predict

MachineLearning.Client.predict(**kwargs)

Generates a prediction for the observation using the specified ML Model .

Note: Not all response parameters will be populated. Whether a response parameter is populated depends on the type of model requested.

See also: AWS API Documentation

Request Syntax

response = client.predict(
    MLModelId='string',
    Record={
        'string': 'string'
    },
    PredictEndpoint='string'
)
Parameters
  • MLModelId (string) --

    [REQUIRED]

    A unique identifier of the MLModel .

  • Record (dict) --

    [REQUIRED]

    A map of variable name-value pairs that represent an observation.

    • (string) --

      The name of a variable. Currently it's used to specify the name of the target value, label, weight, and tags.

      • (string) --

        The value of a variable. Currently it's used to specify values of the target value, weights, and tag variables and for filtering variable values.

  • PredictEndpoint (string) -- [REQUIRED]
Return type

dict

Returns

Response Syntax

{
    'Prediction': {
        'predictedLabel': 'string',
        'predictedValue': ...,
        'predictedScores': {
            'string': ...
        },
        'details': {
            'string': 'string'
        }
    }
}

Response Structure

  • (dict) --

    • Prediction (dict) --

      The output from a Predict operation:

      • Details - Contains the following attributes: DetailsAttributes.PREDICTIVE_MODEL_TYPE - REGRESSION | BINARY | MULTICLASS DetailsAttributes.ALGORITHM - SGD
      • PredictedLabel - Present for either a BINARY or MULTICLASS MLModel request.
      • PredictedScores - Contains the raw classification score corresponding to each label.
      • PredictedValue - Present for a REGRESSION MLModel request.
      • predictedLabel (string) --

        The prediction label for either a BINARY or MULTICLASS MLModel .

      • predictedValue (float) --

        The prediction value for REGRESSION MLModel .

      • predictedScores (dict) --

        Provides the raw classification score corresponding to each label.

        • (string) --
          • (float) --
      • details (dict) --

        Provides any additional details regarding the prediction.

        • (string) --

          Contains the key values of DetailsMap :

          • PredictiveModelType - Indicates the type of the MLModel .
          • Algorithm - Indicates the algorithm that was used for the MLModel .
          • (string) --

Exceptions

  • MachineLearning.Client.exceptions.InvalidInputException
  • MachineLearning.Client.exceptions.ResourceNotFoundException
  • MachineLearning.Client.exceptions.LimitExceededException
  • MachineLearning.Client.exceptions.InternalServerException
  • MachineLearning.Client.exceptions.PredictorNotMountedException