Dataset Bias

Computes the bias of a dataset.

Inputs

• Data: dataset to be evaluated

Dataset Bias computes and displays the bias of a dataset. More specifically, it computes the disparate impact and statistical parity difference metrics for the dataset.
The ideal threshold is 1.0 for disparate impact and 0.0 for statistical parity difference. Values under the ideal threshold indicate bias towards the unprivileged group. Values above the ideal threshold indicate bias towards the privileged group.

Example

This example shows a very simple use of the Dataset Bias widget. First we load one of the fairness datasets, in this case the Adult dataset. Then we connect the dataset to the Dataset Bias widget. The widget displays the disparate impact and statistical parity difference metrics for the dataset.

Note, we did not use the As Fairness Data widget before using the Dataset Bias widget. This is because the Adult dataset already has the required fairness meta-attributes added to it.

Another thing to note is that the Dataset Bias widget (and other fairness widgets) do not support missing values, this is indicated by the warning icon above the widget. Any missing values in the dataset will automatically be imputed with the average or most frequent value before being used by the widget.