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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.
Namespace: Amazon.MachineLearning
Assembly: AWSSDK.dll
Version: (assembly version)
public virtual CreateMLModelResponse CreateMLModel( CreateMLModelRequest request )
Container for the necessary parameters to execute the CreateMLModel service method.
Exception | Condition |
---|---|
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. |
InternalServerException | An error on the server occurred when trying to process a request. |
InvalidInputException | An error on the client occurred. Typically, the cause is an invalid input value. |
.NET Framework:
Supported in: 4.5, 4.0, 3.5