Struct SVRParameters

pub struct SVRParameters<T: Number + FloatNumber + PartialOrd> {
    pub eps: T,
    pub c: T,
    pub tol: T,
    pub kernel: Option<Box<dyn Kernel>>,
}

SVR Parameters

Fields

eps: T

Epsilon in the epsilon-SVR model.

c: T

Regularization parameter.

tol: T

Tolerance for stopping criterion.

kernel: Option<Box<dyn Kernel>>

The kernel function.

Implementations

impl<T: Number + FloatNumber + PartialOrd> SVRParameters<T>

pub fn with_eps(self, eps: T) -> Self

Epsilon in the epsilon-SVR model.

pub fn with_c(self, c: T) -> Self

Regularization parameter.

pub fn with_tol(self, tol: T) -> Self

Tolerance for stopping criterion.

pub fn with_kernel<K: Kernel + 'static>(self, kernel: K) -> Self

The kernel function.

Trait Implementations

impl<T: Debug + Number + FloatNumber + PartialOrd> Debug for SVRParameters<T>

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

Formats the value using the given formatter.

impl<T: Number + FloatNumber + PartialOrd> Default for SVRParameters<T>

fn default() -> Self

Returns the “default value” for a type.

impl<'a, T: Number + FloatNumber + PartialOrd, X: Array2<T>, Y: Array1<T>> SupervisedEstimatorBorrow<'a, X, Y, SVRParameters<T>> for SVR<'a, T, X, Y>

fn new() -> Self

Empty constructor, instantiate an empty estimator. Object is dropped as soon as fit() is called. used to pass around the correct fit() implementation. by calling ::fit(). mostly used to be used with model_selection::cross_validate(...)

fn fit( x: &'a X, y: &'a Y, parameters: &'a SVRParameters<T>, ) -> Result<Self, Failed>

Fit a model to a training dataset, estimate model’s parameters.