{"id":28371392,"url":"https://github.com/lin93555/titanic-kaggle","last_synced_at":"2026-06-28T21:31:52.121Z","repository":{"id":293183877,"uuid":"983212415","full_name":"Lin93555/titanic-kaggle","owner":"Lin93555","description":"Kaggle Titanic - Feature Engineering and Fusion Project, Fusion Strategy Project, including multiple models and pseudo labels","archived":false,"fork":false,"pushed_at":"2025-06-17T03:03:13.000Z","size":393,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-28T06:05:00.898Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","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/Lin93555.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,"zenodo":null}},"created_at":"2025-05-14T03:50:34.000Z","updated_at":"2025-06-17T03:03:17.000Z","dependencies_parsed_at":"2025-07-29T08:04:54.991Z","dependency_job_id":"308d997f-b3f6-4a25-b2e7-573a0e4eae9a","html_url":"https://github.com/Lin93555/titanic-kaggle","commit_stats":null,"previous_names":["lin93555/titanic-kaggle"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Lin93555/titanic-kaggle","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lin93555%2Ftitanic-kaggle","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lin93555%2Ftitanic-kaggle/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lin93555%2Ftitanic-kaggle/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lin93555%2Ftitanic-kaggle/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Lin93555","download_url":"https://codeload.github.com/Lin93555/titanic-kaggle/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Lin93555%2Ftitanic-kaggle/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34905180,"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":"2026-06-28T02:00:05.809Z","response_time":54,"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":"2025-05-29T08:45:58.974Z","updated_at":"2026-06-28T21:31:52.100Z","avatar_url":"https://github.com/Lin93555.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# 🚢 Titanic - Machine Learning from Disaster（Kaggle 0.81+ 精细建模项目）\n\n本项目基于 Kaggle 经典入门竞赛《Titanic》，目标是预测泰坦尼克号乘客是否生还。  \n通过系统构建特征工程 + 模型融合 + 半监督学习等模块，冲击排行榜高分（最高得分：**0.78468**）。\n\n---\n\n## 📌 项目亮点\n\n- 📦 增强型特征工程（姓氏/家庭/船舱/票号等高阶特征构造）\n- 🧠 集成学习融合模型（RandomForest、XGBoost、LightGBM、Stacking）\n- 🔁 半监督伪标签学习（使用高置信度样本扩充训练集）\n- 🛠️ 人工规则修正机制（针对弱模型误判人群定向优化）\n- 📊 多策略得分对比（冲击 0.81 的精细路线图）\n\n---\n\n## 🏆 模型方法对比分数表\n\n| 方法编号 | 方法名称 | 是否融合 | 得分 | 提升效果 |\n|----------|-----------|-----------|--------|-----------|\n| 方法 A | 随机森林 + 增强特征 | 否 | ✅ **0.78468** | ⭐ 当前最佳 |\n| 方法 B | VotingClassifier 融合 | 是 | ~0.77990 | 中 |\n| 方法 C | Stacking 模型融合 | 是 | ~0.78229 | 中 |\n| 方法 D | 人工规则修正 | 是 | ~0.75598 | ❌ |\n| 方法 E | Voting + 精修规则组合 | 是 | ~0.76794 | ❌ |\n| 方法 F | Voting + 伪标签增强 | 是 | ~0.76794 | ❌ |\n\n---\n\n## 📁 项目结构\n\n```\ntitanic-kaggle/\n│\n├── data/               # 原始数据（train/test）\n├── notebooks/          # 分阶段 Jupyter Notebook\n│   └── 0.81+_副本.ipynb\n├── submission/         # 提交文件（含最佳方案）\n├── requirements.txt    # 依赖包列表\n└── README.md           # 项目说明\n```\n\n---\n\n## 🚀 快速开始\n\n```bash\ngit clone https://github.com/Lin93555/titanic-kaggle.git\ncd titanic-kaggle\npip install -r requirements.txt\njupyter notebook\n```\n\n---\n\n## 📎 推荐阅读顺序\n\n1. `notebooks/0.81+_副本.ipynb` → 主体代码与策略清晰记录  \n2. `submission/submission_final_ensemble_boosted.csv` → 各方法输出文件  \n3. `README.md` → 方法总览 + 冲分路径图  \n\n---\n\n## 📈 最佳模型提交分数\n\n🎯 **0.78468**  \n模型：增强特征 + RandomForest（单模型）\n\n---\n\n## 🙋‍♂️ 作者\n\n本项目由 [Lin93555](https://github.com/Lin93555) 构建  \n如果你觉得有帮助，请点击 ⭐ Star 支持一下！\n\n---\n\n## 📫 联系与交流\n\n如需交流建模策略、Kaggle 学习方法、入门路径，欢迎联系我或发 Issue 👇\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flin93555%2Ftitanic-kaggle","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flin93555%2Ftitanic-kaggle","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flin93555%2Ftitanic-kaggle/lists"}