https://github.com/shahzadmustafa15/dbscan-clustering

DBSCAN clustering algorithm applied on synthetic non-linear data (make_moons dataset).
https://github.com/shahzadmustafa15/dbscan-clustering

data-science data-visualization dbscan-clustering density-based-clustering machine-learning ml-projects python scikit-learn unsupervised-learning

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DBSCAN clustering algorithm applied on synthetic non-linear data (make_moons dataset).

• Host: GitHub
• URL: https://github.com/shahzadmustafa15/dbscan-clustering
• Owner: shahzadmustafa15
• License: mit
• Created: 2025-10-02T13:51:07.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2025-10-02T13:53:28.000Z (9 months ago)
• Last Synced: 2025-10-02T15:29:06.072Z (9 months ago)
• Topics: data-science, data-visualization, dbscan-clustering, density-based-clustering, machine-learning, ml-projects, python, scikit-learn, unsupervised-learning
• Language: Jupyter Notebook
• Homepage:
• Size: 95.7 KB
• Stars: 0
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# DBSCAN Clustering on make_moons Dataset

This mini-project applies the **DBSCAN** clustering algorithm to a synthetic non-linear dataset generated using `make_moons`. It demonstrates how DBSCAN can identify arbitrarily shaped clusters and noise.

## Highlights

- Uses `DBSCAN` from `scikit-learn`

- Dataset: `make_moons` with Gaussian noise

- Visualization with `matplotlib` and `seaborn`

- No need to specify number of clusters in advance

- Detects noise points automatically

## Output

Two plots:

1. Original dataset without clustering

2. Clustering result with color-coded labels