Using JMP® Pro to Build Models Using Generalized Regression Variable Selection Techniques

Application Area:
Statistics, Predictive Modeling and Data Mining

Learn to fit models using variable selection techniques, including shrinkage techniques that specifically address modeling correlated and high-dimensional data. See how to use Generalized Regression to examine a variety of distributions for responses that are continuous, binomial, counts, or zero-inflated and to compare models obtained using other techniques.

This webinar covers: penalization techniques and adaptive methods; model selection criteria; handling continuous and categorical data; Maximum Likelihood; Forward Selection; Lasso; Double Lasso; Elastic Net; Ridge Regression; and Two-Stage Forward Selection.