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.

Describes a deployed solution version, otherwise known as a campaign. 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.

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.

Describes the data source that contains the data to upload to a dataset.

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.

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".

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.