Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

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 ...
JSTOR Daily

On Expected Error of Randomized Nyström Kernel Regression

Kernel methods are a class of machine learning algorithms which learn and discover patterns in a high (possibly infinite) dimensional feature space obtained by often nonlinear, possibly infinite ...
JSTOR Daily

Prenatal Metal Concentrations and Childhood Cardiometabolic Risk Using Bayesian Kernel Machine Regression to Assess Mixture and Interaction Effects

We estimated linear associations of each metal with individual z scores and used Bayesian Kernel Machine Regression to assess metal mixtures and interactions. Results: Higher total metals were ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using C#

The goal of a machine learning regression problem is to predict a single numeric value. For example, you might want to predict a person's bank savings account balance based on their age, years of ...