compas.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/compas.R
\docType{data}
\name{compas}
\alias{compas}
\title{Modified COMPAS dataset}
\format{
A data frame with 6172 rows and 9 variables:
\describe{
  \item{Two_yr_Recidivism}{factor, yes/no for recidivism or no recidivism. This is the outcome or target in this dataset}
  \item{Number_of_Priors}{numeric, number of priors, normalized to mean = 0 and standard deviation = 1}
  \item{Age_Above_FourtyFive}{factor, yes/no for age above 45 years or not}
  \item{Age_Below_TwentyFive}{factor, yes/no for age below 25 years or not}
  \item{Female}{factor, female/male for gender}
  \item{Misdemeanor}{factor, yes/no for having recorded misdemeanor(s) or not}
  \item{ethnicity}{factor, Caucasian, African American, Asian, Hispanic, Native American or Other}
  \item{probability}{numeric, predicted probabilities for recidivism, ranges from 0 to 1}
  \item{predicted}{numeric, predicted values for recidivism, 0/1 for no/yes}
}
}
\source{
The dataset is downloaded from Kaggle \url{https://www.kaggle.com/danofer/compass} and has undergone modifications (e.g. ethnicity was originally encoded using one-hot encoding, number or priors have been normalized, variables have been renamed, prediction model was fit and predicted probabilities and predicted status were concatenated to the original dataset).
}
\usage{
compas
}
\description{
\code{\link{compas}} is a landmark dataset to study algorithmic (un)fairness. This data was used to
predict recidivism (whether a criminal will reoffend or not) in the USA. The tool was meant to overcome
human biases and offer an algorithmic, fair solution to predict recidivism in a diverse population.
However, the algorithm ended up propagating existing social biases and thus, offered an unfair algorithmic
solution to the problem. In this dataset, a model to predict recidivism has already been fit and predicted
probabilities and predicted status (yes/no) for recidivism have been concatenated to the original data.
}
\keyword{datasets}