pythonbook/机器学习/SVM/1/SVM-低维映射高维.py

16 lines
455 B
Python

import matplotlib.pyplot as plt
from sklearn import datasets
from mpl_toolkits.mplot3d import Axes3D
x_data, y_data = datasets.make_circles(n_samples=500, factor=.3, noise=.10)
plt.scatter(x_data[:,0], x_data[:,1], c=y_data)
plt.show()
z_data = x_data[:,0]**2 + x_data[:,1]**2
ax = plt.figure().add_subplot(111, projection = '3d')
ax.scatter(x_data[:,0], x_data[:,1], z_data, c = y_data, s = 10) #点为红色三角形
#显示图像
plt.show()