Struct GradientDescent 

pub struct GradientDescent { /* private fields */ }

Gradient descent optimizer configuration

Implementations

impl GradientDescent

pub fn new() -> Self

Creates a new gradient descent optimizer with default settings

pub fn with_learning_rate(self, lr: LearningRate) -> Self

Sets the learning rate strategy

pub fn with_max_iterations(self, max_iter: usize) -> Self

Sets the maximum number of iterations

pub fn with_tolerance(self, tol: f64) -> Self

Sets the convergence tolerance

pub fn with_momentum(self, momentum: f64) -> Self

Sets the momentum coefficient (0.0 = no momentum)

pub fn verbose(self) -> Self

Enables verbose output

pub fn minimize<F, G>( &self, f: F, grad_f: G, initial: &[f64], ) -> Result<OptimizationResult>

where F: Fn(&[f64]) -> f64, G: Fn(&[f64]) -> Vec<f64>,

Minimizes the given function

Arguments

• f - The objective function to minimize
• grad_f - The gradient of the objective function
• initial - Initial parameter values

Returns

Optimization result containing the final parameters

Trait Implementations

impl Default for GradientDescent

fn default() -> Self

Returns the “default value” for a type.