Values (p.awso.0.9.1.doc.awso.personalize.Awso

Sourceval service : Awso.Service.t

Sourceval apiVersion : string

Sourceval endpointPrefix : string

Sourceval serviceFullName : string

Sourceval signatureVersion : string

Sourceval protocol : string

Sourceval globalEndpoint : string

Sourceval targetPrefix : string

Sourceval simple_to_json : ('a -> Awso__Botodata.value) -> 'a -> Yojson.Safe.t

Sourceval composed_to_json : ('a -> Awso__Botodata.value) -> 'a -> Yojson.Safe.t

Sourceval to_query : ('a -> Awso.Client.Query.value) -> 'a -> Awso.Client.Query.t

Source

val structure_to_value_aux : 
  ('a * 'b option) list ->
  f:(('a * 'b) list -> 'c) ->
  [> `Structure of 'c ]

Source

val structure_to_value : 
  ('a * 'b option) list ->
  [> `Structure of ('a * 'b) list ]

Source

val structure_to_wrapped_value : 
  wrapper:'a ->
  response:'a ->
  ('b * 'c option) list ->
  [> `Structure of ('a * [> `Structure of ('b * 'c) list ]) list ]

Sourcemodule CategoricalValue : sig ... end

Sourcemodule ColumnName : sig ... end

Sourcemodule CategoricalValues : sig ... end

Sourcemodule ParameterName : sig ... end

Sourcemodule ContinuousMaxValue : sig ... end

Sourcemodule ContinuousMinValue : sig ... end

Sourcemodule IntegerMaxValue : sig ... end

Sourcemodule IntegerMinValue : sig ... end

Sourcemodule EventType : sig ... end

Sourcemodule EventTypeThresholdValue : sig ... end

Sourcemodule EventTypeWeight : sig ... end

Sourcemodule ColumnNamesList : sig ... end

Sourcemodule DatasetType : sig ... end

Sourcemodule CategoricalHyperParameterRange : sig ... end

Provides the name and range of a categorical hyperparameter.

Sourcemodule ContinuousHyperParameterRange : sig ... end

Provides the name and range of a continuous hyperparameter.

Sourcemodule IntegerHyperParameterRange : sig ... end

Provides the name and range of an integer-valued hyperparameter.

Sourcemodule EventParameters : sig ... end

Describes the parameters of events, which are used in solution creation.

Sourcemodule ParameterValue : sig ... end

Sourcemodule ExcludedDatasetColumns : sig ... end

Sourcemodule IncludedDatasetColumns : sig ... end

Sourcemodule Arn : sig ... end

Sourcemodule HPOObjectiveType : sig ... end

Sourcemodule MetricName : sig ... end

Sourcemodule MetricRegex : sig ... end

Sourcemodule HPOResource : sig ... end

Sourcemodule CategoricalHyperParameterRanges : sig ... end

Sourcemodule ContinuousHyperParameterRanges : sig ... end

Sourcemodule IntegerHyperParameterRanges : sig ... end

Sourcemodule SchedulingExpression : sig ... end

Sourcemodule EventParametersList : sig ... end

Sourcemodule RankingInfluenceType : sig ... end

Sourcemodule RankingInfluenceWeight : sig ... end

Sourcemodule Tunable : sig ... end

Sourcemodule Boolean : sig ... end

Sourcemodule HyperParameters : sig ... end

Sourcemodule TrainingDataConfig : sig ... end

The training data configuration to use when creating a domain recommender or custom solution version (trained model).

Sourcemodule TransactionsPerSecond : sig ... end

Sourcemodule ArnList : sig ... end

Sourcemodule HPOObjective : sig ... end

The metric to optimize during hyperparameter optimization (HPO). Amazon Personalize doesn't support configuring the hpoObjective at this time.

Sourcemodule HPOResourceConfig : sig ... end

Describes the resource configuration for hyperparameter optimization (HPO).

Sourcemodule HyperParameterRanges : sig ... end

Specifies the hyperparameters and their ranges. Hyperparameters can be categorical, continuous, or integer-valued.

Sourcemodule ItemAttribute : sig ... end

Sourcemodule ObjectiveSensitivity : sig ... end

Sourcemodule AutoTrainingConfig : sig ... end

The automatic training configuration to use when performAutoTraining is true.

Sourcemodule EventsConfig : sig ... end

Describes the configuration of events, which are used in solution creation.

Sourcemodule KmsKeyArn : sig ... end

Sourcemodule S3Location : sig ... end

Sourcemodule RankingInfluence : sig ... end

Sourcemodule DefaultCategoricalHyperParameterRange : sig ... end

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).

Sourcemodule DefaultContinuousHyperParameterRange : sig ... end

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).

Sourcemodule DefaultIntegerHyperParameterRange : sig ... end

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).

Sourcemodule MetricExpression : sig ... end

Sourcemodule TagKey : sig ... end

Sourcemodule TagValue : sig ... end

Sourcemodule Date : sig ... end

Sourcemodule Name : sig ... end

Sourcemodule Status : sig ... end

Sourcemodule FailureReason : sig ... end

Sourcemodule TrainingMode : sig ... end

Sourcemodule TrainingType : sig ... end

Sourcemodule Domain : sig ... end

Sourcemodule RecommenderConfig : sig ... end

The configuration details of the recommender.

Sourcemodule ImportMode : sig ... end

Sourcemodule BatchInferenceJobMode : sig ... end

Sourcemodule AutoMLConfig : sig ... end

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.

Sourcemodule EventValueThreshold : sig ... end

Sourcemodule FeatureTransformationParameters : sig ... end

Sourcemodule HPOConfig : sig ... end

Describes the properties for hyperparameter optimization (HPO).

Sourcemodule OptimizationObjective : sig ... end

Describes the additional objective for the solution, such as maximizing streaming minutes or increasing revenue. For more information see Optimizing a solution.

Sourcemodule PerformAutoTraining : sig ... end

Sourcemodule PerformIncrementalUpdate : sig ... end

Sourcemodule SolutionUpdateConfig : sig ... end

The configuration details of the solution update.

Sourcemodule MetricValue : sig ... end

Sourcemodule RoleArn : sig ... end

Sourcemodule S3DataConfig : sig ... end

The configuration details of an Amazon S3 input or output bucket.

Sourcemodule CampaignConfig : sig ... end

The configuration details of a campaign.

Sourcemodule FieldsForThemeGeneration : sig ... end

A string to string map of the configuration details for theme generation.

Sourcemodule DockerURI : sig ... end

Sourcemodule DefaultCategoricalHyperParameterRanges : sig ... end

Sourcemodule DefaultContinuousHyperParameterRanges : sig ... end

Sourcemodule DefaultIntegerHyperParameterRanges : sig ... end

Sourcemodule ErrorMessage : sig ... end

Sourcemodule MetricAttribute : sig ... end

Contains information on a metric that a metric attribution reports on. For more information, see Measuring impact of recommendations.

Sourcemodule Tag : sig ... end

The optional metadata that you apply to resources to help you categorize and organize them. Each tag consists of a key and an optional value, both of which you define. For more information see Tagging Amazon Personalize resources.

Sourcemodule SolutionSummary : sig ... end

Provides a summary of the properties of a solution. For a complete listing, call the DescribeSolution API.

Sourcemodule SolutionVersionSummary : sig ... end

Provides a summary of the properties of a solution version. For a complete listing, call the DescribeSolutionVersion API.

Sourcemodule DatasetSchemaSummary : sig ... end

Provides a summary of the properties of a dataset schema. For a complete listing, call the DescribeSchema API.

Sourcemodule RecommenderSummary : sig ... end

Provides a summary of the properties of the recommender.

Sourcemodule RecipeSummary : sig ... end

Provides a summary of the properties of a recipe. For a complete listing, call the DescribeRecipe API.

Sourcemodule MetricAttributionSummary : sig ... end

Provides a summary of the properties of a metric attribution. For a complete listing, call the DescribeMetricAttribution.

Sourcemodule FilterSummary : sig ... end

A short summary of a filter's attributes.

Sourcemodule EventTrackerSummary : sig ... end

Provides a summary of the properties of an event tracker. For a complete listing, call the DescribeEventTracker API.

Sourcemodule DatasetSummary : sig ... end

Provides a summary of the properties of a dataset. For a complete listing, call the DescribeDataset API.

Sourcemodule DatasetImportJobSummary : sig ... end

Provides a summary of the properties of a dataset import job. For a complete listing, call the DescribeDatasetImportJob API.

Sourcemodule DatasetGroupSummary : sig ... end

Provides a summary of the properties of a dataset group. For a complete listing, call the DescribeDatasetGroup API.

Sourcemodule DatasetExportJobSummary : sig ... end

Provides a summary of the properties of a dataset export job. For a complete listing, call the DescribeDatasetExportJob API.

Sourcemodule DataDeletionJobSummary : sig ... end

Provides a summary of the properties of a data deletion job. For a complete listing, call the DescribeDataDeletionJob API operation.

Sourcemodule CampaignSummary : sig ... end

Provides a summary of the properties of a campaign. For a complete listing, call the DescribeCampaign API.

Sourcemodule BatchSegmentJobSummary : sig ... end

A truncated version of the BatchSegmentJob datatype. ListBatchSegmentJobs operation returns a list of batch segment job summaries.

Sourcemodule BatchInferenceJobSummary : sig ... end

A truncated version of the BatchInferenceJob. The ListBatchInferenceJobs operation returns a list of batch inference job summaries.

Sourcemodule PerformAutoML : sig ... end

Sourcemodule PerformHPO : sig ... end

Sourcemodule SolutionConfig : sig ... end

Describes the configuration properties for the solution.

Sourcemodule TrainingHours : sig ... end

Sourcemodule TunedHPOParams : sig ... end

If hyperparameter optimization (HPO) was performed, contains the hyperparameter values of the best performing model.

Sourcemodule AutoMLResult : sig ... end

When the solution performs AutoML (performAutoML is true in CreateSolution), specifies the recipe that best optimized the specified metric.

Sourcemodule SolutionUpdateSummary : sig ... end

Provides a summary of the properties of a solution update. For a complete listing, call the DescribeSolution API.

Sourcemodule AvroSchema : sig ... end

Sourcemodule Metrics : sig ... end

Sourcemodule RecommenderUpdateSummary : sig ... end

Provides a summary of the properties of a recommender update. For a complete listing, call the DescribeRecommender API.

Sourcemodule Description : sig ... end

Sourcemodule RecipeType : sig ... end

Sourcemodule MetricAttributionOutput : sig ... end

The output configuration details for a metric attribution.

Sourcemodule FilterExpression : sig ... end

Sourcemodule FeaturizationParameters : sig ... end

Sourcemodule AccountId : sig ... end

Sourcemodule TrackingId : sig ... end

Sourcemodule DatasetUpdateSummary : sig ... end

Describes an update to a dataset.

Sourcemodule DataSource : sig ... end

Describes the data source that contains the data to upload to a dataset, or the list of records to delete from Amazon Personalize.

Sourcemodule DatasetExportJobOutput : sig ... end

The output configuration parameters of a dataset export job.

Sourcemodule IngestionMode : sig ... end

Sourcemodule Integer : sig ... end

Sourcemodule CampaignUpdateSummary : sig ... end

Provides a summary of the properties of a campaign update. For a complete listing, call the DescribeCampaign API.

Sourcemodule BatchSegmentJobInput : sig ... end

The input configuration of a batch segment job.

Sourcemodule BatchSegmentJobOutput : sig ... end

The output configuration parameters of a batch segment job.

Sourcemodule NumBatchResults : sig ... end

Sourcemodule BatchInferenceJobConfig : sig ... end

The configuration details of a batch inference job.

Sourcemodule BatchInferenceJobInput : sig ... end

The input configuration of a batch inference job.

Sourcemodule BatchInferenceJobOutput : sig ... end

The output configuration parameters of a batch inference job.

Sourcemodule ThemeGenerationConfig : sig ... end

The configuration details for generating themes with a batch inference job.

Sourcemodule AlgorithmImage : sig ... end

Describes an algorithm image.

Sourcemodule DefaultHyperParameterRanges : sig ... end

Specifies the hyperparameters and their default ranges. Hyperparameters can be categorical, continuous, or integer-valued.

Sourcemodule ResourceConfig : sig ... end

Sourcemodule TrainingInputMode : sig ... end

Sourcemodule InvalidInputException : sig ... end

Provide a valid value for the field or parameter.

Sourcemodule LimitExceededException : sig ... end

The limit on the number of requests per second has been exceeded.

Sourcemodule ResourceInUseException : sig ... end

The specified resource is in use.

Sourcemodule ResourceNotFoundException : sig ... end

Could not find the specified resource.

Sourcemodule ResourceAlreadyExistsException : sig ... end

The specified resource already exists.

Sourcemodule MetricAttributes : sig ... end

Sourcemodule MetricAttributesNamesList : sig ... end

Sourcemodule TooManyTagKeysException : sig ... end

The request contains more tag keys than can be associated with a resource (50 tag keys per resource).

Sourcemodule TagKeys : sig ... end

Sourcemodule TooManyTagsException : sig ... end

You have exceeded the maximum number of tags you can apply to this resource.

Sourcemodule Tags : sig ... end

Sourcemodule InvalidNextTokenException : sig ... end

The token is not valid.

Sourcemodule NextToken : sig ... end

Sourcemodule Solutions : sig ... end

Sourcemodule MaxResults : sig ... end

Sourcemodule SolutionVersions : sig ... end

Sourcemodule Schemas : sig ... end

Sourcemodule Recommenders : sig ... end

Sourcemodule Recipes : sig ... end

Sourcemodule RecipeProvider : sig ... end

Sourcemodule MetricAttributions : sig ... end

Sourcemodule Filters : sig ... end

Sourcemodule EventTrackers : sig ... end

Sourcemodule Datasets : sig ... end

Sourcemodule DatasetImportJobs : sig ... end

Sourcemodule DatasetGroups : sig ... end

Sourcemodule DatasetExportJobs : sig ... end

Sourcemodule DataDeletionJobs : sig ... end

Sourcemodule Campaigns : sig ... end

Sourcemodule BatchSegmentJobs : sig ... end

Sourcemodule BatchInferenceJobs : sig ... end

Sourcemodule SolutionVersion : sig ... end

An object that provides information about a specific version of a Solution in a Custom dataset group.

Sourcemodule Solution : sig ... end

By 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.

Sourcemodule DatasetSchema : sig ... end

Describes the schema for a dataset. For more information on schemas, see CreateSchema.

Sourcemodule Recommender : sig ... end

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.

Sourcemodule Recipe : sig ... end

Provides information about a recipe. Each recipe provides an algorithm that Amazon Personalize uses in model training when you use the CreateSolution operation.

Sourcemodule MetricAttribution : sig ... end

Contains information on a metric attribution. A metric attribution creates reports on the data that you import into Amazon Personalize. Depending on how you import the data, you can view reports in Amazon CloudWatch or Amazon S3. For more information, see Measuring impact of recommendations.

Sourcemodule Filter : sig ... end

Contains information on a recommendation filter, including its ARN, status, and filter expression.

Sourcemodule FeatureTransformation : sig ... end

Provides feature transformation information. Feature transformation is the process of modifying raw input data into a form more suitable for model training.

Sourcemodule EventTracker : sig ... end

Provides information about an event tracker.

Sourcemodule Dataset : sig ... end

Provides metadata for a dataset.

Sourcemodule DatasetImportJob : sig ... end

Describes a job that imports training data from a data source (Amazon S3 bucket) to an Amazon Personalize dataset. For more information, see CreateDatasetImportJob. A dataset import job can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

Sourcemodule DatasetGroup : sig ... end

A dataset group is a collection of related datasets (Item interactions, Users, Items, Actions, Action interactions). 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. You can specify an Key Management Service (KMS) key to encrypt the datasets in the group.

Sourcemodule DatasetExportJob : sig ... end

Describes a job that exports a dataset to an Amazon S3 bucket. For more information, see CreateDatasetExportJob. A dataset export job can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED

Sourcemodule DataDeletionJob : sig ... end

Describes a job that deletes all references to specific users from an Amazon Personalize dataset group in batches. For information about creating a data deletion job, see Deleting users.

Sourcemodule Campaign : sig ... end

An object that describes the deployment of a solution version. For more information on campaigns, see CreateCampaign.

Sourcemodule BatchSegmentJob : sig ... end

Contains information on a batch segment job.

Sourcemodule BatchInferenceJob : sig ... end

Contains information on a batch inference job.

Sourcemodule Algorithm : sig ... end

Describes a custom algorithm.

Sourcemodule UpdateSolutionResponse : sig ... end

Updates an Amazon Personalize solution to use a different automatic training configuration. When you update a solution, you can change whether the solution uses automatic training, and you can change the training frequency. For more information about updating a solution, see Updating a solution. A solution update can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of a solution update, call the DescribeSolution API operation and find the status in the latestSolutionUpdate.

Sourcemodule UpdateSolutionRequest : sig ... end

Updates an Amazon Personalize solution to use a different automatic training configuration. When you update a solution, you can change whether the solution uses automatic training, and you can change the training frequency. For more information about updating a solution, see Updating a solution. A solution update can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of a solution update, call the DescribeSolution API operation and find the status in the latestSolutionUpdate.

Sourcemodule UpdateRecommenderResponse : sig ... end

Updates the recommender to modify the recommender configuration. If you update the recommender to modify the columns used in training, Amazon Personalize automatically starts a full retraining of the models backing your recommender. While the update completes, you can still get recommendations from the recommender. The recommender uses the previous configuration until the update completes. To track the status of this update, use the latestRecommenderUpdate returned in the DescribeRecommender operation.

Sourcemodule UpdateRecommenderRequest : sig ... end

Updates the recommender to modify the recommender configuration. If you update the recommender to modify the columns used in training, Amazon Personalize automatically starts a full retraining of the models backing your recommender. While the update completes, you can still get recommendations from the recommender. The recommender uses the previous configuration until the update completes. To track the status of this update, use the latestRecommenderUpdate returned in the DescribeRecommender operation.

Sourcemodule UpdateMetricAttributionResponse : sig ... end

Updates a metric attribution.

Sourcemodule UpdateMetricAttributionRequest : sig ... end

Updates a metric attribution.

Sourcemodule UpdateDatasetResponse : sig ... end

Update a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.

Sourcemodule UpdateDatasetRequest : sig ... end

Update a dataset to replace its schema with a new or existing one. For more information, see Replacing a dataset's schema.

Sourcemodule UpdateCampaignResponse : sig ... end

Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's minProvisionedTPS, or modify your campaign's configuration. For example, you can set enableMetadataWithRecommendations to true for an existing campaign. To update a campaign to start automatically using the latest solution version, specify the following: For the SolutionVersionArn parameter, specify the Amazon Resource Name (ARN) of your solution in SolutionArn/$LATEST format. In the campaignConfig, set syncWithLatestSolutionVersion to true. To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check the campaign status using the DescribeCampaign operation. You can still get recommendations from a campaign while an update is in progress. The campaign will use the previous solution version and campaign configuration to generate recommendations until the latest campaign update status is Active. For more information about updating a campaign, including code samples, see Updating a campaign. For more information about campaigns, see Creating a campaign.

Sourcemodule UpdateCampaignRequest : sig ... end

Updates a campaign to deploy a retrained solution version with an existing campaign, change your campaign's minProvisionedTPS, or modify your campaign's configuration. For example, you can set enableMetadataWithRecommendations to true for an existing campaign. To update a campaign to start automatically using the latest solution version, specify the following: For the SolutionVersionArn parameter, specify the Amazon Resource Name (ARN) of your solution in SolutionArn/$LATEST format. In the campaignConfig, set syncWithLatestSolutionVersion to true. To update a campaign, the campaign status must be ACTIVE or CREATE FAILED. Check the campaign status using the DescribeCampaign operation. You can still get recommendations from a campaign while an update is in progress. The campaign will use the previous solution version and campaign configuration to generate recommendations until the latest campaign update status is Active. For more information about updating a campaign, including code samples, see Updating a campaign. For more information about campaigns, see Creating a campaign.

Sourcemodule UntagResourceResponse : sig ... end

Removes the specified tags that are attached to a resource. For more information, see Removing tags from Amazon Personalize resources.

Sourcemodule UntagResourceRequest : sig ... end

Removes the specified tags that are attached to a resource. For more information, see Removing tags from Amazon Personalize resources.

Sourcemodule TagResourceResponse : sig ... end

Add a list of tags to a resource.

Sourcemodule TagResourceRequest : sig ... end

Add a list of tags to a resource.

Sourcemodule StopSolutionVersionCreationRequest : sig ... end

Stops creating a solution version that is in a state of CREATE_PENDING or CREATE IN_PROGRESS. Depending on the current state of the solution version, the solution version state changes as follows: CREATE_PENDING > CREATE_STOPPED or CREATE_IN_PROGRESS > CREATE_STOPPING > CREATE_STOPPED You are billed for all of the training completed up until you stop the solution version creation. You cannot resume creating a solution version once it has been stopped.

Sourcemodule StopRecommenderResponse : sig ... end

Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.

Sourcemodule StopRecommenderRequest : sig ... end

Stops a recommender that is ACTIVE. Stopping a recommender halts billing and automatic retraining for the recommender.

Sourcemodule StartRecommenderResponse : sig ... end

Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.

Sourcemodule StartRecommenderRequest : sig ... end

Starts a recommender that is INACTIVE. Starting a recommender does not create any new models, but resumes billing and automatic retraining for the recommender.

Sourcemodule ListTagsForResourceResponse : sig ... end

Get a list of tags attached to a resource.

Sourcemodule ListTagsForResourceRequest : sig ... end

Get a list of tags attached to a resource.

Sourcemodule ListSolutionsResponse : sig ... end

Returns a list of solutions in a given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.

Sourcemodule ListSolutionsRequest : sig ... end

Returns a list of solutions in a given dataset group. When a dataset group is not specified, all the solutions associated with the account are listed. The response provides the properties for each solution, including the Amazon Resource Name (ARN). For more information on solutions, see CreateSolution.

Sourcemodule ListSolutionVersionsResponse : sig ... end

Returns a list of solution versions for the given solution. When a solution is not specified, all the solution versions associated with the account are listed. The response provides the properties for each solution version, including the Amazon Resource Name (ARN).

Sourcemodule ListSolutionVersionsRequest : sig ... end

Returns a list of solution versions for the given solution. When a solution is not specified, all the solution versions associated with the account are listed. The response provides the properties for each solution version, including the Amazon Resource Name (ARN).

Sourcemodule ListSchemasResponse : sig ... end

Returns the list of schemas associated with the account. The response provides the properties for each schema, including the Amazon Resource Name (ARN). For more information on schemas, see CreateSchema.

Sourcemodule ListSchemasRequest : sig ... end

Returns the list of schemas associated with the account. The response provides the properties for each schema, including the Amazon Resource Name (ARN). For more information on schemas, see CreateSchema.

Sourcemodule ListRecommendersResponse : sig ... end

Returns a list of recommenders in a given Domain dataset group. When a Domain dataset group is not specified, all the recommenders associated with the account are listed. The response provides the properties for each recommender, including the Amazon Resource Name (ARN). For more information on recommenders, see CreateRecommender.

Sourcemodule ListRecommendersRequest : sig ... end

Returns a list of recommenders in a given Domain dataset group. When a Domain dataset group is not specified, all the recommenders associated with the account are listed. The response provides the properties for each recommender, including the Amazon Resource Name (ARN). For more information on recommenders, see CreateRecommender.

Sourcemodule ListRecipesResponse : sig ... end

Returns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).

Sourcemodule ListRecipesRequest : sig ... end

Returns a list of available recipes. The response provides the properties for each recipe, including the recipe's Amazon Resource Name (ARN).

Sourcemodule ListMetricAttributionsResponse : sig ... end

Lists metric attributions.

Sourcemodule ListMetricAttributionsRequest : sig ... end

Lists metric attributions.

Sourcemodule ListMetricAttributionMetricsResponse : sig ... end

Lists the metrics for the metric attribution.

Sourcemodule ListMetricAttributionMetricsRequest : sig ... end

Lists the metrics for the metric attribution.

Sourcemodule ListFiltersResponse : sig ... end

Lists all filters that belong to a given dataset group.

Sourcemodule ListFiltersRequest : sig ... end

Lists all filters that belong to a given dataset group.

Sourcemodule ListEventTrackersResponse : sig ... end

Returns the list of event trackers associated with the account. The response provides the properties for each event tracker, including the Amazon Resource Name (ARN) and tracking ID. For more information on event trackers, see CreateEventTracker.

Sourcemodule ListEventTrackersRequest : sig ... end

Returns the list of event trackers associated with the account. The response provides the properties for each event tracker, including the Amazon Resource Name (ARN) and tracking ID. For more information on event trackers, see CreateEventTracker.

Sourcemodule ListDatasetsResponse : sig ... end

Returns the list of datasets contained in the given dataset group. The response provides the properties for each dataset, including the Amazon Resource Name (ARN). For more information on datasets, see CreateDataset.

Sourcemodule ListDatasetsRequest : sig ... end

Returns the list of datasets contained in the given dataset group. The response provides the properties for each dataset, including the Amazon Resource Name (ARN). For more information on datasets, see CreateDataset.

Sourcemodule ListDatasetImportJobsResponse : sig ... end

Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.

Sourcemodule ListDatasetImportJobsRequest : sig ... end

Returns a list of dataset import jobs that use the given dataset. When a dataset is not specified, all the dataset import jobs associated with the account are listed. The response provides the properties for each dataset import job, including the Amazon Resource Name (ARN). For more information on dataset import jobs, see CreateDatasetImportJob. For more information on datasets, see CreateDataset.

Sourcemodule ListDatasetGroupsResponse : sig ... end

Returns a list of dataset groups. The response provides the properties for each dataset group, including the Amazon Resource Name (ARN). For more information on dataset groups, see CreateDatasetGroup.

Sourcemodule ListDatasetGroupsRequest : sig ... end

Returns a list of dataset groups. The response provides the properties for each dataset group, including the Amazon Resource Name (ARN). For more information on dataset groups, see CreateDatasetGroup.

Sourcemodule ListDatasetExportJobsResponse : sig ... end

Returns a list of dataset export jobs that use the given dataset. When a dataset is not specified, all the dataset export jobs associated with the account are listed. The response provides the properties for each dataset export job, including the Amazon Resource Name (ARN). For more information on dataset export jobs, see CreateDatasetExportJob. For more information on datasets, see CreateDataset.

Sourcemodule ListDatasetExportJobsRequest : sig ... end

Returns a list of dataset export jobs that use the given dataset. When a dataset is not specified, all the dataset export jobs associated with the account are listed. The response provides the properties for each dataset export job, including the Amazon Resource Name (ARN). For more information on dataset export jobs, see CreateDatasetExportJob. For more information on datasets, see CreateDataset.

Sourcemodule ListDataDeletionJobsResponse : sig ... end

Returns a list of data deletion jobs for a dataset group ordered by creation time, with the most recent first. When a dataset group is not specified, all the data deletion jobs associated with the account are listed. The response provides the properties for each job, including the Amazon Resource Name (ARN). For more information on data deletion jobs, see Deleting users.

Sourcemodule ListDataDeletionJobsRequest : sig ... end

Returns a list of data deletion jobs for a dataset group ordered by creation time, with the most recent first. When a dataset group is not specified, all the data deletion jobs associated with the account are listed. The response provides the properties for each job, including the Amazon Resource Name (ARN). For more information on data deletion jobs, see Deleting users.

Sourcemodule ListCampaignsResponse : sig ... end

Returns a list of campaigns that use the given solution. When a solution is not specified, all the campaigns associated with the account are listed. The response provides the properties for each campaign, including the Amazon Resource Name (ARN). For more information on campaigns, see CreateCampaign.

Sourcemodule ListCampaignsRequest : sig ... end

Returns a list of campaigns that use the given solution. When a solution is not specified, all the campaigns associated with the account are listed. The response provides the properties for each campaign, including the Amazon Resource Name (ARN). For more information on campaigns, see CreateCampaign.

Sourcemodule ListBatchSegmentJobsResponse : sig ... end

Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.

Sourcemodule ListBatchSegmentJobsRequest : sig ... end

Gets a list of the batch segment jobs that have been performed off of a solution version that you specify.

Sourcemodule ListBatchInferenceJobsResponse : sig ... end

Gets a list of the batch inference jobs that have been performed off of a solution version.

Sourcemodule ListBatchInferenceJobsRequest : sig ... end

Gets a list of the batch inference jobs that have been performed off of a solution version.

Sourcemodule GetSolutionMetricsResponse : sig ... end

Gets the metrics for the specified solution version.

Sourcemodule GetSolutionMetricsRequest : sig ... end

Gets the metrics for the specified solution version.

Sourcemodule DescribeSolutionVersionResponse : sig ... end

Describes a specific version of a solution. For more information on solutions, see CreateSolution

Sourcemodule DescribeSolutionVersionRequest : sig ... end

Describes a specific version of a solution. For more information on solutions, see CreateSolution

Sourcemodule DescribeSolutionResponse : sig ... end

Describes a solution. For more information on solutions, see CreateSolution.

Sourcemodule DescribeSolutionRequest : sig ... end

Describes a solution. For more information on solutions, see CreateSolution.

Sourcemodule DescribeSchemaResponse : sig ... end

Describes a schema. For more information on schemas, see CreateSchema.

Sourcemodule DescribeSchemaRequest : sig ... end

Describes a schema. For more information on schemas, see CreateSchema.

Sourcemodule DescribeRecommenderResponse : sig ... end

Describes the given recommender, including its status. A recommender can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE DELETE PENDING > DELETE IN_PROGRESS When the status is CREATE FAILED, the response includes the failureReason key, which describes why. The modelMetrics key is null when the recommender is being created or deleted. For more information on recommenders, see CreateRecommender.

Sourcemodule DescribeRecommenderRequest : sig ... end

Describes the given recommender, including its status. A recommender can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE DELETE PENDING > DELETE IN_PROGRESS When the status is CREATE FAILED, the response includes the failureReason key, which describes why. The modelMetrics key is null when the recommender is being created or deleted. For more information on recommenders, see CreateRecommender.

Sourcemodule DescribeRecipeResponse : sig ... end

Describes a recipe. A recipe contains three items: An algorithm that trains a model. Hyperparameters that govern the training. Feature transformation information for modifying the input data before training. Amazon Personalize provides a set of predefined recipes. You specify a recipe when you create a solution with the CreateSolution API. CreateSolution trains a model by using the algorithm in the specified recipe and a training dataset. The solution, when deployed as a campaign, can provide recommendations using the GetRecommendations API.

Sourcemodule DescribeRecipeRequest : sig ... end

Describes a recipe. A recipe contains three items: An algorithm that trains a model. Hyperparameters that govern the training. Feature transformation information for modifying the input data before training. Amazon Personalize provides a set of predefined recipes. You specify a recipe when you create a solution with the CreateSolution API. CreateSolution trains a model by using the algorithm in the specified recipe and a training dataset. The solution, when deployed as a campaign, can provide recommendations using the GetRecommendations API.

Sourcemodule DescribeMetricAttributionResponse : sig ... end

Describes a metric attribution.

Sourcemodule DescribeMetricAttributionRequest : sig ... end

Describes a metric attribution.

Sourcemodule DescribeFilterResponse : sig ... end

Describes a filter's properties.

Sourcemodule DescribeFilterRequest : sig ... end

Describes a filter's properties.

Sourcemodule DescribeFeatureTransformationResponse : sig ... end

Describes the given feature transformation.

Sourcemodule DescribeFeatureTransformationRequest : sig ... end

Describes the given feature transformation.

Sourcemodule DescribeEventTrackerResponse : sig ... end

Describes an event tracker. The response includes the trackingId and status of the event tracker. For more information on event trackers, see CreateEventTracker.

Sourcemodule DescribeEventTrackerRequest : sig ... end

Describes an event tracker. The response includes the trackingId and status of the event tracker. For more information on event trackers, see CreateEventTracker.

Sourcemodule DescribeDatasetResponse : sig ... end

Describes the given dataset. For more information on datasets, see CreateDataset.

Sourcemodule DescribeDatasetRequest : sig ... end

Describes the given dataset. For more information on datasets, see CreateDataset.

Sourcemodule DescribeDatasetImportJobResponse : sig ... end

Describes the dataset import job created by CreateDatasetImportJob, including the import job status.

Sourcemodule DescribeDatasetImportJobRequest : sig ... end

Describes the dataset import job created by CreateDatasetImportJob, including the import job status.

Sourcemodule DescribeDatasetGroupResponse : sig ... end

Describes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.

Sourcemodule DescribeDatasetGroupRequest : sig ... end

Describes the given dataset group. For more information on dataset groups, see CreateDatasetGroup.

Sourcemodule DescribeDatasetExportJobResponse : sig ... end

Describes the dataset export job created by CreateDatasetExportJob, including the export job status.

Sourcemodule DescribeDatasetExportJobRequest : sig ... end

Describes the dataset export job created by CreateDatasetExportJob, including the export job status.

Sourcemodule DescribeDataDeletionJobResponse : sig ... end

Describes the data deletion job created by CreateDataDeletionJob, including the job status.

Sourcemodule DescribeDataDeletionJobRequest : sig ... end

Describes the data deletion job created by CreateDataDeletionJob, including the job status.

Sourcemodule DescribeCampaignResponse : sig ... end

Describes the given campaign, including its status. A campaign can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS When the status is CREATE FAILED, the response includes the failureReason key, which describes why. For more information on campaigns, see CreateCampaign.

Sourcemodule DescribeCampaignRequest : sig ... end

Describes the given campaign, including its status. A campaign can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS When the status is CREATE FAILED, the response includes the failureReason key, which describes why. For more information on campaigns, see CreateCampaign.

Sourcemodule DescribeBatchSegmentJobResponse : sig ... end

Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate segments.

Sourcemodule DescribeBatchSegmentJobRequest : sig ... end

Gets the properties of a batch segment job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate segments.

Sourcemodule DescribeBatchInferenceJobResponse : sig ... end

Gets the properties of a batch inference job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate the recommendations.

Sourcemodule DescribeBatchInferenceJobRequest : sig ... end

Gets the properties of a batch inference job including name, Amazon Resource Name (ARN), status, input and output configurations, and the ARN of the solution version used to generate the recommendations.

Sourcemodule DescribeAlgorithmResponse : sig ... end

Describes the given algorithm.

Sourcemodule DescribeAlgorithmRequest : sig ... end

Describes the given algorithm.

Sourcemodule DeleteSolutionRequest : sig ... end

Deletes all versions of a solution and the Solution object itself. Before deleting a solution, you must delete all campaigns based on the solution. To determine what campaigns are using the solution, call ListCampaigns and supply the Amazon Resource Name (ARN) of the solution. You can't delete a solution if an associated SolutionVersion is in the CREATE PENDING or IN PROGRESS state. For more information on solutions, see CreateSolution.

Sourcemodule DeleteSchemaRequest : sig ... end

Deletes a schema. Before deleting a schema, you must delete all datasets referencing the schema. For more information on schemas, see CreateSchema.

Sourcemodule DeleteRecommenderRequest : sig ... end

Deactivates and removes a recommender. A deleted recommender can no longer be specified in a GetRecommendations request.

Sourcemodule DeleteMetricAttributionRequest : sig ... end

Deletes a metric attribution.

Sourcemodule DeleteFilterRequest : sig ... end

Deletes a filter.

Sourcemodule DeleteEventTrackerRequest : sig ... end

Deletes the event tracker. Does not delete the dataset from the dataset group. For more information on event trackers, see CreateEventTracker.

Sourcemodule DeleteDatasetRequest : sig ... end

Deletes a dataset. You can't delete a dataset if an associated DatasetImportJob or SolutionVersion is in the CREATE PENDING or IN PROGRESS state. For more information about deleting datasets, see Deleting a dataset.

Sourcemodule DeleteDatasetGroupRequest : sig ... end

Deletes a dataset group. Before you delete a dataset group, you must delete the following: All associated event trackers. All associated solutions. All datasets in the dataset group.

Sourcemodule DeleteCampaignRequest : sig ... end

Removes a campaign by deleting the solution deployment. The solution that the campaign is based on is not deleted and can be redeployed when needed. A deleted campaign can no longer be specified in a GetRecommendations request. For information on creating campaigns, see CreateCampaign.

Sourcemodule CreateSolutionVersionResponse : sig ... end

Trains or retrains an active solution in a Custom dataset group. A solution is created using the CreateSolution operation and must be in the ACTIVE state before calling CreateSolutionVersion. A new version of the solution is created every time you call this operation. Status A solution version can be in one of the following states: CREATE PENDING CREATE IN_PROGRESS ACTIVE CREATE FAILED CREATE STOPPING CREATE STOPPED To get the status of the version, call DescribeSolutionVersion. Wait until the status shows as ACTIVE before calling CreateCampaign. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed. Related APIs ListSolutionVersions DescribeSolutionVersion ListSolutions CreateSolution DescribeSolution DeleteSolution

Sourcemodule CreateSolutionVersionRequest : sig ... end

Trains or retrains an active solution in a Custom dataset group. A solution is created using the CreateSolution operation and must be in the ACTIVE state before calling CreateSolutionVersion. A new version of the solution is created every time you call this operation. Status A solution version can be in one of the following states: CREATE PENDING CREATE IN_PROGRESS ACTIVE CREATE FAILED CREATE STOPPING CREATE STOPPED To get the status of the version, call DescribeSolutionVersion. Wait until the status shows as ACTIVE before calling CreateCampaign. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed. Related APIs ListSolutionVersions DescribeSolutionVersion ListSolutions CreateSolution DescribeSolution DeleteSolution

Sourcemodule CreateSolutionResponse : sig ... end

By 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. Creates the configuration for training a model (creating a solution version). This configuration includes the recipe to use for model training and optional training configuration, such as columns to use in training and feature transformation parameters. For more information about configuring a solution, see Creating and configuring a solution. By default, new solutions use automatic training to create solution versions every 7 days. You can change the training frequency. Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information, see Configuring automatic training. To turn off automatic training, set performAutoTraining to false. If you turn off automatic training, you must manually create a solution version by calling the CreateSolutionVersion operation. After training starts, you can get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. To get its status, use the DescribeSolutionVersion. After training completes you can evaluate model accuracy by calling GetSolutionMetrics. When you are satisfied with the solution version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API. Amazon Personalize doesn't support configuring the hpoObjective for solution hyperparameter optimization at this time. Status A solution can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the solution, call DescribeSolution. If you use manual training, the status must be ACTIVE before you call CreateSolutionVersion. Related APIs UpdateSolution ListSolutions CreateSolutionVersion DescribeSolution DeleteSolution ListSolutionVersions DescribeSolutionVersion

Sourcemodule CreateSolutionRequest : sig ... end

By 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. Creates the configuration for training a model (creating a solution version). This configuration includes the recipe to use for model training and optional training configuration, such as columns to use in training and feature transformation parameters. For more information about configuring a solution, see Creating and configuring a solution. By default, new solutions use automatic training to create solution versions every 7 days. You can change the training frequency. Automatic solution version creation starts within one hour after the solution is ACTIVE. If you manually create a solution version within the hour, the solution skips the first automatic training. For more information, see Configuring automatic training. To turn off automatic training, set performAutoTraining to false. If you turn off automatic training, you must manually create a solution version by calling the CreateSolutionVersion operation. After training starts, you can get the solution version's Amazon Resource Name (ARN) with the ListSolutionVersions API operation. To get its status, use the DescribeSolutionVersion. After training completes you can evaluate model accuracy by calling GetSolutionMetrics. When you are satisfied with the solution version, you deploy it using CreateCampaign. The campaign provides recommendations to a client through the GetRecommendations API. Amazon Personalize doesn't support configuring the hpoObjective for solution hyperparameter optimization at this time. Status A solution can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the solution, call DescribeSolution. If you use manual training, the status must be ACTIVE before you call CreateSolutionVersion. Related APIs UpdateSolution ListSolutions CreateSolutionVersion DescribeSolution DeleteSolution ListSolutionVersions DescribeSolutionVersion

Sourcemodule CreateSchemaResponse : sig ... end

Creates an Amazon Personalize schema from the specified schema string. The schema you create must be in Avro JSON format. Amazon Personalize recognizes three schema variants. Each schema is associated with a dataset type and has a set of required field and keywords. If you are creating a schema for a dataset in a Domain dataset group, you provide the domain of the Domain dataset group. You specify a schema when you call CreateDataset. Related APIs ListSchemas DescribeSchema DeleteSchema

Sourcemodule CreateSchemaRequest : sig ... end

Creates an Amazon Personalize schema from the specified schema string. The schema you create must be in Avro JSON format. Amazon Personalize recognizes three schema variants. Each schema is associated with a dataset type and has a set of required field and keywords. If you are creating a schema for a dataset in a Domain dataset group, you provide the domain of the Domain dataset group. You specify a schema when you call CreateDataset. Related APIs ListSchemas DescribeSchema DeleteSchema

Sourcemodule CreateRecommenderResponse : sig ... end

Creates a recommender with the recipe (a Domain dataset group use case) you specify. You create recommenders for a Domain dataset group and specify the recommender's Amazon Resource Name (ARN) when you make a GetRecommendations request. Minimum recommendation requests per second A high minRecommendationRequestsPerSecond will increase your bill. We recommend starting with 1 for minRecommendationRequestsPerSecond (the default). Track your usage using Amazon CloudWatch metrics, and increase the minRecommendationRequestsPerSecond as necessary. When you create a recommender, you can configure the recommender's minimum recommendation requests per second. The minimum recommendation requests per second (minRecommendationRequestsPerSecond) specifies the baseline recommendation request throughput provisioned by Amazon Personalize. The default minRecommendationRequestsPerSecond is 1. A recommendation request is a single GetRecommendations operation. Request throughput is measured in requests per second and Amazon Personalize uses your requests per second to derive your requests per hour and the price of your recommender usage. If your requests per second increases beyond minRecommendationRequestsPerSecond, Amazon Personalize auto-scales the provisioned capacity up and down, but never below minRecommendationRequestsPerSecond. There's a short time delay while the capacity is increased that might cause loss of requests. Your bill is the greater of either the minimum requests per hour (based on minRecommendationRequestsPerSecond) or the actual number of requests. The actual request throughput used is calculated as the average requests/second within a one-hour window. We recommend starting with the default minRecommendationRequestsPerSecond, track your usage using Amazon CloudWatch metrics, and then increase the minRecommendationRequestsPerSecond as necessary. Status A recommender can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE DELETE PENDING > DELETE IN_PROGRESS To get the recommender status, call DescribeRecommender. Wait until the status of the recommender is ACTIVE before asking the recommender for recommendations. Related APIs ListRecommenders DescribeRecommender UpdateRecommender DeleteRecommender

Sourcemodule CreateRecommenderRequest : sig ... end

Creates a recommender with the recipe (a Domain dataset group use case) you specify. You create recommenders for a Domain dataset group and specify the recommender's Amazon Resource Name (ARN) when you make a GetRecommendations request. Minimum recommendation requests per second A high minRecommendationRequestsPerSecond will increase your bill. We recommend starting with 1 for minRecommendationRequestsPerSecond (the default). Track your usage using Amazon CloudWatch metrics, and increase the minRecommendationRequestsPerSecond as necessary. When you create a recommender, you can configure the recommender's minimum recommendation requests per second. The minimum recommendation requests per second (minRecommendationRequestsPerSecond) specifies the baseline recommendation request throughput provisioned by Amazon Personalize. The default minRecommendationRequestsPerSecond is 1. A recommendation request is a single GetRecommendations operation. Request throughput is measured in requests per second and Amazon Personalize uses your requests per second to derive your requests per hour and the price of your recommender usage. If your requests per second increases beyond minRecommendationRequestsPerSecond, Amazon Personalize auto-scales the provisioned capacity up and down, but never below minRecommendationRequestsPerSecond. There's a short time delay while the capacity is increased that might cause loss of requests. Your bill is the greater of either the minimum requests per hour (based on minRecommendationRequestsPerSecond) or the actual number of requests. The actual request throughput used is calculated as the average requests/second within a one-hour window. We recommend starting with the default minRecommendationRequestsPerSecond, track your usage using Amazon CloudWatch metrics, and then increase the minRecommendationRequestsPerSecond as necessary. Status A recommender can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED STOP PENDING > STOP IN_PROGRESS > INACTIVE > START PENDING > START IN_PROGRESS > ACTIVE DELETE PENDING > DELETE IN_PROGRESS To get the recommender status, call DescribeRecommender. Wait until the status of the recommender is ACTIVE before asking the recommender for recommendations. Related APIs ListRecommenders DescribeRecommender UpdateRecommender DeleteRecommender

Sourcemodule CreateMetricAttributionResponse : sig ... end

Creates a metric attribution. A metric attribution creates reports on the data that you import into Amazon Personalize. Depending on how you imported the data, you can view reports in Amazon CloudWatch or Amazon S3. For more information, see Measuring impact of recommendations.

Sourcemodule CreateMetricAttributionRequest : sig ... end

Creates a metric attribution. A metric attribution creates reports on the data that you import into Amazon Personalize. Depending on how you imported the data, you can view reports in Amazon CloudWatch or Amazon S3. For more information, see Measuring impact of recommendations.

Sourcemodule CreateFilterResponse : sig ... end

Creates a recommendation filter. For more information, see Filtering recommendations and user segments.

Sourcemodule CreateFilterRequest : sig ... end

Creates a recommendation filter. For more information, see Filtering recommendations and user segments.

Sourcemodule CreateEventTrackerResponse : sig ... end

Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API. Only one event tracker can be associated with a dataset group. You will get an error if you call CreateEventTracker using the same dataset group as an existing event tracker. When you create an event tracker, the response includes a tracking ID, which you pass as a parameter when you use the PutEvents operation. Amazon Personalize then appends the event data to the Item interactions dataset of the dataset group you specify in your event tracker. The event tracker can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the event tracker, call DescribeEventTracker. The event tracker must be in the ACTIVE state before using the tracking ID. Related APIs ListEventTrackers DescribeEventTracker DeleteEventTracker

Sourcemodule CreateEventTrackerRequest : sig ... end

Creates an event tracker that you use when adding event data to a specified dataset group using the PutEvents API. Only one event tracker can be associated with a dataset group. You will get an error if you call CreateEventTracker using the same dataset group as an existing event tracker. When you create an event tracker, the response includes a tracking ID, which you pass as a parameter when you use the PutEvents operation. Amazon Personalize then appends the event data to the Item interactions dataset of the dataset group you specify in your event tracker. The event tracker can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the event tracker, call DescribeEventTracker. The event tracker must be in the ACTIVE state before using the tracking ID. Related APIs ListEventTrackers DescribeEventTracker DeleteEventTracker

Sourcemodule CreateDatasetResponse : sig ... end

Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset. There are 5 types of datasets: Item interactions Items Users Action interactions Actions Each dataset type has an associated schema with required field types. Only the Item interactions dataset is required in order to train a model (also referred to as creating a solution). A dataset can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the dataset, call DescribeDataset. Related APIs CreateDatasetGroup ListDatasets DescribeDataset DeleteDataset

Sourcemodule CreateDatasetRequest : sig ... end

Creates an empty dataset and adds it to the specified dataset group. Use CreateDatasetImportJob to import your training data to a dataset. There are 5 types of datasets: Item interactions Items Users Action interactions Actions Each dataset type has an associated schema with required field types. Only the Item interactions dataset is required in order to train a model (also referred to as creating a solution). A dataset can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the status of the dataset, call DescribeDataset. Related APIs CreateDatasetGroup ListDatasets DescribeDataset DeleteDataset

Sourcemodule CreateDatasetImportJobResponse : sig ... end

Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset. To allow Amazon Personalize to import the training data, you must specify an IAM service role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it internally. For information on granting access to your Amazon S3 bucket, see Giving Amazon Personalize Access to Amazon S3 Resources. If you already created a recommender or deployed a custom solution version with a campaign, how new bulk records influence recommendations depends on the domain use case or recipe that you use. For more information, see How new data influences real-time recommendations. By default, a dataset import job replaces any existing data in the dataset that you imported in bulk. To add new records without replacing existing data, specify INCREMENTAL for the import mode in the CreateDatasetImportJob operation. Status A dataset import job can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of the import job, call DescribeDatasetImportJob, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed. Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset. Related APIs ListDatasetImportJobs DescribeDatasetImportJob

Sourcemodule CreateDatasetImportJobRequest : sig ... end

Creates a job that imports training data from your data source (an Amazon S3 bucket) to an Amazon Personalize dataset. To allow Amazon Personalize to import the training data, you must specify an IAM service role that has permission to read from the data source, as Amazon Personalize makes a copy of your data and processes it internally. For information on granting access to your Amazon S3 bucket, see Giving Amazon Personalize Access to Amazon S3 Resources. If you already created a recommender or deployed a custom solution version with a campaign, how new bulk records influence recommendations depends on the domain use case or recipe that you use. For more information, see How new data influences real-time recommendations. By default, a dataset import job replaces any existing data in the dataset that you imported in bulk. To add new records without replacing existing data, specify INCREMENTAL for the import mode in the CreateDatasetImportJob operation. Status A dataset import job can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of the import job, call DescribeDatasetImportJob, providing the Amazon Resource Name (ARN) of the dataset import job. The dataset import is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed. Importing takes time. You must wait until the status shows as ACTIVE before training a model using the dataset. Related APIs ListDatasetImportJobs DescribeDatasetImportJob

Sourcemodule CreateDatasetGroupResponse : sig ... end

Creates an empty dataset group. A dataset group is a container for Amazon Personalize resources. A dataset group can contain at most three datasets, one for each type of dataset: Item interactions Items Users Actions Action interactions A dataset group can be a Domain dataset group, where you specify a domain and use pre-configured resources like recommenders, or a Custom dataset group, where you use custom resources, such as a solution with a solution version, that you deploy with a campaign. If you start with a Domain dataset group, you can still add custom resources such as solutions and solution versions trained with recipes for custom use cases and deployed with campaigns. A dataset group can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING To get the status of the dataset group, call DescribeDatasetGroup. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the creation failed. You must wait until the status of the dataset group is ACTIVE before adding a dataset to the group. You can specify an Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an Identity and Access Management (IAM) role that has permission to access the key. APIs that require a dataset group ARN in the request CreateDataset CreateEventTracker CreateSolution Related APIs ListDatasetGroups DescribeDatasetGroup DeleteDatasetGroup

Sourcemodule CreateDatasetGroupRequest : sig ... end

Creates an empty dataset group. A dataset group is a container for Amazon Personalize resources. A dataset group can contain at most three datasets, one for each type of dataset: Item interactions Items Users Actions Action interactions A dataset group can be a Domain dataset group, where you specify a domain and use pre-configured resources like recommenders, or a Custom dataset group, where you use custom resources, such as a solution with a solution version, that you deploy with a campaign. If you start with a Domain dataset group, you can still add custom resources such as solutions and solution versions trained with recipes for custom use cases and deployed with campaigns. A dataset group can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING To get the status of the dataset group, call DescribeDatasetGroup. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the creation failed. You must wait until the status of the dataset group is ACTIVE before adding a dataset to the group. You can specify an Key Management Service (KMS) key to encrypt the datasets in the group. If you specify a KMS key, you must also include an Identity and Access Management (IAM) role that has permission to access the key. APIs that require a dataset group ARN in the request CreateDataset CreateEventTracker CreateSolution Related APIs ListDatasetGroups DescribeDatasetGroup DeleteDatasetGroup

Sourcemodule CreateDatasetExportJobResponse : sig ... end

Creates a job that exports data from your dataset to an Amazon S3 bucket. To allow Amazon Personalize to export the training data, you must specify an service-linked IAM role that gives Amazon Personalize PutObject permissions for your Amazon S3 bucket. For information, see Exporting a dataset in the Amazon Personalize developer guide. Status A dataset export job can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of the export job, call DescribeDatasetExportJob, and specify the Amazon Resource Name (ARN) of the dataset export job. The dataset export is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed.

Sourcemodule CreateDatasetExportJobRequest : sig ... end

Creates a job that exports data from your dataset to an Amazon S3 bucket. To allow Amazon Personalize to export the training data, you must specify an service-linked IAM role that gives Amazon Personalize PutObject permissions for your Amazon S3 bucket. For information, see Exporting a dataset in the Amazon Personalize developer guide. Status A dataset export job can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED To get the status of the export job, call DescribeDatasetExportJob, and specify the Amazon Resource Name (ARN) of the dataset export job. The dataset export is complete when the status shows as ACTIVE. If the status shows as CREATE FAILED, the response includes a failureReason key, which describes why the job failed.

Sourcemodule CreateDataDeletionJobResponse : sig ... end

Creates a batch job that deletes all references to specific users from an Amazon Personalize dataset group in batches. You specify the users to delete in a CSV file of userIds in an Amazon S3 bucket. After a job completes, Amazon Personalize no longer trains on the users’ data and no longer considers the users when generating user segments. For more information about creating a data deletion job, see Deleting users. Your input file must be a CSV file with a single USER_ID column that lists the users IDs. For more information about preparing the CSV file, see Preparing your data deletion file and uploading it to Amazon S3. To give Amazon Personalize permission to access your input CSV file of userIds, you must specify an IAM service role that has permission to read from the data source. This role needs GetObject and ListBucket permissions for the bucket and its content. These permissions are the same as importing data. For information on granting access to your Amazon S3 bucket, see Giving Amazon Personalize Access to Amazon S3 Resources. After you create a job, it can take up to a day to delete all references to the users from datasets and models. Until the job completes, Amazon Personalize continues to use the data when training. And if you use a User Segmentation recipe, the users might appear in user segments. Status A data deletion job can have one of the following statuses: PENDING > IN_PROGRESS > COMPLETED -or- FAILED To get the status of the data deletion job, call DescribeDataDeletionJob API operation and specify the Amazon Resource Name (ARN) of the job. If the status is FAILED, the response includes a failureReason key, which describes why the job failed. Related APIs ListDataDeletionJobs DescribeDataDeletionJob

Sourcemodule CreateDataDeletionJobRequest : sig ... end

Creates a batch job that deletes all references to specific users from an Amazon Personalize dataset group in batches. You specify the users to delete in a CSV file of userIds in an Amazon S3 bucket. After a job completes, Amazon Personalize no longer trains on the users’ data and no longer considers the users when generating user segments. For more information about creating a data deletion job, see Deleting users. Your input file must be a CSV file with a single USER_ID column that lists the users IDs. For more information about preparing the CSV file, see Preparing your data deletion file and uploading it to Amazon S3. To give Amazon Personalize permission to access your input CSV file of userIds, you must specify an IAM service role that has permission to read from the data source. This role needs GetObject and ListBucket permissions for the bucket and its content. These permissions are the same as importing data. For information on granting access to your Amazon S3 bucket, see Giving Amazon Personalize Access to Amazon S3 Resources. After you create a job, it can take up to a day to delete all references to the users from datasets and models. Until the job completes, Amazon Personalize continues to use the data when training. And if you use a User Segmentation recipe, the users might appear in user segments. Status A data deletion job can have one of the following statuses: PENDING > IN_PROGRESS > COMPLETED -or- FAILED To get the status of the data deletion job, call DescribeDataDeletionJob API operation and specify the Amazon Resource Name (ARN) of the job. If the status is FAILED, the response includes a failureReason key, which describes why the job failed. Related APIs ListDataDeletionJobs DescribeDataDeletionJob

Sourcemodule CreateCampaignResponse : sig ... end

You incur campaign costs while it is active. To avoid unnecessary costs, make sure to delete the campaign when you are finished. For information about campaign costs, see Amazon Personalize pricing. Creates a campaign that deploys a solution version. When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request. Minimum Provisioned TPS and Auto-Scaling A high minProvisionedTPS will increase your cost. We recommend starting with 1 for minProvisionedTPS (the default). Track your usage using Amazon CloudWatch metrics, and increase the minProvisionedTPS as necessary. When you create an Amazon Personalize campaign, you can specify the minimum provisioned transactions per second (minProvisionedTPS) for the campaign. This is the baseline transaction throughput for the campaign provisioned by Amazon Personalize. It sets the minimum billing charge for the campaign while it is active. A transaction is a single GetRecommendations or GetPersonalizedRanking request. The default minProvisionedTPS is 1. If your TPS increases beyond the minProvisionedTPS, Amazon Personalize auto-scales the provisioned capacity up and down, but never below minProvisionedTPS. There's a short time delay while the capacity is increased that might cause loss of transactions. When your traffic reduces, capacity returns to the minProvisionedTPS. You are charged for the the minimum provisioned TPS or, if your requests exceed the minProvisionedTPS, the actual TPS. The actual TPS is the total number of recommendation requests you make. We recommend starting with a low minProvisionedTPS, track your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS as necessary. For more information about campaign costs, see Amazon Personalize pricing. Status A campaign can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the campaign status, call DescribeCampaign. Wait until the status of the campaign is ACTIVE before asking the campaign for recommendations. Related APIs ListCampaigns DescribeCampaign UpdateCampaign DeleteCampaign

Sourcemodule CreateCampaignRequest : sig ... end

You incur campaign costs while it is active. To avoid unnecessary costs, make sure to delete the campaign when you are finished. For information about campaign costs, see Amazon Personalize pricing. Creates a campaign that deploys a solution version. When a client calls the GetRecommendations and GetPersonalizedRanking APIs, a campaign is specified in the request. Minimum Provisioned TPS and Auto-Scaling A high minProvisionedTPS will increase your cost. We recommend starting with 1 for minProvisionedTPS (the default). Track your usage using Amazon CloudWatch metrics, and increase the minProvisionedTPS as necessary. When you create an Amazon Personalize campaign, you can specify the minimum provisioned transactions per second (minProvisionedTPS) for the campaign. This is the baseline transaction throughput for the campaign provisioned by Amazon Personalize. It sets the minimum billing charge for the campaign while it is active. A transaction is a single GetRecommendations or GetPersonalizedRanking request. The default minProvisionedTPS is 1. If your TPS increases beyond the minProvisionedTPS, Amazon Personalize auto-scales the provisioned capacity up and down, but never below minProvisionedTPS. There's a short time delay while the capacity is increased that might cause loss of transactions. When your traffic reduces, capacity returns to the minProvisionedTPS. You are charged for the the minimum provisioned TPS or, if your requests exceed the minProvisionedTPS, the actual TPS. The actual TPS is the total number of recommendation requests you make. We recommend starting with a low minProvisionedTPS, track your usage using Amazon CloudWatch metrics, and then increase the minProvisionedTPS as necessary. For more information about campaign costs, see Amazon Personalize pricing. Status A campaign can be in one of the following states: CREATE PENDING > CREATE IN_PROGRESS > ACTIVE -or- CREATE FAILED DELETE PENDING > DELETE IN_PROGRESS To get the campaign status, call DescribeCampaign. Wait until the status of the campaign is ACTIVE before asking the campaign for recommendations. Related APIs ListCampaigns DescribeCampaign UpdateCampaign DeleteCampaign

Sourcemodule CreateBatchSegmentJobResponse : sig ... end

Creates a batch segment job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Getting batch recommendations and user segments.

Sourcemodule CreateBatchSegmentJobRequest : sig ... end

Creates a batch segment job. The operation can handle up to 50 million records and the input file must be in JSON format. For more information, see Getting batch recommendations and user segments.

Sourcemodule CreateBatchInferenceJobResponse : sig ... end

Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket. To generate batch recommendations, specify the ARN of a solution version and an Amazon S3 URI for the input and output data. For user personalization, popular items, and personalized ranking solutions, the batch inference job generates a list of recommended items for each user ID in the input file. For related items solutions, the job generates a list of recommended items for each item ID in the input file. For more information, see Creating a batch inference job . If you use the Similar-Items recipe, Amazon Personalize can add descriptive themes to batch recommendations. To generate themes, set the job's mode to THEME_GENERATION and specify the name of the field that contains item names in the input data. For more information about generating themes, see Batch recommendations with themes from Content Generator . You can't get batch recommendations with the Trending-Now or Next-Best-Action recipes.

Sourcemodule CreateBatchInferenceJobRequest : sig ... end

Generates batch recommendations based on a list of items or users stored in Amazon S3 and exports the recommendations to an Amazon S3 bucket. To generate batch recommendations, specify the ARN of a solution version and an Amazon S3 URI for the input and output data. For user personalization, popular items, and personalized ranking solutions, the batch inference job generates a list of recommended items for each user ID in the input file. For related items solutions, the job generates a list of recommended items for each item ID in the input file. For more information, see Creating a batch inference job . If you use the Similar-Items recipe, Amazon Personalize can add descriptive themes to batch recommendations. To generate themes, set the job's mode to THEME_GENERATION and specify the name of the field that contains item names in the input data. For more information about generating themes, see Batch recommendations with themes from Content Generator . You can't get batch recommendations with the Trending-Now or Next-Best-Action recipes.