Module aws_sdk_personalize::model
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Data structures used by operation inputs/outputs.
Modules
Structs
Describes a custom algorithm.
Describes an algorithm image.
When the solution performs AutoML (performAutoML is true in CreateSolution), Amazon Personalize determines which recipe, from the specified list, optimizes the given metric. Amazon Personalize then uses that recipe for the solution.
When the solution performs AutoML (performAutoML is true in CreateSolution), specifies the recipe that best optimized the specified metric.
Contains information on a batch inference job.
The configuration details of a batch inference job.
The input configuration of a batch inference job.
The output configuration parameters of a batch inference job.
A truncated version of the BatchInferenceJob datatype. The ListBatchInferenceJobs operation returns a list of batch inference job summaries.
Contains information on a batch segment job.
The input configuration of a batch segment job.
The output configuration parameters of a batch segment job.
A truncated version of the BatchSegmentJob datatype. The ListBatchSegmentJobs operation returns a list of batch segment job summaries.
An object that describes the deployment of a solution version. For more information on campaigns, see CreateCampaign.
The configuration details of a campaign.
Provides a summary of the properties of a campaign. For a complete listing, call the DescribeCampaign API.
Provides a summary of the properties of a campaign update. For a complete listing, call the DescribeCampaign API.
Provides the name and range of a categorical hyperparameter.
Provides the name and range of a continuous hyperparameter.
Describes the data source that contains the data to upload to a dataset.
Provides metadata for a dataset.
Describes a job that exports a dataset to an Amazon S3 bucket. For more information, see CreateDatasetExportJob.
The output configuration parameters of a dataset export job.
Provides a summary of the properties of a dataset export job. For a complete listing, call the DescribeDatasetExportJob API.
A dataset group is a collection of related datasets (Interactions, User, and Item). You create a dataset group by calling CreateDatasetGroup. You then create a dataset and add it to a dataset group by calling CreateDataset. The dataset group is used to create and train a solution by calling CreateSolution. A dataset group can contain only one of each type of dataset.
Provides a summary of the properties of a dataset group. For a complete listing, call the DescribeDatasetGroup API.
Describes a job that imports training data from a data source (Amazon S3 bucket) to an Amazon Personalize dataset. For more information, see CreateDatasetImportJob.
Provides a summary of the properties of a dataset import job. For a complete listing, call the DescribeDatasetImportJob API.
Describes the schema for a dataset. For more information on schemas, see CreateSchema.
Provides a summary of the properties of a dataset schema. For a complete listing, call the DescribeSchema API.
Provides a summary of the properties of a dataset. For a complete listing, call the DescribeDataset API.
Provides the name and default range of a categorical hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
Provides the name and default range of a continuous hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
Specifies the hyperparameters and their default ranges. Hyperparameters can be categorical, continuous, or integer-valued.
Provides the name and default range of a integer-valued hyperparameter and whether the hyperparameter is tunable. A tunable hyperparameter can have its value determined during hyperparameter optimization (HPO).
Provides information about an event tracker.
Provides a summary of the properties of an event tracker. For a complete listing, call the DescribeEventTracker API.
Provides feature transformation information. Feature transformation is the process of modifying raw input data into a form more suitable for model training.
Contains information on a recommendation filter, including its ARN, status, and filter expression.
A short summary of a filter's attributes.
Describes the properties for hyperparameter optimization (HPO).
The metric to optimize during hyperparameter optimization (HPO).
Describes the resource configuration for hyperparameter optimization (HPO).
Specifies the hyperparameters and their ranges. Hyperparameters can be categorical, continuous, or integer-valued.
Provides the name and range of an integer-valued hyperparameter.
Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.
Provides information about a recipe. Each recipe provides an algorithm that Amazon Personalize uses in model training when you use the CreateSolution operation.
Provides a summary of the properties of a recipe. For a complete listing, call the DescribeRecipe API.
Describes a recommendation generator for a Domain dataset group. You create a recommender in a Domain dataset group for a specific domain use case (domain recipe), and specify the recommender in a GetRecommendations request.
The configuration details of the recommender.
Provides a summary of the properties of the recommender.
Provides a summary of the properties of a recommender update. For a complete listing, call the DescribeRecommender API operation.
The configuration details of an Amazon S3 input or output bucket.
An object that provides information about a solution. A solution is a trained model that can be deployed as a campaign.
Describes the configuration properties for the solution.
Provides a summary of the properties of a solution. For a complete listing, call the DescribeSolution API.
An object that provides information about a specific version of a Solution in a Custom dataset group.
Provides a summary of the properties of a solution version. For a complete listing, call the DescribeSolutionVersion API.
If hyperparameter optimization (HPO) was performed, contains the hyperparameter values of the best performing model.