Struct GridSearchRegressor 

pub struct GridSearchRegressor { /* private fields */ }

Grid search over regression learners, scored by the mean squared error of the held-out folds.

Implementations

impl GridSearchRegressor

pub fn new(candidates: Vec<Box<dyn Regressor>>) -> Self

candidates, e.g. the same learner with different hyperparameters.

pub fn cv(self, cv: usize) -> Self

Number of cross-validation folds (default 5).

pub fn best_index(&self) -> Option<usize>

Index of the chosen candidate after fitting.

pub fn cv_scores(&self) -> &[f64]

Cross-validated mean squared error of every candidate.

Trait Implementations

impl Clone for GridSearchRegressor

fn clone(&self) -> Self

An unfitted copy with the same candidates.

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

Performs copy-assignment from source.

impl Regressor for GridSearchRegressor

fn fit_weighted( &mut self, x: ArrayView2<'_, f64>, y: ArrayView1<'_, f64>, w: ArrayView1<'_, f64>, ) -> Result<()>

Candidates are fitted with the weights; folds are scored unweighted.

fn fit(&mut self, x: ArrayView2<'_, f64>, y: ArrayView1<'_, f64>) -> Result<()>

fn predict(&self, x: ArrayView2<'_, f64>) -> Result<Array1<f64>>

fn fresh(&self) -> Box<dyn Regressor>