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% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/dataset.R
\name{binary_label_dataset}
\alias{binary_label_dataset}
\title{AIF360 dataset}
\usage{
binary_label_dataset(data_path, favor_label, unfavor_label,
unprivileged_protected_attribute,
privileged_protected_attribute,
target_column, protected_attribute)
}
\arguments{
\item{data_path}{Path to the input CSV file or a R dataframe.}
\item{favor_label}{Label value which is considered favorable (i.e. “positive”).}
\item{unfavor_label}{Label value which is considered unfavorable (i.e. “negative”).}
\item{unprivileged_protected_attribute}{A unprotected attribute value which is considered privileged from a fairness perspective.}
\item{privileged_protected_attribute}{A protected attribute value which is considered privileged from a fairness perspective.}
\item{target_column}{Name describing the label.}
\item{protected_attribute}{A feature for which fairness is desired.}
}
\description{
Function to create AIF compatible dataset.
}
\examples{
\dontrun{
load_aif360_lib()
# Input dataset
data <- data.frame("feat" = c(0,0,1,1,1,1,0,1,1,0), "label" = c(1,0,0,1,0,0,1,0,1,1))
# Create aif compatible input dataset
act <- aif360::binary_label_dataset(data_path = data, favor_label=0, unfavor_label=1,
unprivileged_protected_attribute=0,
privileged_protected_attribute=1,
target_column="label", protected_attribute="feat")
}
}
\seealso{
\href{https://aif360.readthedocs.io/en/latest/modules/datasets.html#binary-label-dataset}{More about AIF binary dataset.}
}
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