> `Double of ContinuousMinValue.t
| `Integer of IntegerMinValue.t
| `List of
[> `String of CategoricalValue.t ] list
| `String of ParameterName.t ])
list ]
list
| `String of HPOObjectiveType.t ])
list ])
list
| `Timestamp of Date.t ])
list
| `Timestamp of Date.t ])
list ]