Crate anofox_ml_naive_bayes 

Naive Bayes classifiers.

This crate implements several Naive Bayes algorithms:

• GaussianNB — assumes features follow a normal distribution within each class.
• MultinomialNB — for count-based or TF-IDF features (non-negative values).
• BernoulliNB — for binary/boolean features, with automatic binarization.

Examples

use ndarray::array;
use anofox_ml_core::{Fit, Predict};
use anofox_ml_naive_bayes::GaussianNB;

// Two well-separated classes
let x_train = array![
    [1.0, 1.0],
    [1.1, 0.9],
    [0.9, 1.1],
    [10.0, 10.0],
    [10.1, 9.9],
    [9.9, 10.1]
];
let y_train = array![0.0, 0.0, 0.0, 1.0, 1.0, 1.0];

let nb = GaussianNB::new();
let fitted = Fit::fit(&nb, &x_train, &y_train).unwrap();

let x_test = array![[1.0, 1.0], [10.0, 10.0]];
let preds = fitted.predict(&x_test).unwrap();
assert!((preds[0] - 0.0_f64).abs() < 1e-10);
assert!((preds[1] - 1.0_f64).abs() < 1e-10);

Structs

BernoulliNB

Bernoulli Naive Bayes classifier parameters (unfitted state).

FittedBernoulliNB

Fitted Bernoulli Naive Bayes classifier.

FittedGaussianNB

Fitted Gaussian Naive Bayes classifier.

FittedMultinomialNB

Fitted Multinomial Naive Bayes classifier.

GaussianNB

Gaussian Naive Bayes classifier parameters (unfitted state).

MultinomialNB

Multinomial Naive Bayes classifier parameters (unfitted state).