Struct GradientDescent

pub struct GradientDescent<T> { /* private fields */ }

A simple Gradient Descent optimizer.

Implementations

impl GradientDescent<ArmijoLineSearch>

pub fn new() -> GradientDescent<ArmijoLineSearch>

Creates a new GradientDescent optimizer using the following defaults:

• line_search = ArmijoLineSearch(0.5, 1.0, 0.5)
• gradient_tolerance = 1e-4
• max_iterations = None

impl<T: LineSearch> GradientDescent<T>

pub fn line_search<S: LineSearch>(self, line_search: S) -> GradientDescent<S>

Specifies the line search method to use.

pub fn gradient_tolerance(self, gradient_tolerance: f64) -> Self

Adjusts the gradient tolerance which is used as abort criterion to decide whether we reached a plateau.

pub fn max_iterations(self, max_iterations: Option<u64>) -> Self

Adjusts the number of maximally run iterations. A value of None instructs the optimizer to ignore the nubmer of iterations.

Trait Implementations

impl<T: Default> Default for GradientDescent<T>

fn default() -> GradientDescent<T>

Returns the “default value” for a type.

impl<F: Function1, S: LineSearch> Minimizer<F> for GradientDescent<S>

type Solution = Solution

Type of the solution the Minimizer returns.

fn minimize(&self, function: &F, initial_position: Vec<f64>) -> Solution

Performs the actual minimization and returns a solution that might be better than the initially provided one.