Author Archives: jamesdmccaffrey

I wrote an article titled “Quadratic Regression with Pseudo-Inverse Training Using C#” in the May 2026 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2026/05/01/quadratic-regression-with-pseudo-inverse-training-using-csharp.aspx. The goal of a machine learning regression problem is to predict a single numeric value. For … Continue reading →

I write code almost every day. Like many skills, writing code is something that must be practiced, and anyway, I just enjoy writing code. One morning before work, I figured I’d run the well-known Diabetes Dataset through an AdaBoost regression … Continue reading →

In machine learning, to train a linear model (linear regression, quadratic regression, etc.) you can use several techniques including stochastic gradient descent (SGD), L-BFGS optimization, and pseudo-inverse. There are two main categories of pseudo-inverse algorithms for machine learning scenarios where … Continue reading →

Bottom line: When using linear regression on data that has categorical predictor variables, you must use drop-first encoding instead of one-hot encoding if you train the model using a closed form pseudo-inverse technique (left pseudo-inverse, Moore-Penrose pseudo-inverse). If you use … Continue reading →

I write code almost every day. Like many activities, writing code is a skill that must be practiced, plus I just enjoy writing code. And in the emerging world of AI-generated software, it’s still important to write code by hand … Continue reading →

The goal of a machine learning regression model is to predict a single numeric value. For example, you might want to predict a person’s credit score based on age, annual income, bank account balance, and so on. Common regression techniques … Continue reading →

One Sunday morning, I figured I’d refactor one of my implementations of matrix pseudo-inverse via normal equations, sometimes called the left pseudo-inverse. The technique is not a general purpose pseudo-inverse such as the Moore-Penrose pseudo-inverse — it is used in … Continue reading →