Table Of Contents


User Guide

First time using the AWS CLI? See the User Guide for help getting started.

[ aws . machinelearning ]



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



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


--ml-model-id <value>
--record <value>
--predict-endpoint <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]


--ml-model-id (string)

A unique identifier of the MLModel .

--record (map)

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

Shorthand Syntax:


JSON Syntax:

{"string": "string"

--predict-endpoint (string)

--cli-input-json (string) Performs service operation based on the JSON string provided. The JSON string follows the format provided by --generate-cli-skeleton. If other arguments are provided on the command line, the CLI values will override the JSON-provided values.

--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. If provided with the value output, it validates the command inputs and returns a sample output JSON for that command.


Prediction -> (structure)

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 -> (map)

Provides the raw classification score corresponding to each label.

key -> (string)

value -> (float)

details -> (map)

Provides any additional details regarding the prediction.

key -> (string)

Contains the key values of DetailsMap : PredictiveModelType - Indicates the type of the MLModel . Algorithm - Indicates the algorithm that was used for the MLModel .

value -> (string)