DBSCAN: Density-Based Spatial Clustering of Applications with Noise, Technique Exploration

Author: Maciej Kuchciak
Date: January 2024

DBSCAN Technique Exploration RPubs link

GitHub Pages link to project

This project explores the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) clustering technique, applied to a synthetic dataset. DBSCAN is a powerful method for identifying arbitrary-shaped clusters and noise/outliers.

Project Overview

DBSCAN is a clustering algorithm that excels at identifying clusters of varying shapes and handling noise in data. This project demonstrates how DBSCAN works, including:

• Cluster detection in datasets with different densities.
• Noise and outlier identification.
• Visualization of the clustering process, including epsilon-neighborhood reachability and k-distance graphs.
• Use of a synthetic dataset to showcase DBSCAN’s flexibility and robustness.

Project Files

dbscan-exploration/
├── README.md
├── LICENSE
├── DBSCAN.Rproj
├── .gitignore
├── Clustering.Rmd
├── docs/
│   ├── index.md                 # Main page (formerly Clustering.md)
│   ├── _config.yml              # Jekyll config for GitHub Pages
│   ├── Clustering_files/        # Figures and generated files
│   │   └── figure-gfm/
│   │       └── plotting-1.png   # Images and figures
│   ├── images/                  # Extra project images
└── Clustering_files/
    └── figure-gfm/              # Generated figures

Getting Started

To replicate this analysis, you need to install the required R packages and set up your environment:

Prerequisites:

R (>= 4.0) RStudio (Optional but recommended) r Copy code

Install necessary packages

if (!requireNamespace("Rtsne", quietly = TRUE)) install.packages("Rtsne") if (!requireNamespace("ggplot2", quietly = TRUE)) install.packages("ggplot2") if (!requireNamespace("magick", quietly = TRUE)) install.packages("magick")

License

This project is licensed under the GNU General Public License v3.0 (GPL-3.0). You are free to modify, share, and use this project under the terms of the GPL-3.0 license. If you distribute modified versions of this work, you must release them under the same license.

Contributing

Contributions are welcome! If you have suggestions or improvements, feel free to open an issue or submit a pull request.