{"id":29638235,"url":"https://github.com/celestialtaha/unbalanced-dataset-classification","last_synced_at":"2026-04-21T09:33:38.777Z","repository":{"id":48477736,"uuid":"356169775","full_name":"celestialtaha/Unbalanced-dataset-Classification","owner":"celestialtaha","description":"Classification on Unbalanced Datasets using Boost Techniques (AdaBoost M2, SMOTE Boost, RusBoost,..)","archived":false,"fork":false,"pushed_at":"2021-07-23T16:53:59.000Z","size":737,"stargazers_count":5,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-21T19:26:57.976Z","etag":null,"topics":["adaboost-classifier","classification","machine-learning","rusboost","smote-algorithm","unbalanced-data"],"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/celestialtaha.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2021-04-09T07:00:50.000Z","updated_at":"2025-05-03T05:27:10.000Z","dependencies_parsed_at":"2022-09-11T14:00:47.552Z","dependency_job_id":null,"html_url":"https://github.com/celestialtaha/Unbalanced-dataset-Classification","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/celestialtaha/Unbalanced-dataset-Classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/celestialtaha%2FUnbalanced-dataset-Classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/celestialtaha%2FUnbalanced-dataset-Classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/celestialtaha%2FUnbalanced-dataset-Classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/celestialtaha%2FUnbalanced-dataset-Classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/celestialtaha","download_url":"https://codeload.github.com/celestialtaha/Unbalanced-dataset-Classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/celestialtaha%2FUnbalanced-dataset-Classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32085564,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-21T06:27:27.065Z","status":"ssl_error","status_checked_at":"2026-04-21T06:27:21.250Z","response_time":128,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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":["adaboost-classifier","classification","machine-learning","rusboost","smote-algorithm","unbalanced-data"],"created_at":"2025-07-21T19:07:10.253Z","updated_at":"2026-04-21T09:33:38.755Z","avatar_url":"https://github.com/celestialtaha.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Unbalanced-dataset-Classification\nClassification on Unbalanced Datasets using Boost Techniques (AdaBoost M2, SMOTE Boost, RusBoost,..)\n\nBelow is the detailed results:\n\n![image](https://github.com/tahasamavati/Unbalanced-dataset-Classification/blob/main/results.png)\n\nAverage Classifier Precision for AdaBoost :          0.77\n\nAverage Classifier Precision for RUSBoost :          0.82\n\nAverage Classifier Precision for SMOTEBoost :        0.66\n\nAverage Classifier Precision for RandomBalanceBoost :0.6\n\nAverage Classifier Precision for RandomForest :      0.95\n\nAverage Classifier Precision for SVM :               1.0\n\n--------------------------------------------------------------\n* Best performing method based on Average Precision of classifiers: \"SVM\"\n\n* Best Performing Ensemble Classifier is \"Random Forset\" Runner up (second best) is RUSBOOST\n--------------------------------------------------------------------------------\n\nTaha Samavati - Analysis of final results\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcelestialtaha%2Funbalanced-dataset-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcelestialtaha%2Funbalanced-dataset-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcelestialtaha%2Funbalanced-dataset-classification/lists"}