Monthly Archives: January 2025

I wrote an article titled “Gradient Boosting Regression Using C#” in the January 2025 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/Articles/2025/01/15/Gradient-Boosting-Regression-Using-CSharp.aspx. A machine learning gradient boosting regression system, also called a gradient boosting machine (GBM), predicts a single numeric … Continue reading →

Recently, I had been taking an extended look into implementing various machine learning regression algorithms using C# — linear regression, k-nearest neighbors regression, kernel ridge regression, Gaussian process regression, AdaBoost regression, gradient boosting regression, random forest regression, Poisson regression, naive … Continue reading →

I put together a demo of an old regression technique called naive Bayes regression. Naive Bayes regression is essentially a variation of basic linear regression. In simple linear regression, there is a single predictor variable x, and a single target … Continue reading →

Finding the inverse of a matrix is one of the most difficult problems in numerical programming. There are dozens of algorithms, each with pros and cons. One of the oldest and simplest techniques is to use the Newton iteration algorithm. … Continue reading →