Function fold_stability 

pub fn fold_stability<F, S1, S2, D>(
    x: &ArrayBase<S1, Ix2>,
    labels: &ArrayBase<S2, D>,
    n_folds: Option<usize>,
    fold_size: Option<f64>,
    random_seed: Option<u64>,
) -> Result<F>
where
    F: Float + NumCast + Debug + ScalarOperand + AddAssign + DivAssign,
    S1: Data<Elem = F>,
    S2: Data<Elem = usize>,
    D: Dimension,

Calculate fold stability of a clustering algorithm

Measures how stable a clustering is when applied to different subsets of data. Higher values indicate more robust clustering.

Arguments

• x - Array of shape (n_samples, n_features) - The data
• labels - Array of shape (n_samples,) - Predicted cluster labels
• n_folds - Number of folds to split the data into (default: 5)
• fold_size - Fraction of data to include in each fold (default: 0.8)
• random_seed - Optional seed for reproducibility

Returns

• Fold stability index (between 0 and 1)

Examples

use scirs2_core::ndarray::{array, Array2};
use scirs2_metrics::clustering::validation::fold_stability;

let x = Array2::from_shape_vec((10, 2), vec![
    1.0, 2.0, 1.5, 1.8, 1.2, 2.2, 1.3, 2.1, 1.4, 1.9,
    5.0, 6.0, 5.2, 5.8, 5.5, 6.2, 5.3, 6.1, 5.4, 5.9,
]).unwrap();

let labels = array![0, 0, 0, 0, 0, 1, 1, 1, 1, 1];

let stability = fold_stability(&x, &labels, None, None, None).unwrap();