AWS SDK for C++  1.8.95
AWS SDK for C++
Public Member Functions | List of all members
Aws::Comprehend::Model::ClassifyDocumentResult Class Reference

#include <ClassifyDocumentResult.h>

Public Member Functions

 ClassifyDocumentResult ()
 
 ClassifyDocumentResult (const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &result)
 
ClassifyDocumentResultoperator= (const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &result)
 
const Aws::Vector< DocumentClass > & GetClasses () const
 
void SetClasses (const Aws::Vector< DocumentClass > &value)
 
void SetClasses (Aws::Vector< DocumentClass > &&value)
 
ClassifyDocumentResultWithClasses (const Aws::Vector< DocumentClass > &value)
 
ClassifyDocumentResultWithClasses (Aws::Vector< DocumentClass > &&value)
 
ClassifyDocumentResultAddClasses (const DocumentClass &value)
 
ClassifyDocumentResultAddClasses (DocumentClass &&value)
 
const Aws::Vector< DocumentLabel > & GetLabels () const
 
void SetLabels (const Aws::Vector< DocumentLabel > &value)
 
void SetLabels (Aws::Vector< DocumentLabel > &&value)
 
ClassifyDocumentResultWithLabels (const Aws::Vector< DocumentLabel > &value)
 
ClassifyDocumentResultWithLabels (Aws::Vector< DocumentLabel > &&value)
 
ClassifyDocumentResultAddLabels (const DocumentLabel &value)
 
ClassifyDocumentResultAddLabels (DocumentLabel &&value)
 

Detailed Description

Definition at line 29 of file ClassifyDocumentResult.h.

Constructor & Destructor Documentation

◆ ClassifyDocumentResult() [1/2]

Aws::Comprehend::Model::ClassifyDocumentResult::ClassifyDocumentResult ( )

◆ ClassifyDocumentResult() [2/2]

Aws::Comprehend::Model::ClassifyDocumentResult::ClassifyDocumentResult ( const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &  result)

Member Function Documentation

◆ AddClasses() [1/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::AddClasses ( const DocumentClass value)
inline

The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

Definition at line 83 of file ClassifyDocumentResult.h.

◆ AddClasses() [2/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::AddClasses ( DocumentClass &&  value)
inline

The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

Definition at line 91 of file ClassifyDocumentResult.h.

◆ AddLabels() [1/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::AddLabels ( const DocumentLabel value)
inline

The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Definition at line 146 of file ClassifyDocumentResult.h.

◆ AddLabels() [2/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::AddLabels ( DocumentLabel &&  value)
inline

The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Definition at line 155 of file ClassifyDocumentResult.h.

◆ GetClasses()

const Aws::Vector<DocumentClass>& Aws::Comprehend::Model::ClassifyDocumentResult::GetClasses ( ) const
inline

The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

Definition at line 43 of file ClassifyDocumentResult.h.

◆ GetLabels()

const Aws::Vector<DocumentLabel>& Aws::Comprehend::Model::ClassifyDocumentResult::GetLabels ( ) const
inline

The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Definition at line 101 of file ClassifyDocumentResult.h.

◆ operator=()

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::operator= ( const Aws::AmazonWebServiceResult< Aws::Utils::Json::JsonValue > &  result)

◆ SetClasses() [1/2]

void Aws::Comprehend::Model::ClassifyDocumentResult::SetClasses ( const Aws::Vector< DocumentClass > &  value)
inline

The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

Definition at line 51 of file ClassifyDocumentResult.h.

◆ SetClasses() [2/2]

void Aws::Comprehend::Model::ClassifyDocumentResult::SetClasses ( Aws::Vector< DocumentClass > &&  value)
inline

The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

Definition at line 59 of file ClassifyDocumentResult.h.

◆ SetLabels() [1/2]

void Aws::Comprehend::Model::ClassifyDocumentResult::SetLabels ( const Aws::Vector< DocumentLabel > &  value)
inline

The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Definition at line 110 of file ClassifyDocumentResult.h.

◆ SetLabels() [2/2]

void Aws::Comprehend::Model::ClassifyDocumentResult::SetLabels ( Aws::Vector< DocumentLabel > &&  value)
inline

The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Definition at line 119 of file ClassifyDocumentResult.h.

◆ WithClasses() [1/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::WithClasses ( const Aws::Vector< DocumentClass > &  value)
inline

The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

Definition at line 67 of file ClassifyDocumentResult.h.

◆ WithClasses() [2/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::WithClasses ( Aws::Vector< DocumentClass > &&  value)
inline

The classes used by the document being analyzed. These are used for multi-class trained models. Individual classes are mutually exclusive and each document is expected to have only a single class assigned to it. For example, an animal can be a dog or a cat, but not both at the same time.

Definition at line 75 of file ClassifyDocumentResult.h.

◆ WithLabels() [1/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::WithLabels ( const Aws::Vector< DocumentLabel > &  value)
inline

The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Definition at line 128 of file ClassifyDocumentResult.h.

◆ WithLabels() [2/2]

ClassifyDocumentResult& Aws::Comprehend::Model::ClassifyDocumentResult::WithLabels ( Aws::Vector< DocumentLabel > &&  value)
inline

The labels used the document being analyzed. These are used for multi-label trained models. Individual labels represent different categories that are related in some manner and are not mutually exclusive. For example, a movie can be just an action movie, or it can be an action movie, a science fiction movie, and a comedy, all at the same time.

Definition at line 137 of file ClassifyDocumentResult.h.


The documentation for this class was generated from the following file: