Struct MixedTypeFeatureExtractor 

pub struct MixedTypeFeatureExtractor {
    pub feature_types: Vec<FeatureType>,
    pub normalize_numerical: bool,
    pub handle_missing_values: bool,
    pub missing_value_strategy: MissingValueStrategy,
    pub encoding_strategy: CategoricalEncoding,
    pub include_interaction_features: bool,
    pub random_state: Option<u64>,
}

Mixed-type feature extractor for handling heterogeneous data

This extractor can handle different types of features (numerical, categorical, binary, ordinal) and apply appropriate transformations to each type, creating a unified feature matrix.

Fields

feature_types: Vec<FeatureType>

Types of features for each column

normalize_numerical: bool

Whether to normalize numerical features

handle_missing_values: bool

Whether to handle missing values

missing_value_strategy: MissingValueStrategy

Strategy for handling missing values

encoding_strategy: CategoricalEncoding

Categorical encoding strategy

include_interaction_features: bool

Whether to include interaction features

random_state: Option<u64>

Random state for reproducible results

Implementations

impl MixedTypeFeatureExtractor

pub fn new() -> Self

Create a new mixed-type feature extractor

pub fn feature_types(self, types: Vec<FeatureType>) -> Self

Set feature types for each column

pub fn normalize_numerical(self, normalize: bool) -> Self

Set whether to normalize numerical features

pub fn handle_missing_values(self, handle: bool) -> Self

Set whether to handle missing values

pub fn missing_value_strategy(self, strategy: MissingValueStrategy) -> Self

Set missing value strategy

pub fn encoding_strategy(self, strategy: CategoricalEncoding) -> Self

Set categorical encoding strategy

pub fn include_interaction_features(self, include: bool) -> Self

Set whether to include interaction features

pub fn random_state(self, seed: u64) -> Self

Set random state

Trait Implementations

impl Clone for MixedTypeFeatureExtractor

fn clone(&self) -> Self

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MixedTypeFeatureExtractor

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

Formats the value using the given formatter.

impl Default for MixedTypeFeatureExtractor

fn default() -> Self

Returns the “default value” for a type.

impl Estimator for MixedTypeFeatureExtractor

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<OwnedRepr<f64>, Dim<[usize; 2]>>, ()> for MixedTypeFeatureExtractor

type Fitted = FittedMixedTypeFeatureExtractor

The fitted model type

fn fit(self, X: &Array2<f64>, _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