pub struct ClassificationMetrics {
pub accuracy: f64,
pub precision: f64,
pub recall: f64,
pub f1_score: f64,
pub auc: f64,
pub confusion_matrix: Array2<f64>,
pub class_accuracies: Vec<f64>,
pub class_labels: Vec<String>,
pub average_loss: f64,
}
Expand description
Metrics for evaluating classification performance
Fields§
§accuracy: f64
Accuracy (ratio of correctly classified samples)
precision: f64
Precision (ratio of correctly predicted positive observations to the total predicted positives)
recall: f64
Recall (ratio of correctly predicted positive observations to all actual positives)
f1_score: f64
F1 score (harmonic mean of precision and recall)
auc: f64
Area under the ROC curve
confusion_matrix: Array2<f64>
Confusion matrix
class_accuracies: Vec<f64>
Per-class accuracy values
class_labels: Vec<String>
Class labels
average_loss: f64
Average loss value
Trait Implementations§
Source§impl Clone for ClassificationMetrics
impl Clone for ClassificationMetrics
Source§fn clone(&self) -> ClassificationMetrics
fn clone(&self) -> ClassificationMetrics
Returns a duplicate of the value. Read more
1.0.0 · Source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source
. Read moreAuto Trait Implementations§
impl Freeze for ClassificationMetrics
impl RefUnwindSafe for ClassificationMetrics
impl Send for ClassificationMetrics
impl Sync for ClassificationMetrics
impl Unpin for ClassificationMetrics
impl UnwindSafe for ClassificationMetrics
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
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fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more
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if into_left
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Converts
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impl<T> Pointable for T
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fn to_subset(&self) -> Option<SS>
The inverse inclusion map: attempts to construct
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Checks if
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Use with care! Same as
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fn from_subset(element: &SS) -> SP
The inclusion map: converts
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