Struct MultinomialNBParameters 

pub struct MultinomialNBParameters {
    pub alpha: f64,
    pub priors: Option<Vec<f64>>,
}

MultinomialNB parameters. Use Default::default() for default values.

Fields

alpha: f64

Additive (Laplace/Lidstone) smoothing parameter (0 for no smoothing).

priors: Option<Vec<f64>>

Prior probabilities of the classes. If specified the priors are not adjusted according to the data

Implementations

impl MultinomialNBParameters

pub fn with_alpha(self, alpha: f64) -> Self

Additive (Laplace/Lidstone) smoothing parameter (0 for no smoothing).

pub fn with_priors(self, priors: Vec<f64>) -> Self

Prior probabilities of the classes. If specified the priors are not adjusted according to the data

Trait Implementations

impl Clone for MultinomialNBParameters

fn clone(&self) -> MultinomialNBParameters

Returns a duplicate of the value.

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

Performs copy-assignment from source.

impl Debug for MultinomialNBParameters

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

Formats the value using the given formatter.

impl Default for MultinomialNBParameters

fn default() -> Self

Returns the “default value” for a type.

impl<TX: Number + Unsigned, TY: Number + Ord + Unsigned, X: Array2<TX>, Y: Array1<TY>> SupervisedEstimator<X, Y, MultinomialNBParameters> for MultinomialNB<TX, TY, 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: &X, y: &Y, parameters: MultinomialNBParameters, ) -> Result<Self, Failed>

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