Function relative_squared_error 

pub fn relative_squared_error<F, S1, S2, D1, D2>(
    y_true: &ArrayBase<S1, D1>,
    y_pred: &ArrayBase<S2, D2>,
) -> Result<F>
where
    F: Float + NumCast + Debug + SimdUnifiedOps,
    S1: Data<Elem = F>,
    S2: Data<Elem = F>,
    D1: Dimension,
    D2: Dimension,

Calculates the relative squared error (RSE)

RSE is the ratio of the sum of squared errors to the sum of squared deviations from the mean of the true values.

Arguments

• y_true - Ground truth (correct) target values
• y_pred - Estimated target values

Returns

• The relative squared error

Examples

use scirs2_core::ndarray::array;
use scirs2_metrics::regression::relative_squared_error;

let y_true = array![3.0, -0.5, 2.0, 7.0];
let y_pred = array![2.5, 0.0, 2.0, 8.0];

let rse = relative_squared_error(&y_true, &y_pred).unwrap();
assert!(rse > 0.0 && rse < 1.0);