{"id":25046079,"url":"https://github.com/ronmondshein/symnmf","last_synced_at":"2026-05-03T02:43:47.664Z","repository":{"id":210222297,"uuid":"702011497","full_name":"RonMondshein/SymNMF","owner":"RonMondshein","description":"Implementation of ML models, including the k-means algorithm and symNMF, in both C and Python 💻.","archived":false,"fork":false,"pushed_at":"2025-01-27T21:24:55.000Z","size":702,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-06T06:42:19.479Z","etag":null,"topics":["c","k-means","python","symnmf"],"latest_commit_sha":null,"homepage":"","language":"C","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/RonMondshein.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2023-10-08T08:32:32.000Z","updated_at":"2025-01-27T21:25:58.000Z","dependencies_parsed_at":"2023-12-01T13:57:49.817Z","dependency_job_id":"9d261b05-f1ae-4a4c-88a2-2eeb345a0533","html_url":"https://github.com/RonMondshein/SymNMF","commit_stats":null,"previous_names":["ronmondshein/software_project"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RonMondshein%2FSymNMF","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RonMondshein%2FSymNMF/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RonMondshein%2FSymNMF/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/RonMondshein%2FSymNMF/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/RonMondshein","download_url":"https://codeload.github.com/RonMondshein/SymNMF/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246400581,"owners_count":20771045,"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":["c","k-means","python","symnmf"],"created_at":"2025-02-06T06:34:48.746Z","updated_at":"2026-05-03T02:43:42.620Z","avatar_url":"https://github.com/RonMondshein.png","language":"C","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Software_Project\n4 projects in c and python.\nMain purpose- Implementation of k-means algorithm.\n\n***********\nAssignment_0\n***********\nBase conventer- get familiar with C.\n\n************\nAssignment_1\n************\nIn this assignment, the K-means algorithm was implemented, a widely-used clustering method that partitions a set of N unlabeled observations into K distinct clusters, with K being a user-defined parameter. The implementation was carried out in both Python and C.\n\nThe K-means algorithm involves an iterative process of assigning data points to clusters based on their proximity to cluster centroids, followed by updating the centroids to minimize the overall intra-cluster variance. The Python implementation leverages the language's expressive syntax and ease of use, while the C implementation emphasizes efficiency and low-level control over computational resources.\n\n************\nAssignment_2\n************\nThe assignment involved implementing the K-means++ algorithm in Python to determine initial centroids for the K-means algorithm. This implementation was then integrated with the K-means algorithm from Assignment_1, which was ported to a C extension using the C API.\n\nThe assignment's objectives were met through:\nPorting the existing C extension using the C API.\nGaining hands-on experience with external packages like Numpy, Pandas, and others.\n\n*********\nProject\n********\nA clustering algorithm based on symmetric Non-negative Matrix Factorization (symNMF) was implemented in this project. Furthermore, the algorithm was compared to the K-means algorithm. \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fronmondshein%2Fsymnmf","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fronmondshein%2Fsymnmf","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fronmondshein%2Fsymnmf/lists"}