Struct google_cloud_bigquery::http::model::AggregateClassificationMetrics

pub struct AggregateClassificationMetrics {
    pub precision: Option<f64>,
    pub recall: Option<f64>,
    pub accuracy: Option<f64>,
    pub threshold: Option<f64>,
    pub f1_score: Option<f64>,
    pub log_loss: Option<f64>,
    pub roc_auc: Option<f64>,
}

Fields

precision: Option<f64>

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.

recall: Option<f64>

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

accuracy: Option<f64>

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

threshold: Option<f64>

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.

f1_score: Option<f64>

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

log_loss: Option<f64>

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

roc_auc: Option<f64>

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

Trait Implementations

impl Clone for AggregateClassificationMetrics

fn clone(&self) -> AggregateClassificationMetrics

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl Debug for AggregateClassificationMetrics

fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter.

impl Default for AggregateClassificationMetrics

fn default() -> AggregateClassificationMetrics

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for AggregateClassificationMetrics

fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl PartialEq for AggregateClassificationMetrics

fn eq(&self, other: &AggregateClassificationMetrics) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl Serialize for AggregateClassificationMetrics

fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for AggregateClassificationMetrics