Struct MultiClassSVC 

pub struct MultiClassSVC<State = Untrained> { /* private fields */ }

Multi-class Support Vector Classification

Implementations

impl MultiClassSVC<Untrained>

pub fn new() -> Self

Create a new multi-class SVC

pub fn c(self, c: Float) -> Self

Set the regularization parameter C

pub fn linear(self) -> Self

Set the kernel to linear

pub fn rbf(self, gamma: Option<Float>) -> Self

Set the kernel to RBF with optional gamma

pub fn poly(self, degree: usize, gamma: Option<Float>, coef0: Float) -> Self

Set the kernel to polynomial

pub fn tol(self, tol: Float) -> Self

Set the tolerance for stopping criterion

pub fn max_iter(self, max_iter: usize) -> Self

Set the maximum number of iterations

pub fn strategy(self, strategy: MultiClassStrategy) -> Self

Set the multi-class strategy

pub fn one_vs_rest(self) -> Self

Set One-vs-Rest strategy

pub fn one_vs_one(self) -> Self

Set One-vs-One strategy

pub fn one_vs_one_decision(self) -> Self

Set One-vs-One strategy with decision-based voting

pub fn ecoc(self) -> Self

Set Error-Correcting Output Codes (ECOC) strategy

pub fn hierarchical_tree(self) -> Self

Set hierarchical tree strategy

pub fn balanced(self) -> Self

Set balanced class weights

impl MultiClassSVC<Trained>

pub fn classes(&self) -> &Array1<Float>

Get the classes

pub fn n_estimators(&self) -> usize

Get the number of estimators

pub fn estimators(&self) -> &[SVC<Trained>]

Get a reference to the binary estimators

pub fn decision_function(&self, x: &Array2<Float>) -> Result<Array2<Float>>

Compute decision function values for each binary classifier

Trait Implementations

impl<State: Clone> Clone for MultiClassSVC<State>

fn clone(&self) -> MultiClassSVC<State>

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<State: Debug> Debug for MultiClassSVC<State>

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

Formats the value using the given formatter.

impl Default for MultiClassSVC<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>> for MultiClassSVC<Untrained>

type Fitted = MultiClassSVC<Trained>

The fitted model type

fn fit(self, x: &Array2<Float>, y: &Array1<Float>) -> 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 Predict<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<f64>, Dim<[usize; 1]>>> for MultiClassSVC<Trained>

fn predict(&self, x: &Array2<Float>) -> Result<Array1<Float>>

Make predictions on the provided data

fn predict_with_uncertainty( &self, x: &X, ) -> Result<(Output, UncertaintyMeasure), SklearsError>

Make predictions with confidence intervals