JSTOR Daily

Learning from a lot: Empirical Bayes for high-dimensional model-based prediction

Empirical Bayes is a versatile approach to “learn from a lot” in two ways: first, from a large number of variables and, second, from a potentially large amount of prior information, for example, ...
technologynetworks

Linear Regression

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 ...
Nature

Gaussian Process Regression‐Based Bayesian Optimisation (G‐BO) of Model Parameters—A WRF Model Case Study of Southeast Australia Heat Extremes

The Nature Index 2025 Research Leaders — previously known as Annual Tables — reveal the leading institutions and countries/territories in the natural and health sciences, according to their output in ...
Visual Studio Magazine

Linear Support Vector Regression Using C# with Particle Swarm Training

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of the linear support vector regression (linear SVR) technique, where the goal is to predict a single numeric ...
Visual Studio Magazine

Logistic Regression with Batch SGD Training and Weight Decay Using C#

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end program that explains how to perform binary classification (predicting a variable with two possible discrete values) using ...