Struct MinMaxScaler 

pub struct MinMaxScaler<F: Float> {
    pub data_min: Option<Array1<F>>,
    pub data_max: Option<Array1<F>>,
    pub feature_min: F,
    pub feature_max: F,
}

Scale features to a given range [feature_min, feature_max] (default [0, 1]).

X_scaled = (X - X_min) / (X_max - X_min) * (feature_max - feature_min) + feature_min

Example

use scirs2_core::preprocessing::MinMaxScaler;
use ndarray::array;

let data = array![[1.0, 10.0], [2.0, 20.0], [3.0, 30.0]];
let mut scaler = MinMaxScaler::<f64>::new(0.0, 1.0);
scaler.fit(&data).expect("fit failed");
let scaled = scaler.transform(&data).expect("transform failed");

Fields

data_min: Option<Array1<F>>

Per-feature minimum from training data

data_max: Option<Array1<F>>

Per-feature maximum from training data

feature_min: F

Target range minimum

feature_max: F

Target range maximum

Implementations

impl<F: Float + FromPrimitive + Debug + Display> MinMaxScaler<F>

pub fn new(feature_min: F, feature_max: F) -> Self

Create a new MinMaxScaler with target range [feature_min, feature_max].

pub fn unit_range() -> Self

Create a scaler mapping to [0, 1].

pub fn fit(&mut self, data: &Array2<F>) -> CoreResult<()>

Fit the scaler from data.

pub fn transform(&self, data: &Array2<F>) -> CoreResult<Array2<F>>

Transform data.

pub fn fit_transform(&mut self, data: &Array2<F>) -> CoreResult<Array2<F>>

Fit and transform.

pub fn inverse_transform(&self, data: &Array2<F>) -> CoreResult<Array2<F>>

Inverse transform.

Trait Implementations

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

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

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

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

Formats the value using the given formatter.