Bias and Fairness in Machine Learning, Part 3: building a bias-aware model

Let's begin to construct a more bias-aware model using two feature engineering techniques. We will begin by applying a familiar transformation to construct a new less-biased column and then move on to our feature extraction method of the book. Our goal is to minimize the bias of our model without sacrificing a great deal of model performance. We're going to do something similar to the box-cox transformation to transform some of our features in order to make them appear more normal. To set up why we have to investigate the reasons for which our model is under-predicting recidivism for non-African-American people.