/** * 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