Git Product home page Git Product logo

toxic_comment_classification's Introduction

Toxic Comment Classification

This is my codes for the toxic comment classification competition hosted in Kaggle. Fully modified to another level from the base code here

To download datasets please run get_data.sh

The Task

The dataset comprises of comments from Wikipedia’s talk page edits. It is a large number of Wikipedia comments which have been labeled by human raters for toxic behavior. The types of toxicity are:

  • toxic
  • severe_toxic
  • obscene
  • threat
  • insult
  • identity_hate

The Approach

Creating an ensemble model which predicts a probability of each type of toxicity for each comment.Full explaination of my approach is documented here

Install Pre-requisites

run install.sh and then run pip install -r requirements.txt

toxic_comment_classification's People

Contributors

dicksonchin93 avatar

Watchers

 avatar  avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.