Struct FittedWhitener

pub struct FittedWhitener<F: Float> { /* private fields */ }

Struct that can be used to whiten data. Data will be scaled according to the whitening matrix learned during fitting. Obtained by fitting a Whitener.

Transforming the data used during fitting will yield a scaled data matrix with unit diagonal covariance matrix.

Example

use linfa::traits::{Fit, Transformer};
use linfa_preprocessing::whitening::Whitener;

// Load dataset
let dataset = linfa_datasets::diabetes();
// Learn whitening parameters
let whitener = Whitener::pca().fit(&dataset).unwrap();
// transform dataset according to whitening parameters
let dataset = whitener.transform(dataset);

Implementations

impl<F: Float> FittedWhitener<F>

pub fn transformation_matrix(&self) -> ArrayView2<'_, F>

The matrix used for scaling the data

pub fn mean(&self) -> ArrayView1<'_, F>

The means that will be subtracted to the features before scaling the data

Trait Implementations

impl<F: Clone + Float> Clone for FittedWhitener<F>

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

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F: Debug + Float> Debug for FittedWhitener<F>

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

Formats the value using the given formatter.

impl<F: PartialEq + Float> PartialEq for FittedWhitener<F>

fn eq(&self, other: &FittedWhitener<F>) -> bool

Tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

Tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<F: Float> Transformer<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for FittedWhitener<F>

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

impl<F: Float, D: Data<Elem = F>, T: AsTargets> Transformer<DatasetBase<ArrayBase<D, Dim<[usize; 2]>>, T>, DatasetBase<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, T>> for FittedWhitener<F>

fn transform( &self, x: DatasetBase<ArrayBase<D, Ix2>, T>, ) -> DatasetBase<Array2<F>, T>

impl<F: Eq + Float> Eq for FittedWhitener<F>

impl<F: Float> StructuralPartialEq for FittedWhitener<F>