This is the project for CSC311 Fall2022 (Introduction to Machine Learning), taught by Rahul Krishnan and Alice Gao.
It is build on code provided https://www.cs.toronto.edu/~rahulgk/courses/csc311_f22/index.html#project.
In this project, we implemented various machine learning algorithms to predict students' correctness of a given diagnostic question.
In part A, we explored three different approaches for our project, namely KNN, IRT (Item Response Theory), and Neural Networks. Additionally, we implemented an ensemble method for IRT to enhance the stability and accuracy of our base model.
In part B, we extended the IRT algorithm to further improve its accuracy and rigorously tested its performance.
All code can be found in /starter_code.
Results and analysis are in final_report.pdf.