Hi,
This repository contains my work for the second project of the GE-461: Introduction to Data Science course.
The project involves dimensionality reduction and data vizualization for MNIST dataset. In order to evaluate the performance, we use a Quadratic Gaussian classifier.
We experiment with Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) in order to determine their effect on classification error.
We use more complex techniques such as Sammon’s mapping, and t-Distributed Stochastic Neighbor Embedding to visualize our high dimensional data in two dimension.
My report can be accessed here: https://xmassmx.github.io/GE-461-Dimensionality-Reduction-and-Data-Visualization/
Note: Please do not copy this work and stay away from plagiarism. The work in this repository is my solution and is meant to be used as a guide only.