Struct TrainedSequentialFeatureSelection 

pub struct TrainedSequentialFeatureSelection { /* private fields */ }

Trained Sequential Feature Selection model

Implementations

impl TrainedSequentialFeatureSelection

pub fn support(&self) -> &Array1<bool>

Get the support mask (selected features)

pub fn selection_path(&self) -> &[usize]

Get the selection path

pub fn scores(&self) -> &[Float]

Get the scores at each step

pub fn n_features(&self) -> usize

Get the number of selected features

pub fn get_support_indices(&self) -> Vec<usize>

Get the selected feature indices

pub fn estimator(&self) -> &LinearDiscriminantAnalysis<Trained>

Get the final trained estimator

Trait Implementations

impl Clone for TrainedSequentialFeatureSelection

fn clone(&self) -> TrainedSequentialFeatureSelection

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for TrainedSequentialFeatureSelection

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

Formats the value using the given formatter.

impl Predict<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<i32>, Dim<[usize; 1]>>> for TrainedSequentialFeatureSelection

fn predict(&self, x: &Array2<Float>) -> Result<Array1<i32>>

Make predictions on the provided data

fn predict_with_uncertainty( &self, x: &X, ) -> Result<(Output, UncertaintyMeasure), SklearsError>

Make predictions with confidence intervals

impl Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for TrainedSequentialFeatureSelection

fn transform(&self, x: &Array2<Float>) -> Result<Array2<Float>>

Transform the input data