Struct SparseStandardScaler 

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

Sparse-aware standard scaler

Implementations

impl SparseStandardScaler<Untrained>

pub fn new() -> Self

pub fn with_mean(self, with_mean: bool) -> Self

pub fn with_std(self, with_std: bool) -> Self

impl SparseStandardScaler<Untrained>

pub fn get_config(&self) -> &SparseStandardScalerConfig

Trait Implementations

impl<S: Clone> Clone for SparseStandardScaler<S>

fn clone(&self) -> SparseStandardScaler<S>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<S: Debug> Debug for SparseStandardScaler<S>

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

Formats the value using the given formatter.

impl Default for SparseStandardScaler<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for SparseStandardScaler<Untrained>

type Config = SparseStandardScalerConfig

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<SparseMatrix, ()> for SparseStandardScaler<Untrained>

type Fitted = SparseStandardScalerFitted

The fitted model type

fn fit(self, x: &SparseMatrix, _y: &()) -> 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