Struct PowerTransformer 

pub struct PowerTransformer {
    pub standardize: bool,
}

Parameters for PowerTransformer (unfitted state).

Applies a Yeo-Johnson power transform to each feature to make the data more Gaussian-like, then optionally standardizes to zero mean and unit variance.

The optimal lambda per feature is found via grid search (maximizing the log-likelihood of the resulting normal distribution).

Fields

standardize: bool

If true, standardize the transformed data to zero mean, unit variance.

Implementations

impl PowerTransformer

pub fn new() -> PowerTransformer

Create a new PowerTransformer with defaults (standardization enabled).

pub fn standardize(self, standardize: bool) -> PowerTransformer

Set whether to standardize after the power transform.

Trait Implementations

impl Clone for PowerTransformer

fn clone(&self) -> PowerTransformer

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for PowerTransformer

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

Formats the value using the given formatter.

impl Default for PowerTransformer

fn default() -> PowerTransformer

Returns the “default value” for a type.

impl<'de> Deserialize<'de> for PowerTransformer

fn deserialize<__D>( __deserializer: __D, ) -> Result<PowerTransformer, <__D as Deserializer<'de>>::Error>

where __D: Deserializer<'de>,

Deserialize this value from the given Serde deserializer.

impl<F> FitUnsupervised<F> for PowerTransformer

where F: Float,

type Fitted = FittedPowerTransformer<F>

fn fit( &self, x: &ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, ) -> Result<<PowerTransformer as FitUnsupervised<F>>::Fitted, RustMlError>

impl Serialize for PowerTransformer

fn serialize<__S>( &self, __serializer: __S, ) -> Result<<__S as Serializer>::Ok, <__S as Serializer>::Error>

where __S: Serializer,

Serialize this value into the given Serde serializer.