Our speakers for the night will be Elizabeth Mauer & Kat Hoffman from Weill Cornell Medicine. Elizabeth will be talking about parameterized reporting in R Markdown. Kat will be discussing the Superlearner machine learning algorithm using the sl3 package.
6:30-6:45 pm Introductions & Social
6:45-6:55 pm R-Ladies New York Announcements
6:55-7:25 pm Parameterized Reporting in R Markdown
7:25-7:55 pm Become a Superlearner: Using sl3 to build ensemble learning models
7:55-8:00 pm Community Announcements
8:00-8:30 pm Networking
Title: Parameterized Reporting in R Markdown
Abstract: Elizabeth's talk will focus on how to take customizability of your R Markdown reports to the next level with the help of parameters. Parameters allow the user to change certain aspects of their report without having to go back & make changes within the R Markdown document itself. This is very helpful when producing the same report but under different conditions/assumptions.
Title: Become a Superlearner: Using sl3 to build ensemble learning models
Abstract: Kat will discuss ensemble machine learning in R. Ensemble models combine multiple models to create a stronger overall prediction model. She will give an overview of ensemble learning methods & the packages available in R. She will then focus on understanding & using one algorithm for ensemble learning - stacking, or superlearning - through the R package sl3
Bios: Elizabeth Mauer & Kat Hoffman are research biostatisticians in the Division of Biostatistics & Epidemiology at Weill Cornell Medicine. They engage in short-term & long-term bio-statistical consultations with investigators throughout different departments of New York Presbyterian/Weill Cornell Medical Center. Elizabeth received her Masters from Temple University & her Bachelors from the University of Scranton (home of the show The Office!). Kat received her Masters from the University of Michigan & her Bachelors from the University of Detroit Mercy.