/**
* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
* SPDX-License-Identifier: Apache-2.0.
*/
#pragma once
#include
#include
#include
#include
namespace Aws
{
namespace Utils
{
namespace Json
{
class JsonValue;
class JsonView;
} // namespace Json
} // namespace Utils
namespace MachineLearning
{
namespace Model
{
/**
* 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.
See Also:
AWS
* API Reference
*/
class PerformanceMetrics
{
public:
AWS_MACHINELEARNING_API PerformanceMetrics();
AWS_MACHINELEARNING_API PerformanceMetrics(Aws::Utils::Json::JsonView jsonValue);
AWS_MACHINELEARNING_API PerformanceMetrics& operator=(Aws::Utils::Json::JsonView jsonValue);
AWS_MACHINELEARNING_API Aws::Utils::Json::JsonValue Jsonize() const;
inline const Aws::Map& GetProperties() const{ return m_properties; }
inline bool PropertiesHasBeenSet() const { return m_propertiesHasBeenSet; }
inline void SetProperties(const Aws::Map& value) { m_propertiesHasBeenSet = true; m_properties = value; }
inline void SetProperties(Aws::Map&& value) { m_propertiesHasBeenSet = true; m_properties = std::move(value); }
inline PerformanceMetrics& WithProperties(const Aws::Map& value) { SetProperties(value); return *this;}
inline PerformanceMetrics& WithProperties(Aws::Map&& value) { SetProperties(std::move(value)); return *this;}
inline PerformanceMetrics& AddProperties(const Aws::String& key, const Aws::String& value) { m_propertiesHasBeenSet = true; m_properties.emplace(key, value); return *this; }
inline PerformanceMetrics& AddProperties(Aws::String&& key, const Aws::String& value) { m_propertiesHasBeenSet = true; m_properties.emplace(std::move(key), value); return *this; }
inline PerformanceMetrics& AddProperties(const Aws::String& key, Aws::String&& value) { m_propertiesHasBeenSet = true; m_properties.emplace(key, std::move(value)); return *this; }
inline PerformanceMetrics& AddProperties(Aws::String&& key, Aws::String&& value) { m_propertiesHasBeenSet = true; m_properties.emplace(std::move(key), std::move(value)); return *this; }
inline PerformanceMetrics& AddProperties(const char* key, Aws::String&& value) { m_propertiesHasBeenSet = true; m_properties.emplace(key, std::move(value)); return *this; }
inline PerformanceMetrics& AddProperties(Aws::String&& key, const char* value) { m_propertiesHasBeenSet = true; m_properties.emplace(std::move(key), value); return *this; }
inline PerformanceMetrics& AddProperties(const char* key, const char* value) { m_propertiesHasBeenSet = true; m_properties.emplace(key, value); return *this; }
private:
Aws::Map m_properties;
bool m_propertiesHasBeenSet = false;
};
} // namespace Model
} // namespace MachineLearning
} // namespace Aws