NAME
Paws::MachineLearning::PerformanceMetrics
USAGE
This class represents one of two things:
Arguments in a call to a service
Use the attributes of this class as arguments to methods. You shouldn't make instances of this class. Each attribute should be used as a named argument in the calls that expect this type of object.
As an example, if Att1 is expected to be a Paws::MachineLearning::PerformanceMetrics object:
$service_obj->Method(Att1 => { Properties => $value, ..., Properties => $value });
Results returned from an API call
Use accessors for each attribute. If Att1 is expected to be an Paws::MachineLearning::PerformanceMetrics object:
$result = $service_obj->Method(...);
$result->Att1->Properties
DESCRIPTION
Measurements of how well the MLModel
performed on known observations. One of the following metrics is returned, based on the type of the MLModel
:
BinaryAUC: The binary
MLModel
uses the Area Under the Curve (AUC) technique to measure performance.RegressionRMSE: The regression
MLModel
uses the Root Mean Square Error (RMSE) technique to measure performance. RMSE measures the difference between predicted and actual values for a single variable.MulticlassAvgFScore: The multiclass
MLModel
uses the F1 score technique to measure performance.
For more information about performance metrics, please see the Amazon Machine Learning Developer Guide (https://docs.aws.amazon.com/machine-learning/latest/dg).
ATTRIBUTES
Properties => Paws::MachineLearning::PerformanceMetricsProperties
SEE ALSO
This class forms part of Paws, describing an object used in Paws::MachineLearning
BUGS and CONTRIBUTIONS
The source code is located here: https://github.com/pplu/aws-sdk-perl
Please report bugs to: https://github.com/pplu/aws-sdk-perl/issues