Dataset: COMPAS Recidivism Algorithm

[pbiecek]

Problem

This is a regression problem. On the basis of historical data, models (of varying degrees of complexity) should be developed to predict the COMPAS scores. The best models should be explained using XAI tools at the instance level and at the data set level.

Data

COMPAS Recidivism Risk Scores are suspected of being biased https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm. Let's check this. The data can be downloaded from the propublica website. https://github.com/propublica/compas-analysis

Example solution

An interesting description of performed analysis can be found here: https://github.com/propublica/compas-analysis/blob/master/Compas%20Analysis.ipynb and here https://www.propublica.org/article/how-we-analyzed-the-compas-recidivism-algorithm

[marta-generation]

So much can be done using this flagship data set for ML fairness! If anyone's interested in this project - ping me on Slack, happy to support :)