A new study presents a machine learning model that accurately predicts the compressive strength of high-strength concrete, ...

The R package rcssci offers an intuitive solution for visualizing Restricted Cubic Splines (RCS) in regression analyses. It automates the generation of spline plots for outcomes like odds ratios (OR), ...

Proper handling of continuous variables is crucial in healthcare research, for example, within regression modelling for descriptive, explanatory, or predictive purposes. However, inadequate methods ...

Nature is marked not only by struggles for survival, but also by remarkable feats of cooperation. From microbes to insects to humans, organisms work together in a variety of ways to gather and share ...

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 ...

Although remnant cholesterol has been associated with cardiovascular disease, the risk of remnant cholesterol and blood pressure remains unclear. This study aimed to investigate the association ...

If the solution of the above equation for zm, zm = &eegr; (z1, ··· ; a1, ···) gives rise to a function &eegr; which is nonlinear in the ai, then one may rely on a version of Gaussian regression [1, 2] ...

The c-regression model is a method that simultaneously performs clustering and regression to obtain regression equations for each cluster and express the overall structure of the dataset. Gaussian ...

On the other hand, polynomial regression is a useful technique when the pattern of the data indicates a nonlinear relationship between the dependent and independent variables. Moreover, higher-degree ...