Authors: Aatmun Baxi, Andy Chen, Johnny Mo, and Abhi Vemulapati
This repository contains the total sum of the work done for our final project for Math 156. This includes the LaTeX source and compiled PDFs for the proposal, report, and slides for the report, and the Python notebook of our implementations (all .py files are scripts that we used for testing).
The purpose of the project is to gain a strong mathematical understanding of the linear discriminant analysis (LDA) model for two problems in machine learning: classifcation problems and dimesionality reduction. We will present the mathematical formalities of the LDA and give two main application: one for classification of stars and one for dimensionality reduction of chest X-ray images of pneumonia patients, with extra applications that further describe the strengths and weaknesses of the model.
Note: The image datasets are not present in this repository, but a text file on how to recreate the directory structure so the code will run properly is available in the source/data directory.
Ensure git has been installed and run the following command inside the directory you'd like this repository to live in:
git clone https://github.com/warewaware/LDA156FinalProj
Click the dropdown menu of the green Code button above the repository contents and choose Download ZIP. Extract in your desired location.