pub struct AggregateClassificationMetrics {
pub roc_auc: Option<f64>,
pub precision: Option<f64>,
pub f_1_score: Option<f64>,
pub accuracy: Option<f64>,
pub threshold: Option<f64>,
pub log_loss: Option<f64>,
pub recall: Option<f64>,
}
Fields§
§roc_auc: Option<f64>
Area Under a ROC Curve. For multiclass this is a macro-averaged metric.
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.
f_1_score: Option<f64>
The F1 score is an average of recall and precision. 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.
log_loss: Option<f64>
Logarithmic Loss. For multiclass this is a macro-averaged metric.
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.
Trait Implementations§
Source§impl Clone for AggregateClassificationMetrics
impl Clone for AggregateClassificationMetrics
Source§fn clone(&self) -> AggregateClassificationMetrics
fn clone(&self) -> AggregateClassificationMetrics
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moreSource§impl Default for AggregateClassificationMetrics
impl Default for AggregateClassificationMetrics
Source§fn default() -> AggregateClassificationMetrics
fn default() -> AggregateClassificationMetrics
Source§impl<'de> Deserialize<'de> for AggregateClassificationMetrics
impl<'de> Deserialize<'de> for AggregateClassificationMetrics
Source§fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error>where
__D: Deserializer<'de>,
Auto Trait Implementations§
impl Freeze for AggregateClassificationMetrics
impl RefUnwindSafe for AggregateClassificationMetrics
impl Send for AggregateClassificationMetrics
impl Sync for AggregateClassificationMetrics
impl Unpin for AggregateClassificationMetrics
impl UnwindSafe for AggregateClassificationMetrics
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T: ?Sized,
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T: ?Sized,
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T: Clone,
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fn into_request(self) -> Request<T>
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in a tonic::Request