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At a Nextmv tech talk a couple weeks ago, I showed a least absolute deviations (LAD) regression model using OR-Tools. This isn’t new – I pulled the formulation from Rob Vanderbei’s “Local Warming” paper, and I’ve shown similar models at conference talks in the past using other modeling APIs and solvers. There are a couple reasons I keep coming back to this problem. One is that it’s a great example of how to build a machine learning model using an optimization solver. Unless you have an optimization background, it’s probably not obvious you can do this. Building a regression or classification model with a solver directly is a great way to understand the model better. And you can customize it in interesting ways, like adding epsilon insensitivity. ...