#include <aggregate_classification_metrics.h>

Inheritance diagram for google_bigquery_api::AggregateClassificationMetrics:

Public Member Functions
	AggregateClassificationMetrics (const Json::Value &storage)

	AggregateClassificationMetrics (Json::Value *storage)

virtual	~AggregateClassificationMetrics ()

const StringPiece	GetTypeName () const

bool	has_accuracy () const

void	clear_accuracy ()

double	get_accuracy () const

void	set_accuracy (double value)

bool	has_f1_score () const

void	clear_f1_score ()

double	get_f1_score () const

void	set_f1_score (double value)

bool	has_log_loss () const

void	clear_log_loss ()

double	get_log_loss () const

void	set_log_loss (double value)

bool	has_precision () const

void	clear_precision ()

double	get_precision () const

void	set_precision (double value)

bool	has_recall () const

void	clear_recall ()

double	get_recall () const

void	set_recall (double value)

bool	has_roc_auc () const

void	clear_roc_auc ()

double	get_roc_auc () const

void	set_roc_auc (double value)

bool	has_threshold () const

void	clear_threshold ()

double	get_threshold () const

void	set_threshold (double value)

Static Public Member Functions
static AggregateClassificationMetrics *	New ()

Detailed Description

Aggregate metrics for classification/classifier models. For multi-class models, the metrics are either macro-averaged or micro-averaged. When macro-averaged, the metrics are calculated for each label and then an unweighted average is taken of those values. When micro-averaged, the metric is calculated globally by counting the total number of correctly predicted rows.

Constructor & Destructor Documentation

◆ AggregateClassificationMetrics() [1/2]

google_bigquery_api::AggregateClassificationMetrics::AggregateClassificationMetrics ( const Json::Value & storage )

explicit

Standard constructor for an immutable data object instance.

Parameters

[in] storage The underlying data storage for this instance.

◆ AggregateClassificationMetrics() [2/2]

google_bigquery_api::AggregateClassificationMetrics::AggregateClassificationMetrics ( Json::Value * storage )

explicit

Standard constructor for a mutable data object instance.

Parameters

[in] storage The underlying data storage for this instance.

◆ ~AggregateClassificationMetrics()

google_bigquery_api::AggregateClassificationMetrics::~AggregateClassificationMetrics ( )

virtual

Standard destructor.

Member Function Documentation

◆ clear_accuracy()

void google_bigquery_api::AggregateClassificationMetrics::clear_accuracy ( )

inline

Clears the 'accuracy' attribute.

◆ clear_f1_score()

void google_bigquery_api::AggregateClassificationMetrics::clear_f1_score ( )

inline

Clears the 'f1Score' attribute.

◆ clear_log_loss()

void google_bigquery_api::AggregateClassificationMetrics::clear_log_loss ( )

inline

Clears the 'logLoss' attribute.

◆ clear_precision()

void google_bigquery_api::AggregateClassificationMetrics::clear_precision ( )

inline

Clears the 'precision' attribute.

◆ clear_recall()

void google_bigquery_api::AggregateClassificationMetrics::clear_recall ( )

inline

Clears the 'recall' attribute.

◆ clear_roc_auc()

void google_bigquery_api::AggregateClassificationMetrics::clear_roc_auc ( )

inline

Clears the 'rocAuc' attribute.

◆ clear_threshold()

void google_bigquery_api::AggregateClassificationMetrics::clear_threshold ( )

inline

Clears the 'threshold' attribute.

◆ get_accuracy()

double google_bigquery_api::AggregateClassificationMetrics::get_accuracy ( ) const

inline

Get the value of the 'accuracy' attribute.

◆ get_f1_score()

double google_bigquery_api::AggregateClassificationMetrics::get_f1_score ( ) const

inline

Get the value of the 'f1Score' attribute.

◆ get_log_loss()

double google_bigquery_api::AggregateClassificationMetrics::get_log_loss ( ) const

inline

Get the value of the 'logLoss' attribute.

◆ get_precision()

double google_bigquery_api::AggregateClassificationMetrics::get_precision ( ) const

inline

Get the value of the 'precision' attribute.

◆ get_recall()

double google_bigquery_api::AggregateClassificationMetrics::get_recall ( ) const

inline

Get the value of the 'recall' attribute.

◆ get_roc_auc()

double google_bigquery_api::AggregateClassificationMetrics::get_roc_auc ( ) const

inline

Get the value of the 'rocAuc' attribute.

◆ get_threshold()

double google_bigquery_api::AggregateClassificationMetrics::get_threshold ( ) const

inline

Get the value of the 'threshold' attribute.

◆ GetTypeName()

const StringPiece google_bigquery_api::AggregateClassificationMetrics::GetTypeName ( ) const

inline

Returns a string denoting the type of this data object.

Returns: google_bigquery_api::AggregateClassificationMetrics

◆ has_accuracy()

bool google_bigquery_api::AggregateClassificationMetrics::has_accuracy ( ) const

inline

Determine if the 'accuracy' attribute was set.

Returns: true if the 'accuracy' attribute was set.

◆ has_f1_score()

bool google_bigquery_api::AggregateClassificationMetrics::has_f1_score ( ) const

inline

Determine if the 'f1Score' attribute was set.

Returns: true if the 'f1Score' attribute was set.

◆ has_log_loss()

bool google_bigquery_api::AggregateClassificationMetrics::has_log_loss ( ) const

inline

Determine if the 'logLoss' attribute was set.

Returns: true if the 'logLoss' attribute was set.

◆ has_precision()

bool google_bigquery_api::AggregateClassificationMetrics::has_precision ( ) const

inline

Determine if the 'precision' attribute was set.

Returns: true if the 'precision' attribute was set.

◆ has_recall()

bool google_bigquery_api::AggregateClassificationMetrics::has_recall ( ) const

inline

Determine if the 'recall' attribute was set.

Returns: true if the 'recall' attribute was set.

◆ has_roc_auc()

bool google_bigquery_api::AggregateClassificationMetrics::has_roc_auc ( ) const

inline

Determine if the 'rocAuc' attribute was set.

Returns: true if the 'rocAuc' attribute was set.

◆ has_threshold()

bool google_bigquery_api::AggregateClassificationMetrics::has_threshold ( ) const

inline

Determine if the 'threshold' attribute was set.

Returns: true if the 'threshold' attribute was set.

◆ New()

AggregateClassificationMetrics * google_bigquery_api::AggregateClassificationMetrics::New ( )

static

Creates a new default instance.

Returns: Ownership is passed back to the caller.

◆ set_accuracy()

void google_bigquery_api::AggregateClassificationMetrics::set_accuracy ( double value )

inline

Change the 'accuracy' attribute.

Accuracy is the fraction of predictions given the correct label. For multiclass this is a micro-averaged metric.

Parameters

[in] value The new value.

◆ set_f1_score()

void google_bigquery_api::AggregateClassificationMetrics::set_f1_score ( double value )

inline

Change the 'f1Score' attribute.

The F1 score is an average of recall and precision. For multiclass this is a macro-averaged metric.

Parameters

[in] value The new value.

◆ set_log_loss()

void google_bigquery_api::AggregateClassificationMetrics::set_log_loss ( double value )

inline

Change the 'logLoss' attribute.

Logarithmic Loss. For multiclass this is a macro-averaged metric.

Parameters

[in] value The new value.

◆ set_precision()

void google_bigquery_api::AggregateClassificationMetrics::set_precision ( double value )

inline

Change the 'precision' attribute.

Precision is the fraction of actual positive predictions that had positive actual labels. For multiclass this is a macro-averaged metric treating each class as a binary classifier.

Parameters

[in] value The new value.

◆ set_recall()

void google_bigquery_api::AggregateClassificationMetrics::set_recall ( double value )

inline

Change the 'recall' attribute.

Recall is the fraction of actual positive labels that were given a positive prediction. For multiclass this is a macro-averaged metric.

Parameters

[in] value The new value.

◆ set_roc_auc()

void google_bigquery_api::AggregateClassificationMetrics::set_roc_auc ( double value )

inline

Change the 'rocAuc' attribute.

Area Under a ROC Curve. For multiclass this is a macro-averaged metric.

Parameters

[in] value The new value.

◆ set_threshold()

void google_bigquery_api::AggregateClassificationMetrics::set_threshold ( double value )

inline

Change the 'threshold' attribute.

Threshold at which the metrics are computed. For binary classification models this is the positive class threshold. For multi-class classfication models this is the confidence threshold.

Parameters

[in] value The new value.

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

google/bigquery_api/aggregate_classification_metrics.h
google/bigquery_api/aggregate_classification_metrics.cc

Public Member Functions

Static Public Member Functions

Detailed Description

Constructor & Destructor Documentation

◆ AggregateClassificationMetrics() [1/2]

◆ AggregateClassificationMetrics() [2/2]

◆ ~AggregateClassificationMetrics()

Member Function Documentation

◆ clear_accuracy()

◆ clear_f1_score()

◆ clear_log_loss()

◆ clear_precision()

◆ clear_recall()

◆ clear_roc_auc()

◆ clear_threshold()

◆ get_accuracy()

◆ get_f1_score()

◆ get_log_loss()

◆ get_precision()

◆ get_recall()

◆ get_roc_auc()

◆ get_threshold()

◆ GetTypeName()

◆ has_accuracy()

◆ has_f1_score()

◆ has_log_loss()

◆ has_precision()

◆ has_recall()

◆ has_roc_auc()

◆ has_threshold()

◆ New()

◆ set_accuracy()

◆ set_f1_score()

◆ set_log_loss()

◆ set_precision()

◆ set_recall()

◆ set_roc_auc()

◆ set_threshold()