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 ...

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 ...

Discover how linear regression works, from simple to multiple linear regression, with step-by-step examples, graphs and real-world applications.

A linear regression is a statistical model that attempts to show the relationship between two variables with a linear equation. A regression analysis involves graphing a line over a set of data ...

Sparse matrix regression (SMR) is a two-dimensional supervised feature selection method that can directly select the features on matrix data. It uses several couples of left and right regression ...

Nonlinear regression modeling is similar to linear regression modeling in that both seek to track a particular response from a set of variables graphically.

In standard linear regression it's usually a mistake to use one-hot encoding because the resulting columns are mathematically correlated, which causes matrix inversion to fail. Standard linear ...