Function normalized_root_mean_squared_error 

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

Calculates the normalized root mean squared error (NRMSE)

Arguments

• y_true - Ground truth (correct) target values
• y_pred - Estimated target values
• normalization - Method used for normalization:
  • “mean” - RMSE / mean(y_true)
  • “range” - RMSE / (max(y_true) - min(y_true))
  • “iqr” - RMSE / interquartile range of y_true

Returns

• The normalized root mean squared error

Examples

use scirs2_core::ndarray::array;
use scirs2_metrics::regression::normalized_root_mean_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 nrmse_mean: f64 = normalized_root_mean_squared_error(&y_true, &y_pred, "mean").unwrap();
let nrmse_range: f64 = normalized_root_mean_squared_error(&y_true, &y_pred, "range").unwrap();
assert!(nrmse_mean > 0.0);
assert!(nrmse_range > 0.0);