Struct ElasticNetRegularization 

pub struct ElasticNetRegularization {
    pub alpha: Float,
    pub l1_ratio: Float,
}

Elastic Net regularization: α * (ρ * ||w||₁ + (1-ρ)/2 * ||w||²₂)

Fields

alpha: Float

Total regularization strength

l1_ratio: Float

L1 ratio (ρ): 0 = Ridge, 1 = Lasso

Implementations

impl ElasticNetRegularization

pub fn new(alpha: Float, l1_ratio: Float) -> Result<Self>

Create a new Elastic Net regularization

pub fn l1_strength(&self) -> Float

Get the L1 regularization strength

pub fn l2_strength(&self) -> Float

Get the L2 regularization strength

Trait Implementations

impl Clone for ElasticNetRegularization

fn clone(&self) -> ElasticNetRegularization

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ElasticNetRegularization

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

Formats the value using the given formatter.

impl Regularization for ElasticNetRegularization

fn penalty(&self, coefficients: &Array1<Float>) -> Result<Float>

Compute the regularization penalty value

fn penalty_gradient( &self, coefficients: &Array1<Float>, ) -> Result<Array1<Float>>

Compute the regularization gradient (subgradient for non-smooth penalties)

fn proximal_operator( &self, coefficients: &Array1<Float>, step_size: Float, ) -> Result<Array1<Float>>

Apply the proximal operator (for proximal gradient methods)

fn is_non_smooth(&self) -> bool

Check if this regularization is non-smooth (requires proximal methods)

fn strength(&self) -> Float

Get the regularization strength

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

Get the name of this regularization