Function to create AIF compatible dataset.
Usage
binary_label_dataset(data_path, favor_label, unfavor_label,
unprivileged_protected_attribute,
privileged_protected_attribute,
target_column, protected_attribute)Arguments
- data_path
Path to the input CSV file or a R dataframe.
- favor_label
Label value which is considered favorable (i.e. “positive”).
- unfavor_label
Label value which is considered unfavorable (i.e. “negative”).
- unprivileged_protected_attribute
A unprotected attribute value which is considered privileged from a fairness perspective.
- privileged_protected_attribute
A protected attribute value which is considered privileged from a fairness perspective.
- target_column
Name describing the label.
- protected_attribute
A feature for which fairness is desired.
Examples
if (FALSE) {
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")
}