{"id":19663322,"url":"https://github.com/jonasaacampos/ensemble-learning-em-python","last_synced_at":"2026-06-10T03:31:24.682Z","repository":{"id":107933272,"uuid":"518655903","full_name":"jonasaacampos/Ensemble-learning-em-python","owner":"jonasaacampos","description":"Ensemble learning em python para classificação de texto em nótícias","archived":false,"fork":false,"pushed_at":"2024-03-06T00:17:26.000Z","size":10471,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-11-22T03:03:38.156Z","etag":null,"topics":["algorithms-and-data-structures","data-science","ensemble-learning","ensemble-model","python"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"bsd-3-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/jonasaacampos.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,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2022-07-28T01:02:33.000Z","updated_at":"2022-08-09T12:30:39.000Z","dependencies_parsed_at":"2024-03-06T01:39:51.982Z","dependency_job_id":null,"html_url":"https://github.com/jonasaacampos/Ensemble-learning-em-python","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/jonasaacampos/Ensemble-learning-em-python","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonasaacampos%2FEnsemble-learning-em-python","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonasaacampos%2FEnsemble-learning-em-python/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonasaacampos%2FEnsemble-learning-em-python/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonasaacampos%2FEnsemble-learning-em-python/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/jonasaacampos","download_url":"https://codeload.github.com/jonasaacampos/Ensemble-learning-em-python/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/jonasaacampos%2FEnsemble-learning-em-python/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34136112,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-10T02:00:07.152Z","response_time":89,"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":["algorithms-and-data-structures","data-science","ensemble-learning","ensemble-model","python"],"created_at":"2024-11-11T16:14:11.120Z","updated_at":"2026-06-10T03:31:24.667Z","avatar_url":"https://github.com/jonasaacampos.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cp align=\"center\"\u003e\n\t  \u003ca href='https://jonasaacampos.github.io/portfolio/'\u003e\n      \u003cimg alt=\"Engenheiro de Machine Learning - Badge\" src=\"https://img.shields.io/static/v1?color=red\u0026label=Engenieer\u0026message=Machine-Learning\u0026style=for-the-badge\u0026logo=ia\"/\u003e\n      \u003c/a\u003e\n\u003c/p\u003e\n\n\u003ch1\u003eModelagem de tópicos do noticiário financeiro\u003c/h1\u003e\n\n------\n\n\u003cimg alt=\"brain\" src=\"img/noticia.png\" width=150 align=right\u003e\n\n\u003ch2\u003eEnsemble learning em python para classificação de texto em nótícias\u003c/h2\u003e\n\n![](https://img.shields.io/badge/BackEnd-Python-informational?style=flat\u0026logo=Python\u0026logoColor=white\u0026color=059A10)\n\nAnotações e projetos do curso de **formação em Engenharia de Machine Learning** da DS Academy.\n\n\u003e Extrair, tratar e classificar textos para filtrar dados relevantes para auxílio de tomada de decisão do investidor\n\n\u003ch2\u003eÍndice / Table of Contents / Tabla de Contenido\u003c/h2\u003e\n\n[![](https://img.shields.io/badge/feito%20com%20%E2%9D%A4%20por-jaac-cyan)](https://jonasaacampos.github.io/portfolio/)\n[![LinkedIn Badge](https://img.shields.io/badge/LinkedIn-Profile-informational?style=flat\u0026logo=linkedin\u0026logoColor=white\u0026color=0D76A8)](https://www.linkedin.com/in/jonasaacampos)\n- [Definição do projeto](#definição-do-projeto)\n- [Conjuntos de dados](#conjuntos-de-dados)\n- [Para saber mais](#para-saber-mais)\n- [Crédito das imagens](#crédito-das-imagens)\n- [Contato](#contato)\n\n--------\n\n## Definição do projeto\n\n\u003e Com alguns parágrafos de texto, podemos afirmar sobre qual assunto é discutido?\n\nModelos de entrada: trechos de notícias\nModelos de saída: categorias, baseadas em dados históricos\n\n\u003e A etiquetagem é um processo demorado e CARO, geralmente bancos de dados etiquetados são guardados secretamente.\n\nA aprendizagem ensemble é um paradigma de aprendizagem de máquina em que vários\nmodelos (frequentemente chamados de “estimadores fracos”) são treinados para resolver o\nmesmo problema e combinados para obter melhores resultados. A hipótese principal é que\nquando modelos fracos são combinados corretamente podemos obter modelos mais precisos\ne/ou robustos.\n\n## Conjuntos de dados\n\nOs dados utilizados são notícias da BBC[^1]. Para esta análise foram utilizados os dados brutos. \n\n![](https://media2.giphy.com/media/v1.Y2lkPTc5MGI3NjExcjQ2bnVtdHdrNzB0emJsYnBwNDB0dDA5eTl0dGRpbWcwdWZuZjVqaSZlcD12MV9pbnRlcm5hbF9naWZfYnlfaWQmY3Q9Zw/YqENbSOVvEAnCYbhM5/giphy.gif)\n\n\u003e dados brutos na área...\n\n\u003cimg alt=\"dados brutos na área...\" src=\"img/dados-brutos.gif\" width=150 align=center\u003e\n\n```bash\n// para baixar os dados, acese o site da bbc, ou baixe o arquivo diretamente via terminal\n\nwget http://mlg.ucd.ie/files/datasets/bbc-fulltext.zip\n\nunzip bbc-fulltext.zip\n\n```\n\nConsiste em 2.225 documentos do site de notícias da BBC, publicadas entre 2004 e 2005, correspondentes a histórias em cinco áreas temáticas:\n\n1. negócios\n2. entretenimento\n3. política\n4. esporte\n5. tecnologia\n\nVotin = todos os modelos fazem as previsões, e suas saídas passam por uma votação\nStaking = as saídas dos modelos individuais alimentam um terceiro modelo\n\n## Para saber mais\n\n- [[S2E2] Ensemble Methods | 5 Minutes With Ingo](https://youtu.be/dhvmVScjrzE)\n- Tom Michael, Machine Learning\n- Mark Fenne, Machine Learning with Python for Everyone\n- Andriy Burkov, The Hundred-Page Machine Learning Book\n- [sklearn.ensemble.StackingClassifier](https://scikit-learn.org/stable/modules/generated/sklearn.ensemble.StackingClassifier.html)\n- [Stacked generalization¶](https://scikit-learn.org/stable/modules/ensemble.html#stacking)\n\n## Crédito das imagens\n\n- Desenhos no título by [flaticon](https://www.flaticon.com)\n- Badges e demos do projeto feitos por mim\n\n\u003c!-- CONTACT --\u003e\n## Contato\n\n**Author:** Jonas Araujo de Avila Campos\n\n**Confira mais projetos: [AQUI](https://jonasaacampos.github.io/portfolio/)**\n\n\u003cp align='center'\u003e\n  \u003ca href='https://github.com/jonasaacampos'\u003e\n    \u003cimg src='https://img.shields.io/badge/GitHub-100000?style=for-the-badge\u0026logo=github\u0026logoColor=white'/\u003e\n  \u003c/a\u003e\n  \u003ca href='https://www.linkedin.com/in/jonasaacampos/'\u003e\n    \u003cimg src='https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge\u0026logo=linkedin\u0026logoColor=white'/\u003e\n  \u003c/a\u003e\n\u003c/p\u003e\n\n\n## Referências\n\n[^1]: D. Greene and P. Cunningham. (\"Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clustering\")[D. Greene and P. Cunningham. \"Practical Solutions to the Problem of Diagonal Dominance in Kernel Document Clustering\", Proc. ICML 2006. ], Proc. ICML 2006.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonasaacampos%2Fensemble-learning-em-python","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjonasaacampos%2Fensemble-learning-em-python","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjonasaacampos%2Fensemble-learning-em-python/lists"}