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.gitignore

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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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env/
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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# Installer logs
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pip-log.txt
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pip-delete-this-directory.txt
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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.hypothesis/
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# Translations
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*.mo
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*.pot
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# Django stuff:
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*.log
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local_settings.py
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# Flask stuff:
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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# Sphinx documentation
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docs/_build/
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# PyBuilder
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target/
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# Jupyter Notebook
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.ipynb_checkpoints
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# pyenv
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.python-version
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# celery beat schedule file
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celerybeat-schedule
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# SageMath parsed files
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*.sage.py
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# dotenv
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.env
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# virtualenv
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.venv
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venv/
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ENV/
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# Spyder project settings
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.spyderproject
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.spyproject
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# Rope project settings
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.ropeproject
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.DS_Store
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# gitbook
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_book
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# node.js
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node_modules
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# windows
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Thumbs.db
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# word
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~$*.docx
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~$*.doc
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# custom
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docs/README.md

.nojekyll

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.travis.yml

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language: python
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python: 3.6
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install:
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- ':'
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script:
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- ':'
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after_script:
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- git config user.name ${GH_UN}
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- git config user.email ${GH_EMAIL}
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- git push "https://${GH_TOKEN}@github.com/${GH_USER}/${GH_REPO}.git" v0.19.x-md:${GH_BRANCH} -f
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env:
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global:
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- GH_UN=jiangzhonglian
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- GH_EMAIL=jiang-s@163.com
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- GH_USER=apachecn
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- GH_REPO=sklearn-doc-zh
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- GH_BRANCH=gh-pages

CNAME

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sklearn.apachecn.org

CONTRIBUTING.md

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# 贡献指南
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## 参与翻译 & 发现错误
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1. 在 github 上 fork 该 repository.
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2. 翻译 doc/zh/modules 和 doc/zh/tutorial 下面的 rst 文件即可, 例如, tutorial.rst.
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3. 然后, 在你的 github 发起 New pull request 请求.
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4. 工具使用, 可参考下面的内容.
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## 工具使用(针对新手)
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工欲善其事, 必先利其器 ...
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工具随意, 能达到效果就好.
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我这里使用的是 `VSCode` 编辑器.
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简易的使用指南请参阅: [VSCode Windows 平台入门使用指南](help/vscode-windows-usage.md), 介绍了 `VSCode``github` 一起搭配的简易使用的方法.
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如果要将 VSCode 的 Markdown 预览风格切换为 github 的风格,请参阅: [VSCode 修改 markdown 的预览风格为 github 的风格](help/vscode-markdown-preview-github-style.md).
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**注意注意注意:**
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为了尽量正规化各顶级项目的翻译,更便于以后的迭代更新,我们在 `scikit-learn` 文档翻译中使用了 `Git` 的分支,具体应用方法请参阅: [使用 Git 分支进行迭代翻译](help/git-branch-usage.md).
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## 角色分配
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目前有如下可分配的角色:
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* 翻译: 负责文章内容的翻译.
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* 校验: 负责文章内容的校验, 比如格式, 正确度之类的.
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* 负责人: 负责整个 Projcet, 不至于让该 Project 成为垃圾项目, 需要在 sklearn 方面经验稍微丰富点.
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有兴趣参与的朋友, 可以看看最后的联系方式.

README.md

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# scikit-learn (sklearn) 官方文档中文版
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![](docs/img/scikit-learn-logo.png)
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scikit-learn 是基于 Python 语言的机器学习工具。
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1. 简单高效的数据挖掘和数据分析工具
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2. 可供大家在各种环境中重复使用
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3. 建立在 NumPy ,SciPy 和 matplotlib 上
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4. 开源,可商业使用 - BSD许可证
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## 维护地址
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+ [Github](https://github.com/apachecn/scikit-learn-doc-zh/): <>
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+ [在线阅读](http://www.apachecn.org)
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+ [EPUB 格式](https://github.com/apachecn/scikit-learn-doc-zh/raw/dl/scikit-learn%200.19%20%E4%B8%AD%E6%96%87%E6%96%87%E6%A1%A3.epub)
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## 历史版本
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* [scikit-learn (sklearn) 0.18 官方文档中文版](http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030181): <http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030181>
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## 贡献指南
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[请见这里](CONTRIBUTING.md)
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## 负责人
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* [@chenyyx](https://github.com/chenyyx)(Joy yx)
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## 贡献者
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贡献者可自行编辑如下内容(排名不分先后).
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### 0.19.0
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**翻译者(人人皆大佬~):**
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* [@wangyangting](https://github.com/wangyangting)(那伊抹微笑)
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* [@jiangzhonglian](https://github.com/jiangzhonglian)(片刻)
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* [@chenyyx](https://github.com/chenyyx)(Joy yx)
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* [@survivingME](https://github.com/survivingME)(Trembleguy)
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* [@mtobeiyf](https://github.com/mtobeiyf)(Fing)
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* [@Leon-Jin](https://github.com/Leon-Jin)(Leon晋)
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* [@X1aoFang](https://github.com/X1aoFang)(X1aoFang)
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* [@loverollcat](https://github.com/loverollcat)(loverollcat)
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* [@helloheshee](https://github.com/helloheshee)(helloheshee)
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* [@SkyDreamStart](https://github.com/SkyDreamStart)(SkyDreamStart)
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* [@HazekiahWon](https://github.com/HazekiahWon)(Hazekiah Wang)
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* [@201419](https://github.com/201419)(tree)
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* [@busesese](https://github.com/busesese)(wenyi)
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* [@chrzc](https://github.com/chrzc)(changzhicheng)
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* [@Zoctan](https://github.com/Zoctan)(Zoctan)
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* [@JanzenLiu](https://github.com/JanzenLiu)(Janzen_Liu)
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* [@charleschou520](https://github.com/charleschou520)(charleschou520)
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* [@zhangqiking](https://github.com/zhangqiking)(BigBird)
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* [@mikechengwei](https://github.com/mikechengwei)(Mike)
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* [@wodekwan](https://github.com/wodekwan)(wodekwan)
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* [@sehriff](https://github.com/sehriff)(sehriff)
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* [@Kdotm](https://github.com/Kdotm)(kngines)
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* [@patientman](https://github.com/patientman)(YuanMingLiu)
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* [@DamonDay](https://github.com/DamonDay)(DamonDay)
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* [@cszhangbo](https://github.com/cszhangbo)(cszhangbo)
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* [@XingxGit](https://github.com/XingxGit)(XingxGit)
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* [@KrokYin](https://github.com/KrokYin)(KrokYin)
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* [@yw10](https://github.com/yw10)(Andrew Yao)
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* [@GlassyWu](https://github.com/GlassyWu)(glassy)
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* [@PrivateRookie](https://github.com/PrivateRookie)(PrivateRookie)
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* [@linweijiang](https://github.com/linweijiang)(linweijiang)
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* [@jiaqiangbandongg](https://github.com/jiaqiangbandongg)(jiaqiangbandongg)
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* [@supportingvector](https://github.com/supportingvector)(supportingvector)
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* [@stealthsMrs](https://github.com/stealthsMrs)(stealthsMrs)
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* [@lhwlhw90](https://github.com/lhwlhw90)(lhwlhw90)
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* [@sheepmen](https://github.com/sheepmen)(羊三)
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* [@guohao916](https://github.com/guohao916)(guohao_dm)
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* [@Daemon-ser](https://github.com/Daemon-ser)(csu_hgq)
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* [@wangxiancai](https://github.com/wangxiancai)(BWM-蜜蜂)
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* [@夜神月](@qq760514101)(夜神月)
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* [@liyangbit](https://github.com/liyangbit)(Lemon)
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* [@XuJianzhi](https://github.com/XuJianzhi)(XuJianzhi)
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**校验者(人人皆大佬~)**(现在还不齐全,贡献者大佬们可随意修改)
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* [@weiyd](https://github.com/weiyd)(尔了个达)
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* [@FontTian](https://github.com/FontTian)(FontTian)
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* [@XuJianzhi](https://github.com/XuJianzhi)(XuJianzhi)
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* [@caopeirui](https://github.com/caopeirui)(Veyron C)
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* [@HelloSilicat](https://github.com/HelloSilicat)(Jialiang Pei)
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* [@AnybodyHome](https://github.com/AnybodyHome)(loop)
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* [@RyanZhiNie](https://github.com/RyanZhiNie)(Zhi Nie)
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* [@zehuichen123](https://github.com/zehuichen123)(loveSnowBest)
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* [@hlxstc](https://github.com/hlxstc)(Jokers)
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* [@NellyLuo](https://github.com/NellyLuo)(NellyLuo)
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* [@yuezhao9210](https://github.com/yuezhao9210)(Yue Zhao)
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* [@why2lyj](https://github.com/why2lyj)(Snow Wong)
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* [@pan8664716](https://github.com/pan8664716)(pan8664716)
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* [@xrj](https://github.com/xrj)(xrj)
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* [@qvduoduo1997](https://github.com/qvduoduo1997)(qvduoduo1997)
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* [@marsjhao](https://github.com/marsjhao)(Zhang Junhao)
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* [@tiantian1412](https://github.com/tiantian1412)(tiantian1412)
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* [@sheepmen](https://github.com/sheepmen)(羊三)
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* [@wangyangting](https://github.com/wangyangting)(那伊抹微笑)
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* [@jiangzhonglian](https://github.com/jiangzhonglian)(片刻)
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* [@chenyyx](https://github.com/chenyyx)(Joy yx)
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* [@mikechengwei](https://github.com/mikechengwei)(Mike)
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* [@wangxiancai](https://github.com/wangxiancai)(BWM-蜜蜂)
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* [@busesese](https://github.com/busesese)(wenyi)
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* [@GlassyWu](https://github.com/GlassyWu)(glassy)
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* [@wodekwan](https://github.com/wodekwan)(wodekwan)
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* [@gbyy422990](https://github.com/gbyy422990)(Bin GAO)
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* [@charleschou520](https://github.com/charleschou520)(charleschou520)
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* [@DataMonk2017](https://github.com/DataMonk2017)(Jeremy Zheng)
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* [@Lixu518](https://github.com/Lixu518)(Mysry)
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* [@linxiamen](https://github.com/linxiamen)(YUNCHUAN LIN)
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* [@llcing](https://github.com/llcing)(Mayouji)
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* [@KyrieHee](https://github.com/KyrieHee)(HeYun)
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* [@ziepenn](https://github.com/ziepenn)(ziepenn)
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* [@FAN0521](https://github.com/FAN0521)(FAN0521)
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* [@Daemon-ser](https://github.com/Daemon-ser)(csu_hgq)
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* [@shaoyy147](https://github.com/shaoyy147)(Y.Shao)
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* [@Kdotm](https://github.com/Kdotm)(kngines)
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* [@chrzc](https://github.com/chrzc)(changzhicheng)
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* [@ywujudy](https://github.com/ywujudy)(ywujudy)
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* [@污剑客](https://github.com/apachecn)(污剑客)
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* [@爱吹牛逼的小明](https://github.com/apachecn)(爱吹牛逼的小明)
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* [@JanzenLiu](https://github.com/JanzenLiu)(Janzen_Liu)
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* [@Ecauchy](https://github.com/Ecauchy)(Ecauchy)
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### 0.18
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请参阅: [http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030181](http://cwiki.apachecn.org/pages/viewpage.action?pageId=10030181)
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## 联系方式
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有任何建议反馈, 或想参与文档翻译, 麻烦联系下面的企鹅:
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* 企鹅: 1042658081(那伊抹微笑), 190442212(小瑶), 529815144(片刻)

SUMMARY.md

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+ [安装 scikit-learn](docs/79.md)
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+ 用户指南
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+ [1\. 监督学习](docs/1.md)
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+ [1.1\. 广义线性模型](docs/2.md)
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+ [1.2\. 线性和二次判别分析](docs/3.md)
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+ [1.3\. 内核岭回归](docs/4.md)
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+ [1.4\. 支持向量机](docs/5.md)
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+ [1.5\. 随机梯度下降](docs/6.md)
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+ [1.6\. 最近邻](docs/7.md)
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+ [1.7\. 高斯过程](docs/8.md)
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+ [1.8\. 交叉分解](docs/9.md)
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+ [1.9\. 朴素贝叶斯](docs/10.md)
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+ [1.10\. 决策树](docs/11.md)
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+ [1.11\. 集成方法](docs/12.md)
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+ [1.12\. 多类和多标签算法](docs/13.md)
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+ [1.13\. 特征选择](docs/14.md)
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+ [1.14\. 半监督学习](docs/15.md)
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+ [1.15\. 等式回归](docs/16.md)
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+ [1.16\. 概率校准](docs/17.md)
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+ [1.17\. 神经网络模型(有监督)](docs/18.md)
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+ [2\. 无监督学习](docs/19.md)
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+ [2.1\. 高斯混合模型](docs/20.md)
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+ [2.2\. 流形学习](docs/21.md)
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+ [2.3\. 聚类](docs/22.md)
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+ [2.4\. 双聚类](docs/23.md)
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+ [2.5\. 分解成分中的信号(矩阵分解问题)](docs/24.md)
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+ [2.6\. 协方差估计](docs/25.md)
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+ [2.7\. 经验协方差](docs/26.md)
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+ [2.8\. 收敛协方差](docs/27.md)
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+ [2.9\. 稀疏逆协方差](docs/28.md)
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+ [2.10\. Robust 协方差估计](docs/29.md)
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+ [2.11\. 新奇和异常值检测](docs/30.md)
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+ [2.12\. 密度估计](docs/31.md)
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+ [2.13\. 神经网络模型(无监督)](docs/32.md)
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+ [3\. 模型选择和评估](docs/33.md)
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+ [3.1\. 交叉验证:评估估算器的表现](docs/34.md)
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+ [3.2\. 调整估计器的超参数](docs/35.md)
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+ [3.3\. 模型评估: 量化预测的质量](docs/53.md)
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+ [3.4\. 模型持久化](docs/54.md)
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+ [3.5\. 验证曲线: 绘制分数以评估模型](docs/55.md)
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+ [4\. 数据集转换](docs/56.md)
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+ [4.1\. Pipeline(管道)和 FeatureUnion(特征联合): 合并的评估器](docs/57.md)
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+ [4.2\. 特征提取](docs/58.md)
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+ [4.3\. 预处理数据](docs/59.md)
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+ [4.4\. 无监督降维](docs/60.md)
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+ [4.5\. 随机投影](docs/61.md)
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+ [4.6\. 内核近似](docs/62.md)
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+ [4.7\. 成对的矩阵, 类别和核函数](docs/63.md)
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+ [4.8\. 预测目标 (`y`.md) 的转换](docs/64.md)
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+ [5\. 数据集加载工具](docs/65.md)
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+ [6\. 大规模计算的策略: 更大量的数据](docs/66.md)
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+ [7\. 计算性能](docs/67.md)
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+ 教程
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+ [使用 scikit-learn 介绍机器学习](docs/68.md)
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+ [关于科学数据处理的统计学习教程](docs/69.md)
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+ [机器学习: scikit-learn 中的设置以及预估对象](docs/70.md)
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+ [监督学习:从高维观察预测输出变量](docs/71.md)
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+ [模型选择:选择估计量及其参数](docs/72.md)
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+ [无监督学习: 寻求数据表示](docs/73.md)
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+ [把它们放在一起](docs/74.md)
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+ [寻求帮助](docs/75.md)
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+ [处理文本数据](docs/76.md)
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+ [选择正确的评估器(estimator.md)](docs/77.md)
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+ [外部资源,视频和谈话](docs/78.md)
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+ [API 参考](https://scikit-learn.org/stable/modules/classes.html)
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+ [常见问题](docs/80.md)
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+ [时光轴](docs/81.md)

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