{"id":21446252,"url":"https://github.com/rexlow/fuzzy-clustering-method","last_synced_at":"2026-01-02T18:47:57.451Z","repository":{"id":109778166,"uuid":"115395949","full_name":"rexlow/Fuzzy-Clustering-Method","owner":"rexlow","description":"Fuzzy Clustering Method with MATLAB","archived":false,"fork":false,"pushed_at":"2017-12-26T07:13:20.000Z","size":2,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-01-23T11:23:59.537Z","etag":null,"topics":["clustering","fuzzy-logic"],"latest_commit_sha":null,"homepage":null,"language":"Matlab","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/rexlow.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":"2017-12-26T07:07:05.000Z","updated_at":"2018-03-08T22:58:10.000Z","dependencies_parsed_at":"2023-06-11T19:15:44.839Z","dependency_job_id":null,"html_url":"https://github.com/rexlow/Fuzzy-Clustering-Method","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rexlow%2FFuzzy-Clustering-Method","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rexlow%2FFuzzy-Clustering-Method/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rexlow%2FFuzzy-Clustering-Method/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rexlow%2FFuzzy-Clustering-Method/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rexlow","download_url":"https://codeload.github.com/rexlow/Fuzzy-Clustering-Method/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243955976,"owners_count":20374411,"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","fuzzy-logic"],"created_at":"2024-11-23T02:42:34.223Z","updated_at":"2026-01-02T18:47:57.421Z","avatar_url":"https://github.com/rexlow.png","language":"Matlab","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Fuzzy Clustering Method\n\n## To run\n* Point MATLAB working directory to this folder.\n\nDefine two initial cluster centres.\n\n`Cts = [0.5 0.5; 0.8 0.8]`\n\nDefine a fuzziness exponent.\n\n`q = 2`\n\nClustering is now a matter of iteration.\n\n`[Cts, M] = defcm(Cts,q)`\n\nYou should see a plot with the data, and a membership matrix on the Matlab command line. Iterate the above command and watch the plot changes. The closer q is to 1, the more crisp the partitions. It cannot be 1, because q-1 occurs in a denominator, but close to 1 is good enough.\n\nFor more information, type\n`help defcm`","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frexlow%2Ffuzzy-clustering-method","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frexlow%2Ffuzzy-clustering-method","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frexlow%2Ffuzzy-clustering-method/lists"}