AIF360

Fairness metrics for datasets and machine learning models.

EstablishedOpen SourceLow lock-in

Pricing

See website

Flat rate

Adoption

Stable

License

Open Source

Data freshness

Overview

What is AIF360?

A comprehensive set of fairness metrics to evaluate the bias in datasets and machine learning models, crucial for ensuring ethical AI practices.

Key differentiator

The only open-source library that provides a wide range of fairness metrics and tools for both datasets and machine learning models.

Capability profile

Strength Radar

Comprehensive fa…Supports multipl…Extensive docume…

Honest assessment

Strengths & Weaknesses

↑ Strengths

Comprehensive fairness metrics for datasets and models

Supports multiple types of bias detection

Extensive documentation and examples

Fit analysis

Who is it for?

✓ Best for

Teams needing to ensure their ML models are fair and unbiased

Organizations that require detailed fairness metrics for regulatory compliance

✕ Not a fit for

Projects where real-time bias detection is required (AIF360 is primarily a post-training evaluation tool)

Applications with very limited computational resources, as AIF360 can be resource-intensive

Cost structure

Pricing

Free Tier

None

Starts at

See website

Model

Flat rate

Enterprise

None

Performance benchmarks

How Fast Is It?

Ecosystem

Relationships

Alternatives

Next step

Get Started with AIF360

Step-by-step setup guide with code examples and common gotchas.

View Setup Guide →