Event sponsored by:
Biostatistics and Bioinformatics
Academic Resource Center (ARC)
BERD Core
Duke Clinical and Translational Science Institute (CTSI)
School of Medicine (SOM)
Contact:
BERD Methods CoreSpeaker:
Amanda Brucker, PhD
Amanda will provide an overview of Extreme Gradient Boosting (XGBoost), a modern machine-learning algorithm, and will walk through an example R workflow that applies XGBoost to a supervised learning task. This seminar will demonstrate how to implement XGBoost along with several benchmark predictive modeling methods, and will compare the methods on predictive performance and interpretability.
Zoom: https://duke.zoom.us/j/99193151349?pwd=a0RaQzdJWEtpcmhZTGQrdmdubWlBUT09
This event is being cross-promoted by the NC BERD Consortium, a collaboration of the CTSA-funded BERD cores at UNC-Chapel Hill, Wake Forest University School of Medicine, and Duke University School of Medicine.