<?xml version="1.0" encoding="utf-8" ?><rss version="2.0"><channel><title><![CDATA[qindan8396的博客]]></title><description><![CDATA[]]></description><link>https://blog.youkuaiyun.com/qindan8396</link><language>zh-cn</language><generator>https://blog.youkuaiyun.com/</generator><copyright><![CDATA[Copyright &copy; qindan8396]]></copyright><item><title><![CDATA[移动Windows-ubuntu-交互全部在固态的方法]]></title><link>https://blog.youkuaiyun.com/qindan8396/article/details/145404468</link><guid>https://blog.youkuaiyun.com/qindan8396/article/details/145404468</guid><author>qindan8396</author><pubDate>Fri, 31 Jan 2025 13:39:06 +0800</pubDate><description><![CDATA[如果 Ubuntu-18.04 没有出现在列表中，可能是因为 WSL 没有正确识别 SSD 中的实例。如果在安装过程中没有选择初始化 Anaconda，可以手动配置环境变量。出现root@LAPTOP-2KBKP7NP:/mnt/z/setup/wsl# 类似这样就可以了。建立虚拟环境之后，进去projects 文件夹，进行代码训练，这个文件夹就是固态硬盘的文件夹。按 Enter 接受默认安装路径（通常是 /home/kunyao/anaconda3）。如果默认版本为 2，则说明设置成功。]]></description><category></category></item><item><title><![CDATA[pymc3安装]]></title><link>https://blog.youkuaiyun.com/qindan8396/article/details/111477777</link><guid>https://blog.youkuaiyun.com/qindan8396/article/details/111477777</guid><author>qindan8396</author><pubDate>Mon, 21 Dec 2020 16:50:42 +0800</pubDate><description><![CDATA[conda create -n temp python=3.8
conda activate temp
conda install -c conda-forge pymc3
conda install m2w64-toolchain
conda install libpython
pip install arviz
pip install ipykernel#jyputer 添加内核
python -c "import pymc3; print(pymc3.__version__)"


]]></description><category></category></item><item><title><![CDATA[01-特征工程]]></title><link>https://blog.youkuaiyun.com/qindan8396/article/details/110859387</link><guid>https://blog.youkuaiyun.com/qindan8396/article/details/110859387</guid><author>qindan8396</author><pubDate>Fri, 11 Dec 2020 10:16:06 +0800</pubDate><description><![CDATA[4.1特征变换
4.1.1离散化
parts = np.array([0,18.5,25,28,100])
types = ["silght","normal","overweight","fat"]
boys["wtype"] = [types[np.where(x&lt;= parts)[0][0]-1] if not np.isnan(x) else "Nan" for x in boys.bmi]

其中parts是设置离散区间，types是区间内取值，最后通过列表生成器构建离散化数据。

列表生成]]></description><category></category></item></channel></rss>