COMPAS Analysis Using Aequitas
Fairness analysis for machine learning models using COMPAS dataset
Pricing
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→StableLicense
Open Source
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—Overview
What is COMPAS Analysis Using Aequitas?
A tool to analyze and mitigate bias in machine learning models, specifically using the COMPAS recidivism prediction dataset. It helps ensure fairness and transparency in AI decision-making processes.
Key differentiator
“The only tool offering detailed fairness analysis specifically tailored for the COMPAS recidivism prediction dataset, providing a unique angle on algorithmic bias.”
Capability profile
Strength Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
Fit analysis
Who is it for?
✓ Best for
Researchers studying algorithmic fairness using the COMPAS dataset
Teams needing detailed analysis of model biases in recidivism prediction
Educators teaching about machine learning ethics and bias
✕ Not a fit for
Projects requiring real-time fairness analysis
Applications that do not involve the COMPAS dataset or similar structured data
Cost structure
Pricing
Free Tier
None
Starts at
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Model
Flat rate
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None
Performance benchmarks
How Fast Is It?
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Next step
Get Started with COMPAS Analysis Using Aequitas
Step-by-step setup guide with code examples and common gotchas.