Enum RegressionMetricKind 

pub enum RegressionMetricKind {
    Mse,
    Rmse,
    Mae,
    R2,
    Accuracy,
    BalancedAccuracy,
}

Variants

Mse

Rmse

Mae

R2

Accuracy

Classification accuracy: fraction of predictions whose label matches the target (integer label encoding, matched within 0.5). Meaningless on continuous regression targets (≈0) but always emitted so the host can score classification natively without a separate code path.

BalancedAccuracy

Balanced classification accuracy: the macro-average of per-class recall (mean over the classes present in y_true of correct_in_class / count_in_class), matching scikit-learn’s balanced_accuracy_score. This is nirs4all’s DEFAULT classification ranking metric (its _resolve_effective_metric returns balanced_accuracy for a classification candidate), so it must be emitted natively for the dag-ml engine to reproduce the legacy classification cv_best_score. On a class-collapsed predictor it can be far below plain accuracy; on a continuous regression target it is meaningless (≈ chance) but always emitted, like accuracy.

Implementations

impl RegressionMetricKind

pub fn name(self) -> &'static str

pub fn objective(self) -> MetricObjective

Trait Implementations

impl Clone for RegressionMetricKind

fn clone(&self) -> RegressionMetricKind

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Copy for RegressionMetricKind

impl Debug for RegressionMetricKind

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

Formats the value using the given formatter.

impl<'de> Deserialize<'de> for RegressionMetricKind

fn deserialize<__D>( __deserializer: __D, ) -> Result<RegressionMetricKind, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl Eq for RegressionMetricKind

impl Ord for RegressionMetricKind

fn cmp(&self, other: &RegressionMetricKind) -> Ordering

This method returns an Ordering between self and other.

fn max(self, other: Self) -> Self

where Self: Sized,

Compares and returns the maximum of two values.

fn min(self, other: Self) -> Self

where Self: Sized,

Compares and returns the minimum of two values.

fn clamp(self, min: Self, max: Self) -> Self

where Self: Sized,

Restrict a value to a certain interval.

impl PartialEq for RegressionMetricKind

fn eq(&self, other: &RegressionMetricKind) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl PartialOrd for RegressionMetricKind

fn partial_cmp(&self, other: &RegressionMetricKind) -> Option<Ordering>

This method returns an ordering between self and other values if one exists.

fn lt(&self, other: &Rhs) -> bool

Tests less than (for self and other) and is used by the < operator.

fn le(&self, other: &Rhs) -> bool

Tests less than or equal to (for self and other) and is used by the <= operator.

fn gt(&self, other: &Rhs) -> bool

Tests greater than (for self and other) and is used by the > operator.

fn ge(&self, other: &Rhs) -> bool

Tests greater than or equal to (for self and other) and is used by the >= operator.

impl Serialize for RegressionMetricKind

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

where __S: Serializer,

Serialize this value into the given Serde serializer.

impl StructuralPartialEq for RegressionMetricKind