aif360.algorithms.preprocessing.Reweighing

class aif360.algorithms.preprocessing.Reweighing(unprivileged_groups, privileged_groups)

Reweighing is a preprocessing technique that Weights the examples in each (group, label) combination differently to ensure fairness before classification [4].

References

[4]

F. Kamiran and T. Calders, “Data Preprocessing Techniques for Classification without Discrimination,” Knowledge and Information Systems, 2012.

Parameters:

• unprivileged_groups (list(dict)) – Representation for unprivileged group.

• privileged_groups (list(dict)) – Representation for privileged group.

Methods

fit	Compute the weights for reweighing the dataset.
fit_predict	Train a model on the input and predict the labels.
fit_transform	Train a model on the input and transform the dataset accordingly.
predict	Return a new dataset with labels predicted by running this Transformer on the input.
transform	Transform the dataset to a new dataset based on the estimated transformation.

__init__(unprivileged_groups, privileged_groups)

Parameters:

• unprivileged_groups (list(dict)) – Representation for unprivileged group.

• privileged_groups (list(dict)) – Representation for privileged group.

fit(dataset)

Compute the weights for reweighing the dataset.

Parameters:

dataset (BinaryLabelDataset) – Dataset containing true labels.

Returns:

Reweighing – Returns self.

transform(dataset)

Transform the dataset to a new dataset based on the estimated transformation.

Parameters:

dataset (BinaryLabelDataset) – Dataset that needs to be transformed.

Returns:

dataset (BinaryLabelDataset) –

Dataset with transformed

instance_weights attribute.