[ aws . machinelearning ]
Generates a prediction for the observation using the specified ML Model
.
Note
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
See ‘aws help’ for descriptions of global parameters.
predict
--ml-model-id <value>
--record <value>
--predict-endpoint <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
[--cli-auto-prompt <value>]
--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
| --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.
--cli-auto-prompt
(boolean)
Automatically prompt for CLI input parameters.
See ‘aws help’ for descriptions of global parameters.
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 aBINARY
orMULTICLASS
MLModel
request.
PredictedScores
- Contains the raw classification score corresponding to each label.
PredictedValue
- Present for aREGRESSION
MLModel
request.predictedLabel -> (string)
The prediction label for either a
BINARY
orMULTICLASS
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 theMLModel
.Algorithm
- Indicates the algorithm that was used for theMLModel
.value -> (string)