Struct FeatureUnion 

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

Feature Union for parallel feature extraction

Applies multiple transformers in parallel and concatenates their results.

Examples

use sklears_compose::FeatureUnion;
use scirs2_core::ndarray::array;

let data = array![[1.0, 2.0], [3.0, 4.0]];
let union = FeatureUnion::new()
    .transformer("trans1", Box::new(MockTransformer::new()))
    .transformer("trans2", Box::new(MockTransformer::new()));

Implementations

impl FeatureUnion<Untrained>

pub fn new() -> Self

Create a new FeatureUnion

pub fn transformer(self, name: &str, transformer: Box<dyn PipelineStep>) -> Self

Add a transformer

pub fn n_jobs(self, n_jobs: Option<i32>) -> Self

Set number of jobs

pub fn transformer_weights(self, weights: HashMap<String, f64>) -> Self

Set transformer weights

pub fn preserve_dataframe(self, preserve: bool) -> Self

Set preserve dataframe option

impl FeatureUnion<FeatureUnionTrained>

pub fn transform(&self, x: &ArrayView2<'_, Float>) -> SklResult<Array2<f64>>

Transform data using all fitted transformers and concatenate results

pub fn transformers(&self) -> &[(String, Box<dyn PipelineStep>)]

Get the fitted transformers

Trait Implementations

impl<S: Debug> Debug for FeatureUnion<S>

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

Formats the value using the given formatter.

impl Default for FeatureUnion<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for FeatureUnion<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 FeatureUnion<Untrained>

type Fitted = FeatureUnion<FeatureUnionTrained>

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