Struct KernelCenterer 

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

KernelCenterer centers a kernel matrix

Let K(x, z) be a kernel matrix computed from samples x and z. KernelCenterer computes the centered kernel matrix K_c as:

K_c(x, z) = K(x, z) - K_mean_x - K_mean_z + K_mean_all

where:

• K_mean_x is the mean of K along samples x
• K_mean_z is the mean of K along samples z
• K_mean_all is the overall mean of K

Implementations

impl KernelCenterer<Untrained>

pub fn new() -> Self

Create a new KernelCenterer

Trait Implementations

impl<State: Clone> Clone for KernelCenterer<State>

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

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl<State: Debug> Debug for KernelCenterer<State>

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

Formats the value using the given formatter.

impl Default for KernelCenterer<Untrained>

fn default() -> Self

Returns the “default value” for a type.

impl Fit<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>, ()> for KernelCenterer<Untrained>

type Fitted = KernelCenterer<Trained>

The fitted model type

fn fit(self, k: &Array2<Float>, _y: &()) -> 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 Transform<ArrayBase<OwnedRepr<f64>, Dim<[usize; 2]>>> for KernelCenterer<Trained>

fn transform(&self, k: &Array2<Float>) -> Result<Array2<Float>>

Transform the input data