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https://github.com/shengyuan-lu/cs-178-project

Project for CS 178 Machine Learning and Data Mining. (Course)
https://github.com/shengyuan-lu/cs-178-project

cs-178 data-mining machine-learning uc-irvine

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Project for CS 178 Machine Learning and Data Mining. (Course)

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# CS-178-Project

Compare the effectiveness of K-Nearest Neighbors (KNN), Logistic Regression, Feed-Forward Neural Networks (FNN), and Decision Tree, on the Fashion-MNIST dataset.

## Setup
1. Git Clone
2. Download the [Fashion-MNIST](https://github.com/zalandoresearch/fashion-mnist) dataset, unzip, put the `data` folder under the root folder of this project.

## Report
![Report-01](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/db288b8b-c178-488d-b64c-1434ab471f3c)
![Report-02](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/eab75d92-c0f5-447d-ad31-c819790fa512)
![Report-03](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/fe848a18-0677-4a05-8cf6-91df3d40a4a9)
![Report-04](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/8979bcb2-0f69-4fee-9bf9-6a7c06e6be71)
![Report-05](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/f8ac1640-ee1e-40f6-8dfe-b33003660031)
![Report-06](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/03b9656b-304d-41e9-9a98-5f7693766537)
![Report-07](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/dc4844f0-73fd-42ec-a9d5-619609fe8e1f)
![Report-08](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/f580b632-bf71-461f-8e3a-bade14860808)
![Report-09](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/d4f438b6-bd73-49ed-ad77-667e5b7cb202)
![Report-10](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/f8780b04-01e3-4b0f-8cb1-d04e17230606)
![Report-11](https://github.com/shengyuan-lu/CS-178-Project/assets/70995597/caf9c373-dba6-4bba-8baf-08620869b958)

## Contributors
- [Chi Zhang](https://github.com/Somdit)
- [Shengyuan Lu](https://www.shengyuan-lu.com/)
- [Kaiyuan Hu](https://github.com/kaiyuanh2)