Struct MinMaxScaler 

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

Scale features to a [0, 1] range.

Each feature is transformed as: x' = (x - min) / (max - min). Features with zero range are set to 0.

Implementations

impl MinMaxScaler

pub fn new() -> Self

Create a new unfitted scaler.

impl MinMaxScaler

pub fn fit_sparse(&mut self, features: &CscMatrix) -> Result<()>

Fit on sparse features.

Computes min/max from sparse columns, accounting for implicit zeros.

pub fn transform_sparse(&self, features: &CscMatrix) -> Result<CscMatrix>

Transform sparse features, returning a new CscMatrix.

Trait Implementations

impl Clone for MinMaxScaler

fn clone(&self) -> MinMaxScaler

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MinMaxScaler

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

Formats the value using the given formatter.

impl Default for MinMaxScaler

fn default() -> Self

Returns the “default value” for a type.

impl Transformer for MinMaxScaler

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.