[ aws . machinelearning ]
Creates a new Evaluation
of an MLModel
. An MLModel
is evaluated on a set of observations associated to a DataSource
. Like a DataSource
for an MLModel
, the DataSource
for an Evaluation
contains values for the Target Variable
. The Evaluation
compares the predicted result for each observation to the actual outcome and provides a summary so that you know how effective the MLModel
functions on the test data. Evaluation generates a relevant performance metric, such as BinaryAUC, RegressionRMSE or MulticlassAvgFScore based on the corresponding MLModelType
: BINARY
, REGRESSION
or MULTICLASS
.
CreateEvaluation
is an asynchronous operation. In response toCreateEvaluation
, Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status toPENDING
. After theEvaluation
is created and ready for use, Amazon ML sets the status toCOMPLETED
.
You can use the GetEvaluation
operation to check progress of the evaluation during the creation operation.
See also: AWS API Documentation
See ‘aws help’ for descriptions of global parameters.
create-evaluation
--evaluation-id <value>
[--evaluation-name <value>]
--ml-model-id <value>
--evaluation-data-source-id <value>
[--cli-input-json | --cli-input-yaml]
[--generate-cli-skeleton <value>]
--evaluation-id
(string)
A user-supplied ID that uniquely identifies the
Evaluation
.
--evaluation-name
(string)
A user-supplied name or description of the
Evaluation
.
--ml-model-id
(string)
The ID of the
MLModel
to evaluate.The schema used in creating the
MLModel
must match the schema of theDataSource
used in theEvaluation
.
--evaluation-data-source-id
(string)
The ID of the
DataSource
for the evaluation. The schema of theDataSource
must match the schema used to create theMLModel
.
--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. The generated JSON skeleton is not stable between versions of the AWS CLI and there are no backwards compatibility guarantees in the JSON skeleton generated.
See ‘aws help’ for descriptions of global parameters.
EvaluationId -> (string)
The user-supplied ID that uniquely identifies the
Evaluation
. This value should be identical to the value of theEvaluationId
in the request.