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
.
See https://www.paws-r-sdk.com/docs/machinelearning_create_evaluation/ for full documentation.
machinelearning_create_evaluation(
EvaluationId,
EvaluationName = NULL,
MLModelId,
EvaluationDataSourceId
)
[required] A user-supplied ID that uniquely identifies the Evaluation
.
A user-supplied name or description of the Evaluation
.
[required] The ID of the MLModel
to evaluate.
The schema used in creating the MLModel
must match the schema of the
DataSource
used in the Evaluation
.
[required] The ID of the DataSource
for the evaluation. The schema of the
DataSource
must match the schema used to create the MLModel
.