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.