Create Evaluation
machinelearning_create_evaluation | R Documentation |
Creates a new Evaluation of an MLModel¶
Description¶
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
.
create_evaluation
is an asynchronous operation. In response to
create_evaluation
, 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 get_evaluation
operation to check progress of the
evaluation during the creation operation.
Usage¶
Arguments¶
EvaluationId
[required] A user-supplied ID that uniquely identifies the
Evaluation
.EvaluationName
A user-supplied name or description of the
Evaluation
.MLModelId
[required] The ID of the
MLModel
to evaluate.The schema used in creating the
MLModel
must match the schema of theDataSource
used in theEvaluation
.EvaluationDataSourceId
[required] The ID of the
DataSource
for the evaluation. The schema of theDataSource
must match the schema used to create theMLModel
.
Value¶
A list with the following syntax: