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   /*
    * Copyright 2010-2015 Amazon.com, Inc. or its affiliates. All Rights Reserved.
    * 
    * Licensed under the Apache License, Version 2.0 (the "License").
    * You may not use this file except in compliance with the License.
    * A copy of the License is located at
    * 
    *  http://aws.amazon.com/apache2.0
    * 
   * or in the "license" file accompanying this file. This file is distributed
   * on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either
   * express or implied. See the License for the specific language governing
   * permissions and limitations under the License.
   */
  package com.amazonaws.services.machinelearning;
  
  
  
Asynchronous client for accessing AmazonMachineLearning. All asynchronous calls made using this client are non-blocking. Callers could either process the result and handle the exceptions in the worker thread by providing a callback handler when making the call, or use the returned Future object to check the result of the call in the calling thread.

Definition of the public APIs exposed by Amazon Machine Learning

  
          implements AmazonMachineLearningAsync {

    
Executor service for executing asynchronous requests.
  
      private ExecutorService executorService;
  
      private static final int DEFAULT_THREAD_POOL_SIZE = 50;

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning. A credentials provider chain will be used that searches for credentials in this order:
  • Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_KEY
  • Java System Properties - aws.accessKeyId and aws.secretKey
  • Instance profile credentials delivered through the Amazon EC2 metadata service

All service calls made using this new client object are blocking, and will not return until the service call completes.

  
      public AmazonMachineLearningAsyncClient() {
          this(new DefaultAWSCredentialsProviderChain());
      }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning. A credentials provider chain will be used that searches for credentials in this order:
  • Environment Variables - AWS_ACCESS_KEY_ID and AWS_SECRET_KEY
  • Java System Properties - aws.accessKeyId and aws.secretKey
  • Instance profile credentials delivered through the Amazon EC2 metadata service

All service calls made using this new client object are blocking, and will not return until the service call completes.

Parameters:
clientConfiguration The client configuration options controlling how this client connects to AmazonMachineLearning (ex: proxy settings, retry counts, etc.).
See also:
com.amazonaws.auth.DefaultAWSCredentialsProviderChain
  
      public AmazonMachineLearningAsyncClient(ClientConfiguration clientConfiguration) {
          this(new DefaultAWSCredentialsProviderChain(), clientConfiguration, Executors.newFixedThreadPool(clientConfiguration.getMaxConnections()));
      }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning using the specified AWS account credentials. Default client settings will be used, and a fixed size thread pool will be created for executing the asynchronous tasks.

All calls made using this new client object are non-blocking, and will immediately return a Java Future object that the caller can later check to see if the service call has actually completed.

Parameters:
awsCredentials The AWS credentials (access key ID and secret key) to use when authenticating with AWS services.
 
     public AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials) {
         this(awsCredentials, Executors.newFixedThreadPool());
     }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning using the specified AWS account credentials and executor service. Default client settings will be used.

All calls made using this new client object are non-blocking, and will immediately return a Java Future object that the caller can later check to see if the service call has actually completed.

Parameters:
awsCredentials The AWS credentials (access key ID and secret key) to use when authenticating with AWS services.
executorService The executor service by which all asynchronous requests will be executed.
 
     public AmazonMachineLearningAsyncClient(AWSCredentials awsCredentialsExecutorService executorService) {
         super(awsCredentials);
         this. = executorService;
     }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning using the specified AWS account credentials, executor service, and client configuration options.

All calls made using this new client object are non-blocking, and will immediately return a Java Future object that the caller can later check to see if the service call has actually completed.

Parameters:
awsCredentials The AWS credentials (access key ID and secret key) to use when authenticating with AWS services.
clientConfiguration Client configuration options (ex: max retry limit, proxy settings, etc).
executorService The executor service by which all asynchronous requests will be executed.
 
     public AmazonMachineLearningAsyncClient(AWSCredentials awsCredentials,
                 ClientConfiguration clientConfigurationExecutorService executorService) {
         super(awsCredentialsclientConfiguration);
         this. = executorService;
     }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning using the specified AWS account credentials provider. Default client settings will be used, and a fixed size thread pool will be created for executing the asynchronous tasks.

All calls made using this new client object are non-blocking, and will immediately return a Java Future object that the caller can later check to see if the service call has actually completed.

Parameters:
awsCredentialsProvider The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
 
     public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider) {
         this(awsCredentialsProvider, Executors.newFixedThreadPool());
     }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning using the specified AWS account credentials provider and executor service. Default client settings will be used.

All calls made using this new client object are non-blocking, and will immediately return a Java Future object that the caller can later check to see if the service call has actually completed.

Parameters:
awsCredentialsProvider The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
executorService The executor service by which all asynchronous requests will be executed.
 
     public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProviderExecutorService executorService) {
         this(awsCredentialsProvidernew ClientConfiguration(), executorService);
     }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning using the specified AWS account credentials provider and client configuration options.

All calls made using this new client object are non-blocking, and will immediately return a Java Future object that the caller can later check to see if the service call has actually completed.

Parameters:
awsCredentialsProvider The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
clientConfiguration Client configuration options (ex: max retry limit, proxy settings, etc).
 
     public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider,
                 ClientConfiguration clientConfiguration) {
         this(awsCredentialsProviderclientConfiguration, Executors.newFixedThreadPool(clientConfiguration.getMaxConnections()));
     }

    
Constructs a new asynchronous client to invoke service methods on AmazonMachineLearning using the specified AWS account credentials provider, executor service, and client configuration options.

All calls made using this new client object are non-blocking, and will immediately return a Java Future object that the caller can later check to see if the service call has actually completed.

Parameters:
awsCredentialsProvider The AWS credentials provider which will provide credentials to authenticate requests with AWS services.
clientConfiguration Client configuration options (ex: max retry limit, proxy settings, etc).
executorService The executor service by which all asynchronous requests will be executed.
 
     public AmazonMachineLearningAsyncClient(AWSCredentialsProvider awsCredentialsProvider,
                 ClientConfiguration clientConfigurationExecutorService executorService) {
         super(awsCredentialsProviderclientConfiguration);
         this. = executorService;
     }

    
Returns the executor service used by this async client to execute requests.

Returns:
The executor service used by this async client to execute requests.
 
     public ExecutorService getExecutorService() {
         return ;
     }

    
Shuts down the client, releasing all managed resources. This includes forcibly terminating all pending asynchronous service calls. Clients who wish to give pending asynchronous service calls time to complete should call getExecutorService().shutdown() followed by getExecutorService().awaitTermination() prior to calling this method.
 
     @Override
     public void shutdown() {
         super.shutdown();
         .shutdownNow();
     }
            
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the UpdateEvaluation service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<UpdateEvaluationResultupdateEvaluationAsync(final UpdateEvaluationRequest updateEvaluationRequest
             throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<UpdateEvaluationResult>() {
             public UpdateEvaluationResult call() throws Exception {
                 return updateEvaluation(updateEvaluationRequest);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the UpdateEvaluation service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
             final UpdateEvaluationRequest updateEvaluationRequest,
             final AsyncHandler<UpdateEvaluationRequestUpdateEvaluationResultasyncHandler)
                     throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<UpdateEvaluationResult>() {
             public UpdateEvaluationResult call() throws Exception {
               UpdateEvaluationResult result;
                 try {
                 result = updateEvaluation(updateEvaluationRequest);
               } catch (Exception ex) {
                   asyncHandler.onError(ex);
             throw ex;
               }
               asyncHandler.onSuccess(updateEvaluationRequestresult);
                  return result;
         }
     });
     }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the CreateMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<CreateMLModelResultcreateMLModelAsync(final CreateMLModelRequest createMLModelRequest
             throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<CreateMLModelResult>() {
             public CreateMLModelResult call() throws Exception {
                 return createMLModel(createMLModelRequest);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the CreateMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
             final CreateMLModelRequest createMLModelRequest,
             final AsyncHandler<CreateMLModelRequestCreateMLModelResultasyncHandler)
                     throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<CreateMLModelResult>() {
             public CreateMLModelResult call() throws Exception {
               CreateMLModelResult result;
                 try {
                 result = createMLModel(createMLModelRequest);
               } catch (Exception ex) {
                   asyncHandler.onError(ex);
             throw ex;
               }
               asyncHandler.onSuccess(createMLModelRequestresult);
                  return result;
         }
     });
     }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the CreateRealtimeEndpoint service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<CreateRealtimeEndpointResultcreateRealtimeEndpointAsync(final CreateRealtimeEndpointRequest createRealtimeEndpointRequest
             throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<CreateRealtimeEndpointResult>() {
             public CreateRealtimeEndpointResult call() throws Exception {
                 return createRealtimeEndpoint(createRealtimeEndpointRequest);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the CreateRealtimeEndpoint service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
             final CreateRealtimeEndpointRequest createRealtimeEndpointRequest,
             final AsyncHandler<CreateRealtimeEndpointRequestCreateRealtimeEndpointResultasyncHandler)
                     throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<CreateRealtimeEndpointResult>() {
             public CreateRealtimeEndpointResult call() throws Exception {
               CreateRealtimeEndpointResult result;
                 try {
                 result = createRealtimeEndpoint(createRealtimeEndpointRequest);
               } catch (Exception ex) {
                   asyncHandler.onError(ex);
             throw ex;
               }
               asyncHandler.onSuccess(createRealtimeEndpointRequestresult);
                  return result;
         }
     });
     }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the CreateDataSourceFromS3 service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<CreateDataSourceFromS3ResultcreateDataSourceFromS3Async(final CreateDataSourceFromS3Request createDataSourceFromS3Request
             throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<CreateDataSourceFromS3Result>() {
             public CreateDataSourceFromS3Result call() throws Exception {
                 return createDataSourceFromS3(createDataSourceFromS3Request);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the CreateDataSourceFromS3 service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
             final CreateDataSourceFromS3Request createDataSourceFromS3Request,
             final AsyncHandler<CreateDataSourceFromS3RequestCreateDataSourceFromS3ResultasyncHandler)
                     throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<CreateDataSourceFromS3Result>() {
             public CreateDataSourceFromS3Result call() throws Exception {
               CreateDataSourceFromS3Result result;
                 try {
                 result = createDataSourceFromS3(createDataSourceFromS3Request);
               } catch (Exception ex) {
                   asyncHandler.onError(ex);
             throw ex;
               }
               asyncHandler.onSuccess(createDataSourceFromS3Requestresult);
                  return result;
         }
     });
     }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DeleteMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<DeleteMLModelResultdeleteMLModelAsync(final DeleteMLModelRequest deleteMLModelRequest
             throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<DeleteMLModelResult>() {
             public DeleteMLModelResult call() throws Exception {
                 return deleteMLModel(deleteMLModelRequest);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DeleteMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
             final DeleteMLModelRequest deleteMLModelRequest,
             final AsyncHandler<DeleteMLModelRequestDeleteMLModelResultasyncHandler)
                     throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<DeleteMLModelResult>() {
             public DeleteMLModelResult call() throws Exception {
               DeleteMLModelResult result;
                 try {
                 result = deleteMLModel(deleteMLModelRequest);
               } catch (Exception ex) {
                   asyncHandler.onError(ex);
             throw ex;
               }
               asyncHandler.onSuccess(deleteMLModelRequestresult);
                  return result;
         }
     });
     }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the Predict service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<PredictResultpredictAsync(final PredictRequest predictRequest
             throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<PredictResult>() {
             public PredictResult call() throws Exception {
                 return predict(predictRequest);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the Predict service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<PredictResultpredictAsync(
             final PredictRequest predictRequest,
             final AsyncHandler<PredictRequestPredictResultasyncHandler)
                     throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<PredictResult>() {
             public PredictResult call() throws Exception {
               PredictResult result;
                 try {
                 result = predict(predictRequest);
               } catch (Exception ex) {
                   asyncHandler.onError(ex);
             throw ex;
               }
               asyncHandler.onSuccess(predictRequestresult);
                  return result;
         }
     });
     }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DescribeBatchPredictions service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<DescribeBatchPredictionsResultdescribeBatchPredictionsAsync(final DescribeBatchPredictionsRequest describeBatchPredictionsRequest
             throws AmazonServiceExceptionAmazonClientException {
             public DescribeBatchPredictionsResult call() throws Exception {
                 return describeBatchPredictions(describeBatchPredictionsRequest);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DescribeBatchPredictions service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
             final DescribeBatchPredictionsRequest describeBatchPredictionsRequest,
             final AsyncHandler<DescribeBatchPredictionsRequestDescribeBatchPredictionsResultasyncHandler)
                     throws AmazonServiceExceptionAmazonClientException {
             public DescribeBatchPredictionsResult call() throws Exception {
               DescribeBatchPredictionsResult result;
                 try {
                 result = describeBatchPredictions(describeBatchPredictionsRequest);
               } catch (Exception ex) {
                   asyncHandler.onError(ex);
             throw ex;
               }
               asyncHandler.onSuccess(describeBatchPredictionsRequestresult);
                  return result;
         }
     });
     }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the GetEvaluation service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
 
     public Future<GetEvaluationResultgetEvaluationAsync(final GetEvaluationRequest getEvaluationRequest
             throws AmazonServiceExceptionAmazonClientException {
         return .submit(new Callable<GetEvaluationResult>() {
             public GetEvaluationResult call() throws Exception {
                 return getEvaluation(getEvaluationRequest);
         }
     });
     }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the GetEvaluation service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final GetEvaluationRequest getEvaluationRequest,
            final AsyncHandler<GetEvaluationRequestGetEvaluationResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<GetEvaluationResult>() {
            public GetEvaluationResult call() throws Exception {
              GetEvaluationResult result;
                try {
                result = getEvaluation(getEvaluationRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(getEvaluationRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the UpdateMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<UpdateMLModelResultupdateMLModelAsync(final UpdateMLModelRequest updateMLModelRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<UpdateMLModelResult>() {
            public UpdateMLModelResult call() throws Exception {
                return updateMLModel(updateMLModelRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the UpdateMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final UpdateMLModelRequest updateMLModelRequest,
            final AsyncHandler<UpdateMLModelRequestUpdateMLModelResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<UpdateMLModelResult>() {
            public UpdateMLModelResult call() throws Exception {
              UpdateMLModelResult result;
                try {
                result = updateMLModel(updateMLModelRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(updateMLModelRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the GetDataSource service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<GetDataSourceResultgetDataSourceAsync(final GetDataSourceRequest getDataSourceRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<GetDataSourceResult>() {
            public GetDataSourceResult call() throws Exception {
                return getDataSource(getDataSourceRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the GetDataSource service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final GetDataSourceRequest getDataSourceRequest,
            final AsyncHandler<GetDataSourceRequestGetDataSourceResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<GetDataSourceResult>() {
            public GetDataSourceResult call() throws Exception {
              GetDataSourceResult result;
                try {
                result = getDataSource(getDataSourceRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(getDataSourceRequestresult);
                 return result;
        }
    });
    }
    
    

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

Parameters:
describeDataSourcesRequest Container for the necessary parameters to execute the DescribeDataSources operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DescribeDataSources service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<DescribeDataSourcesResultdescribeDataSourcesAsync(final DescribeDataSourcesRequest describeDataSourcesRequest
            throws AmazonServiceExceptionAmazonClientException {
            public DescribeDataSourcesResult call() throws Exception {
                return describeDataSources(describeDataSourcesRequest);
        }
    });
    }

    

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

Parameters:
describeDataSourcesRequest Container for the necessary parameters to execute the DescribeDataSources operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DescribeDataSources service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final DescribeDataSourcesRequest describeDataSourcesRequest,
            final AsyncHandler<DescribeDataSourcesRequestDescribeDataSourcesResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
            public DescribeDataSourcesResult call() throws Exception {
              DescribeDataSourcesResult result;
                try {
                result = describeDataSources(describeDataSourcesRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(describeDataSourcesRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DeleteEvaluation service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<DeleteEvaluationResultdeleteEvaluationAsync(final DeleteEvaluationRequest deleteEvaluationRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<DeleteEvaluationResult>() {
            public DeleteEvaluationResult call() throws Exception {
                return deleteEvaluation(deleteEvaluationRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DeleteEvaluation service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final DeleteEvaluationRequest deleteEvaluationRequest,
            final AsyncHandler<DeleteEvaluationRequestDeleteEvaluationResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<DeleteEvaluationResult>() {
            public DeleteEvaluationResult call() throws Exception {
              DeleteEvaluationResult result;
                try {
                result = deleteEvaluation(deleteEvaluationRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(deleteEvaluationRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the UpdateBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<UpdateBatchPredictionResultupdateBatchPredictionAsync(final UpdateBatchPredictionRequest updateBatchPredictionRequest
            throws AmazonServiceExceptionAmazonClientException {
            public UpdateBatchPredictionResult call() throws Exception {
                return updateBatchPrediction(updateBatchPredictionRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the UpdateBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final UpdateBatchPredictionRequest updateBatchPredictionRequest,
            final AsyncHandler<UpdateBatchPredictionRequestUpdateBatchPredictionResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
            public UpdateBatchPredictionResult call() throws Exception {
              UpdateBatchPredictionResult result;
                try {
                result = updateBatchPrediction(updateBatchPredictionRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(updateBatchPredictionRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the CreateBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<CreateBatchPredictionResultcreateBatchPredictionAsync(final CreateBatchPredictionRequest createBatchPredictionRequest
            throws AmazonServiceExceptionAmazonClientException {
            public CreateBatchPredictionResult call() throws Exception {
                return createBatchPrediction(createBatchPredictionRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the CreateBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final CreateBatchPredictionRequest createBatchPredictionRequest,
            final AsyncHandler<CreateBatchPredictionRequestCreateBatchPredictionResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
            public CreateBatchPredictionResult call() throws Exception {
              CreateBatchPredictionResult result;
                try {
                result = createBatchPrediction(createBatchPredictionRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(createBatchPredictionRequestresult);
                 return result;
        }
    });
    }
    
    

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

Parameters:
describeMLModelsRequest Container for the necessary parameters to execute the DescribeMLModels operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DescribeMLModels service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<DescribeMLModelsResultdescribeMLModelsAsync(final DescribeMLModelsRequest describeMLModelsRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<DescribeMLModelsResult>() {
            public DescribeMLModelsResult call() throws Exception {
                return describeMLModels(describeMLModelsRequest);
        }
    });
    }

    

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

Parameters:
describeMLModelsRequest Container for the necessary parameters to execute the DescribeMLModels operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DescribeMLModels service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final DescribeMLModelsRequest describeMLModelsRequest,
            final AsyncHandler<DescribeMLModelsRequestDescribeMLModelsResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<DescribeMLModelsResult>() {
            public DescribeMLModelsResult call() throws Exception {
              DescribeMLModelsResult result;
                try {
                result = describeMLModels(describeMLModelsRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(describeMLModelsRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DeleteBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<DeleteBatchPredictionResultdeleteBatchPredictionAsync(final DeleteBatchPredictionRequest deleteBatchPredictionRequest
            throws AmazonServiceExceptionAmazonClientException {
            public DeleteBatchPredictionResult call() throws Exception {
                return deleteBatchPrediction(deleteBatchPredictionRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DeleteBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final DeleteBatchPredictionRequest deleteBatchPredictionRequest,
            final AsyncHandler<DeleteBatchPredictionRequestDeleteBatchPredictionResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
            public DeleteBatchPredictionResult call() throws Exception {
              DeleteBatchPredictionResult result;
                try {
                result = deleteBatchPrediction(deleteBatchPredictionRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(deleteBatchPredictionRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the UpdateDataSource service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<UpdateDataSourceResultupdateDataSourceAsync(final UpdateDataSourceRequest updateDataSourceRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<UpdateDataSourceResult>() {
            public UpdateDataSourceResult call() throws Exception {
                return updateDataSource(updateDataSourceRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the UpdateDataSource service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final UpdateDataSourceRequest updateDataSourceRequest,
            final AsyncHandler<UpdateDataSourceRequestUpdateDataSourceResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<UpdateDataSourceResult>() {
            public UpdateDataSourceResult call() throws Exception {
              UpdateDataSourceResult result;
                try {
                result = updateDataSource(updateDataSourceRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(updateDataSourceRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the CreateDataSourceFromRDS service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            throws AmazonServiceExceptionAmazonClientException {
            public CreateDataSourceFromRDSResult call() throws Exception {
                return createDataSourceFromRDS(createDataSourceFromRDSRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the CreateDataSourceFromRDS service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final CreateDataSourceFromRDSRequest createDataSourceFromRDSRequest,
            final AsyncHandler<CreateDataSourceFromRDSRequestCreateDataSourceFromRDSResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
            public CreateDataSourceFromRDSResult call() throws Exception {
              CreateDataSourceFromRDSResult result;
                try {
                result = createDataSourceFromRDS(createDataSourceFromRDSRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(createDataSourceFromRDSRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the CreateDataSourceFromRedshift service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            throws AmazonServiceExceptionAmazonClientException {
            public CreateDataSourceFromRedshiftResult call() throws Exception {
                return createDataSourceFromRedshift(createDataSourceFromRedshiftRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the CreateDataSourceFromRedshift service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final CreateDataSourceFromRedshiftRequest createDataSourceFromRedshiftRequest,
                    throws AmazonServiceExceptionAmazonClientException {
            public CreateDataSourceFromRedshiftResult call() throws Exception {
              CreateDataSourceFromRedshiftResult result;
                try {
                result = createDataSourceFromRedshift(createDataSourceFromRedshiftRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(createDataSourceFromRedshiftRequestresult);
                 return result;
        }
    });
    }
    
    

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

Parameters:
describeEvaluationsRequest Container for the necessary parameters to execute the DescribeEvaluations operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DescribeEvaluations service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<DescribeEvaluationsResultdescribeEvaluationsAsync(final DescribeEvaluationsRequest describeEvaluationsRequest
            throws AmazonServiceExceptionAmazonClientException {
            public DescribeEvaluationsResult call() throws Exception {
                return describeEvaluations(describeEvaluationsRequest);
        }
    });
    }

    

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

Parameters:
describeEvaluationsRequest Container for the necessary parameters to execute the DescribeEvaluations operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DescribeEvaluations service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final DescribeEvaluationsRequest describeEvaluationsRequest,
            final AsyncHandler<DescribeEvaluationsRequestDescribeEvaluationsResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
            public DescribeEvaluationsResult call() throws Exception {
              DescribeEvaluationsResult result;
                try {
                result = describeEvaluations(describeEvaluationsRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(describeEvaluationsRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the GetMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<GetMLModelResultgetMLModelAsync(final GetMLModelRequest getMLModelRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<GetMLModelResult>() {
            public GetMLModelResult call() throws Exception {
                return getMLModel(getMLModelRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the GetMLModel service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final GetMLModelRequest getMLModelRequest,
            final AsyncHandler<GetMLModelRequestGetMLModelResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<GetMLModelResult>() {
            public GetMLModelResult call() throws Exception {
              GetMLModelResult result;
                try {
                result = getMLModel(getMLModelRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(getMLModelRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the DeleteDataSource service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<DeleteDataSourceResultdeleteDataSourceAsync(final DeleteDataSourceRequest deleteDataSourceRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<DeleteDataSourceResult>() {
            public DeleteDataSourceResult call() throws Exception {
                return deleteDataSource(deleteDataSourceRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the DeleteDataSource service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final DeleteDataSourceRequest deleteDataSourceRequest,
            final AsyncHandler<DeleteDataSourceRequestDeleteDataSourceResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<DeleteDataSourceResult>() {
            public DeleteDataSourceResult call() throws Exception {
              DeleteDataSourceResult result;
                try {
                result = deleteDataSource(deleteDataSourceRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(deleteDataSourceRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the GetBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<GetBatchPredictionResultgetBatchPredictionAsync(final GetBatchPredictionRequest getBatchPredictionRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<GetBatchPredictionResult>() {
            public GetBatchPredictionResult call() throws Exception {
                return getBatchPrediction(getBatchPredictionRequest);
        }
    });
    }

    

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 operation on AmazonMachineLearning.
asyncHandler Asynchronous callback handler for events in the life-cycle of the request. Users could provide the implementation of the four callback methods in this interface to process the operation result or handle the exception.
Returns:
A Java Future object containing the response from the GetBatchPrediction service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
            final GetBatchPredictionRequest getBatchPredictionRequest,
            final AsyncHandler<GetBatchPredictionRequestGetBatchPredictionResultasyncHandler)
                    throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<GetBatchPredictionResult>() {
            public GetBatchPredictionResult call() throws Exception {
              GetBatchPredictionResult result;
                try {
                result = getBatchPrediction(getBatchPredictionRequest);
              } catch (Exception ex) {
                  asyncHandler.onError(ex);
            throw ex;
              }
              asyncHandler.onSuccess(getBatchPredictionRequestresult);
                 return result;
        }
    });
    }
    
    

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 operation on AmazonMachineLearning.
Returns:
A Java Future object containing the response from the CreateEvaluation service method, as returned by AmazonMachineLearning.
Throws:
com.amazonaws.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.
com.amazonaws.AmazonServiceException If an error response is returned by AmazonMachineLearning indicating either a problem with the data in the request, or a server side issue.
    public Future<CreateEvaluationResultcreateEvaluationAsync(final CreateEvaluationRequest createEvaluationRequest
            throws AmazonServiceExceptionAmazonClientException {
        return .submit(new Callable<CreateEvaluationResult>() {
            public CreateEvaluationResult call() throws Exception {
                return createEvaluation(createEvaluationRequest);
        }
    });
    }

    

Creates a new Evaluation of an MLModel . An MLModel is evaluated on a set of observations associated to a Data