170 lines
5.9 KiB
C++
170 lines
5.9 KiB
C++
/**
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* Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved.
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* SPDX-License-Identifier: Apache-2.0.
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*/
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#pragma once
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#include <aws/comprehend/Comprehend_EXPORTS.h>
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#include <aws/comprehend/model/ClassifierEvaluationMetrics.h>
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#include <utility>
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namespace Aws
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{
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namespace Utils
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{
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namespace Json
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{
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class JsonValue;
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class JsonView;
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} // namespace Json
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} // namespace Utils
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namespace Comprehend
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{
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namespace Model
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{
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/**
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* <p>Provides information about a document classifier.</p><p><h3>See Also:</h3>
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* <a
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* href="http://docs.aws.amazon.com/goto/WebAPI/comprehend-2017-11-27/ClassifierMetadata">AWS
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* API Reference</a></p>
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*/
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class AWS_COMPREHEND_API ClassifierMetadata
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{
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public:
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ClassifierMetadata();
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ClassifierMetadata(Aws::Utils::Json::JsonView jsonValue);
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ClassifierMetadata& operator=(Aws::Utils::Json::JsonView jsonValue);
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Aws::Utils::Json::JsonValue Jsonize() const;
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/**
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* <p>The number of labels in the input data. </p>
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*/
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inline int GetNumberOfLabels() const{ return m_numberOfLabels; }
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/**
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* <p>The number of labels in the input data. </p>
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*/
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inline bool NumberOfLabelsHasBeenSet() const { return m_numberOfLabelsHasBeenSet; }
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/**
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* <p>The number of labels in the input data. </p>
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*/
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inline void SetNumberOfLabels(int value) { m_numberOfLabelsHasBeenSet = true; m_numberOfLabels = value; }
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/**
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* <p>The number of labels in the input data. </p>
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*/
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inline ClassifierMetadata& WithNumberOfLabels(int value) { SetNumberOfLabels(value); return *this;}
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/**
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* <p>The number of documents in the input data that were used to train the
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* classifier. Typically this is 80 to 90 percent of the input documents.</p>
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*/
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inline int GetNumberOfTrainedDocuments() const{ return m_numberOfTrainedDocuments; }
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/**
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* <p>The number of documents in the input data that were used to train the
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* classifier. Typically this is 80 to 90 percent of the input documents.</p>
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*/
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inline bool NumberOfTrainedDocumentsHasBeenSet() const { return m_numberOfTrainedDocumentsHasBeenSet; }
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/**
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* <p>The number of documents in the input data that were used to train the
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* classifier. Typically this is 80 to 90 percent of the input documents.</p>
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*/
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inline void SetNumberOfTrainedDocuments(int value) { m_numberOfTrainedDocumentsHasBeenSet = true; m_numberOfTrainedDocuments = value; }
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/**
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* <p>The number of documents in the input data that were used to train the
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* classifier. Typically this is 80 to 90 percent of the input documents.</p>
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*/
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inline ClassifierMetadata& WithNumberOfTrainedDocuments(int value) { SetNumberOfTrainedDocuments(value); return *this;}
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/**
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* <p>The number of documents in the input data that were used to test the
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* classifier. Typically this is 10 to 20 percent of the input documents, up to
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* 10,000 documents.</p>
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*/
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inline int GetNumberOfTestDocuments() const{ return m_numberOfTestDocuments; }
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/**
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* <p>The number of documents in the input data that were used to test the
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* classifier. Typically this is 10 to 20 percent of the input documents, up to
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* 10,000 documents.</p>
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*/
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inline bool NumberOfTestDocumentsHasBeenSet() const { return m_numberOfTestDocumentsHasBeenSet; }
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/**
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* <p>The number of documents in the input data that were used to test the
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* classifier. Typically this is 10 to 20 percent of the input documents, up to
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* 10,000 documents.</p>
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*/
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inline void SetNumberOfTestDocuments(int value) { m_numberOfTestDocumentsHasBeenSet = true; m_numberOfTestDocuments = value; }
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/**
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* <p>The number of documents in the input data that were used to test the
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* classifier. Typically this is 10 to 20 percent of the input documents, up to
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* 10,000 documents.</p>
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*/
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inline ClassifierMetadata& WithNumberOfTestDocuments(int value) { SetNumberOfTestDocuments(value); return *this;}
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/**
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* <p> Describes the result metrics for the test data associated with an
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* documentation classifier.</p>
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*/
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inline const ClassifierEvaluationMetrics& GetEvaluationMetrics() const{ return m_evaluationMetrics; }
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/**
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* <p> Describes the result metrics for the test data associated with an
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* documentation classifier.</p>
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*/
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inline bool EvaluationMetricsHasBeenSet() const { return m_evaluationMetricsHasBeenSet; }
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/**
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* <p> Describes the result metrics for the test data associated with an
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* documentation classifier.</p>
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*/
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inline void SetEvaluationMetrics(const ClassifierEvaluationMetrics& value) { m_evaluationMetricsHasBeenSet = true; m_evaluationMetrics = value; }
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/**
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* <p> Describes the result metrics for the test data associated with an
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* documentation classifier.</p>
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*/
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inline void SetEvaluationMetrics(ClassifierEvaluationMetrics&& value) { m_evaluationMetricsHasBeenSet = true; m_evaluationMetrics = std::move(value); }
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/**
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* <p> Describes the result metrics for the test data associated with an
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* documentation classifier.</p>
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*/
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inline ClassifierMetadata& WithEvaluationMetrics(const ClassifierEvaluationMetrics& value) { SetEvaluationMetrics(value); return *this;}
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/**
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* <p> Describes the result metrics for the test data associated with an
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* documentation classifier.</p>
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*/
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inline ClassifierMetadata& WithEvaluationMetrics(ClassifierEvaluationMetrics&& value) { SetEvaluationMetrics(std::move(value)); return *this;}
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private:
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int m_numberOfLabels;
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bool m_numberOfLabelsHasBeenSet;
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int m_numberOfTrainedDocuments;
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bool m_numberOfTrainedDocumentsHasBeenSet;
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int m_numberOfTestDocuments;
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bool m_numberOfTestDocumentsHasBeenSet;
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ClassifierEvaluationMetrics m_evaluationMetrics;
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bool m_evaluationMetricsHasBeenSet;
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};
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} // namespace Model
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} // namespace Comprehend
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} // namespace Aws
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