com.amazonaws.services.machinelearning

Interface AmazonMachineLearning

All Known Subinterfaces:

AmazonMachineLearningAsync

All Known Implementing Classes:

AmazonMachineLearningAsyncClient, AmazonMachineLearningClient

public interface AmazonMachineLearning

Interface for accessing AmazonMachineLearning.

Definition of the public APIs exposed by Amazon Machine Learning

Method Summary

Methods

Modifier and Type	Method and Description
CreateBatchPredictionResult	createBatchPrediction(CreateBatchPredictionRequest createBatchPredictionRequest) Generates predictions for a group of observations.
CreateDataSourceFromRDSResult	createDataSourceFromRDS(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest) Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS).
CreateDataSourceFromRedshiftResult	createDataSourceFromRedshift(CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest) Creates a DataSource from Amazon Redshift .
CreateDataSourceFromS3Result	createDataSourceFromS3(CreateDataSourceFromS3Request createDataSourceFromS3Request) Creates a DataSource object.
CreateEvaluationResult	createEvaluation(CreateEvaluationRequest createEvaluationRequest) Creates a new Evaluation of an MLModel .
CreateMLModelResult	createMLModel(CreateMLModelRequest createMLModelRequest) Creates a new MLModel using the data files and the recipe as information sources.
CreateRealtimeEndpointResult	createRealtimeEndpoint(CreateRealtimeEndpointRequest createRealtimeEndpointRequest) Creates a real-time endpoint for the MLModel .
DeleteBatchPredictionResult	deleteBatchPrediction(DeleteBatchPredictionRequest deleteBatchPredictionRequest) Assigns the DELETED status to a BatchPrediction , rendering it unusable.
DeleteDataSourceResult	deleteDataSource(DeleteDataSourceRequest deleteDataSourceRequest) Assigns the DELETED status to a DataSource , rendering it unusable.
DeleteEvaluationResult	deleteEvaluation(DeleteEvaluationRequest deleteEvaluationRequest) Assigns the DELETED status to an Evaluation , rendering it unusable.
DeleteMLModelResult	deleteMLModel(DeleteMLModelRequest deleteMLModelRequest) Assigns the DELETED status to an MLModel , rendering it unusable.
DeleteRealtimeEndpointResult	deleteRealtimeEndpoint(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest) Deletes a real time endpoint of an MLModel .
DescribeBatchPredictionsResult	describeBatchPredictions() Returns a list of BatchPrediction operations that match the search criteria in the request.
DescribeBatchPredictionsResult	describeBatchPredictions(DescribeBatchPredictionsRequest describeBatchPredictionsRequest) Returns a list of BatchPrediction operations that match the search criteria in the request.
DescribeDataSourcesResult	describeDataSources() Returns a list of DataSource that match the search criteria in the request.
DescribeDataSourcesResult	describeDataSources(DescribeDataSourcesRequest describeDataSourcesRequest) Returns a list of DataSource that match the search criteria in the request.
DescribeEvaluationsResult	describeEvaluations() Returns a list of DescribeEvaluations that match the search criteria in the request.
DescribeEvaluationsResult	describeEvaluations(DescribeEvaluationsRequest describeEvaluationsRequest) Returns a list of DescribeEvaluations that match the search criteria in the request.
DescribeMLModelsResult	describeMLModels() Returns a list of MLModel that match the search criteria in the request.
DescribeMLModelsResult	describeMLModels(DescribeMLModelsRequest describeMLModelsRequest) Returns a list of MLModel that match the search criteria in the request.
GetBatchPredictionResult	getBatchPrediction(GetBatchPredictionRequest getBatchPredictionRequest) Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request.
ResponseMetadata	getCachedResponseMetadata(AmazonWebServiceRequest request) Returns additional metadata for a previously executed successful request, typically used for debugging issues where a service isn't acting as expected.
GetDataSourceResult	getDataSource(GetDataSourceRequest getDataSourceRequest) Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource .
GetEvaluationResult	getEvaluation(GetEvaluationRequest getEvaluationRequest) Returns an Evaluation that includes metadata as well as the current status of the Evaluation .
GetMLModelResult	getMLModel(GetMLModelRequest getMLModelRequest) Returns an MLModel that includes detailed metadata, and data source information as well as the current status of the MLModel .
PredictResult	predict(PredictRequest predictRequest) Generates a prediction for the observation using the specified MLModel .
void	setEndpoint(String endpoint) Overrides the default endpoint for this client ("https://machinelearning.us-east-1.amazonaws.com").
void	setRegion(Region region) An alternative to setEndpoint(String), sets the regional endpoint for this client's service calls.
void	shutdown() Shuts down this client object, releasing any resources that might be held open.
UpdateBatchPredictionResult	updateBatchPrediction(UpdateBatchPredictionRequest updateBatchPredictionRequest) Updates the BatchPredictionName of a BatchPrediction .
UpdateDataSourceResult	updateDataSource(UpdateDataSourceRequest updateDataSourceRequest) Updates the DataSourceName of a DataSource .
UpdateEvaluationResult	updateEvaluation(UpdateEvaluationRequest updateEvaluationRequest) Updates the EvaluationName of an Evaluation .
UpdateMLModelResult	updateMLModel(UpdateMLModelRequest updateMLModelRequest) Updates the MLModelName and the ScoreThreshold of an MLModel .

Method Detail

setEndpoint

void setEndpoint(String endpoint)
                 throws IllegalArgumentException

Overrides the default endpoint for this client ("https://machinelearning.us-east-1.amazonaws.com"). Callers can use this method to control which AWS region they want to work with.

Callers can pass in just the endpoint (ex: "machinelearning.us-east-1.amazonaws.com") or a full URL, including the protocol (ex: "https://machinelearning.us-east-1.amazonaws.com"). If the protocol is not specified here, the default protocol from this client's ClientConfiguration will be used, which by default is HTTPS.

For more information on using AWS regions with the AWS SDK for Java, and a complete list of all available endpoints for all AWS services, see: http://developer.amazonwebservices.com/connect/entry.jspa?externalID=3912

This method is not threadsafe. An endpoint should be configured when the client is created and before any service requests are made. Changing it afterwards creates inevitable race conditions for any service requests in transit or retrying.

Parameters:

endpoint - The endpoint (ex: "machinelearning.us-east-1.amazonaws.com") or a full URL, including the protocol (ex: "https://machinelearning.us-east-1.amazonaws.com") of the region specific AWS endpoint this client will communicate with.

Throws:

IllegalArgumentException - If any problems are detected with the specified endpoint.

setRegion

void setRegion(Region region)
               throws IllegalArgumentException

An alternative to setEndpoint(String), sets the regional endpoint for this client's service calls. Callers can use this method to control which AWS region they want to work with.

By default, all service endpoints in all regions use the https protocol. To use http instead, specify it in the ClientConfiguration supplied at construction.

This method is not threadsafe. A region should be configured when the client is created and before any service requests are made. Changing it afterwards creates inevitable race conditions for any service requests in transit or retrying.

Parameters:

region - The region this client will communicate with. See Region.getRegion(com.amazonaws.regions.Regions) for accessing a given region.

Throws:

IllegalArgumentException - If the given region is null, or if this service isn't available in the given region. See Region.isServiceSupported(String)

See Also:

Region.getRegion(com.amazonaws.regions.Regions), Region.createClient(Class, com.amazonaws.auth.AWSCredentialsProvider, ClientConfiguration)

updateEvaluation

UpdateEvaluationResult updateEvaluation(UpdateEvaluationRequest updateEvaluationRequest)
                                        throws AmazonServiceException,
                                               AmazonClientException

Updates the EvaluationName of an Evaluation .

You can use the GetEvaluation operation to view the contents of the updated data element.

Parameters:

updateEvaluationRequest - Container for the necessary parameters to execute the UpdateEvaluation service method on AmazonMachineLearning.

Returns:

The response from the UpdateEvaluation service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

createMLModel

CreateMLModelResult createMLModel(CreateMLModelRequest createMLModelRequest)
                                  throws AmazonServiceException,
                                         AmazonClientException

Creates a new MLModel using the data files and the recipe as information sources.

An MLModel is nearly immutable. Users can only update the MLModelName and the ScoreThreshold in an MLModel without creating a new MLModel .

CreateMLModel is an asynchronous operation. In response to CreateMLModel , Amazon Machine Learning (Amazon ML) immediately returns and sets the MLModel status to PENDING . After the MLModel is created and ready for use, Amazon ML sets the status to COMPLETED .

You can use the GetMLModel operation to check progress of the MLModel during the creation operation.

CreateMLModel requires a DataSource with computed statistics, which can be created by setting ComputeStatistics to true in CreateDataSourceFromRDS, CreateDataSourceFromS3, or CreateDataSourceFromRedshift operations.

Parameters:

createMLModelRequest - Container for the necessary parameters to execute the CreateMLModel service method on AmazonMachineLearning.

Returns:

The response from the CreateMLModel service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

IdempotentParameterMismatchException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

createRealtimeEndpoint

CreateRealtimeEndpointResult createRealtimeEndpoint(CreateRealtimeEndpointRequest createRealtimeEndpointRequest)
                                                    throws AmazonServiceException,
                                                           AmazonClientException

Creates a real-time endpoint for the MLModel . The endpoint contains the URI of the MLModel ; that is, the location to send real-time prediction requests for the specified MLModel .

Parameters:

createRealtimeEndpointRequest - Container for the necessary parameters to execute the CreateRealtimeEndpoint service method on AmazonMachineLearning.

Returns:

The response from the CreateRealtimeEndpoint service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

createDataSourceFromS3

CreateDataSourceFromS3Result createDataSourceFromS3(CreateDataSourceFromS3Request createDataSourceFromS3Request)
                                                    throws AmazonServiceException,
                                                           AmazonClientException

Creates a DataSource object. A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

CreateDataSourceFromS3 is an asynchronous operation. In response to CreateDataSourceFromS3 , Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING . After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED . DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.

If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.

The observation data used in a DataSource should be ready to use; that is, it should have a consistent structure, and missing data values should be kept to a minimum. The observation data must reside in one or more CSV files in an Amazon Simple Storage Service (Amazon S3) bucket, along with a schema that describes the data items by name and type. The same schema must be used for all of the data files referenced by the DataSource .

After the DataSource has been created, it's ready to use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel , the DataSource requires another item: a recipe. A recipe describes the observation variables that participate in training an MLModel . A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable, or split apart into word combinations? The recipe provides answers to these questions. For more information, see the Amazon Machine Learning Developer Guide .

Parameters:

createDataSourceFromS3Request - Container for the necessary parameters to execute the CreateDataSourceFromS3 service method on AmazonMachineLearning.

Returns:

The response from the CreateDataSourceFromS3 service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

IdempotentParameterMismatchException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

deleteMLModel

DeleteMLModelResult deleteMLModel(DeleteMLModelRequest deleteMLModelRequest)
                                  throws AmazonServiceException,
                                         AmazonClientException

Assigns the DELETED status to an MLModel , rendering it unusable.

After using the DeleteMLModel operation, you can use the GetMLModel operation to verify that the status of the MLModel changed to DELETED.

Caution The result of the DeleteMLModel operation is irreversible.

Parameters:

deleteMLModelRequest - Container for the necessary parameters to execute the DeleteMLModel service method on AmazonMachineLearning.

Returns:

The response from the DeleteMLModel service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

predict

PredictResult predict(PredictRequest predictRequest)
                      throws AmazonServiceException,
                             AmazonClientException

Generates a prediction for the observation using the specified MLModel .

NOTE: Note Not all response parameters will be populated because this is dependent on the type of requested model.

Parameters:

predictRequest - Container for the necessary parameters to execute the Predict service method on AmazonMachineLearning.

Returns:

The response from the Predict service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

PredictorNotMountedException

LimitExceededException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeBatchPredictions

DescribeBatchPredictionsResult describeBatchPredictions(DescribeBatchPredictionsRequest describeBatchPredictionsRequest)
                                                        throws AmazonServiceException,
                                                               AmazonClientException

Returns a list of BatchPrediction operations that match the search criteria in the request.

Parameters:

describeBatchPredictionsRequest - Container for the necessary parameters to execute the DescribeBatchPredictions service method on AmazonMachineLearning.

Returns:

The response from the DescribeBatchPredictions service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

getEvaluation

GetEvaluationResult getEvaluation(GetEvaluationRequest getEvaluationRequest)
                                  throws AmazonServiceException,
                                         AmazonClientException

Returns an Evaluation that includes metadata as well as the current status of the Evaluation .

Parameters:

getEvaluationRequest - Container for the necessary parameters to execute the GetEvaluation service method on AmazonMachineLearning.

Returns:

The response from the GetEvaluation service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

updateMLModel

UpdateMLModelResult updateMLModel(UpdateMLModelRequest updateMLModelRequest)
                                  throws AmazonServiceException,
                                         AmazonClientException

Updates the MLModelName and the ScoreThreshold of an MLModel .

You can use the GetMLModel operation to view the contents of the updated data element.

Parameters:

updateMLModelRequest - Container for the necessary parameters to execute the UpdateMLModel service method on AmazonMachineLearning.

Returns:

The response from the UpdateMLModel service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

getDataSource

GetDataSourceResult getDataSource(GetDataSourceRequest getDataSourceRequest)
                                  throws AmazonServiceException,
                                         AmazonClientException

Returns a DataSource that includes metadata and data file information, as well as the current status of the DataSource .

GetDataSource provides results in normal or verbose format. The verbose format adds the schema description and the list of files pointed to by the DataSource to the normal format.

Parameters:

getDataSourceRequest - Container for the necessary parameters to execute the GetDataSource service method on AmazonMachineLearning.

Returns:

The response from the GetDataSource service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeDataSources

DescribeDataSourcesResult describeDataSources(DescribeDataSourcesRequest describeDataSourcesRequest)
                                              throws AmazonServiceException,
                                                     AmazonClientException

Returns a list of DataSource that match the search criteria in the request.

Parameters:

describeDataSourcesRequest - Container for the necessary parameters to execute the DescribeDataSources service method on AmazonMachineLearning.

Returns:

The response from the DescribeDataSources service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

deleteEvaluation

DeleteEvaluationResult deleteEvaluation(DeleteEvaluationRequest deleteEvaluationRequest)
                                        throws AmazonServiceException,
                                               AmazonClientException

Assigns the DELETED status to an Evaluation , rendering it unusable.

After invoking the DeleteEvaluation operation, you can use the GetEvaluation operation to verify that the status of the Evaluation changed to DELETED .

Caution The results of the DeleteEvaluation operation are irreversible.

Parameters:

deleteEvaluationRequest - Container for the necessary parameters to execute the DeleteEvaluation service method on AmazonMachineLearning.

Returns:

The response from the DeleteEvaluation service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

updateBatchPrediction

UpdateBatchPredictionResult updateBatchPrediction(UpdateBatchPredictionRequest updateBatchPredictionRequest)
                                                  throws AmazonServiceException,
                                                         AmazonClientException

Updates the BatchPredictionName of a BatchPrediction .

You can use the GetBatchPrediction operation to view the contents of the updated data element.

Parameters:

updateBatchPredictionRequest - Container for the necessary parameters to execute the UpdateBatchPrediction service method on AmazonMachineLearning.

Returns:

The response from the UpdateBatchPrediction service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

createBatchPrediction

CreateBatchPredictionResult createBatchPrediction(CreateBatchPredictionRequest createBatchPredictionRequest)
                                                  throws AmazonServiceException,
                                                         AmazonClientException

Generates predictions for a group of observations. The observations to process exist in one or more data files referenced by a DataSource . This operation creates a new BatchPrediction , and uses an MLModel and the data files referenced by the DataSource as information sources.

CreateBatchPrediction is an asynchronous operation. In response to CreateBatchPrediction , Amazon Machine Learning (Amazon ML) immediately returns and sets the BatchPrediction status to PENDING . After the BatchPrediction completes, Amazon ML sets the status to COMPLETED .

You can poll for status updates by using the GetBatchPrediction operation and checking the Status parameter of the result. After the COMPLETED status appears, the results are available in the location specified by the OutputUri parameter.

Parameters:

createBatchPredictionRequest - Container for the necessary parameters to execute the CreateBatchPrediction service method on AmazonMachineLearning.

Returns:

The response from the CreateBatchPrediction service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

IdempotentParameterMismatchException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeMLModels

DescribeMLModelsResult describeMLModels(DescribeMLModelsRequest describeMLModelsRequest)
                                        throws AmazonServiceException,
                                               AmazonClientException

Returns a list of MLModel that match the search criteria in the request.

Parameters:

describeMLModelsRequest - Container for the necessary parameters to execute the DescribeMLModels service method on AmazonMachineLearning.

Returns:

The response from the DescribeMLModels service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

deleteBatchPrediction

DeleteBatchPredictionResult deleteBatchPrediction(DeleteBatchPredictionRequest deleteBatchPredictionRequest)
                                                  throws AmazonServiceException,
                                                         AmazonClientException

Assigns the DELETED status to a BatchPrediction , rendering it unusable.

After using the DeleteBatchPrediction operation, you can use the GetBatchPrediction operation to verify that the status of the BatchPrediction changed to DELETED.

Caution The result of the DeleteBatchPrediction operation is irreversible.

Parameters:

deleteBatchPredictionRequest - Container for the necessary parameters to execute the DeleteBatchPrediction service method on AmazonMachineLearning.

Returns:

The response from the DeleteBatchPrediction service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

updateDataSource

UpdateDataSourceResult updateDataSource(UpdateDataSourceRequest updateDataSourceRequest)
                                        throws AmazonServiceException,
                                               AmazonClientException

Updates the DataSourceName of a DataSource .

You can use the GetDataSource operation to view the contents of the updated data element.

Parameters:

updateDataSourceRequest - Container for the necessary parameters to execute the UpdateDataSource service method on AmazonMachineLearning.

Returns:

The response from the UpdateDataSource service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

createDataSourceFromRDS

CreateDataSourceFromRDSResult createDataSourceFromRDS(CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest)
                                                      throws AmazonServiceException,
                                                             AmazonClientException

Creates a DataSource object from an Amazon Relational Database Service (Amazon RDS). A DataSource references data that can be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

CreateDataSourceFromRDS is an asynchronous operation. In response to CreateDataSourceFromRDS , Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING . After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED . DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.

Parameters:

createDataSourceFromRDSRequest - Container for the necessary parameters to execute the CreateDataSourceFromRDS service method on AmazonMachineLearning.

Returns:

The response from the CreateDataSourceFromRDS service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

IdempotentParameterMismatchException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

createDataSourceFromRedshift

CreateDataSourceFromRedshiftResult createDataSourceFromRedshift(CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest)
                                                                throws AmazonServiceException,
                                                                       AmazonClientException

Creates a DataSource from Amazon Redshift . A DataSource references data that can be used to perform either CreateMLModel, CreateEvaluation or CreateBatchPrediction operations.

CreateDataSourceFromRedshift is an asynchronous operation. In response to CreateDataSourceFromRedshift , Amazon Machine Learning (Amazon ML) immediately returns and sets the DataSource status to PENDING . After the DataSource is created and ready for use, Amazon ML sets the Status parameter to COMPLETED . DataSource in COMPLETED or PENDING status can only be used to perform CreateMLModel, CreateEvaluation, or CreateBatchPrediction operations.

If Amazon ML cannot accept the input source, it sets the Status parameter to FAILED and includes an error message in the Message attribute of the GetDataSource operation response.

The observations should exist in the database hosted on an Amazon Redshift cluster and should be specified by a SelectSqlQuery . Amazon ML executes Unload command in Amazon Redshift to transfer the result set of SelectSqlQuery to S3StagingLocation.

After the DataSource is created, it's ready for use in evaluations and batch predictions. If you plan to use the DataSource to train an MLModel , the DataSource requires another item -- a recipe. A recipe describes the observation variables that participate in training an MLModel . A recipe describes how each input variable will be used in training. Will the variable be included or excluded from training? Will the variable be manipulated, for example, combined with another variable or split apart into word combinations? The recipe provides answers to these questions. For more information, see the Amazon Machine Learning Developer Guide.

Parameters:

createDataSourceFromRedshiftRequest - Container for the necessary parameters to execute the CreateDataSourceFromRedshift service method on AmazonMachineLearning.

Returns:

The response from the CreateDataSourceFromRedshift service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

IdempotentParameterMismatchException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeEvaluations

DescribeEvaluationsResult describeEvaluations(DescribeEvaluationsRequest describeEvaluationsRequest)
                                              throws AmazonServiceException,
                                                     AmazonClientException

Returns a list of DescribeEvaluations that match the search criteria in the request.

Parameters:

describeEvaluationsRequest - Container for the necessary parameters to execute the DescribeEvaluations service method on AmazonMachineLearning.

Returns:

The response from the DescribeEvaluations service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

getMLModel

GetMLModelResult getMLModel(GetMLModelRequest getMLModelRequest)
                            throws AmazonServiceException,
                                   AmazonClientException

Returns an MLModel that includes detailed metadata, and data source information as well as the current status of the MLModel .

GetMLModel provides results in normal or verbose format.

Parameters:

getMLModelRequest - Container for the necessary parameters to execute the GetMLModel service method on AmazonMachineLearning.

Returns:

The response from the GetMLModel service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

deleteDataSource

DeleteDataSourceResult deleteDataSource(DeleteDataSourceRequest deleteDataSourceRequest)
                                        throws AmazonServiceException,
                                               AmazonClientException

Assigns the DELETED status to a DataSource , rendering it unusable.

After using the DeleteDataSource operation, you can use the GetDataSource operation to verify that the status of the DataSource changed to DELETED.

Caution The results of the DeleteDataSource operation are irreversible.

Parameters:

deleteDataSourceRequest - Container for the necessary parameters to execute the DeleteDataSource service method on AmazonMachineLearning.

Returns:

The response from the DeleteDataSource service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

getBatchPrediction

GetBatchPredictionResult getBatchPrediction(GetBatchPredictionRequest getBatchPredictionRequest)
                                            throws AmazonServiceException,
                                                   AmazonClientException

Returns a BatchPrediction that includes detailed metadata, status, and data file information for a Batch Prediction request.

Parameters:

getBatchPredictionRequest - Container for the necessary parameters to execute the GetBatchPrediction service method on AmazonMachineLearning.

Returns:

The response from the GetBatchPrediction service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

createEvaluation

CreateEvaluationResult createEvaluation(CreateEvaluationRequest createEvaluationRequest)
                                        throws AmazonServiceException,
                                               AmazonClientException

Creates a new Evaluation of an MLModel . An MLModel is evaluated on a set of observations associated to a DataSource . Like a DataSource for an MLModel , the DataSource for an Evaluation contains values for the Target Variable. The Evaluation compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the MLModel functions on the test data. Evaluation generates a relevant performance metric such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding MLModelType : BINARY , REGRESSION or MULTICLASS .

CreateEvaluation is an asynchronous operation. In response to CreateEvaluation , Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status to PENDING . After the Evaluation is created and ready for use, Amazon ML sets the status to COMPLETED .

You can use the GetEvaluation operation to check progress of the evaluation during the creation operation.

Parameters:

createEvaluationRequest - Container for the necessary parameters to execute the CreateEvaluation service method on AmazonMachineLearning.

Returns:

The response from the CreateEvaluation service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

IdempotentParameterMismatchException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

deleteRealtimeEndpoint

DeleteRealtimeEndpointResult deleteRealtimeEndpoint(DeleteRealtimeEndpointRequest deleteRealtimeEndpointRequest)
                                                    throws AmazonServiceException,
                                                           AmazonClientException

Deletes a real time endpoint of an MLModel .

Parameters:

deleteRealtimeEndpointRequest - Container for the necessary parameters to execute the DeleteRealtimeEndpoint service method on AmazonMachineLearning.

Returns:

The response from the DeleteRealtimeEndpoint service method, as returned by AmazonMachineLearning.

Throws:

ResourceNotFoundException

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeBatchPredictions

DescribeBatchPredictionsResult describeBatchPredictions()
                                                        throws AmazonServiceException,
                                                               AmazonClientException

Returns a list of BatchPrediction operations that match the search criteria in the request.

Returns:

The response from the DescribeBatchPredictions service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeDataSources

DescribeDataSourcesResult describeDataSources()
                                              throws AmazonServiceException,
                                                     AmazonClientException

Returns a list of DataSource that match the search criteria in the request.

Returns:

The response from the DescribeDataSources service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeMLModels

DescribeMLModelsResult describeMLModels()
                                        throws AmazonServiceException,
                                               AmazonClientException

Returns a list of MLModel that match the search criteria in the request.

Returns:

The response from the DescribeMLModels service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

describeEvaluations

DescribeEvaluationsResult describeEvaluations()
                                              throws AmazonServiceException,
                                                     AmazonClientException

Returns a list of DescribeEvaluations that match the search criteria in the request.

Returns:

The response from the DescribeEvaluations service method, as returned by AmazonMachineLearning.

Throws:

InvalidInputException

InternalServerException

AmazonClientException - If any internal errors are encountered inside the client while attempting to make the request or handle the response. For example if a network connection is not available.

AmazonServiceException - If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.

shutdown

void shutdown()

Shuts down this client object, releasing any resources that might be held open. This is an optional method, and callers are not expected to call it, but can if they want to explicitly release any open resources. Once a client has been shutdown, it should not be used to make any more requests.

getCachedResponseMetadata

ResponseMetadata getCachedResponseMetadata(AmazonWebServiceRequest request)

Returns additional metadata for a previously executed successful request, typically used for debugging issues where a service isn't acting as expected. This data isn't considered part of the result data returned by an operation, so it's available through this separate, diagnostic interface.

Response metadata is only cached for a limited period of time, so if you need to access this extra diagnostic information for an executed request, you should use this method to retrieve it as soon as possible after executing a request.

Parameters:

request - The originally executed request.

Returns:

The response metadata for the specified request, or null if none is available.