Struct InformationBottleneckExtractor 

pub struct InformationBottleneckExtractor { /* private fields */ }

Information Bottleneck Feature Extractor

Implements the Information Bottleneck principle for feature extraction, finding representations that maximize information about targets while minimizing information about inputs. InformationBottleneckExtractor

Implementations

impl InformationBottleneckExtractor

pub fn new(n_components: usize) -> Self

Create a new Information Bottleneck extractor

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

Set beta parameter (trade-off between compression and prediction)

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

Set number of bins for discretization

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

Set maximum iterations for optimization

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

Set convergence tolerance

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

Set random state

Trait Implementations

impl Clone for InformationBottleneckExtractor

fn clone(&self) -> InformationBottleneckExtractor

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for InformationBottleneckExtractor

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

Formats the value using the given formatter.

impl Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>> for InformationBottleneckExtractor

type Fitted = FittedInformationBottleneckExtractor

The fitted model type

fn fit(self, x: &Array2<f64>, y: &Array1<f64>) -> Result<Self::Fitted>

Fit the model to the provided data with validation

fn fit_with_validation( self, x: &X, y: &Y, _x_val: Option<&X>, _y_val: Option<&Y>, ) -> Result<(Self::Fitted, FitMetrics), SklearsError>

where Self: Sized,

Fit with custom validation and early stopping