[ 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 to CreateEvaluation
, Amazon Machine Learning (Amazon ML) immediately returns and sets the evaluation status to PENDING
. After the Evaluation
is created and ready for use, Amazon ML sets the status to COMPLETED
.
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.
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.