{"id":16228779,"url":"https://github.com/mpgon/master-dissertation","last_synced_at":"2026-02-25T12:40:51.670Z","repository":{"id":70738798,"uuid":"83695714","full_name":"mpgon/master-dissertation","owner":"mpgon","description":"master dissertation dev","archived":false,"fork":false,"pushed_at":"2018-05-02T22:07:08.000Z","size":63039,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"master","last_synced_at":"2025-02-14T03:34:06.543Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"TeX","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/mpgon.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":"2017-03-02T15:52:48.000Z","updated_at":"2018-05-02T22:07:12.000Z","dependencies_parsed_at":"2023-02-22T22:15:13.452Z","dependency_job_id":null,"html_url":"https://github.com/mpgon/master-dissertation","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/mpgon%2Fmaster-dissertation","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpgon%2Fmaster-dissertation/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpgon%2Fmaster-dissertation/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mpgon%2Fmaster-dissertation/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mpgon","download_url":"https://codeload.github.com/mpgon/master-dissertation/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247779763,"owners_count":20994572,"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":[],"created_at":"2024-10-10T12:56:29.384Z","updated_at":"2026-02-25T12:40:51.641Z","avatar_url":"https://github.com/mpgon.png","language":"TeX","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Label Ranking for Election Outcome Prediction (MSc)\n\n[publication](http://hdl.handle.net/10216/111219)\n\nPredicting the election outcome is a complex task. Currently used approaches, such as classic\npools, might not be able to capture the multitude of variables involved in the election results.\nThis work proposes tackling the problem of Election Outcome Prediction with the use\nof Data Mining and Machine Learning. The focus will be in the study of the preferences\nof the parties and their socio-economic context. To tackle this, we suggest to transform the\nprediction of elections into a Label Ranking (LR) problem. \n\nLR is a subtask of the Preference Learning field, which uses a set of tools that allow the discovery of patterns in preferences.\nThis has the advantage of allowing the prediction of, not only who is going to win, but also\nan ordered relation between the political parties or candidates.\nIn particular, we are going to focus on Pairwise Association Rules (PAR). We will use them for\nprediction purposes. They come with the advantage that they provide interpretable results,\nwhich is useful to analyze the predictions.\n\nThe results will be tested both in common LR datasets and in election datasets. We will\ncompare our approach with other LR algorithms.\nIn the end, considering the good results obtained, we believe that this work holds promise\nboth as a contribution to the LR community and the Political Science field.\n\n## run\n`R /src/core.R`\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmpgon%2Fmaster-dissertation","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmpgon%2Fmaster-dissertation","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmpgon%2Fmaster-dissertation/lists"}