code: @Override
      public CreateEvaluationResult createEvaluation(CreateEvaluationRequest request) {
          request = beforeClientExecution(request);
          return executeCreateEvaluation(request);
      }
docs: <p>
  Creates a new <code>Evaluation</code> of an <code>MLModel</code>. An <code>MLModel</code> is evaluated on a set
  of observations associated to a <code>DataSource</code>. Like a <code>DataSource</code> for an
  <code>MLModel</code>, the <code>DataSource</code> for an <code>Evaluation</code> contains values for the
  <code>Target Variable</code>. The <code>Evaluation</code> compares the predicted result for each observation to
  the actual outcome and provides a summary so that you know how effective the <code>MLModel</code> functions on
  the test data. Evaluation generates a relevant performance metric, such as BinaryAUC, RegressionRMSE or
  MulticlassAvgFScore based on the corresponding <code>MLModelType</code>: <code>BINARY</code>,
  <code>REGRESSION</code> or <code>MULTICLASS</code>.
  </p>
  <p>
  <code>CreateEvaluation</code> is an asynchronous operation. In response to <code>CreateEvaluation</code>, Amazon
  Machine Learning (Amazon ML) immediately returns and sets the evaluation status to <code>PENDING</code>. After
  the <code>Evaluation</code> is created and ready for use, Amazon ML sets the status to <code>COMPLETED</code>.
  </p>
  <p>
  You can use the <code>GetEvaluation</code> operation to check progress of the evaluation during the creation
  operation.
  </p>
  
  @param createEvaluationRequest
  @return Result of the CreateEvaluation operation returned by the service.
  @throws InvalidInputException
  An error on the client occurred. Typically, the cause is an invalid input value.
  @throws InternalServerException
  An error on the server occurred when trying to process a request.
  @throws IdempotentParameterMismatchException
  A second request to use or change an object was not allowed. This can result from retrying a request
  using a parameter that was not present in the original request.
  @sample AmazonMachineLearning.CreateEvaluation