Enum EnsembleStrategy 

pub enum EnsembleStrategy {
    MajorityVote,
    WeightedVote {
        weights: Vec<f64>,
    },
    MeanAveraging,
    WeightedAveraging {
        weights: Vec<f64>,
    },
    Stacking {
        meta_weights: Vec<f64>,
    },
}

Aggregation strategy used by the ensemble.

Variants

MajorityVote

Classification: argmax vote; ties broken by lowest class index.

WeightedVote

Classification: each model’s vote is multiplied by its weight. Weights are normalised internally; they need not sum to 1.

Fields

weights: Vec<f64>

MeanAveraging

Regression: arithmetic mean of outputs[0] across all models.

WeightedAveraging

Regression: weighted mean of outputs[0].

Fields

weights: Vec<f64>

Stacking

Linear combination of per-model outputs using meta_weights. Each model’s full outputs vector contributes to the final vector.

Fields

meta_weights: Vec<f64>

Trait Implementations

impl Clone for EnsembleStrategy

fn clone(&self) -> EnsembleStrategy

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for EnsembleStrategy

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

Formats the value using the given formatter.

impl PartialEq for EnsembleStrategy

fn eq(&self, other: &EnsembleStrategy) -> 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 StructuralPartialEq for EnsembleStrategy