Struct linfa_bayes::GaussianNbValidParams

pub struct GaussianNbValidParams<F, L> { /* private fields */ }

A verified hyper-parameter set ready for the estimation of a Gaussian Naive Bayes model

See GaussianNbParams for more informations.

Implementations

impl<F: Float, L> GaussianNbValidParams<F, L>

pub fn var_smoothing(&self) -> F

Get the variance smoothing

Trait Implementations

impl<F: Debug, L: Debug> Debug for GaussianNbValidParams<F, L>

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

Formats the value using the given formatter.

impl<F, L, D, T> Fit<ArrayBase<D, Dim<[usize; 2]>>, T, NaiveBayesError> for GaussianNbValidParams<F, L> where
    F: Float,
    L: Label + Ord,
    D: Data<Elem = F>,
    T: AsTargets<Elem = L> + Labels<Elem = L>, 

type Object = GaussianNb<F, L>

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

impl<'a, F, L, D, T> FitWith<'a, ArrayBase<D, Dim<[usize; 2]>>, T, NaiveBayesError> for GaussianNbValidParams<F, L> where
    F: Float,
    L: Label + 'a,
    D: Data<Elem = F>,
    T: AsTargets<Elem = L> + Labels<Elem = L>, 

type ObjectIn = Option<GaussianNb<F, L>>

type ObjectOut = Option<GaussianNb<F, L>>

fn fit_with(
    &self,
    model_in: Self::ObjectIn,
    dataset: &DatasetBase<ArrayBase<D, Ix2>, T>
) -> Result<Self::ObjectOut>