Trusted-AI/AIF360
AI Fairness 360 is an IBM Research toolkit for detecting and mitigating bias in machine learning models during the AI application lifecycle.
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The toolkit provides a comprehensive set of metrics to test datasets and models for biases, along with explanations for these metrics and algorithms to mitigate detected bias. Available in both Python and R, it supports extensibility through community contributions and targets application domains including finance, healthcare, human capital management, and education.
Frequently asked
- What is Trusted-AI/AIF360?
- AI Fairness 360 is an IBM Research toolkit for detecting and mitigating bias in machine learning models during the AI application lifecycle.
- Is AIF360 open source?
- Yes — Trusted-AI/AIF360 is open source, released under the Apache-2.0 license.
- What language is AIF360 written in?
- Trusted-AI/AIF360 is primarily written in Python.
- How popular is AIF360?
- Trusted-AI/AIF360 has 2.8k stars on GitHub.
- Where can I find AIF360?
- Trusted-AI/AIF360 is on GitHub at https://github.com/Trusted-AI/AIF360.