Struct BayesianOptimizer 

pub struct BayesianOptimizer { /* private fields */ }

let kernel = RBF::new(1.0); let gpr = GaussianProcessRegressor::new().kernel(Box::new(kernel)); let optimizer = BayesianOptimizer::new(gpr) .acquisition(AcquisitionFunction::ExpectedImprovement) .xi(0.01);

// Define bounds and initial points let bounds = array![[0.0, 10.0]]; // 1D optimization between 0 and 10 let X_init = array![[1.0], [5.0], [9.0]]; let y_init = array![1.0, 25.0, 81.0]; // f(x) = x^2

let mut bo = optimizer.fit_initial(&X_init.view(), &y_init.view()).unwrap(); let next_point = bo.suggest_next_point(&bounds.view()).unwrap();

Implementations

impl BayesianOptimizer

pub fn new(_gp: GaussianProcessRegressor) -> Self

Create a new BayesianOptimizer instance

pub fn acquisition(self, acquisition: AcquisitionFunction) -> Self

Set the acquisition function

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

Set the exploration parameter

pub fn n_restarts(self, n_restarts: usize) -> Self

Set the number of random restarts for acquisition optimization

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

Set the random state

pub fn builder() -> BayesianOptimizerBuilder

Create a builder for the Bayesian optimizer

pub fn fit_initial( self, X: &ArrayView2<'_, f64>, y: &ArrayView1<'_, f64>, ) -> SklResult<BayesianOptimizerFitted>

Fit the initial Gaussian Process model

Trait Implementations

impl Clone for BayesianOptimizer

fn clone(&self) -> BayesianOptimizer

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for BayesianOptimizer

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

Formats the value using the given formatter.