Struct DistributedKNNImputer 

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

Distributed KNN Imputer

Implementations

impl DistributedKNNImputer<Untrained>

pub fn new() -> Self

Create a new distributed KNN imputer

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

Set the number of neighbors

pub fn weights(self, weights: String) -> Self

Set the weight function

pub fn distributed_config(self, config: DistributedConfig) -> Self

Set the distributed configuration

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

Set the number of workers

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

Set the chunk size

pub fn communication_strategy(self, strategy: CommunicationStrategy) -> Self

Set the communication strategy

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

Enable fault tolerance

Trait Implementations

impl Default for DistributedKNNImputer<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for DistributedKNNImputer<Untrained>

type Config = DistributedConfig

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]>>, ()> for DistributedKNNImputer<Untrained>

type Fitted = DistributedKNNImputer<DistributedKNNImputerTrained>

The fitted model type

fn fit(self, X: &ArrayView2<'_, Float>, _y: &()) -> 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

impl Transform<ArrayBase<ViewRepr<&f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for DistributedKNNImputer<DistributedKNNImputerTrained>

fn transform(&self, X: &ArrayView2<'_, Float>) -> SklResult<Array2<Float>>

Transform the input data