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Fairo API

  • Welcome
  • Authentication
    • Create API Access Keys
  • API and System Documentation
  • API Responses

Fairo Metrics

  • Getting Started
    • Installation
    • Create Example Data
    • The Fairness Object
    • Metric Parameters
  • Metrics
    • False Negative Rate
    • False Positive Rate
    • True Negative Rate
    • True Positive Rate
    • Positive Predictive Value
    • False Discovery Rate
    • Negative Predictive Value
    • False Omission Rate
    • Parity Difference
    • Parity Ratio
    • Predictive Parity
    • Conditional Use Accuracy Difference
    • Treatment Equality
    • Equal Odds Difference
    • Average Odds Difference
    • Average Odds Ratio
    • Overall Accuracy
    • Accuracy Difference
    • F-Beta Score
    • Grouped F-Beta
    • F-Beta Difference
    • F-Beta Ratio
    • ROCAUC Score
    • Grouped ROCAUC
    • ROCAUC Difference
    • ROCAUC Ratio
    • Gini Coefficient
    • Theil Index
  • Computing Metric Results Via the API

Fairo Policies

  • Overview

Tutorials

  • Quickstart Guides
    • AI Experiment Tracking
    • AI Testing & Metrics

Interfaces

  • Overview
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Installation

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To install the Fairo metrics package as well as the Fairness object that compliments the metric functions, use the following command to install from PyPi.

pip install fairometrics

Updated over 1 year ago


What’s Next
  • Create Example Data