Struct NormScaler 

pub struct NormScaler { /* private fields */ }

Norm scaler: scales all samples in a dataset to have unit norm, according to the specified norm measure

Example

use linfa::traits::Transformer;
use linfa_preprocessing::norm_scaling::NormScaler;

// Load dataset
let dataset = linfa_datasets::diabetes();
// Initialize scaler
let scaler = NormScaler::l2();
// Scale dataset
let dataset = scaler.transform(dataset);

Implementations

impl NormScaler

pub fn l2() -> Self

Initializes a norm scaler that uses l2 norm

pub fn l1() -> Self

Initializes a norm scaler that uses l1 norm

pub fn max() -> Self

Initializes a norm scaler that uses max norm

Trait Implementations

impl Clone for NormScaler

fn clone(&self) -> NormScaler

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for NormScaler

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

Formats the value using the given formatter.

impl PartialEq for NormScaler

fn eq(&self, other: &NormScaler) -> 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 NormScaler

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

Scales all samples in the array of shape (nsamples, nfeatures) to have unit norm.

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 NormScaler

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

Substitutes the records of the dataset with their scaled versions with unit norm.

impl Eq for NormScaler

impl StructuralPartialEq for NormScaler