{"id":22511424,"url":"https://github.com/alessioborgi/Clustering-Deepening","last_synced_at":"2025-08-03T14:32:31.179Z","repository":{"id":163461175,"uuid":"534729410","full_name":"alessioborgi/Clustering_Deepening","owner":"alessioborgi","description":"An in-depth exploration of clustering algorithms and techniques in machine learning, with applications focus on Object Tracking and Image Segmentation.","archived":false,"fork":false,"pushed_at":"2024-09-14T12:52:07.000Z","size":29518,"stargazers_count":1,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2024-09-15T22:36:32.321Z","etag":null,"topics":["clustering","db-index","dbscan","gmm","jupiter","k-medians","k-medoids","kmeans","kmeanspp","mean-shift","notebook","python","rand-index"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/alessioborgi.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-09-09T16:53:34.000Z","updated_at":"2024-09-15T17:48:24.000Z","dependencies_parsed_at":null,"dependency_job_id":"63bcb1f1-c7fd-4876-a1d3-91c15d80939a","html_url":"https://github.com/alessioborgi/Clustering_Deepening","commit_stats":null,"previous_names":["alessioborgi/deep_dive_into_the_clustering_world"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alessioborgi%2FClustering_Deepening","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alessioborgi%2FClustering_Deepening/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alessioborgi%2FClustering_Deepening/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/alessioborgi%2FClustering_Deepening/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/alessioborgi","download_url":"https://codeload.github.com/alessioborgi/Clustering_Deepening/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":228548581,"owners_count":17935226,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["clustering","db-index","dbscan","gmm","jupiter","k-medians","k-medoids","kmeans","kmeanspp","mean-shift","notebook","python","rand-index"],"created_at":"2024-12-07T02:11:55.094Z","updated_at":"2025-08-03T14:32:28.699Z","avatar_url":"https://github.com/alessioborgi.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Clustering Deepening\n\n**Copyright © 2022 Alessio Borgi**\n\n**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.\n\n**PROJECT RESULTS**: \n- Data collection through the Performance Monitoring Windows Application (i.e., Built-in dataset). \n- Number of components choice through Elbow Method and Silhouette Coefficient.\n- K-Means Clustering Deepening: Lloyd and Elkan Algorithm. K-Means++ and Naïve Sharding Initialization.\n- K-Medians Clustering Deepening. \n- K-Medoids Clustering Deepening: PAM, Voronoi Iteration, CLARA and CLARANS Algorithms. \n- Mean-Shift Deepening: Object Tracking and Image Segmentation Applications. \n- DBSCAN Deepening. \n- GMM Deepening. \n- Deepening evaluation Silhouette Score, Accuracy, Purity, Rand Index, Adjusted Rand Index, Davies-Bouldin Index. \n- Final Decision Analysis of the best algorithm given my collected data.\n\n**PROJECT REPOSITORY**: https://github.com/alessioborgi/Deep_Dive_into_the_Clustering_World\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falessioborgi%2FClustering-Deepening","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Falessioborgi%2FClustering-Deepening","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Falessioborgi%2FClustering-Deepening/lists"}