Dendritic Bayesian Statistics Crate

This crate allows for common bayesian methods for regression and classification tasks. The bayes crate currently supports guassian and standard naive bayes.

Features

• Guassian Bayes: Bayesian model that uses gaussian density function for predicting likelihoods
• Naive Bayes: Standard naive bayes model

Disclaimer

The dendritic project is a toy machine learning library built for learning and research purposes. It is not advised by the maintainer to use this library as a production ready machine learning library. This is a project that is still very much a work in progress.

Getting Started

To get started, add this to your Cargo.toml:

[dependencies]
dendritic-bayes = "1.1.0"

Example Usage

This is an example of using both the naive and gaussian bayes models

use dendritic_ndarray::ndarray::NDArray;
use dendritic_ndarray::ops::*;
use dendritic_bayes::naive_bayes::*;
use dendritic_bayes::gaussian_bayes::*;


fn main() {
    // Load datasets from saved ndarray
    let x_path = "data/weather_multi_feature/inputs";
    let y_path = "data/weather_multi_feature/outputs";

    // Load saved ndarrays in memory
    let features = NDArray::load(x_path).unwrap();
    let target = NDArray::load(y_path).unwrap();

    // Create instance of naive bayes model
    let mut nb_clf = NaiveBayes::new(
        &features,
        &target
    ).unwrap();

    // Create instance of guassian bayes model
    let mut gb_clf = GaussianNB::new(
        &features,
        &target
    ).unwrap();
    
    // Make prediction with first row of features
    let row1 = features.axis(0, 0).unwrap();
    let nb_pred = nb_clf.fit(row1.clone());
    let gb_pred = gb_clf.fit(row1.clone()); // This will take in references eventually
}