Struct StratifiedRegressionKFold 

pub struct StratifiedRegressionKFold { /* private fields */ }

Stratified K-Fold cross-validation for regression tasks

This cross-validator stratifies continuous target values by binning them into quantiles and then performs stratified sampling based on these bins. This ensures that each fold has a representative distribution of target values, which is particularly useful for regression problems with non-uniform target distributions.

Implementations

impl StratifiedRegressionKFold

pub fn new(n_splits: usize) -> Self

Create a new StratifiedRegressionKFold cross-validator

pub fn n_bins(self, n_bins: usize) -> Self

Set the number of bins for stratifying continuous targets

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

Set whether to shuffle the data before splitting

pub fn random_state(self, seed: u64) -> Self

Set the random state for shuffling

Trait Implementations

impl Clone for StratifiedRegressionKFold

fn clone(&self) -> StratifiedRegressionKFold

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for StratifiedRegressionKFold

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

Formats the value using the given formatter.

impl RegressionCrossValidator for StratifiedRegressionKFold

fn n_splits(&self) -> usize

Returns the number of splits

fn split_regression( &self, n_samples: usize, y: &Array1<Float>, ) -> Vec<(Vec<usize>, Vec<usize>)>

Generate train/test indices for cross-validation with continuous targets