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[ aws . machinelearning ]

predict

Description

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

Synopsis

  predict
--ml-model-id <value>
--record <value>
--predict-endpoint <value>
[--cli-input-json <value>]
[--generate-cli-skeleton <value>]
[--debug]
[--endpoint-url <value>]
[--no-verify-ssl]
[--no-paginate]
[--output <value>]
[--query <value>]
[--profile <value>]
[--region <value>]
[--version <value>]
[--color <value>]
[--no-sign-request]
[--ca-bundle <value>]
[--cli-read-timeout <value>]
[--cli-connect-timeout <value>]

Options

--ml-model-id (string)

A unique identifier of the MLModel .

--record (map)

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

key -> (string)

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

value -> (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.

Shorthand Syntax:

KeyName1=string,KeyName2=string

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. It is not possible to pass arbitrary binary values using a JSON-provided value as the string will be taken literally.

--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.

Global Options

--debug (boolean)

Turn on debug logging.

--endpoint-url (string)

Override command's default URL with the given URL.

--no-verify-ssl (boolean)

By default, the AWS CLI uses SSL when communicating with AWS services. For each SSL connection, the AWS CLI will verify SSL certificates. This option overrides the default behavior of verifying SSL certificates.

--no-paginate (boolean)

Disable automatic pagination. If automatic pagination is disabled, the AWS CLI will only make one call, for the first page of results.

--output (string)

The formatting style for command output.

• json
• text
• table

--query (string)

A JMESPath query to use in filtering the response data.

--profile (string)

Use a specific profile from your credential file.

--region (string)

The region to use. Overrides config/env settings.

--version (string)

Display the version of this tool.

--color (string)

Turn on/off color output.

• on
• off
• auto

--no-sign-request (boolean)

Do not sign requests. Credentials will not be loaded if this argument is provided.

--ca-bundle (string)

The CA certificate bundle to use when verifying SSL certificates. Overrides config/env settings.

--cli-read-timeout (int)

The maximum socket read time in seconds. If the value is set to 0, the socket read will be blocking and not timeout. The default value is 60 seconds.

--cli-connect-timeout (int)

The maximum socket connect time in seconds. If the value is set to 0, the socket connect will be blocking and not timeout. The default value is 60 seconds.

Output

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)