From 10a7d1178ecb68a8d66e04e68fe377d160c9b364 Mon Sep 17 00:00:00 2001 From: Rayid Ghani Date: Tue, 26 Mar 2024 09:19:39 -0400 Subject: [PATCH] Update README.md --- README.md | 10 +++++----- 1 file changed, 5 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index a9cd60f0..968803c0 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -# *Aequitas*: Bias Auditing & Fair ML Toolkit +# *Aequitas*: Bias Auditing & "Correction" Toolkit [![](https://pepy.tech/badge/aequitas)](https://pypi.org/project/aequitas/) [![License: MIT](https://badgen.net/pypi/license/aequitas)](https://github.com/dssg/aequitas/blob/master/LICENSE) @@ -14,7 +14,7 @@ For more context around dealing with bias and fairness issues in AI//ML systems, > > **Version 1.0.0: Aequitas Flow - Optimizing Fairness in ML Pipelines** > -> Explore Aequitas Flow, our latest update in version 1.0.0, designed to enrich Fair ML experimentation with new, streamlined capabilities. Elevate your ML fairness journey today. +> Explore Aequitas Flow, our latest update in version 1.0.0, designed to augment bias audits with bias mitigation and allow enrich experimentation with Fair ML methods using our new, streamlined capabilities. > @@ -40,11 +40,11 @@ or pip install git+https://github.com/dssg/aequitas.git ``` -### 📔Example Notebooks +### 📔Example Notebooks supporting various tasks and workflows | Notebook | Description | |-|-| -| [Audit a Model's Predictions](https://colab.research.google.com/github/dssg/aequitas/blob/notebooks/compas_demo.ipynb) | Check how to do an in-depth bias audit with the COMPAS example notebook. | +| [Audit a Model's Predictions](https://colab.research.google.com/github/dssg/aequitas/blob/notebooks/compas_demo.ipynb) | Check how to do an in-depth bias audit with the COMPAS example notebook or use your own data. | | [Correct a Model's Predictions](https://colab.research.google.com/github/dssg/aequitas/blob/notebooks/aequitas_flow_model_audit_and_correct.ipynb) | Create a dataframe to audit a specific model, and correct the predictions with group-specific thresholds in the Model correction notebook. | | [Train a Model with Fairness Considerations](https://colab.research.google.com/github/dssg/aequitas/blob/notebooks/aequitas_flow_experiment.ipynb) | Experiment with your own dataset or methods and check the results of a Fair ML experiment. | | [Add your method to Aequitas Flow](https://colab.research.google.com/github/dssg/aequitas/blob/notebooks/aequitas_flow_add_method.ipynb) | Learn how to add your own method to the Aequitas Flow toolkit. | @@ -84,7 +84,7 @@ audit.disparity_plot(attribute="sens_attr_2", metrics=["fpr"]) ``` -### 🧪 Quickstart on Fair ML Experimenting +### 🧪 Quickstart on experimenting with Bias Reduction (Fair ML) methods To perform an experiment, a dataset is required. It must have a label column, a sensitive attribute column, and features.