Struct ARDBayesianRegression 

pub struct ARDBayesianRegression {
    pub max_iter: usize,
    pub tol: f64,
    pub alpha_init: Option<Array1<f64>>,
    pub beta_init: f64,
    pub fit_intercept: bool,
}

Automatic Relevance Determination (ARD) Bayesian regression

ARD uses separate precision parameters for each feature to perform automatic feature selection by driving irrelevant features to zero.

Fields

max_iter: usize

Maximum number of iterations

tol: f64

Convergence tolerance

alpha_init: Option<Array1<f64>>

Initial alpha (precision) parameters

beta_init: f64

Initial beta (noise precision) parameter

fit_intercept: bool

Whether to fit intercept

Implementations

impl ARDBayesianRegression

pub fn new() -> Self

Create a new ARD Bayesian regression model

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

Set maximum iterations

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

Set convergence tolerance

pub fn fit( &self, x: ArrayView2<'_, f64>, y: ArrayView1<'_, f64>, ) -> StatsResult<ARDRegressionResult>

Fit ARD Bayesian regression using iterative optimization

Trait Implementations

impl Clone for ARDBayesianRegression

fn clone(&self) -> ARDBayesianRegression

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for ARDBayesianRegression

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

Formats the value using the given formatter.

impl Default for ARDBayesianRegression

fn default() -> Self

Returns the “default value” for a type.