Struct RepeatedKFold 

pub struct RepeatedKFold { /* private fields */ }

Repeated K-Fold cross-validator

Repeats K-Fold n times with different randomization in each repetition. This provides more robust estimates by reducing the variance that comes from a single random split of the data.

Examples

use sklears_model_selection::{RepeatedKFold, CrossValidator};

let cv = RepeatedKFold::new(5, 3)  // 5-fold repeated 3 times
    .random_state(42);
let splits = cv.split(100, None);
assert_eq!(splits.len(), 15);  // 5 * 3 = 15 splits

Implementations

impl RepeatedKFold

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

Create a new RepeatedKFold 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 RepeatedKFold

fn clone(&self) -> RepeatedKFold

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl CrossValidator for RepeatedKFold

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 RepeatedKFold

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

Formats the value using the given formatter.