:doc:`MachineLearning <../../machinelearning>` / Client / update_ml_model

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update_ml_model
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.. py:method:: MachineLearning.Client.update_ml_model(**kwargs)

  

  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 <https://docs.aws.amazon.com/goto/WebAPI/machinelearning-2014-12-12/UpdateMLModel>`_  


  **Request Syntax**
  ::

    response = client.update_ml_model(
        MLModelId='string',
        MLModelName='string',
        ScoreThreshold=...
    )
    
  :type MLModelId: string
  :param MLModelId: **[REQUIRED]** 

    The ID assigned to the ``MLModel`` during creation.

    

  
  :type MLModelName: string
  :param MLModelName: 

    A user-supplied name or description of the ``MLModel``.

    

  
  :type ScoreThreshold: float
  :param ScoreThreshold: 

    The ``ScoreThreshold`` used in binary classification ``MLModel`` that marks the boundary between a positive prediction and a negative prediction.

     

    Output values greater than or equal to the ``ScoreThreshold`` receive a positive result from the ``MLModel``, such as ``true``. Output values less than the ``ScoreThreshold`` receive a negative response from the ``MLModel``, such as ``false``.

    

  
  
  :rtype: dict
  :returns: 
    
    **Response Syntax**

    
    ::

      {
          'MLModelId': 'string'
      }
      
    **Response Structure**

    

    - *(dict) --* 

      Represents the output of an ``UpdateMLModel`` operation.

       

      You can see the updated content by using the ``GetMLModel`` operation.

      
      

      - **MLModelId** *(string) --* 

        The ID assigned to the ``MLModel`` during creation. This value should be identical to the value of the ``MLModelID`` in the request.

        
  
  **Exceptions**
  
  *   :py:class:`MachineLearning.Client.exceptions.InvalidInputException`

  
  *   :py:class:`MachineLearning.Client.exceptions.ResourceNotFoundException`

  
  *   :py:class:`MachineLearning.Client.exceptions.InternalServerException`

  