Struct ConfusionMatrix

pub struct ConfusionMatrix { /* private fields */ }

(Binary) Confusion Matrix.

Implementations

impl ConfusionMatrix

pub fn new(c: [f64; 4]) -> Self

Construct a new confusion matrix.

pub fn negative(&self) -> f64

Negative (N = TN + FP).

pub fn true_negative(&self) -> f64

True negative (TN).

pub fn false_negative(&self) -> f64

False negative (FN).

pub fn true_negative_rate(&self) -> f64

True negative rate, i.e. specificity (TNR = TN / N).

pub fn false_negative_rate(&self) -> f64

False negative rate, i.e. miss-rate (FNR = FN / P).

pub fn negative_predictive_value(&self) -> f64

Negative predictive values (NPV = TN / (TN + FN)).

pub fn false_omission_rate(&self) -> f64

False omission rate (FOR = FN / (FN + TN)).

pub fn positive(&self) -> f64

Positive (P = TP + FN).

pub fn true_positive(&self) -> f64

True positive (TP).

pub fn false_positive(&self) -> f64

False positive (FP).

pub fn true_positive_rate(&self) -> f64

True positive rate, i.e. sensitivity, recall, hit-rate (TPR = TP / P).

pub fn false_positive_rate(&self) -> f64

False positive rate, i.e. fall-out (FPR = FN / N).

pub fn positive_predictive_value(&self) -> f64

Positive predictive value, i.e. precision (PPV = TP / (TP + FP)).

pub fn false_discovery_rate(&self) -> f64

False discovery rate (FDR = FP / (FP + TP)).

pub fn accuracy(&self) -> f64

Accuracy (A = (TP + TN) / (P + N)).

pub fn balanced_accuracy(&self) -> f64

Balanced accuracy (BA = (TPR + TNR) / 2).

pub fn f1_score(&self) -> f64

F1-Score (F1 = (2 * TP) / (2 * TP + FP + FN)).

Trait Implementations

impl Clone for ConfusionMatrix

fn clone(&self) -> ConfusionMatrix

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ConfusionMatrix

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

Formats the value using the given formatter.

impl Default for ConfusionMatrix

fn default() -> ConfusionMatrix

Returns the “default value” for a type.

impl Deref for ConfusionMatrix

type Target = [f64; 4]

The resulting type after dereferencing.

fn deref(&self) -> &Self::Target

Dereferences the value.

impl From<(DirectedDenseAdjacencyMatrixGraph, DirectedDenseAdjacencyMatrixGraph)> for ConfusionMatrix

fn from((true_graph, pred_graph): (DiGraph, DiGraph)) -> Self

Converts to this type from the input type.

impl<I, J> From<(I, J)> for ConfusionMatrix

where I: IntoIterator<Item = bool>, J: IntoIterator<Item = bool>,

fn from((true_class, pred_class): (I, J)) -> Self

Converts to this type from the input type.

impl From<(UndirectedDenseAdjacencyMatrixGraph, UndirectedDenseAdjacencyMatrixGraph)> for ConfusionMatrix

fn from((true_graph, pred_graph): (Graph, Graph)) -> Self

Converts to this type from the input type.

impl From<ConfusionMatrix> for [f64; 4]

fn from(other: ConfusionMatrix) -> Self

Converts to this type from the input type.

impl Copy for ConfusionMatrix