Struct linfa_bayes::MultinomialNb
source · pub struct MultinomialNb<F: PartialEq, L: Eq + Hash> { /* private fields */ }
Expand description
Fitted Multinomial Naive Bayes classifier.
See MultinomialNbParams for more information on the hyper-parameters.
Model assumptions
The family of Naive Bayes classifiers assume independence between variables. They do not model moments between variables and lack therefore in modelling capability. The advantage is a linear fitting time with maximum-likelihood training in a closed form.
Model usage example
The example below creates a set of hyperparameters, and then uses it to fit a Multinomial Naive Bayes classifier on provided data.
use linfa_bayes::{MultinomialNbParams, MultinomialNbValidParams, Result};
use linfa::prelude::*;
use ndarray::array;
let x = array![
[-2., -1.],
[-1., -1.],
[-1., -2.],
[1., 1.],
[1., 2.],
[2., 1.]
];
let y = array![1, 1, 1, 2, 2, 2];
let ds = DatasetView::new(x.view(), y.view());
// create a new parameter set with smoothing parameter equals `1`
let unchecked_params = MultinomialNbParams::new()
.alpha(1.0);
// fit model with unchecked parameter set
let model = unchecked_params.fit(&ds)?;
// transform into a verified parameter set
let checked_params = unchecked_params.check()?;
// update model with the verified parameters, this only returns
// errors originating from the fitting process
let model = checked_params.fit_with(Some(model), &ds)?;
Implementations§
source§impl<F: Float, L: Label> MultinomialNb<F, L>
impl<F: Float, L: Label> MultinomialNb<F, L>
sourcepub fn params() -> MultinomialNbParams<F, L>
pub fn params() -> MultinomialNbParams<F, L>
Construct a new set of hyperparameters
Trait Implementations§
source§impl<F: Clone + PartialEq, L: Clone + Eq + Hash> Clone for MultinomialNb<F, L>
impl<F: Clone + PartialEq, L: Clone + Eq + Hash> Clone for MultinomialNb<F, L>
source§fn clone(&self) -> MultinomialNb<F, L>
fn clone(&self) -> MultinomialNb<F, L>
Returns a copy of the value. Read more
1.0.0 · source§fn clone_from(&mut self, source: &Self)
fn clone_from(&mut self, source: &Self)
Performs copy-assignment from
source
. Read moresource§impl<F: PartialEq + PartialEq, L: PartialEq + Eq + Hash> PartialEq for MultinomialNb<F, L>
impl<F: PartialEq + PartialEq, L: PartialEq + Eq + Hash> PartialEq for MultinomialNb<F, L>
source§fn eq(&self, other: &MultinomialNb<F, L>) -> bool
fn eq(&self, other: &MultinomialNb<F, L>) -> bool
This method tests for
self
and other
values to be equal, and is used
by ==
.source§impl<F: Float, L: Label, D> PredictInplace<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<L>, Dim<[usize; 1]>>> for MultinomialNb<F, L>where
D: Data<Elem = F>,
impl<F: Float, L: Label, D> PredictInplace<ArrayBase<D, Dim<[usize; 2]>>, ArrayBase<OwnedRepr<L>, Dim<[usize; 1]>>> for MultinomialNb<F, L>where D: Data<Elem = F>,
impl<F: PartialEq, L: Eq + Hash> StructuralPartialEq for MultinomialNb<F, L>
Auto Trait Implementations§
impl<F, L> RefUnwindSafe for MultinomialNb<F, L>where F: RefUnwindSafe, L: RefUnwindSafe,
impl<F, L> Send for MultinomialNb<F, L>where F: Send, L: Send,
impl<F, L> Sync for MultinomialNb<F, L>where F: Sync, L: Sync,
impl<F, L> Unpin for MultinomialNb<F, L>where F: Unpin, L: Unpin,
impl<F, L> UnwindSafe for MultinomialNb<F, L>where F: UnwindSafe + RefUnwindSafe, L: UnwindSafe,
Blanket Implementations§
source§impl<T> BorrowMut<T> for Twhere
T: ?Sized,
impl<T> BorrowMut<T> for Twhere T: ?Sized,
source§fn borrow_mut(&mut self) -> &mut T
fn borrow_mut(&mut self) -> &mut T
Mutably borrows from an owned value. Read more