Struct StreamingPipeline 

pub struct StreamingPipeline<S = Untrained> { /* private fields */ }

Streaming pipeline processor

Implementations

impl StreamingPipeline<Untrained>

pub fn new( base_estimator: Box<dyn PipelinePredictor>, config: StreamConfig, ) -> Self

Create a new streaming pipeline

pub fn update_strategy(self, strategy: UpdateStrategy) -> Self

Set update strategy

pub fn tumbling_time( base_estimator: Box<dyn PipelinePredictor>, window_duration: Duration, ) -> Self

Create a tumbling time window pipeline

pub fn sliding_window( base_estimator: Box<dyn PipelinePredictor>, window_size: usize, slide_step: usize, ) -> Self

Create a sliding window pipeline

pub fn session_window( base_estimator: Box<dyn PipelinePredictor>, session_gap: Duration, ) -> Self

Create a session window pipeline

impl StreamingPipeline<StreamingPipelineTrained>

pub fn process_point( &mut self, point: StreamDataPoint, ) -> SklResult<Option<Array1<f64>>>

Process a single data point from the stream

pub fn process_batch( &mut self, points: Vec<StreamDataPoint>, ) -> SklResult<Array2<f64>>

Process batch of data points

pub fn statistics(&self) -> &StreamStats

Get current statistics

pub fn buffer_size(&self) -> usize

Get current buffer size

pub fn active_windows(&self) -> usize

Get number of active windows

pub fn checkpoint(&self) -> SklResult<HashMap<String, String>>

Checkpoint the current state

pub fn clear_buffers(&mut self)

Clear internal buffers and windows

pub fn drift_metrics(&self) -> &HashMap<String, f64>

Get drift detection metrics

pub fn detect_drift( &mut self, reference_window: &StreamWindow, current_window: &StreamWindow, ) -> SklResult<f64>

Detect concept drift (simplified implementation)

Trait Implementations

impl Estimator for StreamingPipeline<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 Fit<ArrayBase<ViewRepr<&f64>, Dim<[usize; 2]>>, Option<&ArrayBase<ViewRepr<&f64>, Dim<[usize; 1]>>>> for StreamingPipeline<Untrained>

type Fitted = StreamingPipeline<StreamingPipelineTrained>

The fitted model type

fn fit( self, x: &ArrayView2<'_, Float>, y: &Option<&ArrayView1<'_, Float>>, ) -> SklResult<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