{"id":20513451,"url":"https://github.com/slimani-dev/datamining-with-weka","last_synced_at":"2026-04-20T02:03:20.796Z","repository":{"id":126700122,"uuid":"238339053","full_name":"slimani-dev/datamining-with-weka","owner":"slimani-dev","description":"see this website for documentation","archived":false,"fork":false,"pushed_at":"2020-04-03T08:52:13.000Z","size":3066,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-10-11T13:52:56.430Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"https://moh-slimani.github.io/datamining-with-weka","language":"Java","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/slimani-dev.png","metadata":{"files":{"readme":"docs/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":"2020-02-05T00:54:28.000Z","updated_at":"2020-04-03T08:52:16.000Z","dependencies_parsed_at":"2023-06-17T17:45:28.812Z","dependency_job_id":null,"html_url":"https://github.com/slimani-dev/datamining-with-weka","commit_stats":null,"previous_names":["slimani-dev/datamining-with-weka"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/slimani-dev/datamining-with-weka","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slimani-dev%2Fdatamining-with-weka","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slimani-dev%2Fdatamining-with-weka/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slimani-dev%2Fdatamining-with-weka/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slimani-dev%2Fdatamining-with-weka/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/slimani-dev","download_url":"https://codeload.github.com/slimani-dev/datamining-with-weka/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/slimani-dev%2Fdatamining-with-weka/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32029860,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-20T00:18:06.643Z","status":"online","status_checked_at":"2026-04-20T02:00:06.527Z","response_time":94,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":[],"created_at":"2024-11-15T21:11:09.396Z","updated_at":"2026-04-20T02:03:20.757Z","avatar_url":"https://github.com/slimani-dev.png","language":"Java","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Introduction sur Weka \n\n![](images/weka_gui.png)\n\n\nWeka est un atelier d'exploration de données ou un environnement Waikato pour l'analyse des connaissances.\n\nIl contient des algorithmes d'apprentissage automatique pour les tâches d'exploration de données\n\n- 100+ algorithmes de classification\n- 75 pour le prétraitement des données\n- 25 pour aider à la sélection des fonctionnalités\n- 20 pour le clustering, la recherche de règles d'association, etc.\n\n## Site officiel\n\nPour télécharger Weka et obtenir de la documentation, consultez [cs.waikato.ac.nz/ml/weka/](https://www.cs.waikato.ac.nz/ml/weka/)\n\n## Utilisation\n\nWeka est un outil Java standard pour effectuer à la fois des expériences d'apprentissage \nautomatique et pour intégrer des modèles formés dans des applications Java. \n \nIl peut être utilisé pour un apprentissage supervisé et non supervisé. \n \nIl y a trois façons d'utiliser Weka d'abord en utilisant [la ligne de commande](cli.md), \nen second lieu, en utilisant l'interface graphique Weka comme [Explorer](explorer.md),[\nExperementer](explorer.md) et [knowledeFlow](explorer.md) ,\net en troisième via son [API avec Java](java.md). \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fslimani-dev%2Fdatamining-with-weka","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fslimani-dev%2Fdatamining-with-weka","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fslimani-dev%2Fdatamining-with-weka/lists"}