Struct linfa_linear::TweedieRegressorValidParams

pub struct TweedieRegressorValidParams<F> { /* private fields */ }

The set of hyperparameters that can be specified for the execution of the Tweedie Regressor.

Implementations

impl<F: Float> TweedieRegressorValidParams<F>

pub fn alpha(&self) -> F

pub fn fit_intercept(&self) -> bool

pub fn power(&self) -> F

pub fn link(&self) -> Link

pub fn max_iter(&self) -> usize

pub fn tol(&self) -> F

Trait Implementations

impl<F: Clone> Clone for TweedieRegressorValidParams<F>

fn clone(&self) -> TweedieRegressorValidParams<F>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<F: Debug> Debug for TweedieRegressorValidParams<F>

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

Formats the value using the given formatter.

impl<F, D: Data<Elem = F>, T: AsSingleTargets<Elem = F>> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, LinearError<F>> for TweedieRegressorValidParams<F>

where Array1<F>: ArgminAdd<Array1<F>, Array1<F>> + ArgminSub<Array1<F>, Array1<F>> + ArgminSub<F, Array1<F>> + ArgminAdd<F, Array1<F>> + ArgminMul<F, Array1<F>> + ArgminMul<Array1<F>, Array1<F>> + ArgminDot<Array1<F>, F> + ArgminL2Norm<F> + ArgminL1Norm<F> + ArgminSignum + ArgminMinMax, F: ArgminMul<Array1<F>, Array1<F>> + ArgminZero + Float,

type Object = TweedieRegressor<F>

fn fit(&self, ds: &DatasetBase<ArrayBase<D, Ix2>, T>) -> Result<Self::Object, F>

impl<F: PartialEq> PartialEq for TweedieRegressorValidParams<F>

fn eq(&self, other: &TweedieRegressorValidParams<F>) -> bool

This method tests for self and other values to be equal, and is used by ==.

fn ne(&self, other: &Rhs) -> bool

This method tests for !=. The default implementation is almost always sufficient, and should not be overridden without very good reason.

impl<F> StructuralPartialEq for TweedieRegressorValidParams<F>