Introduction to the COMPAS dataset case study

In the realm of machine learning, where data drives decision-making, the line between algorithmic precision and ethical fairness often blurs. The COMPAS dataset, a collection of criminal offenders screened in Broward County, Florida, during 2013-2014, serves as a poignant reminder of this intricate dance. While, on the surface, it might appear as a straightforward binary classification task, the implications ripple far beyond simple predictions. Each row and feature isn’t just a digit or a class; it represents years, if not decades, of human experiences, ambitions, and lives. As we dive into this case study, we are reminded that these aren’t mere rows and columns but people with aspirations, dreams, and challenges. With a primary focus on predicting recidivism (the likelihood of an offender to re-offend), we’re confronted with not just the challenge of achieving model accuracy but also the monumental responsibility...