{"id":19599296,"url":"https://github.com/msikorski93/seed-clustering","last_synced_at":"2026-05-13T08:02:23.426Z","repository":{"id":203601252,"uuid":"709992251","full_name":"msikorski93/Seed-Clustering","owner":"msikorski93","description":"Performing basic clustering on a seeds dataset.","archived":false,"fork":false,"pushed_at":"2023-10-25T20:05:56.000Z","size":951,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-09T07:51:10.687Z","etag":null,"topics":["agglomerative","clustering","dbscan","gaussian-mixture-model","gmm","mini-batch-kmeans","scikit-learn","seeds"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/msikorski93.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}},"created_at":"2023-10-25T19:36:08.000Z","updated_at":"2023-10-25T19:42:27.000Z","dependencies_parsed_at":null,"dependency_job_id":"f1e5fe2e-a201-4dc4-a5e0-ae353e3cd3c5","html_url":"https://github.com/msikorski93/Seed-Clustering","commit_stats":null,"previous_names":["msikorski93/seed-clustering"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msikorski93%2FSeed-Clustering","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msikorski93%2FSeed-Clustering/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msikorski93%2FSeed-Clustering/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/msikorski93%2FSeed-Clustering/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/msikorski93","download_url":"https://codeload.github.com/msikorski93/Seed-Clustering/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240876855,"owners_count":19871903,"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":["agglomerative","clustering","dbscan","gaussian-mixture-model","gmm","mini-batch-kmeans","scikit-learn","seeds"],"created_at":"2024-11-11T09:09:38.341Z","updated_at":"2026-05-13T08:02:18.396Z","avatar_url":"https://github.com/msikorski93.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Seed-Clustering\n![ alt text ](https://img.shields.io/badge/license-MIT-green?style=\u0026logo=)\n![ alt text ](https://img.shields.io/badge/Python-3776AB?logo=python\u0026logoColor=fff)\n![ alt text ](https://img.shields.io/badge/-Jupyter-F37626?logo=Jupyter\u0026logoColor=white)\n![ alt text ](https://img.shields.io/badge/-pandas-150458?logo=Pandas\u0026logoColor=white)\n![ alt text ](https://img.shields.io/badge/-SciPy-8CAAE6?logo=SciPy\u0026logoColor=fff)\n![ alt text ](https://img.shields.io/badge/-scikit--learn-F7931E?logo=scikitlearn\u0026logoColor=white)\n\nThe subject of this repository was to perform basic cluster analysis on a seed dataset. The dataset contains geometrical properties of kernels belonging to three different varieties of wheat. We performed four different clustering approaches and obtained these results:\n\n\u003cp align='center'\u003e\n\u003cimg src='https://github.com/msikorski93/Seed-Clustering/assets/45270023/874a42ae-5254-45e7-a27b-7fe3cb945edd' width='750'/\u003e\n\u003c/p\u003e\n\nThe agglomerative clustering turned out to be the best choice. DBSCAN had the lowest performance, however it looks more suitable for detecting outliers in datasets.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmsikorski93%2Fseed-clustering","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmsikorski93%2Fseed-clustering","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmsikorski93%2Fseed-clustering/lists"}