Skip to main content

A package to facilitate bias mitigation techniques that work for educationnal data

Project description

DebiasED is a package that groups existing bias mitigation techniques from AIED, EDM, LAK, L@S and FAccT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

debiased-0.1.2.tar.gz (158.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

debiased-0.1.2-py3-none-any.whl (194.9 kB view details)

Uploaded Python 3

File details

Details for the file debiased-0.1.2.tar.gz.

File metadata

  • Download URL: debiased-0.1.2.tar.gz
  • Upload date:
  • Size: 158.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for debiased-0.1.2.tar.gz
Algorithm Hash digest
SHA256 031febbaabd9870b4ffbb9a8bc0b36f20ffa7715f5e366bdf22928954fa48602
MD5 7e866667aceeeb565c0a663a234da980
BLAKE2b-256 8aecf5f32510b750de64ac5ec0b85f356c29e4134bda2af0a846e5d5f2e11283

See more details on using hashes here.

File details

Details for the file debiased-0.1.2-py3-none-any.whl.

File metadata

  • Download URL: debiased-0.1.2-py3-none-any.whl
  • Upload date:
  • Size: 194.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for debiased-0.1.2-py3-none-any.whl
Algorithm Hash digest
SHA256 6045fd94d148b93e2c34641654729a6cde2a850e4bf194bd5730fbe817325086
MD5 f5f26d6dfb324e4c23eff1db0f7f0707
BLAKE2b-256 986611b8073066a8949be1af6f899f3ccaf75439cbe7b16b2e1f031df60b81fc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page