Fairness In ML.pdf

hilda-fairdags.pdf
Preview of Fairness in ML
🔗 Source: ssc.io
📊 Size: 513 KB
👤 Author: Ke Yang, Biao Huang, Julia and Sebastian Schelter
⬇️ Downloads: 141

Summary

Researchers propose fair-DAGs, a library to identify and mitigate bias in machine learning preprocessing pipelines by extracting a directed acyclic graph representation of data flow and instrumenting pipelines with tracing and visualization code to capture changes in data distributions and identify distortions with respect to protected group membership.

Description

Researchers propose fair-DAGs, a library to identify and mitigate bias in machine learning preprocessing pipelines by extracting a directed acyclic graph...

Technical Information

  • File Format: PDF
  • File Size: 513 KB
  • Pages: 4
  • Language: EN
  • Author: Ke Yang, Biao Huang, Julia and Sebastian Schelter
  • Total Downloads: 141
  • Last Updated: 2 weeks ago

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This PDF document about Fairness in ML provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Fairness in ML.

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