npm package discovery and stats viewer.

Discover Tips

  • General search

    [free text search, go nuts!]

  • Package details

    pkg:[package-name]

  • User packages

    @[username]

Sponsor

Optimize Toolset

I’ve always been into building performant and accessible sites, but lately I’ve been taking it extremely seriously. So much so that I’ve been building a tool to help me optimize and monitor the sites that I build to make sure that I’m making an attempt to offer the best experience to those who visit them. If you’re into performant, accessible and SEO friendly sites, you might like it too! You can check it out at Optimize Toolset.

About

Hi, 👋, I’m Ryan Hefner  and I built this site for me, and you! The goal of this site was to provide an easy way for me to check the stats on my npm packages, both for prioritizing issues and updates, and to give me a little kick in the pants to keep up on stuff.

As I was building it, I realized that I was actually using the tool to build the tool, and figured I might as well put this out there and hopefully others will find it to be a fast and useful way to search and browse npm packages as I have.

If you’re interested in other things I’m working on, follow me on Twitter or check out the open source projects I’ve been publishing on GitHub.

I am also working on a Twitter bot for this site to tweet the most popular, newest, random packages from npm. Please follow that account now and it will start sending out packages soon–ish.

Open Software & Tools

This site wouldn’t be possible without the immense generosity and tireless efforts from the people who make contributions to the world and share their work via open source initiatives. Thank you 🙏

© 2024 – Pkg Stats / Ryan Hefner

node-naive-bayes

v0.1.4

Published

A Nodejs Naive Bayes implementation

Downloads

12

Readme

Node-Naive-Bayes

This is a Nodejs implementation of the Naive Bayes classifer. This is basically part of my final year project which also includes a real-time messaging app to show the classifier in action.

The algorithm used here is based on a book, "Programming Collective Intelligence" by Toby Segaran.

Usage

const NaiveBayes = require('node-naive-bayes');

const naiveBayes = new NaiveBayes();

naiveBayes.trainInline('the quick rabbit jumps fences', 'good');

console.log('quick rabbit: ', naiveBayes.classify('quick rabbit', 'unknown'));

You can set thresholds for a category so that the classifier does not classify an item or document wrongly when it does not have enough information

naiveBayes.setThreshold('bad', 3);

Training methods

There are two methods of training the classifier;

  • Inline

    naiveBayes.trainInline('make quick money at the online casino', 'bad');

    This function accepts two parameters; first is the training text and second is the category

    Update: You can now save training data to a file so that they can be easily reused later. You do this by passing true as the third parameter and then the path to the file as the fourth.

    ...
    naiveBayes.trainInline('join bet to make excess cash in one day', 'bad', true, './my_file.txt');
    ...
    // next time just do like below, to reuse the training data
    naiveBayes.trainFromFile('./my_file.txt');
  • From files

    This has the format of text:::category and are separated by new lines.

    Example is: make quick money at the online casino:::bad

    After which, you let the classifier know about the file like below

    naiveBayes.trainFromFile('path_to_file');

Contribution

Feel free to contact me or send PRs for improvements