Module smartcore::naive_bayes::bernoulli

Bernoulli Naive Bayes

Bernoulli Naive Bayes classifier is a variant of Naive Bayes for the data that is distributed according to multivariate Bernoulli distribution. It is used for discrete data with binary features. One example of a binary feature is a word that occurs in the text or not.

Example:

use smartcore::linalg::naive::dense_matrix::*;
use smartcore::naive_bayes::bernoulli::BernoulliNB;

// Training data points are:
// Chinese Beijing Chinese (class: China)
// Chinese Chinese Shanghai (class: China)
// Chinese Macao (class: China)
// Tokyo Japan Chinese (class: Japan)
let x = DenseMatrix::<f64>::from_2d_array(&[
          &[1., 1., 0., 0., 0., 0.],
          &[0., 1., 0., 0., 1., 0.],
          &[0., 1., 0., 1., 0., 0.],
          &[0., 1., 1., 0., 0., 1.],
]);
let y = vec![0., 0., 0., 1.];

let nb = BernoulliNB::fit(&x, &y, Default::default()).unwrap();

// Testing data point is:
// Chinese Chinese Chinese Tokyo Japan
let x_test = DenseMatrix::<f64>::from_2d_array(&[&[0., 1., 1., 0., 0., 1.]]);
let y_hat = nb.predict(&x_test).unwrap();

References:

• "Introduction to Information Retrieval", Manning C. D., Raghavan P., Schutze H., 2009, Chapter 13

Structs

BernoulliNB	BernoulliNB implements the categorical naive Bayes algorithm for categorically distributed data.
BernoulliNBParameters	BernoulliNB parameters. Use Default::default() for default values.