- Year 2022
- NSF Award #1949831
- Registration Current Noyce Scholar
- First Name Justin
- Last Name Vollmuth
- Discipline Mathematics
- Institution Augustana College
Abstract
In the field of education, data is constantly being collected, such as test scores, spending and demographics… but what can we do with it? Oftentimes it is too big and too messy so it is just set aside. The availability of this data and computing power is increasing as time goes on. In our project, we plan to learn Supervised Machine Learning methods and how to evaluate their effectiveness in identifying features that lead to success in our educational system. The Supervised Learning methods we plan to use and compare are Linear methods, Naïve Bayes, Decision Tree, Random Forest, K Nearest Neighbor and Support Vector Machine. We will also learn preprocessing techniques, such as scaling and dimension reduction, that will make these methods more effective.
