The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

The latest trends in software development from the Computer Weekly Application Developer Network. This is a guest post for the Computer Weekly Developer Network written by Yana Yelina in her role as ...

Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...

In a recent write-up, [David Delony] explains how he built a Wolfram Mathematica-like engine with Python. Core to the system is SymPy for symbolic math support. [David] said being able to work ...

When Gaussian errors are inappropriate in a multivariate linear regression setting, it is often assumed that the errors are iid from a distribution that is a scale mixture of multivariate normals.

We show that the homotopy algorithm of Osborne, Presnell, and Turlach (2000), which has proved such an effective optimal path following method for implementing Tibshirani's "lasso" for variable ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of k-nearest neighbors regression to predict a single numeric value. Compared to other machine learning ...