Struct rusty_machine::data::transforms::standardize::Standardizer

pub struct Standardizer<T: Float> { /* fields omitted */ }

The Standardizer

The Standardizer provides an implementation of Transformer which allows us to transform the input data to have a new mean and standard deviation.

See the module description for more information.

Methods

impl<T: Float> Standardizer<T>

fn new(mean: T, stdev: T) -> Standardizer<T>

Constructs a new Standardizer with the given mean and variance

Examples

use rusty_machine::data::transforms::Standardizer;

// Constructs a new `Standardizer` which will give the data
// mean `0` and standard deviation `2`.
let transformer = Standardizer::new(0.0, 2.0);

Trait Implementations

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

fn fmt(&self, __arg_0: &mut Formatter) -> Result

Formats the value using the given formatter.

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

Create a Standardizer with mean 0 and standard deviation 1.

fn default() -> Standardizer<T>

Returns the "default value" for a type.

impl<T: Float + FromPrimitive> Transformer<Matrix<T>> for Standardizer<T>

fn fit(&mut self, inputs: &Matrix<T>) -> Result<(), Error>

Fit Transformer to input data, and stores the transformation in the Transformer

fn transform(&mut self, inputs: Matrix<T>) -> Result<Matrix<T>, Error>

Transforms the inputs and stores the transformation in the Transformer

impl<T: Float + FromPrimitive> Invertible<Matrix<T>> for Standardizer<T>

fn inv_transform(&self, inputs: Matrix<T>) -> Result<Matrix<T>, Error>

Maps the inputs using the inverse of the fitted transform.