/** * Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. * SPDX-License-Identifier: Apache-2.0. */ #pragma once #include <aws/machinelearning/MachineLearning_EXPORTS.h> #include <aws/core/utils/memory/stl/AWSMap.h> #include <aws/core/utils/memory/stl/AWSString.h> #include <utility> namespace Aws { namespace Utils { namespace Json { class JsonValue; class JsonView; } // namespace Json } // namespace Utils namespace MachineLearning { namespace Model { /** * <p>Measurements of how well the <code>MLModel</code> performed on known * observations. One of the following metrics is returned, based on the type of the * <code>MLModel</code>: </p> <ul> <li> <p>BinaryAUC: The binary * <code>MLModel</code> uses the Area Under the Curve (AUC) technique to measure * performance. </p> </li> <li> <p>RegressionRMSE: The regression * <code>MLModel</code> uses the Root Mean Square Error (RMSE) technique to measure * performance. RMSE measures the difference between predicted and actual values * for a single variable.</p> </li> <li> <p>MulticlassAvgFScore: The multiclass * <code>MLModel</code> uses the F1 score technique to measure performance. </p> * </li> </ul> <p> For more information about performance metrics, please see the * <a href="https://docs.aws.amazon.com/machine-learning/latest/dg">Amazon Machine * Learning Developer Guide</a>. </p><p><h3>See Also:</h3> <a * href="http://docs.aws.amazon.com/goto/WebAPI/machinelearning-2014-12-12/PerformanceMetrics">AWS * API Reference</a></p> */ 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<Aws::String, Aws::String>& GetProperties() const{ return m_properties; } inline bool PropertiesHasBeenSet() const { return m_propertiesHasBeenSet; } inline void SetProperties(const Aws::Map<Aws::String, Aws::String>& value) { m_propertiesHasBeenSet = true; m_properties = value; } inline void SetProperties(Aws::Map<Aws::String, Aws::String>&& value) { m_propertiesHasBeenSet = true; m_properties = std::move(value); } inline PerformanceMetrics& WithProperties(const Aws::Map<Aws::String, Aws::String>& value) { SetProperties(value); return *this;} inline PerformanceMetrics& WithProperties(Aws::Map<Aws::String, Aws::String>&& 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<Aws::String, Aws::String> m_properties; bool m_propertiesHasBeenSet = false; }; } // namespace Model } // namespace MachineLearning } // namespace Aws