pub struct RidgeFit {}Expand description
Result of a ridge regression fit.
Contains the fitted model coefficients, predictions, and diagnostic metrics.
§Fields
lambda- The regularization strength usedintercept- Intercept coefficient (never penalized)coefficients- Slope coefficients (penalized)fitted_values- Predicted values on training dataresiduals- Residuals (y - fitted_values)df- Approximate effective degrees of freedomr_squared- Coefficient of determinationadj_r_squared- Adjusted R²mse- Mean squared errorrmse- Root mean squared errormae- Mean absolute errorlog_likelihood- Log-likelihood of the model (for model comparison)aic- Akaike Information Criterion (lower = better)bic- Bayesian Information Criterion (lower = better)
§Example
let fit = ridge_fit(&x, &y, &options).unwrap();
// Access model coefficients
println!("Intercept: {}", fit.intercept);
println!("Slopes: {:?}", fit.coefficients);
// Access predictions and diagnostics
println!("R²: {}", fit.r_squared);
println!("RMSE: {}", fit.rmse);
println!("AIC: {}", fit.aic);Fields§
§lambda: f64§intercept: f64§coefficients: Vec<f64>§fitted_values: Vec<f64>§residuals: Vec<f64>§df: f64§r_squared: f64§adj_r_squared: f64§mse: f64§rmse: f64§mae: f64§log_likelihood: f64§aic: f64§bic: f64Trait Implementations§
Auto Trait Implementations§
impl Freeze for RidgeFit
impl RefUnwindSafe for RidgeFit
impl Send for RidgeFit
impl Sync for RidgeFit
impl Unpin for RidgeFit
impl UnwindSafe for RidgeFit
Blanket Implementations§
Source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere
T: ?Sized,
Source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
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