Windows 10下Python环境安装sklearn步骤详解

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本篇文档详细介绍了如何在Windows 10环境下,针对Python编程语言及其机器学习库sklearn进行安装。首先,确保你的环境中已经安装了Python,然后针对sklearn的安装,你需要安装numpy+mkl和scipy这两个关键库。 一、环境准备 - Python基础环境:确保已安装Python,这是进行任何Python开发的基础。 - Windows 10系统:本文指导针对Windows操作系统,可能需要对其他系统进行相应的调整。 二、Scipy安装 - 安装方法:推荐使用pip工具,执行`pip install -U scipy` 进行升级安装,确保你安装的是最新稳定版。 三、numpy+mkl安装 - 避免pip3默认安装:由于pip3默认安装的numpy不包含mkl加速,需要特别注意。 - 手动下载安装:访问[第三方库网址](https://www.lfd.uci.edu/~gohlke/pythonlibs/),找到适合你Python版本的numpy+mkl wheel文件。 - 安装步骤: 1. 安装wheel软件包工具:`python -m pip install --upgrade pip` 2. 确认Python版本:`pip debug --verbose`,了解支持的Python版本。 3. 下载对应版本的NumPy+mkl wheel文件。 4. 在下载的文件所在的文件夹(例如D:\ProgramFiles\桌面)中,使用pip进行安装:`pip install numpy-1.22.4+mkl-cp39-cp39-win_amd64.whl --user` 四、sklearn安装 - 最后,安装sklearn:利用已经安装的numpy+mkl,通过`pip install -U scikit-learn --user`来完成安装。`--user`选项表示将库安装到个人用户目录,而不是系统全局位置。 总结起来,安装sklearn的过程包括先确保Python环境,然后安装必要的依赖库scipy,接着是关键的numpy+mkl,最后才是sklearn本身。每一步都需要确保选择正确的版本和正确的方法,以便在Windows 10上实现高效且稳定的机器学习开发环境。如果你遇到任何问题,可能需要查阅更详细的文档或在线寻求帮助。

再pycharm安装sklearn时出现Looking in indexes: https://pypi.tuna.tsinghua.edu.cn/simple Collecting sklearn Downloading https://pypi.tuna.tsinghua.edu.cn/packages/7a/93/e0e1b1e98f39dfca7ec9795cb46f6e09e88a2fd5d4a28e4b3d1f618a2aec/sklearn-0.0.post5.tar.gz (3.7 kB) Preparing metadata (setup.py): started Preparing metadata (setup.py): finished with status 'error' error: subprocess-exited-with-error python setup.py egg_info did not run successfully. exit code: 1 [18 lines of output] The 'sklearn' PyPI package is deprecated, use 'scikit-learn' rather than 'sklearn' for pip commands. Here is how to fix this error in the main use cases: - use 'pip install scikit-learn' rather than 'pip install sklearn' - replace 'sklearn' by 'scikit-learn' in your pip requirements files (requirements.txt, setup.py, setup.cfg, Pipfile, etc ...) - if the 'sklearn' package is used by one of your dependencies, it would be great if you take some time to track which package uses 'sklearn' instead of 'scikit-learn' and report it to their issue tracker - as a last resort, set the environment variable SKLEARN_ALLOW_DEPRECATED_SKLEARN_PACKAGE_INSTALL=True to avoid this error More information is available at https://github.com/scikit-learn/sklearn-pypi-package If the previous advice does not cover your use case, feel free to report it at https://github.com/scikit-learn/sklearn-pypi-package/issues/new [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. error: metadata-generation-failed Encountered error while generating package metadata. See above for output. note: This is an issue with the package mentioned above, not pip. hint: See above for details.是什么问题?该怎样解决?如何安装sklearn库?

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