Women in Math • Directed Reading Program • An Introduction to Explainable AI

Please note: This seminar will take place in DC 1304.

Jaimee Yeung, Sanika Poojary, Undergraduate computer science students
David R. Cheriton School of Computer Science

Mentor: Trang Bui

Artificial intelligence is quickly seeping its way into society, and will soon have a huge influence on how decisions are made. While useful and impactful, the technicalities behind the machine learning models are very complex and hard to understand for an end user. It is important to be able to explain the predictions of an AI model for maintaining transparency and allowing for less error.

This project will experiment with a few basic machine learning models to predict early classification of diabetes. We focus on permutation feature importance on extracting the important characteristics and symptoms that signal for the diagnosis of diabetes.