Arnold Stromberg, Ph.D., Department of Statistics, University of Kentucky

"Better Prediction Using Machine Learning and Regression Models"

Abstract: Using real data, we’ll discuss how to decide if machine learning and/or regression models are appropriate for prediction, then we’ll do the analyses. Finally, we’ll discuss how to present results from these analyses in ways that are useful to our collaborators.

Biosketch: Dr. Stromberg is a professor and past department chair of Department of Statistics at University of Kentucky, as well as current chair of the ASA Caucus of Academic Representatives. He completed his doctorate in Statistics at University of North Carolina at Chapel Hill in 1989. His research interests are in Statistical Bioinformatics, Computational Statistics, Nonlinear Models and Shiny application for Feasible Solution Algorithm.

Schedule: Seminar begins at 10:30. Free lunch and discussion to follow.

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