These are the slides and journal that I used in my tutorial "Variable selection made easy using the Generalized Regression platform in JMP Pro".
Variable selection is the process of selecting a subset of relevant variables or predictors to use in modeling the response. It is a crucial task that yields simpler models that generalize better to new data, but it does not have to be a difficult process. The Generalized Regression ("Genreg") platform in JMP Pro enables you to do variable selection quickly, easily and interactively in a variety of settings (including least squares, logistic and Poisson regression). We will review the variable selection techniques available within Genreg (forward selection, Lasso and more) and then look at how the platform makes these techniques easy to employ. Examples will range from designed experiments to predictive modeling.