#[non_exhaustive]
pub struct Solution {
Show 13 fields pub name: Option<String>, pub solution_arn: Option<String>, pub perform_hpo: bool, pub perform_auto_ml: bool, pub recipe_arn: Option<String>, pub dataset_group_arn: Option<String>, pub event_type: Option<String>, pub solution_config: Option<SolutionConfig>, pub auto_ml_result: Option<AutoMlResult>, pub status: Option<String>, pub creation_date_time: Option<DateTime>, pub last_updated_date_time: Option<DateTime>, pub latest_solution_version: Option<SolutionVersionSummary>,
}
Expand description

An object that provides information about a solution. A solution is a trained model that can be deployed as a campaign.

Fields (Non-exhaustive)

This struct is marked as non-exhaustive
Non-exhaustive structs could have additional fields added in future. Therefore, non-exhaustive structs cannot be constructed in external crates using the traditional Struct { .. } syntax; cannot be matched against without a wildcard ..; and struct update syntax will not work.
name: Option<String>

The name of the solution.

solution_arn: Option<String>

The ARN of the solution.

perform_hpo: bool

Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.

perform_auto_ml: bool

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.

recipe_arn: Option<String>

The ARN of the recipe used to create the solution.

dataset_group_arn: Option<String>

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

event_type: Option<String>

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.

solution_config: Option<SolutionConfig>

Describes the configuration properties for the solution.

auto_ml_result: Option<AutoMlResult>

When performAutoML is true, specifies the best recipe found.

status: Option<String>

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

creation_date_time: Option<DateTime>

The creation date and time (in Unix time) of the solution.

last_updated_date_time: Option<DateTime>

The date and time (in Unix time) that the solution was last updated.

latest_solution_version: Option<SolutionVersionSummary>

Describes the latest version of the solution, including the status and the ARN.

Implementations

The name of the solution.

The ARN of the solution.

Whether to perform hyperparameter optimization (HPO) on the chosen recipe. The default is false.

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.

The ARN of the recipe used to create the solution.

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

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.

Describes the configuration properties for the solution.

When performAutoML is true, specifies the best recipe found.

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

The creation date and time (in Unix time) of the solution.

The date and time (in Unix time) that the solution was last updated.

Describes the latest version of the solution, including the status and the ARN.

Creates a new builder-style object to manufacture Solution

Trait Implementations

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