Struct Normalizer 

#[non_exhaustive]
pub struct Normalizer { /* private fields */ }

Normalize samples individually to unit norm.

Each sample (row) is scaled independently so that its chosen norm equals 1.0. This is useful for text classification or clustering where the direction of the feature vector matters more than magnitude.

fit() is a no-op — normalizer is stateless.

Example

let mut norm = Normalizer::new(Norm::L2);
norm.transform(&mut ds)?;

Implementations

impl Normalizer

pub fn new(norm: Norm) -> Self

Create a normalizer with the given norm type.

pub fn l2() -> Self

Create a normalizer with L2 norm (default).

Trait Implementations

impl Clone for Normalizer

fn clone(&self) -> Normalizer

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for Normalizer

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

Formats the value using the given formatter.

impl Default for Normalizer

fn default() -> Self

Returns the “default value” for a type.

impl Transformer for Normalizer

fn fit(&mut self, data: &Dataset) -> Result<()>

Learn parameters from the training data.

fn transform(&self, data: &mut Dataset) -> Result<()>

Apply the learned transformation to a dataset (in-place).

fn inverse_transform(&self, _data: &mut Dataset) -> Result<()>

Reverse the transformation (if invertible).

fn fit_transform(&mut self, data: &mut Dataset) -> Result<()>

Convenience: fit + transform in one call.