README.md

AI Fairness 360 (AIF360) R Package

Overview

The AI Fairness 360 toolkit is an open-source library to help detect and mitigate bias in machine learning models. The AI Fairness 360 R package includes a comprehensive set of metrics for datasets and models to test for biases, explanations for these metrics, and algorithms to mitigate bias in datasets and models.

Installation

Install the CRAN version:

install.packages("aif360")

Or install the development version from GitHub:

# install.packages("devtools")
devtools::install_github("IBM/AIF360/aif360/aif360-r") 

Then, use the install_aif360() function to install AIF360:

library(aif360)
install_aif360()

Getting Started

load_aif360_lib()

# load a toy dataset
data <- data.frame("feature1" = c(0,0,1,1,1,1,0,1,1,0), 
                   "feature2" = c(0,1,0,1,1,0,0,0,0,1),
+                  "label" = c(1,0,0,1,0,0,1,0,1,1))
# format the dataset
formatted_dataset <- aif360::aif_dataset(data_path = data, 
                                          favor_label = 0, 
                                          unfavor_label = 1, 
                                          unprivileged_protected_attribute = 0, 
                                          privileged_protected_attribute = 1, 
                                          target_column = "label", 
                                          protected_attribute = "feature1")

Contributing

If you’d like to contribute to the development of aif360, please read these guidelines.

Please note that the aif360 project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.