Struct QuantileTransformer 

pub struct QuantileTransformer { /* private fields */ }

QuantileTransformer for non-linear transformations

This transformer transforms features to follow a uniform or normal distribution using quantiles information. This method reduces the impact of outliers.

Implementations

impl QuantileTransformer

pub fn new( n_quantiles: usize, outputdistribution: &str, clip: bool, ) -> Result<Self>

Creates a new QuantileTransformer

Arguments

• n_quantiles - Number of quantiles to estimate (default: 1000)
• output_distribution - Target distribution (‘uniform’ or ‘normal’)
• clip - Whether to clip transformed values

Returns

• A new QuantileTransformer instance

pub fn fit<S>(&mut self, x: &ArrayBase<S, Ix2>) -> Result<()>

where S: Data, S::Elem: Float + NumCast,

Fits the QuantileTransformer to the input data

Arguments

• x - The input data, shape (n_samples, n_features)

Returns

• Result<()> - Ok if successful, Err otherwise

pub fn transform<S>(&self, x: &ArrayBase<S, Ix2>) -> Result<Array2<f64>>

where S: Data, S::Elem: Float + NumCast,

Transforms the input data using the fitted QuantileTransformer

Arguments

• x - The input data, shape (n_samples, n_features)

Returns

• Result<Array2<f64>> - The transformed data

pub fn fit_transform<S>(&mut self, x: &ArrayBase<S, Ix2>) -> Result<Array2<f64>>

where S: Data, S::Elem: Float + NumCast,

Fits the QuantileTransformer to the input data and transforms it

Arguments

• x - The input data, shape (n_samples, n_features)

Returns

• Result<Array2<f64>> - The transformed data

pub fn quantiles(&self) -> Option<&Array2<f64>>

Returns the quantiles for each feature

Returns

• Option<&Array2<f64>> - The quantiles, shape (n_features, n_quantiles)