Struct OneHotEncoder 

pub struct OneHotEncoder { /* private fields */ }

OneHotEncoder for converting categorical features to binary features

This transformer converts categorical features into a one-hot encoded representation, where each category is represented by a binary feature.

Implementations

impl OneHotEncoder

pub fn new( _drop: Option<String>, handleunknown: &str, sparse: bool, ) -> Result<Self>

Creates a new OneHotEncoder

Arguments

• drop - Strategy for dropping categories (‘first’, ‘if_binary’, or None)
• handleunknown - How to handle unknown categories (‘error’ or ‘ignore’)
• sparse - Whether to return sparse arrays

Returns

• A new OneHotEncoder instance

pub fn with_defaults() -> Self

Creates a OneHotEncoder with default settings

pub fn fit<S>(&mut self, x: &ArrayBase<S, Ix2>) -> Result<()>

where S: Data, S::Elem: Float + NumCast,

Fits the OneHotEncoder to the input data

Arguments

• x - The input categorical data, shape (n_samples, n_features)

Returns

• Result<()> - Ok if successful, Err otherwise

pub fn transform<S>(&self, x: &ArrayBase<S, Ix2>) -> Result<EncodedOutput>

where S: Data, S::Elem: Float + NumCast,

Transforms the input data using the fitted OneHotEncoder

Arguments

• x - The input categorical data, shape (n_samples, n_features)

Returns

• Result<EncodedOutput> - The one-hot encoded data (dense or sparse)

pub fn fit_transform<S>( &mut self, x: &ArrayBase<S, Ix2>, ) -> Result<EncodedOutput>

where S: Data, S::Elem: Float + NumCast,

Fits the OneHotEncoder to the input data and transforms it

Arguments

• x - The input categorical data, shape (n_samples, n_features)

Returns

• Result<EncodedOutput> - The one-hot encoded data (dense or sparse)

pub fn transform_dense<S>(&self, x: &ArrayBase<S, Ix2>) -> Result<Array2<f64>>

where S: Data, S::Elem: Float + NumCast,

Convenience method that always returns dense output for backward compatibility

Arguments

• x - The input categorical data, shape (n_samples, n_features)

Returns

• Result<Array2<f64>> - The one-hot encoded data as dense matrix

pub fn fit_transform_dense<S>( &mut self, x: &ArrayBase<S, Ix2>, ) -> Result<Array2<f64>>

where S: Data, S::Elem: Float + NumCast,

Convenience method that fits and transforms returning dense output

Arguments

• x - The input categorical data, shape (n_samples, n_features)

Returns

• Result<Array2<f64>> - The one-hot encoded data as dense matrix

pub fn categories(&self) -> Option<&Vec<Vec<u64>>>

Returns the categories for each feature

Returns

• Option<&Vec<Vec<u64>>> - The categories for each feature

pub fn get_feature_names( &self, inputfeatures: Option<&[String]>, ) -> Result<Vec<String>>

Gets the feature names for the transformed output

Arguments

• inputfeatures - Names of input features

Returns

• Result<Vec<String>> - Names of output features