{"id":20839315,"url":"https://github.com/ailln/machine-learning-classical-algorithm","last_synced_at":"2026-04-13T01:15:57.193Z","repository":{"id":37068992,"uuid":"145582918","full_name":"Ailln/machine-learning-classical-algorithm","owner":"Ailln","description":"🧠机器学习经典算法","archived":false,"fork":false,"pushed_at":"2024-06-17T22:52:43.000Z","size":1491,"stargazers_count":1,"open_issues_count":2,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-12-30T09:58:39.732Z","etag":null,"topics":["algorithm","knn","linear-regression","machine-learning","svm"],"latest_commit_sha":null,"homepage":"","language":"Python","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/Ailln.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,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2018-08-21T15:23:40.000Z","updated_at":"2019-11-19T10:38:43.000Z","dependencies_parsed_at":"2022-09-07T07:01:22.895Z","dependency_job_id":null,"html_url":"https://github.com/Ailln/machine-learning-classical-algorithm","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Ailln/machine-learning-classical-algorithm","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ailln%2Fmachine-learning-classical-algorithm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ailln%2Fmachine-learning-classical-algorithm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ailln%2Fmachine-learning-classical-algorithm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ailln%2Fmachine-learning-classical-algorithm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Ailln","download_url":"https://codeload.github.com/Ailln/machine-learning-classical-algorithm/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Ailln%2Fmachine-learning-classical-algorithm/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31735895,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-12T22:19:12.206Z","status":"ssl_error","status_checked_at":"2026-04-12T22:18:33.088Z","response_time":58,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 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":["algorithm","knn","linear-regression","machine-learning","svm"],"created_at":"2024-11-18T01:13:16.782Z","updated_at":"2026-04-13T01:15:57.115Z","avatar_url":"https://github.com/Ailln.png","language":"Python","readme":"# machine-learning-classical-algorithm\n\n🧠 机器学习经典算法\n\n\u003e 「纸上得来终觉，绝知此事要躬行」\n\n## 1 数据集\n\n### 1. Iris（分类）\n\n- [数据介绍](https://www.v2ai.cn/ml/2018/06/30/ML-3.html)\n- [数据来源](https://archive.ics.uci.edu/ml/datasets/iris)\n\n### 2. Pokemon（回归）\n\n- [数据介绍](https://www.v2ai.cn/ml/2019/04/25/ML-10.html)\n- [数据来源](https://www.openintro.org/stat/data/?data=pokemon)\n\n## 2 准备\n\n```bash\n# 克隆代码\ngit clone https://github.com/Ailln/machine-learning-classical-algorithm.git\n\ncd machine-learning-classical-algorithm\n\n# 安装依赖\npip install -r requirements.txt\n```\n\n## 3 算法\n\n### 1. KNN\n\n`k-近邻算法` 采用测量不同特征值之间的距离方法进行分类。\n\n```bash\npython -m KNN.knn\n```\n\n### 2. LR\n\n`线性回归` 是一种用来确定一个或多个自变量和因变量之间关系的回归分析方法。\n\n```bash\n# 最小二乘法\npython -m LR.least_squares\n\n# 梯度下降法\npython -m LR.gradient_descent\n```\n\n![](./src/pokemon-gradient-descent.gif)\n\n参考文章：[预测「宝可梦」升级后的战斗力](https://www.v2ai.cn/ml/2018/08/31/ML-6.html)\n\n## 4 License\n\n[MIT License](./LICENSE)\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Failln%2Fmachine-learning-classical-algorithm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Failln%2Fmachine-learning-classical-algorithm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Failln%2Fmachine-learning-classical-algorithm/lists"}