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

catboost

v1.25.1

Published

Node bindings for CatBoost library to apply models. CatBoost is a machine learning method based on gradient boosting over decision trees.

Downloads

240

Readme

CatBoost Model Node package

A Node.js package for applying pretrained CatBoost model.

Usage example

  1. Install the package. You have two options:

    • Install from npm registry:
    npm i catboost
    • Build package from source. Navigate to this directory inside the repo and run:
    npm install

    Now you can link this package in your project via:

    npm install $PATH_TO_CATBOOST_REPO/catboost/node-package
  2. Apply the pretrained model:

catboost = require('catboost');

model = new catboost.Model();
model.loadModel('test_data/adult.cbm');

prediction = model.predict([
            [40., 85019., 16., 0., 0., 45.],
            [28., 85019., 13., 0., 0., 13.],
        ],
        [
            ["Private", "Doctorate", "Married-civ-spouce", "Prof-specialty", "Husband", "Asian-Pac-Islander", "Male", "nan"],
            ["Self-emp-not-inc", "Bachelors", "Married-civ-spouce", "Exec-managerial", "Husband", "White", "Male", "United-States"],
        ]
);
console.log(prediction);

Development roadmap

  • [x] Implement basic API calls.
  • [ ] Extend exposed API, improve test coverage.
  • [X] Migrate away from shell scripts.
  • [X] Support Windows and MacOS platforms.
  • [X] Switch to downloading and verifying the pre-built binary instead of building it from scratch.
  • [X] Publish the alpha version of the package.
  • [ ] Publish the generally available version of the package.

Release procedure

See DEMPLOYMENT.md.