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