Struct LabelBinarizer 

pub struct LabelBinarizer<T: Eq + Hash + Clone = i32, State = Untrained> { /* private fields */ }

LabelBinarizer transforms labels to binary form

Implementations

impl<T: Eq + Hash + Clone> LabelBinarizer<T, Untrained>

pub fn new() -> Self

Create a new LabelBinarizer with default configuration

pub fn neg_label(self, neg_label: i32) -> Self

Set the negative label value

pub fn pos_label(self, pos_label: i32) -> Self

Set the positive label value

impl<T: Eq + Hash + Clone> LabelBinarizer<T, Trained>

pub fn classes(&self) -> &Vec<T>

Get the classes

pub fn inverse_transform(&self, y: &Array2<Float>) -> Result<Array1<T>>

Transform binary matrix back to original labels

Trait Implementations

impl<T: Eq + Hash + Clone> Default for LabelBinarizer<T, Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl<T: Eq + Hash + Clone> Estimator for LabelBinarizer<T, Untrained>

type Config = LabelBinarizerConfig

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<T: Eq + Hash + Clone> Estimator for LabelBinarizer<T, Trained>

type Config = LabelBinarizerConfig

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<T: Eq + Hash + Clone + Ord + Send + Sync> Fit<ArrayBase<OwnedRepr<T>, Dim<[usize; 1]>>, ()> for LabelBinarizer<T, Untrained>

type Fitted = LabelBinarizer<T, Trained>

The fitted model type

fn fit(self, y: &Array1<T>, _x: &()) -> 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

impl<T: Eq + Hash + Clone> Transform<ArrayBase<OwnedRepr<T>, Dim<[usize; 1]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for LabelBinarizer<T, Trained>

fn transform(&self, y: &Array1<T>) -> Result<Array2<Float>>

Transform the input data