Struct smartcore::naive_bayes::multinomial::MultinomialNBParameters

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

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

Fields

alpha: T

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

priors: Option<Vec<T>>

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

Implementations

impl<T: RealNumber> MultinomialNBParameters<T>

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

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

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

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

Trait Implementations

impl<T: Clone + RealNumber> Clone for MultinomialNBParameters<T>

pub fn clone(&self) -> MultinomialNBParameters<T>

Returns a copy of the value.

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

Performs copy-assignment from source.

impl<T: Debug + RealNumber> Debug for MultinomialNBParameters<T>

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

Formats the value using the given formatter.

impl<T: RealNumber> Default for MultinomialNBParameters<T>

pub fn default() -> Self

Returns the "default value" for a type.

impl<'de, T: RealNumber> Deserialize<'de> for MultinomialNBParameters<T> where
    T: Deserialize<'de>, 

pub fn deserialize<__D>(__deserializer: __D) -> Result<Self, __D::Error> where
    __D: Deserializer<'de>, 

Deserialize this value from the given Serde deserializer.

impl<T: RealNumber> Serialize for MultinomialNBParameters<T> where
    T: Serialize, 

pub fn serialize<__S>(&self, __serializer: __S) -> Result<__S::Ok, __S::Error> where
    __S: Serializer, 

Serialize this value into the given Serde serializer.

impl<T: RealNumber, M: Matrix<T>> SupervisedEstimator<M, <M as BaseMatrix<T>>::RowVector, MultinomialNBParameters<T>> for MultinomialNB<T, M>

pub fn fit(
    x: &M,
    y: &M::RowVector,
    parameters: MultinomialNBParameters<T>
) -> Result<Self, Failed>

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