Category Archives: JavaScript

One morning before work, I realized that I hadn’t written any JavaScript code for several weeks. For mental exercise, I decided to implement a regression system (to predict a single numeric value), using a neural network with exactly two hidden … Continue reading →

In machine learning, if training data is multicollinear, the interpretability of the resulting model will likely be poor (the details are tricky and out of the scope of this post). Multicollinear data has two or more rows that are highly … Continue reading →

The goal of a machine learning regression problem is to predict a single numeric value. For example, a bank might want to predict the maximum safe loan amount for a customer, based on age, account balance, annual income, and so … Continue reading →

I wrote an article titled “Decision Tree Regression from Scratch Using JavaScript” in the April 2026 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2026/04/01/decision-tree-regression-from-scratch-using-javascript.aspx. Decision tree regression is a machine learning technique that incorporates a set of if-then rules in … Continue reading →

Decision tree regression is a machine learning technique that incorporates a set of if-then rules in a tree data structure to predict a single numeric value. For example, a decision tree regression model prediction might be, “If employee age is … Continue reading →

Decision tree regression is a machine learning technique that incorporates a set of if-then rules in a tree data structure to predict a single numeric value. For example, a decision tree regression model prediction might be, “If employee age is … Continue reading →

I wrote an article titled “Quadratic Regression with SGD Training Using JavaScript” in the March 2026 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2026/03/11/quadratic-regression-with-sgd-training-using-javascript.aspx. The goal of a machine learning regression problem is to predict a single numeric value. For … Continue reading →

Bottom line: I implemented SVD using the Householder + QR algorithm, with JavaScript. The implementation works but it’s not as stable as my implementation that uses the Jacobi algorithm. In other words, the code in this post is interesting, but … Continue reading →

The goal of machine learning regression problem is to predict a single numeric value. For example, you might want to predict an employee’s salary based on age, height, high school grade point average, and so on. There are approximately a … Continue reading →

I wrote an article titled “Linear Regression with Pseudo-Inverse Training Using JavaScript” in the February 2026 edition of Microsoft Visual Studio Magazine. See https://visualstudiomagazine.com/articles/2026/02/02/linear-regression-with-pseudo-inverse-training-using-javascript.aspx. The goal of a machine learning regression problem is to predict a single numeric value. For … Continue reading →