[][src]Crate rusoto_machinelearning

Definition of the public APIs exposed by Amazon Machine Learning

If you're using the service, you're probably looking for MachineLearningClient and MachineLearning.

Structs

AddTagsInput
AddTagsOutput

Amazon ML returns the following elements.

BatchPrediction

Represents the output of a GetBatchPrediction operation.

The content consists of the detailed metadata, the status, and the data file information of a Batch Prediction.

CreateBatchPredictionInput
CreateBatchPredictionOutput

Represents the output of a CreateBatchPrediction operation, and is an acknowledgement that Amazon ML received the request.

The CreateBatchPrediction operation is asynchronous. You can poll for status updates by using the >GetBatchPrediction operation and checking the Status parameter of the result.

CreateDataSourceFromRDSInput
CreateDataSourceFromRDSOutput

Represents the output of a CreateDataSourceFromRDS operation, and is an acknowledgement that Amazon ML received the request.

The CreateDataSourceFromRDS> operation is asynchronous. You can poll for updates by using the GetBatchPrediction operation and checking the Status parameter. You can inspect the Message when Status shows up as FAILED. You can also check the progress of the copy operation by going to the DataPipeline console and looking up the pipeline using the pipelineId from the describe call.

CreateDataSourceFromRedshiftInput
CreateDataSourceFromRedshiftOutput

Represents the output of a CreateDataSourceFromRedshift operation, and is an acknowledgement that Amazon ML received the request.

The CreateDataSourceFromRedshift operation is asynchronous. You can poll for updates by using the GetBatchPrediction operation and checking the Status parameter.

CreateDataSourceFromS3Input
CreateDataSourceFromS3Output

Represents the output of a CreateDataSourceFromS3 operation, and is an acknowledgement that Amazon ML received the request.

The CreateDataSourceFromS3 operation is asynchronous. You can poll for updates by using the GetBatchPrediction operation and checking the Status parameter.

CreateEvaluationInput
CreateEvaluationOutput

Represents the output of a CreateEvaluation operation, and is an acknowledgement that Amazon ML received the request.

CreateEvaluation operation is asynchronous. You can poll for status updates by using the GetEvcaluation operation and checking the Status parameter.

CreateMLModelInput
CreateMLModelOutput

Represents the output of a CreateMLModel operation, and is an acknowledgement that Amazon ML received the request.

The CreateMLModel operation is asynchronous. You can poll for status updates by using the GetMLModel operation and checking the Status parameter.

CreateRealtimeEndpointInput
CreateRealtimeEndpointOutput

Represents the output of an CreateRealtimeEndpoint operation.

The result contains the MLModelId and the endpoint information for the MLModel.

The endpoint information includes the URI of the MLModel; that is, the location to send online prediction requests for the specified MLModel.

DataSource

Represents the output of the GetDataSource operation.

The content consists of the detailed metadata and data file information and the current status of the DataSource.

DeleteBatchPredictionInput
DeleteBatchPredictionOutput

Represents the output of a DeleteBatchPrediction operation.

You can use the GetBatchPrediction operation and check the value of the Status parameter to see whether a BatchPrediction is marked as DELETED.

DeleteDataSourceInput
DeleteDataSourceOutput

Represents the output of a DeleteDataSource operation.

DeleteEvaluationInput
DeleteEvaluationOutput

Represents the output of a DeleteEvaluation operation. The output indicates that Amazon Machine Learning (Amazon ML) received the request.

You can use the GetEvaluation operation and check the value of the Status parameter to see whether an Evaluation is marked as DELETED.

DeleteMLModelInput
DeleteMLModelOutput

Represents the output of a DeleteMLModel operation.

You can use the GetMLModel operation and check the value of the Status parameter to see whether an MLModel is marked as DELETED.

DeleteRealtimeEndpointInput
DeleteRealtimeEndpointOutput

Represents the output of an DeleteRealtimeEndpoint operation.

The result contains the MLModelId and the endpoint information for the MLModel.

DeleteTagsInput
DeleteTagsOutput

Amazon ML returns the following elements.

DescribeBatchPredictionsInput
DescribeBatchPredictionsOutput

Represents the output of a DescribeBatchPredictions operation. The content is essentially a list of BatchPredictions.

DescribeDataSourcesInput
DescribeDataSourcesOutput

Represents the query results from a DescribeDataSources operation. The content is essentially a list of DataSource.

DescribeEvaluationsInput
DescribeEvaluationsOutput

Represents the query results from a DescribeEvaluations operation. The content is essentially a list of Evaluation.

DescribeMLModelsInput
DescribeMLModelsOutput

Represents the output of a DescribeMLModels operation. The content is essentially a list of MLModel.

DescribeTagsInput
DescribeTagsOutput

Amazon ML returns the following elements.

Evaluation

Represents the output of GetEvaluation operation.

The content consists of the detailed metadata and data file information and the current status of the Evaluation.

GetBatchPredictionInput
GetBatchPredictionOutput

Represents the output of a GetBatchPrediction operation and describes a BatchPrediction.

GetDataSourceInput
GetDataSourceOutput

Represents the output of a GetDataSource operation and describes a DataSource.

GetEvaluationInput
GetEvaluationOutput

Represents the output of a GetEvaluation operation and describes an Evaluation.

GetMLModelInput
GetMLModelOutput

Represents the output of a GetMLModel operation, and provides detailed information about a MLModel.

MLModel

Represents the output of a GetMLModel operation.

The content consists of the detailed metadata and the current status of the MLModel.

MachineLearningClient

A client for the Amazon Machine Learning API.

PerformanceMetrics

Measurements of how well the MLModel performed on known observations. One of the following metrics is returned, based on the type of the MLModel:

  • BinaryAUC: The binary MLModel uses the Area Under the Curve (AUC) technique to measure performance.

  • RegressionRMSE: The regression MLModel uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.

  • MulticlassAvgFScore: The multiclass MLModel uses the F1 score technique to measure performance.

For more information about performance metrics, please see the Amazon Machine Learning Developer Guide.

PredictInput
PredictOutput
Prediction

The output from a Predict operation:

  • Details - Contains the following attributes: DetailsAttributes.PREDICTIVEMODELTYPE - REGRESSION | BINARY | MULTICLASS DetailsAttributes.ALGORITHM - SGD

  • PredictedLabel - Present for either a BINARY or MULTICLASS MLModel request.

  • PredictedScores - Contains the raw classification score corresponding to each label.

  • PredictedValue - Present for a REGRESSION MLModel request.

RDSDataSpec

The data specification of an Amazon Relational Database Service (Amazon RDS) DataSource.

RDSDatabase

The database details of an Amazon RDS database.

RDSDatabaseCredentials

The database credentials to connect to a database on an RDS DB instance.

RDSMetadata

The datasource details that are specific to Amazon RDS.

RealtimeEndpointInfo

Describes the real-time endpoint information for an MLModel.

RedshiftDataSpec

Describes the data specification of an Amazon Redshift DataSource.

RedshiftDatabase

Describes the database details required to connect to an Amazon Redshift database.

RedshiftDatabaseCredentials

Describes the database credentials for connecting to a database on an Amazon Redshift cluster.

RedshiftMetadata

Describes the DataSource details specific to Amazon Redshift.

S3DataSpec

Describes the data specification of a DataSource.

Tag

A custom key-value pair associated with an ML object, such as an ML model.

UpdateBatchPredictionInput
UpdateBatchPredictionOutput

Represents the output of an UpdateBatchPrediction operation.

You can see the updated content by using the GetBatchPrediction operation.

UpdateDataSourceInput
UpdateDataSourceOutput

Represents the output of an UpdateDataSource operation.

You can see the updated content by using the GetBatchPrediction operation.

UpdateEvaluationInput
UpdateEvaluationOutput

Represents the output of an UpdateEvaluation operation.

You can see the updated content by using the GetEvaluation operation.

UpdateMLModelInput
UpdateMLModelOutput

Represents the output of an UpdateMLModel operation.

You can see the updated content by using the GetMLModel operation.

Enums

AddTagsError

Errors returned by AddTags

CreateBatchPredictionError

Errors returned by CreateBatchPrediction

CreateDataSourceFromRDSError

Errors returned by CreateDataSourceFromRDS

CreateDataSourceFromRedshiftError

Errors returned by CreateDataSourceFromRedshift

CreateDataSourceFromS3Error

Errors returned by CreateDataSourceFromS3

CreateEvaluationError

Errors returned by CreateEvaluation

CreateMLModelError

Errors returned by CreateMLModel

CreateRealtimeEndpointError

Errors returned by CreateRealtimeEndpoint

DeleteBatchPredictionError

Errors returned by DeleteBatchPrediction

DeleteDataSourceError

Errors returned by DeleteDataSource

DeleteEvaluationError

Errors returned by DeleteEvaluation

DeleteMLModelError

Errors returned by DeleteMLModel

DeleteRealtimeEndpointError

Errors returned by DeleteRealtimeEndpoint

DeleteTagsError

Errors returned by DeleteTags

DescribeBatchPredictionsError

Errors returned by DescribeBatchPredictions

DescribeDataSourcesError

Errors returned by DescribeDataSources

DescribeEvaluationsError

Errors returned by DescribeEvaluations

DescribeMLModelsError

Errors returned by DescribeMLModels

DescribeTagsError

Errors returned by DescribeTags

GetBatchPredictionError

Errors returned by GetBatchPrediction

GetDataSourceError

Errors returned by GetDataSource

GetEvaluationError

Errors returned by GetEvaluation

GetMLModelError

Errors returned by GetMLModel

PredictError

Errors returned by Predict

UpdateBatchPredictionError

Errors returned by UpdateBatchPrediction

UpdateDataSourceError

Errors returned by UpdateDataSource

UpdateEvaluationError

Errors returned by UpdateEvaluation

UpdateMLModelError

Errors returned by UpdateMLModel

Traits

MachineLearning

Trait representing the capabilities of the Amazon Machine Learning API. Amazon Machine Learning clients implement this trait.