Struct LinearRegressionConfig 

pub struct LinearRegressionConfig {
    pub learning_rate: Float,
    pub alpha: Float,
    pub max_iter: usize,
    pub tol: Float,
    pub fit_intercept: bool,
    pub solver: String,
}

Example configuration with manual validation implementation

Fields

learning_rate: Float

Learning rate for gradient descent

alpha: Float

L2 regularization parameter

max_iter: usize

Maximum number of iterations

tol: Float

Convergence tolerance

fit_intercept: bool

Whether to fit intercept

solver: String

Solver method

Trait Implementations

impl Clone for LinearRegressionConfig

fn clone(&self) -> LinearRegressionConfig

Returns a duplicate of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl ConfigValidation for LinearRegressionConfig

fn validate_config(&self) -> Result<()>

Validate the entire configuration

fn get_warnings(&self) -> Vec<String>

Get validation warnings (non-fatal issues)

impl Debug for LinearRegressionConfig

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

Formats the value using the given formatter.

impl Default for LinearRegressionConfig

fn default() -> Self

Returns the “default value” for a type.

impl Validate for LinearRegressionConfig

fn validate(&self) -> Result<()>

Validate all parameters and return an error if any validation fails

fn validate_with_context(&self, context: &str) -> Result<()>

Validate and provide detailed error information