Struct BoxCox 

pub struct BoxCox { /* private fields */ }

A transformer that applies the Box-Cox transformation to each item.

The Box-Cox transformation is defined as:

• if lambda == 0: x.ln()
• otherwise: (x^lambda - 1) / lambda

By default the optimal lambda parameter is found from the data in transform using maximum likelihood estimation. If you want to use a specific lambda value, you can use the with_lambda method.

Note that unlike the scikit-learn implementation, this transform does not standardize the data after applying the transformation. This can be done by using the StandardScaler transformer inside a Pipeline.

Implementations

impl BoxCox

pub fn new() -> Self

Create a new BoxCox transformer.

pub fn with_lambda(self, lambda: f64) -> Result<Self, Error>

Set the lambda parameter for the Box-Cox transformation.

Errors

This function returns an error if the lambda parameter is NaN.

pub fn ignore_nans(self, ignore_nans: bool) -> Self

Set whether to ignore NaN values when calculating the transform.

If true, NaN values will be ignored when calculating the optimal lambda and simply passed through the transform.

Defaults to false.

Trait Implementations

impl Clone for BoxCox

fn clone(&self) -> BoxCox

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for BoxCox

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

Formats the value using the given formatter.

impl Default for BoxCox

fn default() -> Self

Returns the “default value” for a type.

impl Transformer for BoxCox

fn fit(&mut self, data: &[f64]) -> Result<(), Error>

Fit the transformation to the given time series.

fn transform(&self, data: &mut [f64]) -> Result<(), Error>

Apply the transformation to the given time series.

fn inverse_transform(&self, data: &mut [f64]) -> Result<(), Error>

Apply the inverse transformation to the given time series.

fn fit_transform(&mut self, data: &mut [f64]) -> Result<(), Error>

Fit the transformation to the given time series and then apply it.

fn boxed(self) -> Box<dyn Transformer>

where Self: Sized + 'static,

Create a boxed version of the transformation.