Struct RegressionMetrics

pub struct RegressionMetrics {
    pub mse: f64,
    pub rmse: f64,
    pub r2: f64,
}

Performance metrics for regression models.

This struct contains common evaluation metrics used to assess the performance of regression models, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and coefficient of determination (R²).

Fields

mse: f64

Mean Squared Error - the average of the squared differences between predicted and actual values. MSE = (1/n) * Σ(y_pred - y_true)². Lower values indicate better fit, with 0 being a perfect fit.

rmse: f64

Root Mean Squared Error - the square root of MSE, which provides an error measure in the same units as the target variable. RMSE = √MSE. Lower values indicate better fit, with 0 being a perfect fit.

r2: f64

Coefficient of determination (R²) - measures the proportion of variance in the dependent variable that is predictable from the independent variable(s). Range: (-∞, 1.0], where:

• 1.0 indicates a perfect fit (all variance is explained by the model)
• 0.0 indicates the model performs no better than a horizontal line (mean of y)
• Negative values indicate the model performs worse than a horizontal line

Trait Implementations

impl Debug for RegressionMetrics

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

Formats the value using the given formatter.