Struct IterativeImputer 

pub struct IterativeImputer<F> { /* private fields */ }

An unfitted iterative imputer.

Calling Fit::fit learns the imputation model and returns a FittedIterativeImputer that can impute missing values in new data.

Parameters

• max_iter — maximum number of imputation rounds (default 10).
• tol — convergence tolerance on the total change in imputed values (default 1e-3).
• initial_strategy — strategy for the initial fill (default Mean).

Examples

use ferrolearn_preprocess::iterative_imputer::{IterativeImputer, InitialStrategy};
use ferrolearn_core::traits::{Fit, Transform};
use ndarray::array;

let imputer = IterativeImputer::<f64>::new(10, 1e-3, InitialStrategy::Mean);
let x = array![[1.0, 2.0], [3.0, f64::NAN], [f64::NAN, 6.0]];
let fitted = imputer.fit(&x, &()).unwrap();
let out = fitted.transform(&x).unwrap();
assert!(!out[[1, 1]].is_nan());
assert!(!out[[2, 0]].is_nan());

Implementations

impl<F: Float + Send + Sync + 'static> IterativeImputer<F>

pub fn new(max_iter: usize, tol: F, initial_strategy: InitialStrategy) -> Self

Create a new IterativeImputer with the given parameters.

pub fn max_iter(&self) -> usize

Return the maximum number of iterations.

pub fn tol(&self) -> F

Return the convergence tolerance.

pub fn initial_strategy(&self) -> InitialStrategy

Return the initial imputation strategy.

Trait Implementations

impl<F: Clone> Clone for IterativeImputer<F>

fn clone(&self) -> IterativeImputer<F>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<F: Debug> Debug for IterativeImputer<F>

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

Formats the value using the given formatter.

impl<F: Float + Send + Sync + 'static> Default for IterativeImputer<F>

fn default() -> Self

Returns the “default value” for a type.

impl<F: Float + Send + Sync + 'static> Fit<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>, ()> for IterativeImputer<F>

fn fit( &self, x: &Array2<F>, _y: &(), ) -> Result<FittedIterativeImputer<F>, FerroError>

Fit the iterative imputer by performing round-robin Ridge regression.

Errors

• FerroError::InsufficientSamples if the input has zero rows.
• FerroError::InvalidParameter if max_iter is zero.

type Fitted = FittedIterativeImputer<F>

The fitted model type returned by fit.

type Error = FerroError

The error type returned by fit.

impl<F: Float + Send + Sync + 'static> FitTransform<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for IterativeImputer<F>

fn fit_transform(&self, x: &Array2<F>) -> Result<Array2<F>, FerroError>

Fit the imputer on x and return the imputed output in one step.

Errors

Returns an error if fitting fails.

type FitError = FerroError

The error type for the combined fit-transform operation.

impl<F: Float + Send + Sync + 'static> Transform<ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>> for IterativeImputer<F>

Implement Transform on the unfitted imputer to satisfy the FitTransform: Transform supertrait bound.

fn transform(&self, _x: &Array2<F>) -> Result<Array2<F>, FerroError>

Always returns an error — the imputer must be fitted first.

type Output = ArrayBase<OwnedRepr<F>, Dim<[usize; 2]>>

The transformed output type.

type Error = FerroError

The error type returned by transform.