In this article, a Bayesian model for a constrained linear regression problem is studied. The constraints arise naturally in the context of predicting the new crop of apples for the year ahead. We ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

Another investigation has applied additive Gaussian process regression models to longitudinal data analysis, bringing to light the ability of Bayesian methods to elucidate complex spatial ...