Struct StreamingEnsemble 

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

Streaming ensemble that adapts to concept drift

Implementations

impl<State> StreamingEnsemble<State>

pub fn model_count(&self) -> usize

Get number of models in ensemble

pub fn drift_count(&self) -> usize

Get number of concept drifts detected

pub fn overall_accuracy(&self) -> Float

Get overall accuracy

pub fn samples_seen(&self) -> usize

Get samples seen

impl StreamingEnsemble<Untrained>

pub fn new() -> Self

Create a new streaming ensemble

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

Set maximum number of models

pub fn drift_threshold(self, threshold: Float) -> Self

Set drift detection threshold

pub fn weight_learning_rate(self, rate: Float) -> Self

Set weight learning rate

pub fn forgetting_factor(self, factor: Float) -> Self

Set forgetting factor

pub fn enable_drift_detection(self, enabled: bool) -> Self

Enable/disable drift detection

pub fn performance_window_size(self, size: usize) -> Self

Set performance window size

pub fn adaptive_ensemble_size(self, enabled: bool) -> Self

Enable adaptive ensemble size

pub fn for_concept_drift() -> Self

Create optimized streaming ensemble for concept drift

pub fn for_real_time() -> Self

Create fast streaming ensemble for real-time applications

impl StreamingEnsemble<Trained>

pub fn partial_fit(&mut self, x: &Array1<Float>, y: Float) -> Result<Float>

Process a single sample in streaming fashion

pub fn predict_single(&self, x: &Array1<Float>) -> Result<Float>

Predict a single sample

Trait Implementations

impl Default for StreamingEnsemble<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for StreamingEnsemble<Untrained>

type Config = StreamingConfig

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 StreamingEnsemble<Untrained>

type Fitted = StreamingEnsemble<Trained>

The fitted model type

fn fit(self, x: &Array2<Float>, y: &Array1<Float>) -> 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 Predict<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>> for StreamingEnsemble<Trained>

fn predict(&self, x: &Array2<Float>) -> Result<Array1<Float>>

Make predictions on the provided data

fn predict_with_uncertainty( &self, x: &X, ) -> Result<(Output, UncertaintyMeasure), SklearsError>

Make predictions with confidence intervals