Struct FittedMultiTaskElasticNetCV 

pub struct FittedMultiTaskElasticNetCV<F> { /* private fields */ }

Fitted multi-task ElasticNet model with cross-validated (alpha, l1_ratio).

Stores the selected hyperparameters, learned coefficient matrix (shape (n_tasks, n_features), the sklearn coef_ layout), and per-task intercept vector.

Implementations

impl<F: Float> FittedMultiTaskElasticNetCV<F>

pub fn alpha(&self) -> F

Returns the alpha value selected by cross-validation (sklearn alpha_).

pub fn l1_ratio(&self) -> F

Returns the l1_ratio selected by cross-validation (sklearn l1_ratio_).

pub fn coef(&self) -> &Array2<F>

Borrow the learned coefficient matrix, shape (n_tasks, n_features) (sklearn coef_).

pub fn intercept(&self) -> &Array1<F>

Borrow the per-task intercept vector, length n_tasks (sklearn intercept_).

Trait Implementations

impl<F: Clone> Clone for FittedMultiTaskElasticNetCV<F>

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F: Debug> Debug for FittedMultiTaskElasticNetCV<F>

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

Formats the value using the given formatter.

impl<F: Float + Send + Sync + ScalarOperand + 'static> Predict<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for FittedMultiTaskElasticNetCV<F>

fn predict(&self, x: &Array2<F>) -> Result<Array2<F>, FerroError>

Predict target values for the given feature matrix.

Computes X · coefᵀ + intercept (broadcast per task column), returning an (n_samples, n_tasks) array.

Errors

Returns FerroError::ShapeMismatch if the number of features does not match the fitted model.

type Output = ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>

The prediction output type (e.g., ndarray::Array1<F> or ndarray::Array1<usize>).

type Error = FerroError

The error type returned by predict.