[ aws . machinelearning ]
Updates the MLModelName and the ScoreThreshold of an MLModel .
You can use the GetMLModel operation to view the contents of the updated data element.
See also: AWS API Documentation
See ‘aws help’ for descriptions of global parameters.
update-ml-model
--ml-model-id <value>
[--ml-model-name <value>]
[--score-threshold <value>]
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
--ml-model-id (string)
The ID assigned to the
MLModelduring creation.
--ml-model-name (string)
A user-supplied name or description of the
MLModel.
--score-threshold (float)
The
ScoreThresholdused in binary classificationMLModelthat marks the boundary between a positive prediction and a negative prediction.Output values greater than or equal to the
ScoreThresholdreceive a positive result from theMLModel, such astrue. Output values less than theScoreThresholdreceive a negative response from theMLModel, such asfalse.
--cli-input-json | --cli-input-yaml (string)
Reads arguments from the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, those values will override the JSON-provided values. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally. This may not be specified along with --cli-input-yaml.
--generate-cli-skeleton (string)
Prints a JSON skeleton to standard output without sending an API request. If provided with no value or the value input, prints a sample input JSON that can be used as an argument for --cli-input-json. Similarly, if provided yaml-input it will print a sample input YAML that can be used with --cli-input-yaml. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.
See ‘aws help’ for descriptions of global parameters.
MLModelId -> (string)
The ID assigned to the
MLModelduring creation. This value should be identical to the value of theMLModelIDin the request.