Struct rusty_machine::data::transforms::minmax::MinMaxFitter

pub struct MinMaxFitter<T: Float> { /* private fields */ }

A builder used to construct a MinMaxScaler

Implementations

impl<T: Float> MinMaxFitter<T>

pub fn new(min: T, max: T) -> Self

Construct a new MinMaxFitter with specified mean and standard deviation.

Note that this function does not create a Transformer only a builder which can be used to produce a fitted Transformer.

Examples

use rusty_machine::data::transforms::MinMaxFitter;
use rusty_machine::linalg::Matrix;

let fitter = MinMaxFitter::new(0.0, 1.0);

// We can call `fit` from the `transform::TransformFitter`
// trait to create a `MinMaxScaler` used to actually transform data.
use rusty_machine::data::transforms::TransformFitter;
let mat = Matrix::new(2,2,vec![1.0, 2.0, 3.0, 5.0]);
let transformer = fitter.fit(&mat);

Trait Implementations

impl<T: Debug + Float> Debug for MinMaxFitter<T>

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

Formats the value using the given formatter.

impl<T: Float> Default for MinMaxFitter<T>

fn default() -> Self

Returns the “default value” for a type.

impl<T: Float> TransformFitter<Matrix<T>, MinMaxScaler<T>> for MinMaxFitter<T>

fn fit(self, inputs: &Matrix<T>) -> LearningResult<MinMaxScaler<T>>

Fit the inputs to create the Transformer