An MCSP Conversation Series Talk: "Applications of Supervised Learning Techniques on Undergraduate Admissions Data"

Come hear MCSP students Thomas Lux, Randall Pittman, and Maya Shende talk about how computer algorithms could help the admissions process at Roanoke and other colleges! Abstract: In making undergraduate admissions decisions, colleges and universities must take a large amount of data into consideration for each applicant. We discuss the use of supervised machine learning techniques, namely perceptions, in predicting admission decisions and enrollment based on historical applicant data. Such predictions can help effectively distribute Admissions' resources (counselors' time and energy) across applicants, and inform admissions offices of the significance of applicant features relative to acceptance and enrollment.