Struct RepeatedStratifiedKFold 

pub struct RepeatedStratifiedKFold { /* private fields */ }

Repeated Stratified K-Fold cross-validator

Repeats Stratified K-Fold n times with different randomization in each repetition. This provides more robust estimates while maintaining the class distribution in each fold. This is particularly useful for imbalanced datasets where you want both stratification and robust estimates.

Examples

use sklears_model_selection::{RepeatedStratifiedKFold, CrossValidator};
use scirs2_core::ndarray::array;

let cv = RepeatedStratifiedKFold::new(2, 2)  // 2-fold repeated 2 times
    .random_state(42);
let y = array![0, 0, 1, 1, 2, 2];
let splits = cv.split(6, Some(&y));
assert_eq!(splits.len(), 4);  // 2 * 2 = 4 splits

Implementations

impl RepeatedStratifiedKFold

pub fn new(n_splits: usize, n_repeats: usize) -> Self

Create a new RepeatedStratifiedKFold cross-validator

Arguments

• n_splits - Number of folds per repetition (must be >= 2)
• n_repeats - Number of repetitions (must be >= 1)

Panics

Panics if n_splits < 2 or n_repeats < 1

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

Set the random state for reproducible results

Arguments

• seed - Random seed value

pub fn n_splits_per_repeat(&self) -> usize

Get the number of splits per repetition

pub fn n_repeats(&self) -> usize

Get the number of repetitions

Trait Implementations

impl Clone for RepeatedStratifiedKFold

fn clone(&self) -> RepeatedStratifiedKFold

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl CrossValidator for RepeatedStratifiedKFold

fn n_splits(&self) -> usize

Returns the number of splits

fn split( &self, n_samples: usize, y: Option<&Array1<i32>>, ) -> Vec<(Vec<usize>, Vec<usize>)>

Generate train/test indices for cross-validation

impl Debug for RepeatedStratifiedKFold

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

Formats the value using the given formatter.