Library Building (LIB)
3287 University Way, Kelowna
This workshop will introduce Generalized Additive Models (GAMs), which allow one to fit models that are complex and nonlinear but easily interpretable, unlike many “black-box” machine learning models.
By the end of this session, participants will be able to fit GAMs in R using the mgcv package and understand the advantages of GAMs over GLMs and LMs.