Handling imbalanced datasets in machine learning – Towards Data Science

This post was co-written with Joseph Rocca. Suppose that you are working in a given company and you are asked to create a model that, based on various measurements at your disposal, predicts whether a product is defective or not. You decide to use your favourite classifier, train it on the data and voila: you get a 96.2% accuracy! Your boss is astonished and decides to use your model without any further tests. A few weeks later he enters your office and underlines the uselessness of your model.