Figure 3 - Flowchart of the methodology applied
In the former methodology, clustering techniques were applied to find peer groups using a small subset of features from the same initial pool, and in the first approach after having applied the linear and nonlinear models , the score was calculated inside every cluster; in the second approach the predictive models were applied in every cluster to later assigned the score within the cluster as well.
As at the end, the features used were the same in both cases, it was prove that it was not only not helping but distorting the fairness. Moreover, using clustering techniques was a method to get a better performance of the predictive method but at the end it doesn’t improve. However, it is still interesting to discuss the process that it can be implemented in a future work.