我们先引入make_blobs并调用，参数请看注释：
from sklearn.datasets import make_blobsX, y = make_blobs(n_samples=20, # 生成20个样本 n_features=2, # 每个样本2个特征 centers=3 # 3个中心 )查看生成的数据长度：
X.shape,y.shape ((20, 2), (20,))查看X,y的值：
X,y (array([[ 5.89960601, 8.71170696], [ -4.97240689, -5.58567093], [-10.84160353, 1.7629505 ], [ -9.97435178, 2.08737815], [ 5.9428016 , 10.73028316], [ 5.66663745, 9.18073685], [ 6.25187124, 10.79703471], [ -7.02515868, -6.5240859 ], [ -5.73605444, -4.19309637], [-10.70728071, 2.36406501], [-10.37438672, 2.07198502], [ 3.96774726, 8.25325771], [ -6.45551268, -4.5922466 ], [ -9.86581166, 3.80563866], [ -7.98049509, -6.16329193], [ -6.78344711, -5.59575455], [ -9.0294714 , 1.21256105], [ -5.74061642, -5.77171784], [ -9.70159157, 3.65504855], [ 6.229 , 8.38946947]]), array([2, 0, 1, 1, 2, 2, 2, 0, 0, 1, 1, 2, 0, 1, 0, 0, 1, 0, 1, 2]))用matplotlib画出来：
import matplotlib.pyplot as pltplt.scatter( X[:,0], #第一个特征值当x坐标 X[:,1], #第二个特征值当y坐标 c=y # 数据类别标签当做颜色，相同标签的颜色也相同)plt.show() 00661066