基于Tsinghua anaconda镜像的下载
更新:
使用pip方式安装更快：
pip install numpy
pip install scipy
pip install scikit-learn
1、镜像配置
在cmd窗口，运行
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/main/
conda config --add channels https://mirrors.tuna.tsinghua.edu.cn/anaconda/pkgs/free/
conda config --set show_channel_urls yes
这里只是配置anaconda （一个python科学计算包）的仓库镜像来安装里边的包。
2、安装numpy/scipy/scikit-learn
conda install numpy
conda install scipy
conda install scikit-learn
如果安装出现失败，提示无法访问****，可以通过使用命令行（管理员）来打开，重新输入指令，即可。
C:\Windows\system32>pip3 install --ignore-installed --upgrade -U scikit-learn
Collecting scikit-learnUsing cached scikit_learn-0.19.1-cp36-cp36m-win_amd64.whlInstalling collected packages: scikit-learn
Successfully installed scikit-learn-0.19.1
其他安装方式，使用pip安装：
pip3 install -U scikit-learn#针对python3以上版本
3、测试是否成功
C:\Users\RoFun>python
Python 3.5.2 |Anaconda custom (64-bit)| (default, Jul 5 2016, 11:41:13) [MSC v.
1900 64 bit (AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.#测试numpy
>>> from numpy import *
>>> random.rand(4,4)
array([[ 0.50577718, 0.28084544, 0.60065843, 0.13602574],[ 0.21017214, 0.95728551, 0.86767926, 0.28480014],[ 0.09599413, 0.1180833 , 0.32564685, 0.86346346],[ 0.44717601, 0.48939418, 0.66523856, 0.59264163]])#测试SciPy
>>> mamat=mat(random.rand(4,4))
>>> mamat.I
matrix([[-0.21932642, -0.21289052, 3.39586459, -0.97625391],[-1.24711187, 2.321002 , -4.25158411, 3.64620557],[ 3.42909455, -5.57118063, 1.78018854, 0.39327149],[-0.63002829, 3.00212206, -2.29609706, -0.79183222]])
测试sk-learn
>>> import scikit
Traceback (most recent call last):File "<stdin>", line 1, in <module>
ImportError: No module named 'scikit'>>> from sklearn import datasets
>>> digits=datasets.load_digits()
>>> print(digits.data)
[[ 0. 0. 5. ..., 0. 0. 0.][ 0. 0. 0. ..., 10. 0. 0.][ 0. 0. 0. ..., 16. 9. 0.]...,[ 0. 0. 1. ..., 6. 0. 0.][ 0. 0. 2. ..., 12. 0. 0.][ 0. 0. 10. ..., 12. 1. 0.]]
参考：
- sk-learn入门教程