A practical guide to SAS Procedures in Viya 4, introducing their purpose, showcasing real-world examples, and highlighting a new downloadable cheat sheet that simplifies navigation across SAS’s advanced analytics portfolio.
A previous article discusses a "Catch-22" paradox for fitting nonlinear regression models: You can't estimate the parameters until you fit the model, but you can't fit the model until you provide an initial guess for the parameters! If your initial guess for the parameters is not good enough, the nonlinear
Hyperparameter autotuning intelligently optimizes machine learning model performance by automatically testing parameter combinations, balancing accuracy and generalizability, as demonstrated in a real-world particle physics use case.
