Struct LassoLars 

pub struct LassoLars<F> {
    pub alpha: F,
    pub max_iter: usize,
    pub fit_intercept: bool,
}

Lasso-LARS: LARS with the Lasso constraint.

Like Lars, but features are removed from the active set when their coefficient crosses zero during the OLS update, enforcing an L1 penalty controlled by alpha.

Type Parameters

• F: The floating-point type (f32 or f64).

Fields

alpha: F

L1 regularization strength. Larger values produce sparser models.

max_iter: usize

Maximum number of forward steps.

fit_intercept: bool

Whether to fit an intercept (bias) term.

Implementations

impl<F: Float> LassoLars<F>

pub fn new() -> Self

Create a new LassoLars with default settings.

Defaults: alpha = 1.0, max_iter = 500, fit_intercept = true.

pub fn with_alpha(self, alpha: F) -> Self

Set the L1 regularization strength.

pub fn with_max_iter(self, max_iter: usize) -> Self

Set the maximum number of forward steps.

pub fn with_fit_intercept(self, fit_intercept: bool) -> Self

Set whether to fit an intercept term.

Trait Implementations

impl<F: Clone> Clone for LassoLars<F>

fn clone(&self) -> LassoLars<F>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F: Debug> Debug for LassoLars<F>

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

Formats the value using the given formatter.

impl<F: Float> Default for LassoLars<F>

fn default() -> Self

Returns the “default value” for a type.

impl<F: Float + Send + Sync + ScalarOperand + FromPrimitive + 'static> Fit<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<F>, Dim<[usize; 1]>>> for LassoLars<F>

fn fit( &self, x: &Array2<F>, y: &Array1<F>, ) -> Result<FittedLassoLars<F>, FerroError>

Fit the Lasso-LARS model.

Like LARS, but features whose coefficients cross zero during the OLS step are removed from the active set, enforcing an implicit L1 penalty. The iteration stops when the maximum absolute correlation with the residual drops below alpha.

Errors

• FerroError::ShapeMismatch — sample count mismatch.
• FerroError::InsufficientSamples — zero samples.
• FerroError::InvalidParameter — alpha is negative.

type Fitted = FittedLassoLars<F>

The fitted model type returned by fit.

type Error = FerroError

The error type returned by fit.

impl<F> PipelineEstimator<F> for LassoLars<F>

where F: Float + FromPrimitive + ScalarOperand + Send + Sync + 'static,

fn fit_pipeline( &self, x: &Array2<F>, y: &Array1<F>, ) -> Result<Box<dyn FittedPipelineEstimator<F>>, FerroError>

Fit this estimator on the given data.