Module smartcore::naive_bayes::multinomial

Multinomial Naive Bayes

Multinomial Naive Bayes classifier is a variant of Naive Bayes for the multinomially distributed data. It is often used for discrete data with predictors representing the number of times an event was observed in a particular instance, for example frequency of the words present in the document.

Example:

use smartcore::linalg::naive::dense_matrix::*;
use smartcore::naive_bayes::multinomial::MultinomialNB;

// 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., 2., 0., 0., 0., 0.],
                  &[0., 2., 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 = MultinomialNB::fit(&x, &y, Default::default()).unwrap();

// Testing data point is:
//  Chinese Chinese Chinese Tokyo Japan
let x_test = DenseMatrix::<f64>::from_2d_array(&[&[0., 3., 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

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