Struct ClassificationMetrics 

pub struct ClassificationMetrics {
    pub accuracy: f64,
    pub precision: f64,
    pub recall: f64,
    pub f1_score: f64,
    pub auc_roc: f64,
    pub auc_pr: f64,
    pub mcc: f64,
}

Classification metrics for binary/multiclass tasks.

Fields

accuracy: f64

Accuracy (correct predictions / total).

precision: f64

Precision (true positives / predicted positives).

recall: f64

Recall (true positives / actual positives).

f1_score: f64

F1 score (harmonic mean of precision and recall).

auc_roc: f64

Area under ROC curve.

auc_pr: f64

Area under precision-recall curve.

mcc: f64

Matthews correlation coefficient.

Implementations

impl ClassificationMetrics

pub fn from_confusion(tp: u64, tn: u64, fp: u64, fn_: u64) -> Self

Create metrics from confusion matrix values.

Trait Implementations

impl Clone for ClassificationMetrics

fn clone(&self) -> ClassificationMetrics

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ClassificationMetrics

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

Formats the value using the given formatter.

impl Default for ClassificationMetrics

fn default() -> ClassificationMetrics

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for ClassificationMetrics

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

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Serialize for ClassificationMetrics

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

where __S: Serializer,

Serialize this value into the given Serde serializer.