Struct aws_sdk_frauddetector::types::TrainingMetrics
source · #[non_exhaustive]pub struct TrainingMetrics {
pub auc: Option<f32>,
pub metric_data_points: Option<Vec<MetricDataPoint>>,
}
Expand description
The training metric details.
Fields (Non-exhaustive)§
This struct is marked as non-exhaustive
Struct { .. }
syntax; cannot be matched against without a wildcard ..
; and struct update syntax will not work.auc: Option<f32>
The area under the curve. This summarizes true positive rate (TPR) and false positive rate (FPR) across all possible model score thresholds. A model with no predictive power has an AUC of 0.5, whereas a perfect model has a score of 1.0.
metric_data_points: Option<Vec<MetricDataPoint>>
The data points details.
Implementations§
source§impl TrainingMetrics
impl TrainingMetrics
sourcepub fn auc(&self) -> Option<f32>
pub fn auc(&self) -> Option<f32>
The area under the curve. This summarizes true positive rate (TPR) and false positive rate (FPR) across all possible model score thresholds. A model with no predictive power has an AUC of 0.5, whereas a perfect model has a score of 1.0.
sourcepub fn metric_data_points(&self) -> &[MetricDataPoint]
pub fn metric_data_points(&self) -> &[MetricDataPoint]
The data points details.
If no value was sent for this field, a default will be set. If you want to determine if no value was sent, use .metric_data_points.is_none()
.
source§impl TrainingMetrics
impl TrainingMetrics
sourcepub fn builder() -> TrainingMetricsBuilder
pub fn builder() -> TrainingMetricsBuilder
Creates a new builder-style object to manufacture TrainingMetrics
.
Trait Implementations§
source§impl Clone for TrainingMetrics
impl Clone for TrainingMetrics
source§fn clone(&self) -> TrainingMetrics
fn clone(&self) -> TrainingMetrics
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
source
. Read moresource§impl Debug for TrainingMetrics
impl Debug for TrainingMetrics
source§impl PartialEq for TrainingMetrics
impl PartialEq for TrainingMetrics
source§fn eq(&self, other: &TrainingMetrics) -> bool
fn eq(&self, other: &TrainingMetrics) -> bool
self
and other
values to be equal, and is used
by ==
.