Macro define_ml_algorithm 

macro_rules! define_ml_algorithm {
    (
        name: $name:ident,
        config: {
            $(
                $field:ident: $field_type:ty = $default:expr
                $(=> validate($validator:expr))?
            ),* $(,)?
        },
        fit_fn: $fit_fn:ident,
        predict_fn: $predict_fn:ident,
        algorithm_type: $algorithm_type:ident
    ) => { ... };
}

Creates a complete ML algorithm with all necessary boilerplate

This macro generates:

• Configuration struct with validation
• State management (trained/untrained)
• Builder pattern implementation
• Core trait implementations
• Basic test suite
• Documentation templates

Examples

use sklears_core::define_ml_algorithm;

define_ml_algorithm! {
    name: LinearRegression,
    config: {
        fit_intercept: bool = true,
        alpha: f64 = 1.0 => validate(|x| x >= 0.0),
        max_iter: usize = 1000 => validate(|x| x > 0)
    },
    fit_fn: fit_linear_regression,
    predict_fn: predict_linear_regression,
    algorithm_type: supervised_regression
}