Struct StratifiedKFold 

pub struct StratifiedKFold {
    pub n_splits: usize,
    pub shuffle: bool,
    pub random_seed: u64,
}

Stratified K-fold cross-validation.

Maintains class distribution in each fold (useful for imbalanced datasets).

Fields

n_splits: usize

Number of folds.

shuffle: bool

Whether to shuffle the data before splitting.

random_seed: u64

Random seed for shuffling.

Implementations

impl StratifiedKFold

pub fn new(n_splits: usize) -> TrainResult<Self>

Create a new stratified K-fold splitter.

Arguments

• n_splits - Number of folds (must be >= 2)

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

Set random seed for shuffling.

pub fn get_stratified_split( &self, fold: usize, labels: &[usize], ) -> TrainResult<(Vec<usize>, Vec<usize>)>

Get stratified split based on class labels.

Arguments

• fold - Fold index
• labels - Class labels for each sample

Trait Implementations

impl Clone for StratifiedKFold

fn clone(&self) -> StratifiedKFold

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl CrossValidationSplit for StratifiedKFold

fn num_splits(&self) -> usize

Get the number of splits.

fn get_split( &self, fold: usize, n_samples: usize, ) -> TrainResult<(Vec<usize>, Vec<usize>)>

Get the train/validation indices for a specific fold.

impl Debug for StratifiedKFold

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

Formats the value using the given formatter.