https://github.com/jakevdp/siglearn

Tools for machine learning & modeling with noisy data
https://github.com/jakevdp/siglearn

Last synced: 24 days ago
JSON representation

Tools for machine learning & modeling with noisy data

• Host: GitHub
• URL: https://github.com/jakevdp/siglearn
• Owner: jakevdp
• License: bsd-2-clause
• Created: 2015-06-12T17:38:37.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2015-06-12T21:34:42.000Z (over 9 years ago)
• Last Synced: 2024-10-05T01:21:00.076Z (about 1 month ago)
• Language: Python
• Size: 141 KB
• Stars: 10
• Watchers: 4
• Forks: 4
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
siglearn: Noisy Machine Learning

================================

Siglearn is an experimental repository for providing a well-defined,

scikit-learn-style API for performing modeling and machine learning tasks

on noisy data.

Often in scientific detector data, we have some estimate of the error in

observed points. Unfortunately, most classic machine learning approaches

are not built with data errors in mind. Siglearn is an attempt to begin

collecting implementations of algorithms which do handle data errors.

The code is very much under development; if you're interested in helping,

I would love your contribution!