Exponential Smoothing Forecasts in SAS and JMP
An example-oriented seminar (with some theory) explores the simpler, but still popular, techniques for time series forecasting.. It will cover simple exponential smoothing, double exponential smoothing, linear exponential smoothing, dampen trend exponential smoothing, additional and multiplicative forms of seasonal exponential smoothing, as well as the winters multiplicative and additive models. Time will be spent on practical suggestions for making cost-effective forecasts, and on some political techniques to help get forecasts adopted.
Decision Trees and Neural Nets in SAS and JMP
This talk explores theory and practice for several of the “trending” machine learning techniques. Using pictures and examples (and some theory), this talk explores decision trees, regression trees, bootstrap forest, boosted trees, neural nets, deep neural nets, naïve Bayesian classifiers/regressors, as well as the KNN algorithm.
About the Instructor
Russ Lavery is a frequent and multiple award-winning presenter at SAS user groups. He has been a technical reviewer on five books on SAS and statistical topics. He has over 25 years of experience using SAS and is still studying. Russ is a contractor and lives outside Philadelphia, PA, where he occasionally teaches as an adjunct in the Drexel University analytic program and dances frequently.