https://github.com/alessioborgi/Clustering-Deepening

An in-depth exploration of clustering algorithms and techniques in machine learning, with applications focus on Object Tracking and Image Segmentation.
https://github.com/alessioborgi/Clustering-Deepening

clustering db-index dbscan gmm jupiter k-medians k-medoids kmeans kmeanspp mean-shift notebook python rand-index

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An in-depth exploration of clustering algorithms and techniques in machine learning, with applications focus on Object Tracking and Image Segmentation.

• Host: GitHub
• URL: https://github.com/alessioborgi/Clustering-Deepening
• Owner: alessioborgi
• License: mit
• Created: 2022-09-09T16:53:34.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2024-09-14T12:52:07.000Z (over 1 year ago)
• Last Synced: 2024-09-15T22:36:32.321Z (over 1 year ago)
• Topics: clustering, db-index, dbscan, gmm, jupiter, k-medians, k-medoids, kmeans, kmeanspp, mean-shift, notebook, python, rand-index
• Language: Jupyter Notebook
• Homepage:
• Size: 28.2 MB
• Stars: 1
• Watchers: 1
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.txt

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README

          
# Clustering Deepening

**Copyright © 2022 Alessio Borgi**

**PROJECT SCOPE**: Deepening in the main Clustering Techniques. An in-depth exploration of clustering algorithms and techniques in machine learning. This project covers a variety of clustering methods, from traditional algorithms like K-Means and DBSCAN to advanced techniques, providing a comprehensive understanding of their applications, strengths, and limitations. Ideal for researchers and practitioners looking to enhance their knowledge of unsupervised learning and data analysis.

**PROJECT RESULTS**: 

- Data collection through the Performance Monitoring Windows Application (i.e., Built-in dataset). 

- Number of components choice through Elbow Method and Silhouette Coefficient.

- K-Means Clustering Deepening: Lloyd and Elkan Algorithm. K-Means++ and Naïve Sharding Initialization.

- K-Medians Clustering Deepening. 

- K-Medoids Clustering Deepening: PAM, Voronoi Iteration, CLARA and CLARANS Algorithms. 

- Mean-Shift Deepening: Object Tracking and Image Segmentation Applications. 

- DBSCAN Deepening. 

- GMM Deepening. 

- Deepening evaluation Silhouette Score, Accuracy, Purity, Rand Index, Adjusted Rand Index, Davies-Bouldin Index. 

- Final Decision Analysis of the best algorithm given my collected data.

**PROJECT REPOSITORY**: https://github.com/alessioborgi/Deep_Dive_into_the_Clustering_World