Matlab_DBSCAN_K-Means

Project Description

This project focuses on using and visualizing data clustering techniques in MATLAB AppDesigner. The implementation includes both DBSCAN and K-Means clustering algorithms.

Project Structure

Group 2 - Matlab_Project.zip
├── Group 2_Presentation.pptx
├── Group 2_Report.pdf
├── Group 2_readme.txt
└── Code
    ├── application.mlapp
    ├── DBSCANClusteringApp.mlapp
    ├── HomePage.mlapp
    └── Kmeansapp.mlapp

Code Overview

• HomePage.mlapp: Serves as the home page for the application.
• application.mlapp: Handles the generation and visualization of data.
• DBSCANClusteringApp.mlapp: Implements the DBSCAN clustering algorithm.
• Kmeansapp.mlapp: Implements the K-Means clustering algorithm.

Documentation

• Group 2_Report.pdf: Contains the detailed project report.
• Group 2_Presentation.pptx: Includes the project presentation slides.

Instructions

1. Extract the contents of the provided ZIP file.
2. Open the MATLAB files (HomePage.mlapp, application.mlapp, DBSCANClusteringApp.mlapp, Kmeansapp.mlapp) using MATLAB AppDesigner.
3. Refer to Group 2_Report.pdf and Group 2_Presentation.pptx for detailed explanations, insights, and project outcomes.

Requirements

• MATLAB with AppDesigner support.
• Required MATLAB toolboxes for clustering algorithms (if applicable).

License

This project is for educational purposes. Feel free to modify and use it as needed.