EASE (Enhanced AI Scoring Engine) is a library that allows for machine learning based classification of textual content. This is useful for tasks such as scoring student essays.
OpenEdge ABL Python Shell
Latest commit a7890ed Jan 19, 2017 Christina Roberts committed on GitHub Merge pull request #72 from edx/christina/archived
Remove "obsolete", as ease is a requirement of ora2.

Readme.md

EASE

Overview

This is a repo with functions that can score arbitrary free text and numeric predictors. This is licensed under the AGPL, please see LICENSE.txt for details. The goal here is to provide a high-performance, scalable solution that can predict targets from arbitrary values.

Note that this is a library. You will need to implement your own code to make it runnable.

Questions?

Feel free to open an issue in the issue tracker or post to the edx-code mailing list.

How to Contribute

Contributions are very welcome. The easiest way is to fork this repo, and then make a pull request from your fork. The first time you make a pull request, you may be asked to sign a Contributor Agreement.

The current backlog is in the issues section. Please feel free to open new issues or work on existing ones.

Detailed Information

Please look in the docs folder for more detailed documentation. There is a README there that explains how to build and view the docs.

Reporting Security Issues

Please do not report security issues in public. Please email security@edx.org.