Struct GraphFeatureSelector 

pub struct GraphFeatureSelector<State = Untrained> { /* private fields */ }

Graph-based feature selector for network-structured data.

This selector uses graph topology and structure to identify important features by analyzing centrality measures, community structure, and other graph properties. It’s particularly useful for social networks, biological networks, citation networks, and other graph-structured data where network topology provides valuable information about feature importance.

Implementations

impl GraphFeatureSelector<Untrained>

pub fn new() -> Self

Creates a new GraphFeatureSelector with default parameters.

pub fn builder() -> GraphFeatureSelectorBuilder

Creates a builder for configuring the GraphFeatureSelector.

Trait Implementations

impl<State: Clone> Clone for GraphFeatureSelector<State>

fn clone(&self) -> GraphFeatureSelector<State>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<State: Debug> Debug for GraphFeatureSelector<State>

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

Formats the value using the given formatter.

impl Default for GraphFeatureSelector<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for GraphFeatureSelector<Untrained>

type Config = ()

Configuration type for the estimator

type Error = SklearsError

Error type for the estimator

type Float = f64

The numeric type used by this estimator

fn config(&self) -> &Self::Config

Get estimator configuration

fn validate_config(&self) -> Result<(), SklearsError>

Validate estimator configuration with detailed error context

fn check_compatibility( &self, n_samples: usize, n_features: usize, ) -> Result<(), SklearsError>

Check if estimator is compatible with given data dimensions

fn metadata(&self) -> EstimatorMetadata

Get estimator metadata

impl Estimator for GraphFeatureSelector<Trained>

type Config = ()

Configuration type for the estimator

type Error = SklearsError

Error type for the estimator

type Float = f64

The numeric type used by this estimator

fn config(&self) -> &Self::Config

Get estimator configuration

fn validate_config(&self) -> Result<(), SklearsError>

Validate estimator configuration with detailed error context

fn check_compatibility( &self, n_samples: usize, n_features: usize, ) -> Result<(), SklearsError>

Check if estimator is compatible with given data dimensions

fn metadata(&self) -> EstimatorMetadata

Get estimator metadata

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

type Fitted = GraphFeatureSelector<Trained>

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

impl SelectorMixin for GraphFeatureSelector<Trained>

fn get_support(&self) -> Result<Array1<bool>>

Get support mask

fn transform_features(&self, indices: &[usize]) -> SklResult<Vec<usize>>

Transform by selecting features

impl Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for GraphFeatureSelector<Trained>

fn transform(&self, x: &Array2<f64>) -> Result<Array2<f64>>

Transform the input data