Struct MarginalLikelihoodOptimizer 

pub struct MarginalLikelihoodOptimizer { /* private fields */ }

let X = array![[1.0], [2.0], [3.0], [4.0]]; let y = array![1.0, 4.0, 9.0, 16.0];

let mut kernel: Box = Box::new(RBF::new(1.0)); let optimizer = MarginalLikelihoodOptimizer::new() .max_iter(100) .tol(1e-6);

let result = optimizer.optimize( &X.view(), &y.view(), &mut kernel, 0.1 ).unwrap();

let optimized_params = result.optimal_params; let final_lml = result.optimal_log_marginal_likelihood;

Implementations

impl MarginalLikelihoodOptimizer

pub fn new() -> Self

Create a new marginal likelihood optimizer

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

Set the maximum number of iterations

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

Set the convergence tolerance

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

Set the learning rate

pub fn adam_params(self, beta1: f64, beta2: f64, epsilon: f64) -> Self

Set Adam optimizer parameters

pub fn line_search(self, line_search: bool) -> Self

Enable or disable line search

pub fn verbose(self, verbose: bool) -> Self

Set verbosity

pub fn optimize( &self, X: &ArrayView2<'_, f64>, y: &ArrayView1<'_, f64>, kernel: &mut Box<dyn Kernel>, sigma_n: f64, ) -> SklResult<OptimizationResult>

Optimize the log marginal likelihood

Trait Implementations

impl Clone for MarginalLikelihoodOptimizer

fn clone(&self) -> MarginalLikelihoodOptimizer

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MarginalLikelihoodOptimizer

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

Formats the value using the given formatter.

impl Default for MarginalLikelihoodOptimizer

fn default() -> Self

Returns the “default value” for a type.